In early 2023, the International Maritime Organization (IMO) set ambitious targets to achieve a ecological marine industry and net-zero emissions by 2050, a dramatic acceleration from the previous target of 2100. The industry has been sailing in rough seas since then, with widespread implications for the life cycle management of ships, from concept design to in-service operation and decommissioning. Most industry stakeholders anticipated this development, having observed the sequence of progressively stricter environmental regulations. During the Clean Energy Action Forum 2022, American Bureau of Shipping (ABS) CEO and President Chris Wiernicki outlined so-called credible fuel pathways, which will be the main driver in ship operators' selection of new fuel types to meet zero carbon targets. The technological readiness schedule is at the heart of decision-making, which can be divided into short, medium and long-term periods. According to Wiernicki, such readiness is given if the following four pillars can be established: A solid business case Scalability Provision and use of certifiable data Mitigation of unintended consequences Short-term solutions for a ecological marine industry Short-term solutions are liquefied natural gas (LNG), methanol and first and second generation biofuels. According to Clarksons, 4.1% of the world's commercial fleet can use LNG as fuel. This represents 91% of the total share of the fleet capable of alternative fuels. Furthermore, the dominance of LNG is reflected in the current order books, with 33.3% opting for LNG, followed by Liquefied Petroleum Gas (LPG) with 2.3%, methanol (1.2%), ethane (0.3%) and hydrogen (<0.3%). %). Orders combining LNG with the “ammonia ready” option represent up to 10% of these orders. The main incentive for using biofuels is that the existing fuel infrastructure requires few or no adjustments. For smaller, short-sea and coastal vessels, suitable battery solutions are already available, and successful prototypes of fully electric and autonomous vessels can be referenced. Liquefied natural gas (LNG) tanker Medium-term solutions The medium-term period will see further methanol advancement, with ammonia rising, as compatible engines become more available over the next two years. Long-term projection In the long term, green fuels (fuel produced from biomass sources through various biological, thermal and chemical processes) will be available alongside blue hydrogen, i.e. hydrogen produced from natural gas and supported by capture and carbon storage (CCS). CCS technology readiness is crucial both onboard and ashore. Classification societies are leading the way in evaluating nuclear power as an option for large commercial ships that can accommodate the technology. Simcenter simulation chain – setting sail Each step of the journey to achieving the net zero goal brings distinct engineering challenges to the ship's operation; to name a few: Gas dispersion After treatment Swinging in tanks Tank boiling (process of unwanted temperature increase in tanks that compromises the cryogenic state of the gas). Post-treatment to reduce and remove emissions (purifiers) Cryogenic gas leaks during refueling (refueling process) Trip planning – fuel generation and emissions profiles Simcenter STAR-CCM+'s multiphysics capabilities for hybrid multiphase modeling are being leveraged to provide simulation-based predictions for these problems in both concept design and forensic analysis. At a higher systems level, Simcenter Amesim enables analysis of engine and propulsion configurations with varying levels of detail and fidelity, extending to trip planning, fuel consumption and emissions profiles. Simcenter Amesim The first coastal ships are already sailing completely electric, while the nautical industry has begun to embark on its electrification mission. Simcenter Amesim, Simcenter Motorsolve and Simcenter STAR-CCM+ offer many standardized solutions to consider battery pack sizing, powertrain design or help prevent thermal runaway. Uncontrolled battery – Simcenter CFD simulation Big ships, zero emissions, ecological marine solutions Turning to the larger ships and workhorses of global commerce, we want to focus on how Simcenter suite simulation technology is helping engineers address short- and medium-term solutions for alternative fuels. Among the four pillars of viable fuel pathways, when it comes to ammonia, mitigating unintended consequences must be addressed early in implementation. LNG and ammonia are stored in a cryogenic state, which means that any exposure to environmental conditions, for example through leaks during fueling, will lead to instantaneous vaporization (flash boiling), putting the crew at risk and presenting numerous environmental hazards . The sudden boiling of liquid spray from a leaking pipe into the environment occurs because the ambient pressure is below the saturation pressure of the liquid fuel. Depending on the direction of the spray and the distance from adjacent structures, dispersed vapor cloud precipitation may occur: the impact of liquid droplets remaining from the spray, mostly vaporized, and therefore highly flammable. Case Study: Bunkering Fueling is a critical operation on board ships at sea or in port. Successful fueling requires the safe transfer of fuel to the ship's tanks without overfilling, spills or leaks. Simulation can help in the first stages of the supply process At the beginning of the fueling process is planning the trip to determine the amount of fuel to be supplied. Simcenter Amesim's marine library allows you to connect your engine and powertrain model to the voyage and maneuver simulation environment, accounting for hotel loads, auxiliary engine fuel consumption, wind, waves, and current effects on power characteristics. After determining the amount of fuel, including the reserves to be filled, planning begins as to which tanks will receive the fuel. Here, a model of the tanks, pipes and valves, ballast system and fuel intake through the supply itself is essential for predicting and monitoring performance and ensuring the desired hydrostatics of the ship. These items and action plans for leaks or spills are typically discussed at the pre-bunker conference – which can be digitally supported by rapid time models for quick responses to what-if scenarios. The key to success The Simcenter Flomaster simulation environment allows you to generate result envelopes for different supply scenarios, but can also be used upstream in the design phase to size pumps and lines to achieve the ideal time for filling, emptying and sounding tanks. Ultimately, critical metrics from the simulation can be automatically entered into the petroleum ledger in accordance with MARPOL Annex I. Avoid possible system failures and hazards The interest now is in possible system failures and dangers to the crew and the environment. Models can be configured to produce explicit responses to relevant regulations, for example IMO IGC and IGF codes for LNG. LNG is generally stored at around -162°C and presents cryogenic hazards such as frostbite and human skin burns, and fire and explosion risks during the transition to a gaseous state within the flammable range. In the case of ammonia, skin burns, irritation and inflammation of the crew's respiratory system and eyes may occur. High concentrations of gas in the air, especially in confined spaces, can lead to explosions or fatal results to human life. Learn how CFD simulation can help you analyze unintended consequences To better understand the dangers of flash spray boiling and gas dispersion, we analyzed the problem of refueling at sea, where we simulated the cryogenic dispersion of ammonia from a tube due to a leak during fueling. Using simulations with Simcenter STAR-CCM+, the complex physics of the instantaneous boiling of cryogenic gas dispersion can be studied. Metrics sought include the extent of the plume, the concentration of ammonia at certain points and whether or not rain will occur. While outdoor deck workers are unlikely to be exposed to fatal concentration levels exceeding 2,000 ppm for 30 minutes or more, stinging or burning sensations in the eyes and respiratory system may occur from exposure to as little as 70 ppm above. in the same time frame, according to the National Institute of Health. These levels are not unattainable within closed rooms such as engine compartments, which highlights the importance of employing simulation technology for risk assessment and countermeasure design. In our fictional supply scenario, liquid ammonia was discharged from a leak horizontally in the receiving vessel's supply infrastructure at a pressure of 8 bar, causing rapid dispersion into the environment. Over the course of 10 seconds, approximately 1 ppm can be measured in typical locations for work operations. No rain was detected on the deck, that is, the entire leaked mass passed into a gaseous state. Stay integrated – all hands on deck for a ecological marine future In this post, engineering problems related to ecological marine targets were presented, from conceptual design to onboard operation and assisting in the generation of mandatory documentation. There will certainly be implications of your specific component or problem studies for fundamental aspects of overall ship design. In the likely event that you become overwhelmed by the complexity and interconnectivity of spanning the design space, Simcenter HEEDS will provide nautical reference points for port solutions. Reveal the ultimate solution: Leverage your insights for the best results The role of Simcenter HEEDS is twofold. On the one hand, its workflow manager acts as a spider in the web of Simcenter CAE tools through real-time I/O mapping and administration. Additionally, its multidisciplinary design optimization can be leveraged in the subtool, holistic process, or a combination of both. Setting realistic optimization constraints and leveraging the powerful Simcenter HEEDS post-processing suite to gain key insights will be critical to a safe return to port. Time to anchor There is an ocean of engineering problems when it comes to the design and operation of ships and floating platforms, and Simcenter has many more tools available than those mentioned in the blog in question. Have you ever wondered about the safety and comfort of passengers on your speedboat? Simcenter Madymo is the beacon to follow. Move full steam ahead towards your ecological marine future using performance engineering integrated with Simcenter. If you are navigating towards a sustainable future in the maritime industry, it is time to act. CAEXPERTS is here to help you chart your course toward short, medium and long-term solutions for greener shipping. Join us for a strategic conversation about the challenges and opportunities that await, and discover how we can help you successfully navigate this new landscape. Schedule your meeting with us now and prepare for a journey towards a more sustainable future for our industry.

The iron & steel industry are highly material and energy intensive industries. Energy constitutes a significant portion of the cost of steel production, from 20% to 40%. Thus, improvements in energy efficiency result in reduced production costs and thereby improved competitiveness. Another challenge with the steel production is that the CO₂ emissions are high. On an average, primary steel plants emit three tons of CO₂ per ton of steel. The global best is 1.4 tons of CO₂ per ton of steel. In order to strengthen the green competitiveness and achieve the goal of low-carbon and clean production, Steel industry adopts four strategies of energy savings: (a) Increase the energy efficiency: waste heat recovery, enhancing the efficiency of energy system/equipment optimizing the operation and energy management. (b) Develop and utilize low-carbon fuels such as bio mass, (c) Maximize the value of fuel gas and (d) Develop the end-of-pipe technology such as CCS. Steel Production Process In the primary ironmaking process, the raw material like iron ore, coke, and lime are melted in a blast furnace resulting in molten iron (hot metal). The key methods are BOS (Basic Oxygen Furnace) and the more modern EAF (Electric Arc Furnace). In the Secondary steelmaking, the molten steel produced from both BOS and EAF routes is treated to adjust the steel composition. The secondary steelmaking processes involve Stirring, Ladle furnace, Ladle injection, Degassing, CAS-OB (composition adjustment by sealed argon bubbling with oxygen blowing). In Continuous casting the molten steel is cast into a cooled mold causing a thin steel shell to solidify. The shell strand is withdrawn using guided rolls and fully cooled and solidified. The strand is cut into desired lengths depending on application; slabs for flat products (plate and strip), blooms for sections (beams), billets for long products (wires) or thin strips. In primary forming, the steel that is cast is then formed into various shapes, often by hot-rolling. Hot rolled products are divided into flat products, long products, seamless tubes, and specialty products. Secondary forming techniques give the steel its final shape and properties. These techniques include cold rolling, Machining (drilling), Joining (welding), Coating (galvanizing), Heat treatment (tempering), Surface treatment (carburizing). Siemens’s Simcenter STAR-CCM+, a Computational Fluid Dynamics (CFD) based offering is used in Steel industry for (a) enhancing the efficiency of energy system and equipment (b) optimizing the operation and energy management (c) Analyzing and comparing various technologies for process optimizations. Simcenter STAR-CCM+ provides detailed analysis of fluid flow, heat transfer and other physio-chemical phenomenon in the equipment at the actual scale, and operating conditions which otherwise is not possible using experimental techniques. This technology gives detailed threedimensional understanding of the process parameters like flow pattern, temperature, mixing profile, chemical composition, heat transfer, combustion, chemical reactions, casting, etc. Simcenter STAR-CCM+ also offers a very robust Discrete Element Method (DEM) capability to model solid particulate flows. Basic Oxygen Furnace Basic Oxygen Furnace The basic oxygen furnace (BOF) is a part of the steel making process where pure oxygen is used to convert molten pig iron into steel by oxidizing carbon. In top-blown furnaces, a supersonic oxygen jet is blown through a vertically oriented lance onto the molten metal bath, creating a cavity at the bath surface. Important parameters are the resulting shape and size of this cavity because they contribute to the interfacial contact area between the oxygen and the metal. The fast decarbonization reactions at the molten metal / gas interface lead to the formation of carbon monoxide (CO), which may react with oxygen in the top space of the furnace to produce carbon dioxide. This latter process is generally referred to as the post-combustion reaction and is highly exothermic (ΔHR = -283 kJ/mol). In order to optimize the energy efficiency of the process and to increase the amount of scrap additions that may be remelted in the bath, there is a strong interest in promoting the post-combustion of carbon monoxide and the transfer of the energy released by this reaction to the liquid metal. Alternatively, bottom-blowing converters are used where the oxygen is injected at the bottom of the furnace. This is leads to additional agitation and mixing, similar to the results shown in the ladle section. Converter geometry, lance configuration, number dimension and positioning of the bottom inlets as well as the flow rates affect the flow field and therefore the oxidation process and this offers opportunities to improve the process and its efficiency. To simulate a top-lance BOF with a focus on the jet penetration and its interaction with the molten metal Simcenter STAR-CCM+ offers the Volume of Fluid (VOF) method as well as the EulerianmMultiphase model with a model extension to capture the free surface correctly, the so-called LargemScale Interface (LSI). Both methods support reactions in each phase and recently a surface reactionmmodel for VOF was introduced to consider reactions only at the free surface, where oxygen gets in contact with the carbon in the liquid melt. Case Set-up and description In the case presented here a pure oxygen jet from above interacts with the melt. The transient VOF simulation is done on a 2D axisymmetric domain with 125.000 hexahedron cells, assuming ideal gas behaviour for the gas phase. Both phases are modelled as multi-component. The gas phase consists of O₂, CO, CO₂ and N₂ while the liquid phase contains Fe and C. To model the decarbonisation, two surface reactions at the interface are applied, forming CO in the gas phase: C(l) + O₂(g) → 2CO(g) C(l) + CO₂ → 2CO(g) 2CO(g) + O₂(g) → 2CO₂(g) Figura 1: Left: Oxygen jet entering the BOF and penetrating the liquid melt. The black line indicates the free surface. Right: Red shows the liquid melt, blue the gas phase, yellowish color indicates liquid droplets. Results Simulation results in Fig. 1 show the deep penetration of the oxygen jet into the melt. Smaller and larger melt droplets are lifted up and splash against the wall. The depth and the form of the cavity is permanently changing since this case is inherently transient, resulting on the one hand in a larger surface area and on the other in an additional mixing due to these fluctuations. Fig. 2 shows the oxygen distribution in the gas phase. At the lance a pure oxygen jet enters the furnace. A part of the oxygen is consumed by the decarbonization at the free surface and another part is converted in the gas phase to carbon dioxide. A closer look to the free surface (Fig. 3 and 4) shows that a lower Carbon content is only found in the vicinity of the free surface. It also indicates that the wiggles are increasing the free surface and therefor the reaction rates significantly, since the lowest C content is found there. On the gas side, a higher CO mole fraction is found in the wiggles but also on the right-hand side close to the free surface. This is an area where the gas velocities are not that high (see Fig. 3) and CO is not transported efficiently into the bulk. Ladle Stirring In a ladle furnace, argon is injected through a refractory-lined lance or through a permeable refractory block in the bottom in order to maintain a uniform temperature and composition. A benchmark exercise for such a furnace is described below. The geometry used and further details are as specified by the German Steel Society’s (VDEh) 7th meeting in 2010. Problem Description The ladle holds 185t of steel at 1600oC. Argon is introduced from the bottom giving rise to heterogenous gas plumes causing the steel to be stirred. The goal of the simulation was to determine the time required to achieve complete mixing. Figure 5: Details for ladle stirring benchmark. Red region: slag and yellow region: the molten metal A volume-of-fluid (VOF) modelling method was used in STAR-CCM+ to account for the interface between gas and liquid. A discrete particle tracking algorithm to track the injected bubbles (with amRosin Rammler size distribution) and ideal gas law dependent density based on the height of the molten metal was used for the injected gas. Two-way-coupling with consideration of drag, lift and turbulent dispersion force is employed between the gas and the liquid phase. A numerical tracer is introduced to track the extent of mixing and the required mixing time. Results of ladle benchmark The results from this study are shown below in Figs. 6(a) to 6(c). Fig. 6a is showing a snapshot of the bubble distribution and rise in the domain. Figure 6b shows the velocity contours of the melt cause by the injection of the Argon jet, clearly showing a developing jet flow with velocity decreasing with height. The velocity magnitude was within 15% of the analytical results. Fig. 6c shows a pictograph from a water-based experiment on a scaled model of the ladle. It indicates that the flow filed matches the simulation results qualitatively (since no velocity measurements were performed in the water experiment). Fig. 7 shows that the mixing time results from simulation (⁓120s) compares well with those from experimental measurements (⁓120-140 seconds) indicating that CFD simulation allows detailed insights in to the flow behaviour. Further geometries can be investigated using simulation combined with an automated direct optimization approach to find an engineering solution to mixing. Figure 6: (a) Plume of rising bubbles (b) Argon jet velocity field (c) Photo of a scaled water experiment Figure 7: Comparison of time required for complete mixing with experimental values. Continuous Casting After a steel alloy has been manufactured, molten steel needs to be processed for further use. We can discern two kinds of wrought material following the steel production: either ingots that can be used down the line in specific shape casting processes or continuously casted steel rods of various cross section geometries. Production Challenges To ensure good overall product quality certain process aspects are key: (a) Transport and location of non-metallic inclusions and slag inside the ingot or strand (b) Temperature management of the alloy to ensure desirable metallurgical properties (c) Defects such as macro and micro shrinkage defects These aspects are closely linked to one another as well as the overall manufacturing efficiency. Thus, the continuous or ingot casting process is a conglomerate of different physical phenomena and engineering challenges involving Heat transfer (radiation, conduction and convection), Phase change (solidification in the metal & boiling due to spray cooling), Material transport, Joule Heating, Magneto Hydro Dynamics (stirring in the strand), Metallurgy including shrinkage defects, Chemical reactions (Exothermic sleeves and powders). Figure 8: Flow pattern during steel ingot solidification. Creation of alpha pore and shrinkage defects Problem & Results Using a pseudo transient approach, Simcenter STAR-CCM+ was used to predict the shell thickness along the strand as well as the position of the solidification tip. The validation work was based on the work of Ushyima where the shell thickness is analytically determined. The caster is assumed to be prefilled with superheated steel, the walls are set to be convective. Inlet speed is also given and at the outlet the casting speed is applied. Figure 9: Shell thickness validation for single strand caster. Left plot shows the comparison of results. Right plot shows the outline of the geometry after Ushijima The volume of fluid multi-phase approach is used to investigate the slag-melt- air interaction. Phase change modelling is enabled inside the VOF model. By expanding the computational domain beyond the fluid domain alone to include i.e. the mold or rollers the effect of assumptions in boundary conditions can be mitigated. Simcenter STAR-CCM+ has a set of criteria functions for defect analysis inside the cast part. Material properties are also key to accurately predict flow and solidification behavior inside the cast. The software’s open structure allows one to import own temperature depended material data or you use the materials on offer inside the dedicated metal material database. Results (Fig. 9) indicate that STAR-CCM+ can predict the shell thickness accurately and can be used to evaluate the casting process effectively.z. Conclusions Simcenter STAR-CCM+ has been used for the detailed analysis of basic oxygen furnaces, ladle mixing and continuous casting. Details including fluid dynamics, decarbonization reactions on the surface as well as oxidation reactions in the gas phase have been accurately modelled. The Volume of Fluid (VOF) method as well as the Eulerian Multiphase model with a LSI extension can be used to capture the free surface correctly. Siemens Simcenter STAR-CCM+ opens the door to further optimization and process improvement. Do you want to take the efficiency and sustainability of your steel industry to a new level? At CAEXPERTS, we can help you design energy-saving strategies and advanced technologies to reduce CO₂ emissions. Schedule a meeting with us and discover how we can help your company optimize processes, reduce costs and achieve your production goals in a more sustainable way. Don't delay, get in touch now and take the first step towards a greener and more competitive future!

For nearly 40 years, Simcenter Femap has been an essential tool for analysts to model complex engineering structures. The latest version, version 2401, includes several new features and improved functionality based on user feedback. Many of our customers use composite materials to reduce weight in their designs, and with new features in Simcenter Femap 2401, it is now easier to model composite structures. This includes having direct access to layups calculated through the Siemens Fibersim product . Layup Builder – Overview Simcenter Femap 2401 introduced a new, more efficient way to create composite finite element structures with different layouts. This is done through a new dockable panel called Layup Builder. In previous versions, creating composites required creating a Laminate property and a corresponding Layup to define stacking, followed by assigning that property to an area or region of the mesh. This process had to be repeated for all other areas. See how the new Layup Builder can provide a different approach and potentially a more efficient way to create composite finite element models. Layup Builder – Using external data The new Layup Builder dockable panel in Simcenter Femap 2401 offers an alternative to manually creating layups by providing the ability to define a general “Ply Stackup”. Once defined, any subset of lines in the Layup Stack can be applied to any part of the model to automatically generate the required layups. One method for defining a “Layup Stack” is to use data provided by another application. As seen in another video, Layup Stacks can be defined manually or loaded from an existing layup, but this video focuses on the “Attach composite HDF5 file” method. Incompressible fluid splashes There are two essential aspects of unrest: (a) predicting its onset and (b) mitigating the effects of unrest once it begins. Avoiding splash-inducing resonance will also reduce liquid pressure on the walls of the container. However, a side effect may be that the vessel is tuned to a resonance that could cause catastrophic failure. Therefore, to avoid splashing and reduce the risk of container failure, it is best to consider the coupled effects of the liquid and container to determine the coupled hydroelastic modes. This technique ensures that the modes that initiate oscillation and failure do not occur. Simcenter Femap 2401 includes extended support for incompressible fluid dynamic analysis. While previous versions of Simcenter Femap included support for modeling incompressible fluid implicitly as a virtual fluid mass, Simcenter Femap 2401 allows users to model incompressible fluid explicitly as a fluid mass defined with solid elements. The defined fluid mass will allow users to model complicated fluid volume shapes and extended fluid volume types, such as volumes with splash-free surfaces. We can use these features to calculate the coupled hydroelastic modes of the structure. Analysis Set Manager Simcenter Femap 2401 makes it easy for ABAQUS users to configure their analyzes using familiar terminology and methodologies. Additionally, improvements have been made to the Simcenter Nastran Multi-Step Nonlinear Structural Solution (Sol 401) due to the large number of strategy parameters it uses. Improvements in quality of life To make the functionality more discoverable, Simcenter Femap implemented a Command Finder in version 2301, enhanced it for version 2306, and improved it again for version 2401. Would you like to maximize your efficiency in modeling composite structures with Simcenter Femap 2401? Schedule a meeting with us at CAEXPERTS and discover how new features like Layup Builder and extended support for incompressible fluid dynamic analysis can optimize your designs. Don't miss the chance to explore these innovations and boost your productivity. Get in touch now!

Since Gordon Moore, co-founder of Intel, postulated the law that bears his name about doubling the number of transistors every two years, there have been dramatic improvements in the computational capabilities of electronic devices. Reducing component sizes coupled with increased demand for computing power has resulted in ever-increasing power densities, requiring optimized and advanced cooling configurations to maintain a safe operating temperature. Electronic thermal management is a separate topic and beyond the scope of this blog. However, I would like to discuss one of the consequences of increased electronic performance – noise! Anyone who works during the summer in an office is no doubt accustomed to their computer or laptop fans spinning as the number of applications running in parallel increases, or even more fun, getting to run advanced Computational Fluid Dynamics (CFD ) or Simulation using the Finite Element Method (FEM). Fan noise, while simply considered an unavoidable inconvenience, is the result of a complex interaction between the fan itself and the airflow it generates. For this reason, it can sometimes be called flow-induced noise or aeroacoustics. Despite the need to properly cool all these electronic components in the cramped space of a modern laptop, people have come to expect the noise generated to be non-intrusive. Noise-canceling headphones can help you here, but they are far from an ideal solution during a hot summer day. What's more, acoustic performance has become one of the key indicators of high-quality laptop brands – combining the gentle hum of fans with a set of clear, vibrant, well-placed speakers that play your favorite tunes. This puts a lot of pressure on the engineers who develop these systems. Let's discover how state-of-the-art acoustic simulation tools can help dedicated engineers predict acoustic performance earlier, faster and more reliably. The inevitable “bad” sound… When analyzing the noise signature of a fan, there are typically two components, tonal noise and broadband noise, as shown in Figure 1. Tones can be clearly visible as higher sound pressure levels resulting from periodic interactions of the incoming air. with the fan blades (blue circles). The broadband noise component is caused by random loading forces on the blades that can be induced by factors such as turbulence ingestion or boundary layer development (green line). Figure 1. Free-field response detailing tonal peaks (blue circles) and broadband noise (green line) Considering that fan noise is the result of the interaction between aerodynamic flow and acoustic wave propagation, both airflow and acoustics need to be simulated. Acoustic wave propagation can be included directly in a CFD simulation already used to evaluate the design's cooling performance, but this – although possible – can present significant challenges. These challenges are mainly caused by the significant differences in length scales between the acoustic waves and the flow. This means that high-order physics schemes and exceptionally long calculation times are required, so this approach is not always viable. Hybrid approaches have been developed in response to this, in which sound generation and sound propagation are separated. CFD data is used to reconstruct sound sources due to flow effects, while acoustic simulation models are used to propagate sound waves caused by these sources. This offers the advantage of enabling more efficient low-order flow simulations and taking advantage of efficient acoustic resolution technologies. Figure 2 illustrates how a model is prepared for an acoustic analysis showing the air finite element mesh around the laptop (2A.), the internal mesh (2B), the connections between the inside and outside, the ventilation openings (2C) and the inlet grille under the laptop (2D). The next step in an acoustic analysis is to define the source region – this can be obtained from CFD or directly from the test data. The equivalent acoustic source is calculated using Simcenter 3D and introduced into the FE model. Once resolved, the sound field generated within the laptop and radiated from it can be analyzed. Simcenter 3D allows the acoustic engineer to understand how sound leaves the laptop, its direction, and also reflections from the immediate environment. Figure 2. FE mesh for acoustic simulation of a laptop: 2A the air around the laptop; 2B the internal mesh of the laptop geometry; 2C the laptop openings and 2D the entrance grille. Notebook OEMs need to understand the sound generated by the cooling architecture and investigate ways to minimize the impact on the user, such as directing noise away from the user through a rear-facing jack. Additionally, sound engineers can understand how the laptop screen shields some noise at various screen angles and user positions, as well as in the closed position if docked or connected to other displays. … and the much sought after “good” sound As mentioned in the introduction, the sound quality of a laptop is considered an indicator of the brand's high quality. Therefore, it is pertinent for the engineer to understand the behavior of the speaker and how it works in the laptop chassis. To optimize sound and maximize quality for the user, the engineer must start with the notebook's stand-alone speaker and work through subsequent integration into the notebook chassis to the notebook's behavior in a realistic user environment – ​​see Figure 3. Figure 3. Acoustic simulation steps to ensure the fidelity of results at the operational level when the product is in use. At the speaker level, as in all simulations, a geometry is defined from which the FE model is created and merged. This structural vibration model of the speaker is then coupled to a small volume of air near the speaker membrane. Specific acoustic radiation conditions are applied to the external surface to allow prediction of far-field sound radiation characteristics. Simplified 1D models based on the Thiele-Small model are used as inputs for the coil loads. These models contain all relevant electromagnetic coupling effects in the speaker driver, and their input parameters are easily obtained from the supplier (or from simple measurements). After solving the model, the sound radiation can be analyzed and post-processed to provide directivity data, impulse responses, and distortion data. Figure 4 provides a graphical representation of this typical workflow. Considering the performance of the speakers and the association with the perceived quality of the laptop, the engineer would be interested in quantifying the intensity of the acoustic source and the uniformity of the speaker's sound field. The image on the right of the video above visualizes the radiated sound waves. The next step is to understand how integrating the speaker into the laptop affects acoustic performance. In a laptop, the behavior of the speaker is strongly influenced by the coupling of the speaker membrane with the volume of air behind it and by the viscothermal effects that occur in the grilles that cover and protect the speakers from dirt and dust. The speaker model in the video is therefore extended to also include the back of the speaker membrane to model the interaction with the rear cavity inside the laptop and the effect of the grille and air volume between it and the speaker membrane, as shown in figure 4. Figure 4. Visualization of a possible laptop speaker configuration illustrating the air volume or rear cavity behind the speaker and speaker grille. The grid effect can be explicitly simulated by: Model the fluid in the holes and apply specific visco-thermal properties of the fluid or Using simplified equivalent transfer admission relations. Figure 5. Comparison of speaker performance before and after installation. Figure 5 illustrates the effect that installation conditions can have on speaker performance after you integrate it into your laptop. For the isolated speaker, the left image in Figure 6 shows that the speaker source intensity is uniform above one kilohertz. In comparison, the image on the right of Figure 6 illustrates a performance degradation above one kilohertz. There is very low sound radiation between the frequency range of four to six kilohertz and this is explained by the interaction between the speaker membrane and the resonance found in the rear cavity. This is a more realistic assessment of the performance of the speakers in the laptop and provides design engineers with valuable information to further optimize their product. The final step in the process is to evaluate how the laptop will perform in the intended user environment – ​​a typical office, for example. However, doing this with a finite element model would require significant time and computing power. An alternative method is to use Ray Acoustics, one of the advanced acoustic solvers available in Simcenter 3D. This technology is based on ray tracing, allowing us to effectively simulate the propagation of sound in wide spaces, over long distances and at high frequencies, much faster than finite element or boundary methodologies ever could. The model discretization and solution times are independent of frequency, making it perfect for solving problems where the geometry is larger than the acoustic wavelengths. Simcenter 3D provides frequency and time domain results as output from this solution. To simulate the office environment, three main modeling features are available in Simcenter 3D: Edge and surface diffraction – useful for typical dividing walls in an office environment Curvature effect correction – accurately captures discretized and mesh surfaces Absorption – surface and air absorption Particle tracking – takes into account late reverberations and diffuse reflection effects typically found indoors The lightning acoustic simulation model can directly calculate sound quality parameters such as reverberation times, clarity values ​​or sound transmissibility indices. Simcenter 3D can also directly incorporate binaural effects into the acoustic response without the need to model the human head – essentially obtaining the sound pressure levels that the listener's left and right ears experience. Figure 6. Typical office environment with visualization of sound propagation – individual ray paths are visualized and the binaural impulse response Figure 6 (left) illustrates a typical office environment with all reflective or absorbent surfaces discretized using a simulation mesh (gray surfaces). The microphone surfaces near the laptop and the subject's head are set to visualize the sound fields, as seen in the upper right corner of Figure 6. Ray tracing models provide information about how different speaker combinations perform. spread to the person's ear. A clear view of how much sound is radiated to the user and how much is being reflected from different surfaces can be unlocked using these ray tracing visualizations. Putting it all together – a cacophony or a symphony? All simulation steps discussed provide quantitative and visual information about the acoustic performance of the individual component through to product integration and incorporation into the real-world environment. However, despite everything, isn't it better to be able to hear the results of the simulations? Simcenter 3D Acoustics offers a sound processing and auralization tool that takes simulation results and combines them with measured sounds, like music, to create acoustic scenes you can hear! Only fan noise Fan noise + low-cost speaker Fan noise + high-end speaker The videos above allow you to test three different scenarios from a laptop: Fan simulation noise A piece of music played in the office environment using a low-cost speaker The same song played on a high-end speaker. In the first scenario, both tonal and broadband components of the noise are present – ​​auralization allows you to check how loud the sound sounds and how irritating or distracting it can be. In scenario two, one can investigate how some music can mask the sound – the fan noise is masked, but some low-frequency components of the music are missing. Scenario three employs a state-of-the-art speaker, providing much clearer and richer sound to the music. Simcenter 3D Acoustics allows you to understand the sound quality and noise of your electrical components. With these features, you can design around inherent noise and give the user of your products a more pleasant listening experience. Interested in optimizing the acoustic performance of your electronic products? Schedule a meeting with CAEXPERTS now and discover how our state-of-the-art acoustic simulation tools can help you predict, understand and improve the sound behavior of your devices quickly and reliably. Don't let noise get in the way of the perceived quality of your products - let's work together to ensure an exceptional listening experience for your users. Schedule your meeting today!

You don't need us to tell you that the planet is getting hotter. In our humble opinion, the greatest engineering challenge of our time is converting the systems that helped create the world as we know it into sustainable products. With Application Engineering for Combustion CFD, we help many customers across multiple industries simulate the burning of methane, propane, gasoline, diesel, and more. Of course, the goal is always to use simulation to design efficient combustion systems that minimize emissions and maximize performance. However, for these combustion systems, internal combustion engines, gas turbines and process burners, the heat is turned on to reduce their carbon footprint. Excellent design of combustion systems that burn fossil fuels can only get you so far. A major focus for engineers is now to adapt or design from scratch combustion systems that burn alternative fuels such as electronic fuels, hydrogen or ammonia. Clean energy The decarbonization of the automotive industry is what we imagine comes to most people's minds when considering the “cleaning” of combustion systems. There are many articles and columns discussing the long debate between internal combustion engines (ICEs) and battery-powered vehicles! We won't add anything here (except the fact that Simcenter STAR-CCM+ is the tool to design both). Ultimately, ICEs will be needed to advance industries where batteries are not viable and if they can function in a way that produces negligible CO₂ emissions, then they should be part of the mix in the future of transportation. Fortunately, Simcenter STAR-CCM+ has been adding tools to ensure that simulation can be leveraged to design such systems. And so, over the past few years, Simcenter STAR-CCM+ has been continually improved to enable the analysis of new fuels and emissions. Fuels proposed for use in In-Cylinder applications may have different fundamental reactive properties. An important example is Laminar Flame Speed ​​(LFS). In Simcenter STAR-CCM+ you can directly calculate the LFS for any fuel mixture and use it with Flamelet, ECFM and Complex Chemistry combustion models. Below we can see an example of an ICE using a mixture of Gasoline and Hydrogen as fuel, with the simulation being carried out using Simcenter STAR-CCM+ In-Cylinder Solution: The methodology allows a quantitative prediction of gross emissions depending on the hydrogen fraction: Exhaust emissions for different fuel mixtures at equal Qth. Naval applications Of course, the shipping industry is not immune to the need to burn cleanly. Maritime transport is responsible for around 2.5% of all greenhouse gas emissions, but it is essential as 90% of all global goods are transported this way. While there may be use cases where electrification is a viable approach, for large operators, batteries (alone) may never be the solution. Engineers designing marine propulsion systems are having to rock the boat with the use of conventional fuel and explore other (decarbonized) fuels during the design process. Ammonia and fuel cell engines can reduce carbon emissions One of these options is the use of Ammonia. Ammonia can be burned without generating CO₂ and is relatively easy to store, making it a good candidate as a future fuel for the shipping industry. Once the logistics (distribution, availability) of ammonia are resolved, it could be the number one topic for the development of internal combustion engines in the near future. However, despite the potential, ammonia has its own challenges, such as the need for high ignition energy. For this reason, ammonia can be used in conjunction with small amounts of diesel to start the combustion process. Ultimately, this still provides much cleaner combustion than traditional use of fossil fuels. Simcenter STAR-CCM+ can be used by designers to understand this process. In the example below, Ammonia and Diesel jets are studied at various injection times and angles. Under certain conditions, for example insufficient or too strong interaction between the two fuel sprays, misfires may occur. Being able to accurately simulate this reduces the need for extensive testing and allows for a detailed understanding of how to design to avoid such a scenario. Using the Complex Chemistry combustion model, excellent prediction of misfire occurrences as well as regular combustion can be predicted. How green is your simulation? Most industrial CFD simulations rely on High Performance Computing (HPC) and crunching the numbers requires energy that inevitably carries its own carbon footprint. This article from the British Computing Society highlights the challenge and states that CO₂ emissions from HPC data centers are expected to grow by 2 to 9 times over the next 10 years. The obvious course of action is to clear the energy that powers your CFD simulations, but of course this is probably not within your control and furthermore leaves us with nothing to do! With the latest versions of Simcenter STAR-CCM+, combustion engineers can now leverage GPU-native Flamelet combustion modeling. Leveraging GPU hardware allows engineers to run their simulations using significantly less power, reducing emissions and costs, as well as achieving faster responses (a rare win-win situation). So let's take a combustion system, in this case a pressurized annular combustor, and add some hydrogen to the fuel to reduce the CO₂ emissions generated. Great, but nothing in life is free, and we've talked in the past about how the simple act of adding hydrogen can disrupt the thermoacoustic stability of the combustion system. All is not lost as this system can be analyzed using high-fidelity LES combined with the Flamelet Generated Manifold combustion model to accurately predict thermoacoustic behavior. And even better, all of this can run natively on GPUs. The 50% reduction in computing time is evaluated here by comparing a 640-core CPU solution (commonly used CPUs with 32 cores per CPU node, 2.4-3.3 Ghz, 256 MB L3 cache) with a of GPU on 8 NVIDIA A100 cards. The end result is a solution that is 50% faster and consumes 60% less energy, in addition to being 42% cheaper. Even more importantly, the frequencies of thermoacoustic instabilities generated due to hydrogen addition are also excellently predicted and can therefore be eliminated or mitigated: Predicted and measured thermoacoustic spectra for a pressurized annular burner with CH4/H2 flame What we have here, folks, is a case of Simcenter STAR-CCM+-inspired carbon emissions creation : we save on emissions while designing to save on emissions! Interested in designing cleaner, more efficient combustion systems to reduce your carbon footprint? Schedule a meeting with CAEXPERTS today and find out how we can help you meet application engineering challenges for combustion CFD. With our experience and the advanced tools of Simcenter STAR-CCM+, we can explore sustainable solutions for your projects, from simulating alternative fuels to optimizing marine propulsion systems. Don't waste time, get in touch now!

Increase simulation speed, performance, and reliability. Enhancements to Solid Edge Simulation and Simcenter FLOEFD for Solid Edge increase simulation performance and speed with improvements to meshing, structural analysis, and interoperability. The new compact IGBT model makes it easy to incorporate electronics into your simulation studies, while the Cartesian Mesh Generator and improved mesh quality checks enable faster meshing and simulation workflows, resulting in a mesh speed of two to three times faster. Solid Edge Simulation Increased interoperability allows Solid Edge Simulation users to import solid temperature results from a Simcenter FLOEFD study into Solid Edge. A new command within Solid Edge Simulation's "External Loads" option, "Import Solid Temperature", is now supported, in addition to the previous commands "Import Fluid Pressure" and "Import Fluid Temperature". This command is only available with linear static studies and is useful for finding thermal stresses and strains in solids. The new option to apply force at any user-defined point allows greater control of simulation studies. The option has been added to the Force command bar, allowing users to apply forces to any 2D or 3D point in geometry, increasing capabilities alongside the traditional "Point" option that supported vertex selection. The visualization of mesh quality controls has been improved to facilitate the identification of areas of poor quality. Colors are now clearer and easier to decipher, and users can increase efficiency by being able to detect errors instantly. Users can also change the filled color of failed elements in the "Check Element Quality" dialog box for better visibility. Simcenter FLOEFD para Solid Edge Compact IGBT model and Cartesian mesh generator The Insulated Gate Bipolar Transistor (IGBT) compact model is now comprised of compact electrical element and two-resistor (2R) component models, providing an efficient representation of the IGBT element. The IGBT element can be described by specifying junction thermal resistances up or down. A set of IC plots for different temperature values ​​can also be defined for detailed analysis and characterization by users. The IGBT edit definition dialog box allows users to easily add the model to a specific analysis. The junction temperature is used to determine the Electrical Power from the IV graph, which is then applied to the model through the 2R component. The Cartesian mesh generator in Simcenter FLOEFD for Solid Edge ensures optimized performance, providing faster meshing while using fewer resources. With accelerated operations, including smart printed circuit board (PCB) importing and meshing, overall efficiency is improved with faster simulation and meshing workflows. Enhanced visualization capabilities and continuous updates after parameters are changed further enhance the overall workflow. Enhanced structural analysis Simcenter FLOEFD for Solid Edge can be connected to the Nastran Simcenter 3D (SC3D) Solver, unlocking the power of nonlinear analysis. The SC3D Nastran solver 401 introduces additional settings in the Calculation Control Options, allowing you to fine-tune simulations. Settings include adjusting scratch memory, refining contact mode, controlling solver steps, setting end time, and exploring large displacement scenarios. The enhancements also provide greater flexibility and control in nonlinear analysis and greater accuracy when working with large displacements. Tolerance-based contacts enable accurate simulations with enhanced contact options. Tolerances can be specified to create gapped body contacts, linear and angular tolerances can be defined, and glue contacts can be created seamlessly to ensure accurate and reliable simulation results. The User Defined Maximum Aspect Ratio in Local Mesh feature enhances the structural mesh with greater accuracy. By specifying maximum proportions for specific components, efficiency can be improved with greater control over the meshing process, especially for thin structures. Additional Enhancements With the powerful Component Explorer, users can manage component attributes, experience simplified organization, and employ efficient component management. Thermal component lists can be exported and imported, allowing easy editing of properties such as material, volume source value, two resistor power (2R), and light-emitting diode (LED) current. Users can simply export the list of components to Microsoft Excel, make the necessary changes, and then seamlessly import the list, simplifying their workflow. Teamcenter FLOEFD item customization offers greater flexibility and adaptability. Users can customize the Simcenter FLOEFD data model for Solid Edge to align with specific requirements and conveniently store FLOEFD data model files using local storage or Teamcenter storage. This customization can also seamlessly integrate FLOEFD into an existing data management system. Simcenter FLOEFD 's enhanced Linux solver for Solid Edge now supports co-simulation with Functional Mock-ups (FMUs) exported from other software, enabling integrated and comprehensive analysis. This solution ensures smooth compatibility and allows users to leverage all essential information stored within the FMU exported from FLOEFD, including model geometry. Increase the efficiency of your simulations right now! With enhancements to Solid Edge Simulation and Simcenter FLOEFD for Solid Edge, you can experience a significant increase in the speed, performance, and reliability of your analyses. Schedule a meeting with CAEXPERTS today and discover how we can optimize your simulations for guaranteed success.

The launch of HEEDS 2310 brings new and updated technology designed to speed up and streamline your optimization and design space exploration journey. With a significant focus on accelerating speed without compromising accuracy, this release marks a significant advancement in achieving optimal design results. Additionally, the integration of advanced AI capabilities and seamless data management functionalities ensure a progressive and intuitive experience for users across multiple industries and applications. Read on to discover how these new HEEDS capabilities, like new AI integration, data import improvements, and refined portal version management, will lead you to discover better designs, even faster! Go Faster: HEEDS AI Simulation Predictor HEEDS AI Simulation Predictor is a revolutionary feature of the HEEDS 2310 – a performance booster for SHERPA. HEEDS AI Simulation Predictor is a companion module for HEEDS, powering SHERPA with AI to enhance its state-of-the-art research technology to operate at even greater speeds. This accelerator is aimed at HEEDS users looking to streamline their search processes for time-consuming CAE analyzes or when time-consuming optimizations need to be performed. HEEDS AI Simulation Predictor empowers users, enabling precision-aware AI as part of the hybrid-adaptive research framework, to actively learn and improve current research, as well as learn for future design processes. Provides a significant reduction in project optimization time while maintaining the same project budget where applicable. Comparable results to SHERPA are possible, with additional potential for even faster performance. The best just got even better! Save up to 40% in computational time for time-consuming optimizations! Furthermore, this new technology allows the reuse of previous data, providing valuable information for the design of new products and systems, ultimately saving time and costs. You don't need AI experience – this cutting-edge technology integrates seamlessly into your existing workflows, accelerating computationally intensive CAE simulations around the SHERPA research framework. HEEDS AI Simulation Predictor allows you to complete tasks faster or run more simulations in the same period of time. In either case, by leveraging HEEDS you can now discover better designs, even faster! Explore the possibilities: HEEDS POST improvements Importing external HEEDS POST data into the HEEDS 2310 streamlines design decisions by seamlessly integrating external data into the postprocessor. This versatile feature allows you to immediately import or append data, leveraging HEEDS POST post-processing techniques without the need for a HEEDS project . With this release, HEEDS POST becomes a standalone data analysis and post-processing tool for working with data from anywhere. Facilitate data mining, gain insights and discoveries, report your findings, export your learnings, and generate reduced order templates for HEEDS MDO or external use. This expansion to easily incorporate data from non-HEEDS project sources extends data applicability support, empowering informed engineering decisions and revealing valuable insights for robust projects. Stay integrated: HEEDS portal versions In HEEDS 2310 , process automation takes a leap forward with the introduction of portal versions. HEEDS is recognized for its process automation capabilities, anchored in portal technology, which automates the parameterization, execution and extraction of results from simulation tool models. Configuring portals in HEEDS is a simple task, just specify the location of your tool and the main options for your workflow. However, what if you are dealing with multiple versions of the same tool or have different versions on various computing resources? HEEDS 2310 addresses these issues, with a simplified solution through support for portal versioning. Easily configure any tool version for local and remote execution, define specific versions for chosen compute resources, and quickly deploy the required version. Now with portal-specific version specification across multiple features, it's easier than ever to incorporate your tools into simple and complex workflows. This feature gives you the flexibility to select the appropriate version of the portal for your workflow and computing resource, simplifying your workflow with computing resources. Conclusion HEEDS 2310 was created to revolutionize your engineering design journey in a way that is not just an improvement, but a true game changer! Go faster by leveraging the power of SHERPA and AI acceleration. Explore possibilities by unlocking expanded data capabilities to discover valuable insights. Stay integrated by simplifying portal management to streamline your workflow with your computing resources. Discover better designs, even faster, with HEEDS 2310 ! Harness the power of AI with HEEDS AI Simulation Predictor, simplify your data analysis with HEEDS POST, and optimize your workflow with HEEDS portal releases. Schedule a meeting with us at CAEXPERTS to discover how the new features in this revolutionary release can accelerate your optimization and design processes. Don't miss the opportunity to discover better designs, even faster. Get in touch now to schedule your meeting and boost your engineering journey!

CFD simulation embedded in CAD New version of Simcenter FLOEFD 2312 software enhances CAD-integrated CFD to reduce preprocessing activities, accelerate electronic thermal design workflows, while adding new capabilities for structural analysis and an application programming interface (API) improved for simulation automation. Read below for information about these and new features, such as faster convergent geometry CFD meshing, improved speed for smart PCB thermal modeling, PCB reflow oven modeling, and more. PCB Reflow Oven Thermal Process Simulation In a PCB reflow oven, as a PCB moves along a conveyor, it is exposed to heating and cooling zones with different airflow speeds and temperature parameters. The parameter values ​​of these zones, as well as the conveyor speed, must be chosen by the PCB customer prior to manufacturing. The operation design challenge is to increase conveyor speed to achieve the highest throughput while meeting thermal constraints to prevent damage to components mounted on the PCB. Experimental approaches to determine these parameters are expensive because failed attempts lead to lost time, reduced product quality, or low yield. Simulating the reflow oven process to optimize operating parameters prior to physical testing is very advantageous. In Simcenter FLOEFD 2312, a design template has been added so that you can create and modify a PCB reflow oven simulation as a transient study to reflect conditions as a board moves through an oven. The model leverages the project parameters functionality in Simcenter FLOEFD and the new EFDAPI automation features are used to modify parameters. The approach simulates the reflow process within a small volume space around the PCB with moving flow boundary conditions, rather than simulating the real furnace with moving bodies. Watch this video to see indicative steps in setting up and running a PCB reflow oven thermal process simulation. Note: Advanced use of this new feature combines Simcenter FLOEFD and the Simcenter HEEDS design exploration and simulation automation tool for extensive optimization studies. PCB Thermal Analysis: EDA Bridge Autonomous Thermal Territories The fidelity of localized PCB thermal modeling provides the accuracy advantage for modeling copper and layers beneath critical components. This computationally efficient solution remains a good alternative to explicit modeling applied to an entire board. Previously in Simcenter FLOEFD, thermal territories were defined centered on a single component and with a defined aspect ratio. Now in Simcenter FLOEFD 2312, users can specify an independent thermal territory that can be placed anywhere independently on a PCB and then define its aspect ratio. This allows localized modeling fidelity to be defined to cover areas with groups of components more easily. Users define the following settings and then select the modeling level: 1) Location (X and Y) 2) Size (Length and Width) PCB thermal analysis: EDA Bridge script Users can now record and playback scripts that capture the workflow in the main EDA Bridge window, where you process imported ECAD data. Functionality that can be recorded and performed includes actions such as changing the plate shaping level and creating thermal territories. Scripts will be improved in subsequent versions from Simcenter FLOEFD 2312 onwards. Thermal Modeling of Electronic Components: Package Creator Updates What is Package Creator? The Package Creator utility in Simcenter FLOEFD allows engineers to quickly and easily create thermal models of IC packages based on 3D CAD geometry in minutes from a list of model guides for common package families. These detailed models can then be used in electronics cooling simulation studies in Simcenter FLOEFD. In Simcenter FLOEFD 2312, the following updates have been implemented in Package Creator: – 2 new initial IC package models: Flip Chip CBGA and Wirebond CBGA. – Creating detailed Simcenter Flotherm-ready models that you can export to share with other organizations Structural Analysis Enhancements in Simcenter FLOEFD 2312 Structural: Mesh Boolean operation to easily handle complex geometry Certain complex geometry models can sometimes create problems whereby Boolean operations simply cannot be completed using Boolean CAD processes, or in other cases Boolean preprocessor approaches can be very time consuming. A new, improved structural mesh generator and geometry preparation now supports Mesh Boolean for structural analysis meshing. This provides a solution that allows engineers to create meshes more quickly and automatically, even for extremely complex geometries. Structural: Nonlinear materials The engineering database has been enhanced to be able to define engineering stress-strain curves for solid materials in Simcenter FLOEFD, to combine with leveraging the existing capabilities of the Simcenter 3D Nastran solver to perform an analysis. As a reminder, the Simcenter NASTRAN nonlinear solver connection to Simcenter FLOEFD was introduced in version 2306. Structural: Large deformation modeling A new option can now be selected for large deformations by activating the corresponding option of the Simcenter 3D nonlinear Nastran solver. Simcenter FLOEFD 2312 now allows recalculation of engineering stress-strain to true stress-strain. This provides more accurate results for analysis where large strain values ​​are reached. Structural: Improved general contacts Using Simcenter FLOEFD and leveraging the Simcenter 3D Nastran nonlinear solver when modeling general contact types now means that contacts can appear and disappear during the iterative calculation process as a result of body deformation. In previous versions of FLOEFD, contacts were created before starting the solver and could not be changed, appear or disappear for deformed bodies. Faster CFD Mesh for Converged, Faceted, and STL Geometries Meshing is now accelerated for convergent, faceted, and STL geometries, so it is as efficient as meshing for parametric solid geometry. An example below being 10x faster for a vehicle model that was converted from STL data as a convergent body for an external aerodynamics study. Simcenter FLOEFD with mesh size of 62 million cells. Comparing mesh time: In the previous version 2306 = 2 hours Now in version 2312 = 12 minutes Smart PCB Thermal Modeling – Fidelity and Speed ​​Improvements The Smart PCB feature is one of several options for PCB thermal shaping. It is a sophisticated approach to efficiently capture the detailed material distribution of a PCB without the additional computational resource and time penalties typically required to explicitly model the PCB. This is done using a grid assembly approach, where a voxel-style grid is generated based on images of each PCB layer in imported EDA data. In Simcenter FLOEFD 2312 , the solver speed for Smart PCB calculation has been significantly optimized so that you can better leverage this modeling option for even faster, high-precision PCB thermal analysis. Additionally, this speedup of the solver allowed changing the default settings for the number of blocks on a PCB. Settings now go from the default 100 to 300, which in turn produces a more accurate solution, especially when using the “Fine” modeling option. The solution times results for 3 different models are shown below comparing the fine and medium settings for the number of parts defined, both in Simcenter FLOEFD 2312 and the previous version 2306. The illustrated solution times show a speed increased by a factor of 1.5 times to 8 times is possible, which is advantageous to perform accurate PCB thermal studies in less time. Clearly, the size and complexity of the PCB is a factor in the possible speedup, as one would expect. You can also notice the significantly shorter solution time for a Smart PCB to solve compared to an Explicit PCB template. Automation – EFDAPI is an enhanced API to speed up your process The new EFDAPI has been introduced and now covers all existing features and parameters in Simcenter FLOEFD . Enhanced functionality and greater ease of use allow engineers to leverage automation to reduce simulation workflow. Consider the case of automating the electronic cooling simulation of a Boost Converter The following short video illustrates the automation of the following steps Run CAD and open the model Create FLOEFD project Configure all boundary conditions and simulation settings Run the simulation and post-process the results Post-processing batch results without opening CAD Typically using CFD embedded in Simcenter FLOEFD CAD in normal operation, a project needs to be opened and the results need to be loaded to create resulting images and spreadsheets. Creating them automatically after calculation uses the “Batch Results Processing” tool. Batch processing of results is now possible without opening CAD. Now you can: – use command line execution export that generates the files needed for batch processing of results on Windows or Linux machines – run the solver on the remote server and batch process the results on the server at the end of a solution automatically, without copying the files back to the client In this short video below, the steps are illustrated: SCD5 Export Support for Simcenter 3D Simcenter FLOEFD fields can now be exported in Simcenter 3D SCD5 format. This results in a binary file for transferring data from FLOEFD to Simcenter 3D. This means that there can be a significant file size advantage using the SCD5 binary format. This helps in transferring fields from a thermal analysis to a thermomechanical stress analysis in Simcenter 3D. You can export steady-state or transient pressure and temperature fields to a CGNS file using the SCD5 mesh file as input data. Simcenter FLOEFD scene files can now be saved in JT format. This allows you to view Teamcenter simulation results using its viewer (which uses the JT format). Would you like to optimize the thermal performance of your electronics projects? With the new version of Simcenter FLOEFD 2312, you can drastically reduce preprocessing time and speed up your project workflow. From advanced structural analysis to intelligent PCB thermal modeling, this enhanced software offers a range of possibilities. Schedule a meeting with CAEXPERTS today to find out how we can help boost your simulation efficiency and accuracy.

Take advantage of integrated SPH technology. Faster with more GPU hardware options. Run turbomachinery CFD faster and more accurately. Model the complexity of tightly coupled fluid-structure interactions. Plus, many more features. With the release of Simcenter STAR-CCM+ 2402, engineers across all industries are provided with computational fluid dynamics (CFD) capabilities to accelerate the modeling of today's complex products. Leverage exciting new capabilities to explore engineering possibilities and turn complexity into a competitive advantage. Run faster, more accurate industrial axial turbomachinery simulations Making turbomachinery blade passes with polyhedral meshes leads to a comparatively high cell count. This typically manifests itself in increased run times in turbomachinery aerodynamic simulations. As the main solution, structured meshes were previously introduced in Simcenter STAR-CCM+. This allows for faster response time for axial machines, making the mesh smaller compared to polyhedral and allowing for faster simulation time. The structured mesh also provides high-quality flow-aligned cells in the main blade passage, providing faster simulation convergence and greater solution accuracy. With Simcenter STAR-CCM+ 2402, the structured mesh capacity of the turbomachine with blade fillet support will be further expanded. These fillets can be on the top or in the center. A seamless user experience is guaranteed with the fillet being automatically detected as part of the blade surface input without any additional input. Overall, the structured mesh of the turbomachine, together with automatic fillet support, leads to even greater accuracy and faster solution time without any additional effort from the user. Tackle highly dynamic fluid loads that lead to large solid deformations For applications where there is a strong bidirectional coupling between a dense fluid and a very flexible structure, convergence and stability of a CFD simulation are very difficult to achieve. With Simcenter STAR-CCM+ 2402, a set of new features are being introduced that enable exactly this type of complex fluid-structure interaction simulations, where highly dynamic fluid loads lead to large deformations in the solid structure: The new Dynamic stabilization method FSI offers very good control over the simulation with just one adjustable coefficient and is fully compatible with the solid stress load step solver. And with the backward differentiation time integration scheme now also available for the solid stress solver, full kinematic consistency between solid and fluid is now guaranteed even for configurations using 2nd order time integration. This next-generation fluid-structure interaction (FSI) modeling reduces barriers to dealing with highly dynamic and tightly coupled two-way FSI applications. Enable applications that involve radiation on participating media Many applications in the food and beverage, medical and processing industries or in additive manufacturing rely heavily on the volumetric interaction of radiation with a processed material. Therefore, to tackle such scenarios with CFD simulation, an accurate model of radiation absorption and scattering in the presence of a participating media is required. With the Simcenter STAR-CCM+ 2402, the already existing Surface Photon Monte Carlo SPMC model (which only considers surface-to-surface radiation and ignores the participant/volumetric effect) is being extended to a fully volumetric PMC. Generally, PMC, a statistical method for solving the Radiative Transfer Equation, is considered one of the most accurate solution approaches. With the expansion to volumetric PMC, a combined modeling of volumetric and surface radiation is enabled and therefore an even higher fidelity approach is provided. This allows for more accurate modeling of complex phenomena such as absorption and scattering of radiation when it interacts with a participating medium. To capture the interaction of radiation with liquids, it can be run in conjunction with Volume Of Fluids (VOF). Thanks to the volume-surface hybrid scheme, users can efficiently use VPMC only in the region where absorption accuracy is required, while maintaining the rest with Surface PMC. This enables impressive speedups of up to 37x compared to a pure Discrete Ordered Method (DOM) solution. VPMC is further expanding the already rich Simcenter STAR-CCM+ physics offering for radiation modeling (DOM, P1 Spherical Harmonics, Surface-to-Surface, SPMC) with the most comprehensive high-fidelity approach. Unlock cross-functional synergy for Design Exploration In a world of increasingly complex products, considering trade-offs between engineering disciplines is of critical importance to maximizing product performance holistically. Therefore, isolated Design Exploration studies not tracked within a single CAE discipline pose the risk of unrealized performance potential. Simcenter STAR-CCM+ 2402 will introduce a Design Manager integration into Teamcenter Simulation. The integrated solution will allow you to receive real-time updates and notifications about changes in geometry, changes in requirements, parameters, etc., from other engineering teams that may affect your Design Exploration project. The integrated Design Manager will help your teams accelerate time to market by leveraging Teamcenter's capabilities for Design Exploration: team members can directly access the right data in Teamcenter, ensuring traceability between requirements and results and leveraging a database of centralized project/product information data. The launch of embedded studies from Active Workspace is further democratizing design exploration. With the resulting improved inter-organizational collaboration, you will be able to realize the full potential through informed optimization of cross-functional product performance. Perform faster surface preparation for complex geometries In exterior aerodynamics, CFD engineers need to strive to achieve an efficient distribution of prism layers on the exterior and interior parts of the vehicle. Using existing surface repair tools, splitting low-y+ and high-y+ surfaces can be a tedious process that can take hours or days, depending on user experience and model complexity. The division of part surfaces is also important in any study when, for example, the reporting of a quantity at a specific limit or the assignment of boundary conditions is desired. The Simcenter STAR-CCM+ 2402 will incorporate an interactive classification tool for surface repair that speeds up the division of part surfaces. The feature comes with an intuitive user interface and state-of-the-art algorithms that enable fast and efficient classification and save time. The tool can be applied to individual parts or to a set of parts that can have different tiling levels. The sorting process is fast and faces can be sorted in seconds. The tool also allows you to record a macro, for even faster classification of different design variants. Therefore, for outdoor aerial simulations, valuable surface preparation time as well as mesh count can be saved. This also leads to reduced solver execution time with minimal differences in drag count. Go faster with access to a wider range of hardware for native GPU acceleration The benefits of GPU-enabled acceleration of CFD simulations are, however, unquestionable. Significantly lower cost per simulation for the same number of designs, massively reduced power consumption, and the ability to replace thousands of CPU cores with a single GPU node. However, until now, GPU-enabled acceleration in Simcenter STAR-CCM+ has been tied to a single GPU hardware vendor, limiting your options. Now, calculations in Simcenter STAR-CCM+ 2402 can be performed on both AMD and NVIDIA GPUs. In this release, you can now take advantage of AMD Instinct™ 200 series GPUs (MI210, MI250, MI250X), with unchanged consistency in results regardless of your chosen hardware, whether CPU or GPU. This offers a wider selection of hardware, easier access to GPU-accelerated CFD, and ultimately more flexibility to obtain CFD results in the most efficient way possible. Run CHT and multi-timescale simulations more efficiently with native GPU solvers As described above, GPU-accelerated CFD simulation has a long list of benefits, including the potential to run your simulations in a cost-effective and energy-efficient manner. Consequently, benchmarks over the last few release cycles have proven the excellent performance of Simcenter STAR-CCM+ on GPUs. And so, it is of fundamental importance to expand the ability to leverage GPUs for more models and, consequently, more applications. Simcenter STAR-CCM+ 2402 therefore follows the portability of solvers and resources to make them equally available for native GPU and CPU simulations. The new version offers GPU-native implicit and explicit fluid-solid and/or solid-solid mapped contact interfaces and a GPU-native multipart solid material properties model. Together, these improvements make it possible to run conjugate heat transfer (CHT), vehicle thermal management (VTM), and other multi-timescale simulations on GPUs with all the associated benefits. CPU-equivalent solutions are guaranteed by maintaining a unified code base. Significantly accelerate multispecies coupled flow simulations Applications involving reactive flows can be found in many sectors. And although CFD simulation can cover all aspects related to chemical reactions with a high level of accuracy, it comes at a cost. Typically, fully coupled flow, energy and species simulations can be very computationally demanding. Therefore, in Simcenter STAR-CCM+ 2402, you now have the possibility to use the Segregated Species solver in conjunction with the Coupled Flow and Energy solver, as an alternative to a fully coupled Flow-Energy-Species approach. Solving species transport in a segregated manner reduces the computational time of the entire system, with large speedup benefits of up to x10 depending on the use case or – more precisely – the number of species involved. Note that while the Coupled Flow/Energy with Segregated Species approach can provide a significant speedup for multi-species simulations, certain more complex reactive cases are expected to require a full Flow/Coupled Energy and Coupled Species approach. Smoothed Particle Hydrodynamics (SPH) Integration in Simcenter STAR-CCM+ 2402 ASmooth-Particle Hydrodynamics (SPH) technology is a very powerful and fast alternative method for modeling complex transient flows with highly dynamic free surface flows, including jets and splashes. However, standalone tools for SPH and mesh-based CFD force users and engineering teams to choose the tool a priori and eventually work across several different tools depending on the exact simulation requirements. In Simcenter STAR-CCM+ 2402, the first version of the SPH solver, which is fully integrated into the platform, was released, allowing you to run SPH and mesh-based simulations from the same tool. Because SPH does not require volume meshing, it allows you to quickly handle complex body movements, even with contact and complex geometries. By integrating with Simcenter STAR-CCM+ you will immediately benefit from the power of Simcenter STAR-CCM+ as a CFD simulation platform: Integrated end-to-end workflow automation, advanced preprocessing with a built-in CAD tool and external CAD connectivity seamless, powerful data analysis and design space exploration integrated with Design Manager. Ultimately, the integration allows you to run multiple types of multiphase applications in a single environment, expanding your options beyond established finite volume methods like VOF or MMP to a fast, meshless SPH method. All this without the need to learn and maintain an additional CFD software tool. In this first version, the lubrication of the powertrain using an oil bath was prioritized. Please note that to be able to run the SPH solver, customers will need an additional license. These are just a few highlights of the Simcenter STAR-CCM+ 2402. These capabilities will enable you to design better products faster than ever before, turning today's engineering complexity into a competitive advantage. Don't miss the opportunity to take advantage of all the advantages offered by Simcenter STAR-CCM+ 2402! With advanced computational fluid dynamics (CFD) capabilities to speed up your simulations, accurate fluid-structure interaction modeling, and expanded access to GPU hardware, there's a lot to explore. Schedule a meeting with CAEXPERTS experts right now and discover how we can help you optimize your engineering projects, transforming complexity into competitive success. Get in touch today to learn more and start taking your engineering to the next level.

The whole engine model (WEM) can be used in the gas turbine industry to accurately calculate the transient thermomechanical behavior of a gas turbine engine under a wide range of operating scenarios. This has clear implications for the service life of the different engine components, as well as the performance and efficiency of the gas turbine itself. But how can we be confident in what we are calculating? Like any simulation tool, if the inputs are bad, we shouldn't expect much from the results. So how can we ensure our contributions are of the highest fidelity? Gas turbine Original Equipment Manufacturers (OEMs) have generated a great deal of knowledge and understanding of their respective engines over the years through extensive simulations, trial and error, and test or validation campaigns. The steady state or baseload/navigation status of an engine is critical to understanding engine performance. However, the challenge is how the engine got to this state: what kind of temperature loads and gradients did the metals experience to get to this steady-state condition. To understand this, heat transfer coefficients (HTCs), fluid temperatures and thermal fluxes are critical information to construct and understand the evolution of the gas turbine thermal state throughout an operational scenario. By capturing the status quo The following Figure is an example of a thermal boundary condition input window for the turbine specific flow boundary condition. Example of thermal flux boundary condition input menu. This is where companies can capture proprietary knowledge of their engine: how flow temperature and pressure evolve as the gas turbine ramps up, reaches base load/cruise speed and altitude, and subsequent deceleration or landing. A crucial input to metal temperature calculation is the heat transfer coefficient: the factor behind the metal temperature evolution through which this boundary condition is placed. In the simple example above, 200 W/m 2•C° is chosen. In reality, as the main physical parameters of the convection fluid (pressure, flow and temperature) evolve throughout engine operation, it is pertinent to take into account the physical changes involved. Below a certain rotational speed, the flow is not transmitted through the motor, which can lead to a different heat transfer process. The entire engine modeling process can explain this phenomenon under boundary conditions in two ways (see Figure below): Incorporation of if/then statements into boundary conditions input fields; Links to key mission/operational cycle parameters that evolve over time. Example of using conditional statements in gas turbine boundary conditions. In addition to the above possibilities, typical heat transfer correlations such as the flat-plate correlation, the Nunner correlation, the Dittus-Boelter equation or some derivative thereof can be included as time-varying or window-input equations. input of heat transfer correlation. It should be noted that companies are able to write company-specific plug-ins that contain proprietary knowledge and information that can be called into Simcenter 3D. This user-defined plug-in function is a feature that allows Simcenter 3D users to utilize its proprietary correlations in modeling the physics of their simulation. Users can code correlations in C++ using application programming interface (API) functions that give access to quantities calculated by the solver. These correlations can be used later in Simcenter 3D when applying and defining boundary conditions. The solver will calculate user-defined functions used in expressions, such as heat transfer correlations, during the solve time. Gas turbines typically have cooling holes for the hottest turbine components or to direct compressor flow into the internal cavities of a rotor. Energy can be transferred to the fluid from such configurations. Windage can be defined as that component of energy that is transmitted from a rotor to the fluid. Simcenter 3D has two dedicated functions that can account for this extra power: Windage for inclined and vertical surfaces; Windage for horizontal cylinders. However, what happens when there is a new gas turbine engine configuration or when the OEM is at the beginning of the design phase of a gas turbine engine where only sketches or operational scenarios are known? Systems engineering: precision and speed This is where a systems engineering tool such as Simcenter Amesim or Simcenter Flomaster is often employed by OEMs to define the main operation of the gas turbine before any computer-aided design (CAD) data is available. These types of models built using existing component libraries in the software are flexible and typically mature with the design as it evolves. In the case of the gas turbine, being able to model and characterize the secondary airflows in and around the gas turbine is critical to understanding the performance and efficiency of the entire engine. Secondary airflow is the portion of the airflow removed from the hot gas path at various stages of the compressor and used for cooling or sealing in the hottest parts of the turbine section. This air needs to be used efficiently and optimally to minimize the impact on engine performance metrics. Simcenter Flomaster has a dedicated library and set of solvers for such simulations. Important physical information, such as swirl correlations relevant to the cavities within a gas turbine, can be calculated and subsequently used as input into boundary conditions throughout the engine model (see Figure below). Similar to WEM's practice of incorporating in-house knowledge and experience, Simcenter Flomaster offers templates for vortex correlations, allowing companies to tailor the solution to reflect their best practices and methodologies. Simcenter Flomaster also contains scripting capabilities so that an enterprise can incorporate its own correlations into the system-level model. Model of part of the secondary air flow system of a gas turbine. These types of system-level models can provide advance information about the operation of a gas turbine engine, and the parameters calculated from the model can be used to tailor the heat transfer correlations of the entire engine model. This type of loose coupling can also be extended where the backlash or deformation calculated from the MAE can be fed back into the systems model, allowing the engineer to understand this effect on the network flow distribution. This approach is also relevant for simulating and understanding the performance of labyrinth seals, typically employed throughout the engine to seal air and hot gas from the metal. Capturing 3D flow phenomena for the 2D world A second source of input for all engine model boundary conditions is computational fluid dynamics (CFD). Using CFD on the complete gas turbine is prohibitively expensive, despite recent advances in hardware and solver speed. However, it can still be used to better understand local conditions and add more fidelity to the entire engine model. There are a few ways to use CFD in MAE, but first, let's see what CFD can elucidate for a full engine model engineer looking at the gas turbine. A gas turbine contains numerous areas of forced convection, not just the hot gas path. It is in these other locations that more information can be derived from CFD to better understand the local flow and heat transfer conditions within a gas turbine; locations such as external extraction cavities, cooling holes within a rotor, or purge streams used to minimize or prevent hot gas ingestion. These conditions could also be simulated and understood at times other than steady-state flow, where local HTCs can have a significant effect on heat transfer to and from the metal. CFD is a valuable tool for understanding local heat transfer conditions within the gas turbine engine. A full engine model engineer can incorporate a speed-controlled HTC into their model, at thermal boundary conditions, or by directly calculating the HTC from a conjugate heat transfer simulation in a tool such as Simcenter STAR-CCM+. A second source of CFD input that can be utilized throughout the engine model is to add fluid domains directly into the 2D WEM. Since Simcenter 3D 2022, 3D fluid domains can be included in the axisymmetric part of the entire engine model (see Figure below). 3D fluid domains within the 2D axisymmetric model of the entire engine to simulate air and heat transfer within the cavities between the turbine blades. This area can be particularly sensitive to temperature changes that can occur due to hot gas ingestion and adversely affect the mechanical life of the spruces. As we have seen, there are several ways to help you fill in the boundary conditions for your entire engine model. Depending on where you are in the development cycle, different levels of input fidelity can be used to help you better understand your engine's performance and the subsequent impact on your engine's metal temperatures and clearances. To ensure your engine model achieves maximum accuracy and effectiveness, schedule a meeting with the experts at CAEXPERTS now. Our team can help you understand and optimize your boundary condition inputs, utilizing industry best practices and customized solutions to meet your specific needs. Don't leave the quality of your results to chance - contact us and take your engine modeling to the next level!

Accelerate, innovate and optimize your electrical machine design process Introducing Simcenter E-Machine Design Software Engineers and engineering managers often face major challenges in the world of electrical machine design. Product development can seem to take years, prototypes are carefully built and tested, and costs often exceed budgets. Furthermore, size, weight and sustainability targets are becoming increasingly strict. But now they have a solution to their problems, a solution that can transform their design process and propel them to success. Siemens is proud to announce Simcenter E-Machine Design, building on the best of Simcenter SPEED , Simcenter Motorsolve and Simcenter MAGNET to replicate experiments with electrical machines. Simcenter E-Machine Design is designed to connect electrical machine V-cycle parts and fulfill Simcenter's vision to help companies reduce product development time from the typical 3-4 years to less than two years. Imagine the possibility of skipping one or more physical prototypes! Simcenter E-Machine Design software is a simulation tool that accelerates the design process, validates designs upfront with multiphysics simulations, and strikes the perfect balance between performance and cost. This was the answer you were waiting for. The Caracteristics But what sets Simcenter E-Machine Design apart? Let's dive into its features: First, Simcenter E-Machine Design uses a model-based design approach. Engineers can leverage predefined models tailored specifically for electrical machines and can design hundreds of machines virtually without being FE experts. This not only reduces design time but also allows them to think outside the box and optimize their creations. Second, Simcenter E-Machine Design relies on virtual multiphysics validation. Engineers can perform simulations early in the design phase, anticipating potential failure modes and ensuring robust performance. The thermal performance of the engine is the center of attention, as temperature can make or break its reliability and useful life. As Toshiba Motors says, “temperature kills engines” and this is because knowing that a mere increase of 10 degrees can halve the life expectancy of a machine. With this tool, engineers can predict and mitigate overheating issues by running fast electrothermal simulations in a single tool. Comparison of engine temperatures, with and without cooling. Don’t get lost with axial flow machines… And there's one more interesting part: Simcenter E-Machine Design now includes an Axial Flux machine module. This module has unique features allowing engineers to predict the performance of axial flow machines in seconds. Thanks to the combination of interface models on the input side and analytical analysis capabilities on the output side, engineers can quickly harness the power of axial flow machines. These machines are being investigated in many industries because the ability to stack them has the potential to significantly increase performance. Users can now evaluate axial versus radial flow alternatives and assess whether higher power densities can be achieved. Many believe that these machines could shape the future of electric mobility. Additionally, Simcenter E-Machine Design allows engineers to validate the electrical machine within the transmission system by integrating it into the Simcenter portfolio. Being able to digitally integrate your components allows you to reach the physical prototype stage with greater confidence, avoiding costly failures. The three examples of this integration that bring the most value to our partners are: System Integration: Optimizing the electrical machine within the system is the only way to achieve the next level of efficiency and take your electrical application to the next level. Simcenter E-Machine Design allows you to create accurate reduced order models (ROMS) that integrate with Simcenter AMESIM for mechatronics simulation. If you are interested in drive-motor integration, you can also embed your ROMs in the Xpedition software or PartQuest Explore software. Thermal Integration: To increase efficiency and performance, engineers continue to explore increasingly complex cooling strategies. The more complex the cooling, the more essential simulation becomes to validate that everything works as planned. That's why Simcenter E-Machine Design helps you leverage your model and build detailed multi-physics solutions in Simcenter STAR-CCM+. Mechanical integration: In particular, validating the NVH performance of the machine, gearbox and casing can be a nightmare. Classical approaches that do not take into account the integration between electromagnetic charges and transmission continue to prove insufficient. That's why Simcenter helps you accurately replicate the integrated e-drive and review the system's NVH. You can test and correlate your results with the physical system. Considering the effect of electromagnetic charges propagating through the transmission and housing allows for a more accurate check of the e-drive's NVH. Don't wait any longer to optimize your electrical machine projects! Schedule a meeting with CAEXPERTS now and discover how Simcenter E-Machine Design can speed up your design process, reducing costs and increasing efficiency. Let's work together to drive the success of your project. Contact us to schedule your meeting!

Effects on NVH and how Simcenter 3D Motion can simulate them. How we used to model deformation and NVH Until now, engineers have faced the challenge of studying the effects of deformation on a system's NVH (Noise, Vibration, and Harshness) performance. They must go through a long modeling process to modify the structural model and change their vibrational behavior. This required a high degree of modeling experience, and even experienced users must go through a time-consuming iterative process of model re-meshing , resolving, and post-processing. To make matters worse, structural modifications often impact all deformation modes of a flexible component, making it difficult to dissociate it in a vibration sensitivity analysis. Modal Edit Now, Simcenter 3D Motion has come to solve your problems. They introduced a new feature called Modal Editing, which exposes the user to all the frequencies of a modal equivalent ERFEM-based flexible body. Each mode is represented by a simple 1-degree-of-freedom spring-mass system, and the oscillations of any modal mass are linked to the corresponding modal shape of the structure through a set of coefficients that represent the deformations measured at any node in all directions. . Performing a modal analysis on this equivalent modal model provides, by definition, precisely the same results as the original model, allowing it to be used as a parametric and editable input for a flexible body of motion. The advantage of equivalent modal modeling The advantage of using an equivalent modal model is that, in principle, the user can modify the frequencies and modal shapes of the flexible body just by editing the modal solver input deck file. In practice, changing deformation shapes is complex due to the many parameters involved, but editing modal frequencies is much easier. Each system in the modal model is completely decoupled from any other, allowing users to edit single modes without affecting the remaining set of modes. Finding the dynamic motion solution This new technology proved useful in evaluating the impact on the vibration levels of the flexible casing of an eDrive powertrain from a 10% increase in the frequency of the 1st flexion mode. By modifying the desired modal frequencies through the Mode Editing tool, a new solution was initiated to compare the vibration results obtained with the new model. The overall level of vibrations at the selected node has been reduced, especially in the speed range up to 4,000 rpm. The results from the Motion dynamic solution were then reused for further acoustic analysis of the box. In conclusion, Simcenter 3D Motion users now have access to new functionality that allows them to edit the modal frequency content of a flexible body. Through a fully automated process, they can perform sensitivity analyzes and what-if scenarios to quickly assess how changes influence engine performance on the flexibility of any component. Unlock the future of deformation and NVH modeling with CAEXPERTS! With Simcenter 3D Motion and the innovative Modal Editing tool, we simplify the process for engineers. Optimize your time and take your modeling to the next level with the efficiency of CAEXPERTS! Schedule a meeting now for fast and valuable transformation.