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Haulotte uses Simcenter to increase Pulseo lift maximum working drive height by 25% and loading capacity by 50% Challenges Make construction sites environmentally friendly Define an optimal e-machine architecture while ensuring machine stability Create first-time-right prototype Results Improved performance while transitioning from an ICE to an electric motor Increased maximum working drive height by 25% and loading capacity by 50% Reduced number of prototypes and the time spent on testing campaigns Aligned with safety and emissions regulations With Simcenter, we went from a 23kW thermal engine to a 12kW electric motor while improving the overall performance of the scissor lift. Arnaud Chaigne, Head of Simulation and Digital Validation Division, Haulotte Safety is paramount Take a look at any construction site and you’ll see lots of scissor lifts being used for a variety of tasks. From indoor paint jobs to outdoor renovations, this type of construction lift with its elevating platform needs to perform well in a variety of challenging conditions. Outdoor projects can be especially hard on this type of equipment. The ground can be muddy, uneven and tough to navigate. Muddy steep slopes require good traction performance to get the job done. Another key driver is noise and emission regulations. Lifts may not emit exhaust and can’t exceed certain decibel levels for operator and overall crew safety, especially indoors. This means engineers need to reduce the overall noise generated by the engine and the actuation systems as well as meet the ever-stricter standards applied to internal combustion engines (ICEs). As more urban areas adopt low-emission zones, manufacturers are being forced to accelerate innovation and produce alternative-energy equipment. In many cases, electric is the most viable way to go. Finally, safety is paramount when it comes to construction equipment and lifts in general. These machines are all about working high above the ground. This means stability is the highest priority for both manufacturers and end users. Know anyone with a scissor lift in the garage? Like other aspects of the construction industry, 80% of final lift customers are not end users, but equipment rental companies. Rental companies need to offer high-performance, versatile machines to their customers. Customers don’t want to rent different machines for the same site. Offering a versatile top performer is a major asset when it comes to managing a rental fleet. Enter the Pulseo range To fill this gap in the market, Haulotte , one of the world’s leading manufacturers and suppliers of lifting equipment based in Lorette, France, has developed Pulseo , a range of next-generation, all-terrain electric scissor lifts. Suitable for both indoor and outdoor work, the all-electric Pulseo platforms offer superior performance compared to previous combustion engine models. To develop these new models, Arnaud Chaigne, head of the simulation and digital validation division at Haulotte , and his team of engineers used simulation to study design possibilities and predict machine performance. “Simulation allowed us to assess the feasibility of different innovation scenarios, taking into account the impact on various systems, like hydraulics, electrics and controls, as well as machine stability and operator safety,” says Chaigne. Design architecture evaluation using Simcenter Amesim. Simulation tools of choice Haulotte uses Simcenter™ software tools for system and mechanical simulation. Simcenter is part of the Siemens Xcelerator business platform of software, hardware and services. Using these simulation tools, the engineers at Haulotte developed a line of market-ready, 12-kilowatt (kW) electric motor scissor lifts. The new lifts delivered better performance compared to the previous model, which featured a 23kW internal combustion engine (ICE). Not only are the new electric scissor lifts pollution-free and quiet, but they also deliver better overall performance, including a maximum working drive height of 15 meters (m) instead of 12m and a load capacity of 750 kilograms (kg) instead of 500kg. To determine the optimal architecture for future all-terrain Pulseo scissor lifts, Chaigne used Simcenter Amesim™ software for system simulation. One of the toughest parts of the task was optimizing the electric motor performance. Unlike conventional ICEs, to obtain the required power from the electric motor the team had to deal with many more design issues and constraints. To start, Chaigne identified the energy losses on all levels: from the engine throughout the entire structure, including hydraulic distribution. “We started by modeling the existing thermal system in order to identify the most energy-consuming parts (energy-loss mapping),” says Chaigne. “By doing this, we were able to define a new architecture more suited to an all-electric machine where all energy consumption counts.” Defining an optimal system architecture As the part of the project to define the optimal architecture, the team worked on sizing the battery of the electrical system. As Chaigne explains, “To size the battery properly, we had to study two major areas: on one hand, the total quantity of required energy for day-to-day operational needs, and on the other hand, the high power demands during transient phases. The risk is oversizing the design to adapt to these power peaks. Therefore, we worked on control law modeling to limit these peaks.” During the analysis phases, Chaigne and his team observed the peaks took place at the very beginning of elevation when the actuators initiated the movement. “In order to optimize the battery size, we had to develop control laws to smooth out the power peaks while offering a similar lifting time,” says Chaigne. “This resulted in a constant power level during the entire elevation movement.” Customized process-oriented workflow tool using NX™ Open software, in Simcenter 3D. Simulation of in-operation machine stability, using Simcenter 3D Motion. Using Simcenter 3D Motion to achieve stability Regulations in various countries stipulate elevating lifts must remain stable, whether they are moving into position on a job site or standing still; for example, with the operator or workers on the platform. “In order to improve productivity with our new scissor lift, it was necessary to study its stability in transit,” says Chaigne. “When the machine is moving and deploying, you need to study the oscillating axle behavior to ensure the overall vehicle stability.” To be able to anticipate all possible scenarios, Chaigne and his team used Simcenter 3D Motion software to study the dynamic behavior of the scissor lift. “We used Simcenter dynamic multibody simulation to size the scissor lifts to ensure stability,” says Chaigne. “This made it possible to find the best compromise between performance and machine weight and save time during development.” Outdoor work in progress with the Pulseo. Democratizing simulation “As a simulation expert, I am responsible for making sure our simulation tools are accessible,” states Chaigne. “The customization possibilities in Simcenter 3D via NX Open have made it possible to integrate our business rules and regulatory norms to speed up the calculation process and reduce the risk of error.” When the Haulotte design office performs the various stability analyses, standard norms drive the process. One of the issues is standards vary from region to region and the requirements can cover quite a few variable factors: from environmental ones, such as wind force, to human-initiated ones, like operator impact or equipment handling, such as load position and working angles. “In parallel with managing the standards parameters, we try to make our models created in the design office as predictive as possible,” explains Chaigne. “This means taking into account parameters influencing stability, like tire behavior, the actual stiffness and its weight distribution. After the model has been defined, we need to check the stability according to the different standards configurations; this step can be relatively long and tedious.” Saving time and eliminating tedious work To save time and improve the analysis process for the stability calculations, the team has developed a customized process-oriented workflow tool using NX™ Open software, an application programming interface (API) automation module for Simcenter 3D . “In concrete terms, NX Open allows us to automate data entry, taking into account the various norms,” says Chaigne. “During post-processing, it provides clear-cut stability information. This enables nonspecialists to use more complex Simcenter 3D Motion models.” Co-simulation improves performance When working on the electric Pulseo series, the engineering team co-simulates Simcenter 3D models used for structure and stability analysis with Simcenter Amesim system simulation models used for energy analysis and battery sizing. Chaigne explains, “For electric-powered machines, energy consumption is extremely important. Using Simcenter 3D Motion allows us to model the forces in the hydraulic actuators taking into account kinematics, mass distribution, friction and dynamic effects. We have real insight into the pressure level details, and therefore the energy required for these actuators.” The team works with two types of co-simulation processes. “In the first case, the two software programs operate simultaneously and exchange information to converge toward a common solution,” says Chaigne. “In the second case, we use Simcenter 3D Motion to generate force tables according to the cylinder position and then we use this information in Simcenter Amesim .” Since scissor lifts mostly operate hydraulically using several actuators, the stress distribution across the structure varies according to the pressure balance in the hydraulic actuators. Chaigne says, “Co-simulation allows us to analyze the stresses under normal conditions and during failures; for example, a hose rupture. We can see how the load transfers take place and the impact on hydraulic cylinder pressure.” Using simulation to reduce physical test campaigns “Calculations and simulations are part of our theoretical validation process to ensure our design has reached a certain maturity level before manufacturing the first prototype,” says Chaigne. “However, the test phase remains essential. Simulation helps us identify the most critical cases in terms of stability, evaluating parameters like machine position, loads and forces.” The identified critical cases are then verified during test trials. “We check whether the test results correspond to the simulation,” confirms Chaigne. “This test-simulation analysis loop is necessary to improve our models. Using simulation models limits prototypes and therefore reduces the time we spend on the testing campaigns.” Using simulation to understand performance behavior “Simulation helps us define the overall system architecture, but we use it during different development phases like trouble-shooting issues that occurred during testing. Certainly, simulation provides a deeper insight into unwanted performance behavior and the causes as well,” explains Chaigne. “To reproduce the performance accurately, you have to model different physical phenomena. This includes identifying influential parameters and evaluating alternatives immediately. Working like this, we are able to reach the prototyping phase with a more mature, even definitive architecture.” According to Chaigne, within a design office, it is essential not to isolate the simulation analysis team from the prototype testing team. Simulation and testing loops must be integrated into a collaborative process to allow the issues detected during testing to be resolved as quickly as possible using simulation. Indoor work in progress with the Pulseo. Superior performance and optimal safety Using Simcenter simulation tools was a key success factor in the design and development of Haulotte’s new electric all-terrain Pulseo scissor lifts. The team was able to comply with all the operational stability safety standards as well as various requirements relating to noise emissions and air pollution. Thanks to Simcenter simulation capabilities, the team created an optimal design that featured a superior performance compared to the previous model with an ICE. “With Simcenter, we went from a 23kW thermal engine to a 12kW electric motor while improving the overall performance of the scissor lift. The maximum working drive height increased 25% from 12m to 15m and the loading capacity increased 50% from 500kg to 750kg,” concludes Chaigne. Do you want to contribute to the innovation and efficiency of your projects? CAEXPERTS can help your company reach new heights with advanced simulation solutions. Schedule a meeting now and discover how the Simcenter portfolio can improve your performance and reduce costs! WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Heat exchangers are essential equipment in several industrial processes. Whether in power generation, the chemical or petrochemical industry or in HVAC systems, they are very important to ensure thermal control, energy efficiency and adequate heat transfer in process lines. The performance of this equipment has a direct impact on energy consumption, operating costs and even the environmental footprint of an industrial process. Despite its importance, designing efficient and compact heat exchangers remains a challenge. This is because the phenomena involved — such as heat transfer, temperature gradients, turbulent flow patterns, and the formation of dead zones or recirculations — are highly complex and interdependent. Small geometric changes can have significant effects on the thermal and hydrodynamic performance of the system. Traditionally, many of these designs are based on empirical correlations or semi-analytical methods, which, although useful, are not always able to capture all the complexity involved in the internal flow of modern exchangers, especially those that are highly compact or have innovative geometries. This is exactly where CFD (Computational Fluid Dynamics) simulation has come into its own, making it possible to create three-dimensional models that reveal in detail the behavior of the fluid, heat exchanges and pressure gradients — all based on real operating conditions. Challenges and Solutions Designing an efficient heat exchanger is not just about ensuring that heat exchange occurs — the real challenge is balancing thermal performance, pressure drop and manufacturing feasibility. A design that transfers heat well but requires more powerful pumps due to the high pressure drop in the flow may make the system unviable in terms of operating costs. Similarly, highly efficient solutions from a thermal point of view may be difficult or expensive to produce. Another recurring problem is the incorrect sizing of baffles, fins and channels, which can generate recirculation or dead zones in the flow, compromising the uniformity of heat exchange and creating hotspots. These details, often invisible in traditional analyses, directly affect the durability and performance of the equipment. This is where CFD simulation with STAR-CCM+ comes in handy. It allows you to visualize the flow in 3D , observe temperature and pressure profiles, and predict exactly where losses or inefficiencies occur. The engineer can test different geometries, modify inlet angles, spacings, and even combine baffles and fins to maximize turbulence where it is desired — all before any physical prototype is manufactured. In addition, simulation results can be used to validate designs in accordance with technical standards, such as ASME, TEMA or API 660 specifications, ensuring that the equipment meets the safety, reliability and performance criteria required by the industry. This not only speeds up the development process, but also reduces rework costs, increases the lifespan of the exchanger and improves the project's return on investment (ROI). Simulation The simulation study, using STAR-CCM+ , in question focuses on the detailed analysis of a shell-and-tube heat exchanger, with the aim of investigating the key variables of heat exchange and operational stability of the equipment. The modeling adopted the conjugate heat transfer (CHT) regime, allowing simultaneous simulation of fluid flow and thermal conduction in the walls of the tubes and shell. Each domain was treated with different physical properties, representing more faithfully the materials and fluids involved. The computational mesh was refined in the critical regions, especially near the tubes, where there is a greater thermal gradient and influence on heat transfer. Figure 1. Geometry and computational mesh Figure 2 shows the temperature profile in a vertical section of the domain. The fluid in the tubes enters at 353 K, while the fluid in the shell starts at 298 K. At the end of the path, the tube outlet temperature showed a reduction of approximately 7 K. This drop is more pronounced in the central region of the exchanger (Figure 3), indicating greater thermal interaction between the flows, favored by the geometry and arrangement of the tubes and internal baffles, which promote turbulence and better mixing. Figure 2. Temperature profile Figure 3. X-axis temperature graph The velocity profile, shown in Figure 4, shows higher velocities in the inlet zones, especially in the upper tube; this acceleration is related to pressure gradients. The formation of recirculation zones and eddies can also be observed just after the inlet, especially near the deflector plates, which promote changes in direction and intensify turbulence. Near the outlet, the fluid accelerates again, reinforcing the hydraulic design in improving thermal efficiency and preventing dead zones with low heat exchange. Figure 4. Velocity profile Figure 5 shows the velocity iso-surface, where it is possible to observe fluctuations caused by the presence of baffles in the hull. These structures play a fundamental role in homogenizing the flow, directing the fluid transversely to the tubes and increasing the efficiency of heat exchange by increasing local turbulence. Figure 5. Velocity iso - surface Increasing complexity Advancing the level of complexity of the model to more accurately represent the thermal and fluid dynamic behavior of the heat exchanger. Highlights include: Use of advanced geometries (finned tubes, helical tubes, etc.) Multiphase modeling in applications with condensation or evaporation Variable thermo-physical properties depending on temperature Parametric analysis and coupling with numerical optimization Conclusion CFD simulation applied to shell-and-tube heat exchangers captures the understanding of the thermal and fluid dynamic phenomena that directly impact the performance of the equipment. Identifying critical recirculation zones, speed variations and regions of intense heat exchange. Being able to predict in detail and accurately the physical phenomena involved in the operation of the equipment allows optimizing performance before manufacturing, ensuring greater efficiency and reliability and lower operating costs, leveraging innovation and development for increasingly better equipment. Do you want to design more efficient, reliable and cost-effective heat exchangers? Schedule a meeting with CAEXPERTS and find out how CFD simulation with STAR-CCM+ can transform your challenges into accurate, cost-effective and high-performance solutions. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Pressure vessels are important components in several industries, such as petrochemicals, pharmaceuticals, food, metallurgy, etc. Designed to store fluids under pressure, these devices must withstand high temperatures and pressures without compromising safety. Any failure can result in serious risks, such as leaks, explosions or contamination of the environment. Below are some of their main functions: Storing gases under pressure, so that they can have a greater weight in a relatively small volume; Intermediate accumulation of gases and liquids, in systems where this function is necessary, between the stages of the same process or even between different processes; Processing of gases and liquids, when the transformation process requires that the conditions be under pressure. In addition, pressure vessels often operate under pressurization and depressurization cycles, which makes them susceptible to structural fatigue. Therefore, standards such as ASME BPVC Section VIII and API 579-1/ASME FFS-1 establish guidelines for their design, manufacturing and numerical analysis, to protect against failures due to continuous loading. Therefore, the application of finite element analysis (FEA) is essential to ensure the structural integrity of this equipment before manufacturing and during its operation. FEA modeling Finite element analysis allows simulating the behavior of a pressure vessel under different operating conditions. For this study, we considered a horizontal cylindrical vessel subjected to internal pressure and temperature. The analysis process followed the following steps: Definition of the CAD model The pressure vessel was modeled in SIEMENS Solid Edge CAD software. Image 1: Solid model   Image 2: Main dimensions Determination of Material Properties The material chosen was ASTM-A516 Grade 70 steel, widely used in the manufacture of pressure vessels due to its mechanical strength and toughness. Yield Strength 260 MPa Rupture Strength 485 MPa  Tangential Modulus 1460 MPa Young's Modulus 200 GPa Poisson's Ratio 0,3 Density 7,80 g/cm³ Coefficient of Thermal Expansion 12x10-6 1/ºC ASTM-516-70 Properties Table Transformation into a shell (surface) model After dimensioning it in Solid Edge , we imported it into Simcenter 3D , SIEMENS' finite element analysis (FEA) software, to transform it into a shell model to optimize the analysis and simplify the geometry. Due to the high thickness of the bases, they were kept as solid elements. Image 3: Shell model Generation of the Mesh Use of 2D meshes (CQUAD4) on the “surfaces” with low refinement due to the simple model and 3D mesh (CTETRA4) on the bases. In the 2D meshes, we specify the thicknesses of the components in the manifold where the meshes are located, so a manifold is required for each thickness. Image 4: Representation of the meshes Application of boundary conditions and restrictions Fully fixed restriction on the left base and the one on the right fixed only for translation in Z.   Image 5: Base restrictions: (a) fixed left and; (b) fixed right translation in Z Internal pressure Pressure of 2 bar on walls and pipes. Image 6: Representation of pressure Temperature The object is at an initial temperature of 20 ºC, with the body going to 100 ºC (image 7) and the base going to 40 ºC (image 8) in the simulation. Image 7: Components at 100 ºC Image 8: Components at 40 ºC Running the simulation using the NASTRAN solver integrated with Simcenter 3D Results The analysis results show that the maximum displacement occurs at the right end of the pressure vessel, reaching approximately 0.78 mm, as shown in image 8. Because it is fixed to the left base, it tends to move to the right, as shown by the simulation behavior. This deformation is relatively small, indicating good structural rigidity for the applied load conditions. Image 9: Displacement results The stress results show that the highest stress concentration is occurring at the base, with a peak of 262.80 MPa (image 9) at the junction with the body, which is consistent since it is a region with sharp corners. It can be seen that it is in this region where the stresses exceed the yield limit (260 MPa) of the material, which may indicate a risk of local plasticization. In the body of the vessel, the maximum stress is 156.58 MPa at the border with the base (image 10), demonstrating that it is within a safe margin of the yield limit. Image 10: Result of tensions Image 11: Stress peak in the body Benefits of FEA Analysis for Pressure Vessels The use of FEA in pressure vessel engineering brings several advantages: Cost Reduction: Minimizes the need for expensive experimental tests and optimizes the use of materials. Accuracy in Structural Analysis: Identifies critical points and improves the design before manufacturing. Increased Safety: Allows for the prediction of structural failures and compliance with strict standards such as ASME BPVC Section VIII and API 579-1/ASME FFS-1 . Design Optimization: Allows for structural adjustments to increase the useful life of the equipment. Designs based on the ASME BPVC Section VIII Division 2 Part 5 (Design by analysis) code can reduce material costs and equipment weight due to its lower rigor and because it allows for higher allowable stresses, compared to Section VIII Division 1 , which is more conservative. ASME BPVC Section VIII Division 2 establishes the following criteria for failure prevention: Plastic Collapse - Evaluates possible locations where major failures may occur. Localized Failure - Small regions that exceed the material's resistance limits. Buckling - Caused by axial compression or vacuum in pressure vessels. Fatigue Failure - Components subjected to cyclic loading. All of these requirements and changes during design, such as changes in thickness and materials, can be achieved using Simcenter 3D in a simple way. With these advantages, FEA analysis becomes an indispensable tool for engineers seeking efficient and safe designs for pressure vessels. Computer simulation not only improves the reliability of projects, but also speeds up validation and certification processes in the industry, with approval from standards such as ASME . Do you want to ensure the structural integrity of your pressure vessels, save on materials and still comply with strict standards such as ASME BPVC ? Schedule a meeting with CAEXPERTS and find out how FEA analysis can increase the safety and efficiency of your projects. We are ready to transform complex challenges into smart and safe solutions! WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

The use of biomass as an energy source has gained relevance in the industrial scenario. Coming from waste from other processes, this type of fuel represents a viable and sustainable alternative. When used in efficient combustion systems, it contributes significantly to reducing operating costs, reduces greenhouse gas emissions and strengthens the company's image, especially in a market that is increasingly attentive to sustainability criteria and seals. Figure 1 – Biomass In the case of boilers that use biomass, the combustion involves organic materials such as wood chips, sugarcane bagasse, rice husks and agricultural waste that provide thermal energy to generate steam for generating electricity or for industrial processes. Figure 2 – Boiler The efficiency of the combustion process in boilers is directly linked to the adequate flow of fuel over the grate. In fixed grate systems, the uneven distribution of material, including the presence of layers already consumed over portions not yet burned, can cause localized accumulations and the formation of regions with incomplete combustion, reducing thermal efficiency. This effect increases the amount of unconsumed residue, increasing specific fuel consumption, since a significant portion of unburned biomass will be present among the ashes. This unburned biomass, in addition to reducing boiler efficiency, can cause accidents due to spontaneous combustion that can occur when it is removed from the boiler while hot and comes into contact with oxygen in the air again. Some companies report accidents, for example, when blowing air to unclog the ash collection hopper and the air comes into contact with the unburned biomass. Figure 3 – Wood chips Given these limitations, different grate configurations have been studied and applied to improve the movement and distribution of biomass during combustion. Modeling the flow of this material in the boiler is essential to optimize its behavior, considering physical properties such as particle size and density, in addition to the characteristics of the grate. These solutions aim to promote a more homogeneous flow, favoring contact between the biomass and the air, reducing regions with excess or deficiency of fuel and allowing the identification of critical zones. Modeling biomass flow with Simcenter Star-CCM Simcenter STAR-CCM+ offers advanced features to simulate the behavior of granular materials and particles through the DEM (Discrete Element Method) methodology. The model is based on the representation of particulate materials as a set of discrete particles that can interact with each other and with solid surfaces. Figure 4 – DEM element This approach allows to accurately represent the interaction between biomass particles and internal boiler components, such as the vibrating grate, in addition to incorporating operational parameters and physical characteristics of the material. Figure 5 – DEM elements in contact During the simulation, it is possible to configure the grate inclination and analyze how this variable, together with gravity, influences the speed and flow pattern of the biomass. It is also possible to adjust the intensity and direction of the vibrations (horizontal, vertical or combined), observing how these forces affect the movement of the material. In the simulation, the behavior of the particles on the same grate was analyzed, one in a static configuration (top) and the other in a vibrating configuration (bottom), both maintained at the same inclination. Video 1 illustrates the simulation of the aforementioned cases. Video 1 – Biomass flow velocity using DEM (side view) Although the grate was inclined, the particles did not present the same flow observed in the vibrating configuration. This behavior is related to the nature of the particle material, which, due to its physical characteristics, does not allow flow in the static configuration. This comparison highlights the importance of simulation, where it is possible to predict behavior under different scenarios. This flexibility allows identifying ideal configurations that avoid clogging, promote uniform flow and maximize combustion efficiency. In addition, specific characteristics of the biomass, such as particle size and distribution, density, roughness and friction coefficients, can be incorporated into the model. This makes the simulation more realistic and faithful to real operating conditions, allowing for more accurate prediction of the behavior of the material inside the boiler. In biomass combustion simulation, the use of numerical models allows for the prediction and correction of problems before they occur, optimizing system performance. In Simcenter STAR-CCM+ , simulations make it possible to evaluate different operational scenarios before building or modifying boilers. By changing parameters such as grate inclination and vibration intensity, it is possible to analyze the impact of these variables on the flow and distribution of biomass, identifying problems such as material accumulation, irregular flows or low-burning zones even in the design phase. This prevents late corrections, resulting in more assertive decisions, reducing the need for field adjustments and preventing unscheduled shutdowns. With these adjustments, there are gains in thermal efficiency, lower fuel consumption and reduced emissions. These approaches illustrate how the use of simulations and numerical models, such as DEM, becomes a strategic tool, providing more efficient and sustainable operations, whether in mineral handling or in the design of burning systems. Do you want to maximize the efficiency of your boiler and reduce operating costs safely and sustainably? Schedule a meeting with CAEXPERTS and find out how DEM simulation in Simcenter STAR-CCM+ can transform the performance of your biomass burning system. Let's find the best solution for your process together! WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

In the modern power generation industry, where competitiveness demands operational excellence, the efficiency of industrial boilers stands out as a crucial pillar for success. Designed to meet performance and sustainability demands, these systems prioritize parameters that aim to: maximize the useful life of boilers and piping, optimize thermal efficiency, reduce emissions and ensure energy generation at maximum levels. In this scenario, furnaces emerge as a reference technology. Their differential lies in the arrangement of independent flames, which ensure stable combustion even under minimum operating loads - a critical advantage in scenarios of variable demand. In addition, their versatile architecture is not restricted to the traditional boiler format, allowing adaptations to different projects without compromising efficiency. Another highlight is the ability to maintain minimum deviations in the temperature of fuel gases along the horizontal flow, ensuring homogeneous thermal distribution and reducing the risk of premature degradation of components. Challenges and Solutions In the search for efficient combustion and reactive flow systems, the technical challenges transcend specific applications, focusing on four essential pillars: reducing pollutant emissions, maximizing energy efficiency, controlling costs (both design and maintenance) and adopting technological innovations, such as alternative fuels, hybrid systems and advanced materials. The strategic solution to these challenges lies in the creation of digital twins – virtual models that simulate real processes with high precision. In practice, companies use these simulations to optimize flame dynamics, heat transfer, thermal wear resistance and emission control (NOx, soot, CO). Furthermore, in complex reactive systems, predictive analyses allow for the prediction of critical parameters such as yield, chemical conversion, product selectivity and undesirable operating conditions, such as hotspots or stagnation zones. CFD simulation with STAR-CCM+ stands out as a strategic tool in this context, enabling the modeling of complex phenomena. Design variants can be quickly explored from the initial phases. This includes everything from adjustments to flame geometry and thermal distribution to the integration of new operating strategies. Simulation The simulation study, using STAR-CCM+ , in question focuses on the detailed analysis of the furnace of an industrial boiler , with the aim of investigating the combustion characteristics of natural gas and its impact on the efficiency and operational stability of the equipment. The simulation was developed based on a non-premixed combustion model , incorporating the detailed chemical kinetics of natural gas through a kinetic mechanism with more than 400 reactions. The computational mesh was strategically refined in critical regions, such as the flame zone and gas outlets, while the boundary conditions replicated real operational scenarios, including proportional fuel and oxidizer input. Figure 1: Geometry and computational mesh The results in Figure 2 show the temperature distribution in the furnace, where the regions close to the central line of the gas flow reach temperatures above 2000 K, indicating intense combustion activity. However, a low temperature zone is observed near the burner nozzles, caused by the high concentration of air in these areas, which dilutes the fuel mixture and reduces local thermal efficiency. Measuring this inefficiency is essential to verify whether the cost of preheating is justifiable or not, for example. Figure 2: Temperature profile From the image of the temperature field above, it is possible to understand the thermal distribution of the boiler and determine whether the areas of interest are at the appropriate temperature and receiving sufficient heat. Figure 3 shows the concentration profiles of CO₂, CO and OH along the height of the boiler. The CO₂ concentration increases progressively as the gases rise, reflecting the complete oxidation of the fuel in contact with the available oxygen. CO, on the other hand, shows peaks close to the burners, resulting from the centralized injection of methane (CH₄) combined with insufficient air in the primary zone. As the gases rise, CO is converted to CO₂ due to the greater availability of oxygen. The OH profile, in turn, confirms the stability of the flame, with high concentrations in regions of intense combustion, signaling combustion efficiency. Figure 3: Concentration profiles: (a) CO₂; (b) C; (c) OH In Figure 4, the velocity field and streamlines reveal how the geometry of the furnace and burners influence the flow of gases. Recirculation zones below the burners stand out, which retain unburned particles and improve combustion efficiency, and "dead" spots (regions of low turbulence), where there is a risk of accumulation of unreacted material. These patterns highlight the need for adjustments in the geometry to optimize the flow and avoid energy losses. Figure 4: Velocity profile Technical implications The results highlight opportunities to improve furnace design: Adjust the air-fuel ratio in the nozzles to reduce low-temperature zones. Redesign the geometry to minimize dead spots and ensure homogeneous flow. Improve the fuel-air mixture to control CO emissions as well as NOx and SOx. Evaluate fuel substitution (heavy oils, for example, for natural gas). Conclusion The optimization of industrial boilers and furnaces through computer simulations, such as those performed with STAR-CCM+ , has proven to be a way to overcome the challenges of the modern energy industry. The use of simulations shows that digital technology improves performance, reduces emissions and increases the useful life of equipment. Investing in these solutions is a sure path to greater sustainability and productivity. References   GANDHI, Mikilkumar B.; VUTHALURU, Rupa; VUTHALURU, Hari; FRENCH, David; SHAH, Kalpit. CFD based prediction of erosion rate in large scale wall-fired boiler . Applied Thermal Engineering, v. 42, p. 90–100, 2012. ISSN 1359-4311. Available at: https://doi.org/10.1016/j.applthermaleng.2012.03.015 . Accessed on: May 20, 2025. WANG, Haopeng; JIN, Haoze; YANG, Zhi; DENG, Shanshan; WU, Xuehong; AN, Jingxue; SHENG, Ranran; TI, Shuguang. CFD modeling of flow, combustion and NOx emission in a wall-fired boiler at different low-load operating conditions . Applied Thermal Engineering, v. 236, Part D, 2024, 121824. ISSN 1359-4311. Available at: https://doi.org/10.1016/j.applthermaleng.2023.121824 . Accessed on: May 20, 2025. Schedule a meeting with CAEXPERTS and discover how computer simulation can transform your industrial processes, optimizing efficiency, reducing emissions and extending the life of your equipment. With STAR-CCM+ , you can implement customized solutions for real challenges. Talk to our experts and take your operation to the next level! WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Not only for Gear Design Optimization specialists For the literal among you, gear grinding is the process of abrading a gear surface to give it its final shape and polish. However, it is also a common expansion to express annoyance at something, i.e., Do you know what grinds gears? X, Y, and Z but not necessarily in that order. Extremely repetitive processes that are easy to make mistakes during, grind our gears. This is especially true when we know a computer could do it in a flash if only I had the code to do it. As a very infrequent coder there is always the urge to code something, but cleaning up buggy code will likely take longer to fix than it would have taken to do the original task. So, it is only worthwhile if the code is likely to get used somewhat regularly. Consider macro and micro geometries Therefore, we sympathize with gear specialists who may face both the literal and metaphorical incarnation of this expression. When developing a transmission, you may need to optimize it for NVH, durability, efficiency, or a combination. To do this, you need to consider both the macro and micro geometry of the gear pairs. In a case with just two gear pairs, there will be approximately 40 design variables, and several objective functions for the microgeometry, plus several more objectives with multiple constraints for the macrogeometry. Code that works As described, setting up a test that looked at two gear sets in mesh could take an experienced engineer weeks. However, you could reduce this to days if you were fortunate enough to be in a company that already has and does a good job of maintaining a script that evaluates gear key performance indicators. Much time is spent by gear specialists on repetitive workflows or maintaining code at much expense to their companies. This is why Simcenter 3D Motion has developed the Simcenter 3D Motion Gear Design Optimization Software, released as part of the Simcenter Mechanical Solution 2412 release. Simcenter 3D Motion Gear Design Optimization This new tool removes the need for coding and maintaining internal scripts. Simcenter 3D Motion Gear Design Optimization enables you to fine-tune the micro geometry of gear faces. Furthermore, it works with Simcenter 3D Motion Transmission builder and HEEDS in an intuitive workflow to optimize your macro and micro gear geometries to ensure a fully optimized design. Do not pass Meshing, Do not collect a designer, Go straight to gear design optimization. Those of you who have had the pleasure of rapidly developing gear systems using Simcenter 3D Motion Transmission builder will know that you can use its wizard to select your required gear parameters and generate a model without having to produce any CAD yourself. You will also see your model generated in Simcenter 3D , where you were able to conduct simulations and test your designs. You may even have included HEEDS in your workflow to optimize your design. With the New Simcenter 3D Motion Gear Design Optimization tool, you follow the same steps to produce your initial macro and micro geometry as Simcenter 3D Motion Transmission builder. But now, with the addition of the new tool, you can also optimize the design using HEEDS and evaluate non-motion Key performance indicators such as efficiency and durability. The new workflow Start in Simcenter 3D Motion Transmission Builder. As you did previously, you start by defining your baseline layout using the Simcenter Motion Transmission builder wizard to parameterize the shaft, gears, and bearings from the selection menus. Once you have your gears defined, you can define/ choose your meshing pairs. Flanks can be either predefined by common standards or loaded from a CSV file to provide your own initial design. Note that if you are planning to complete an optimization using HEEDS , this initial input is only used for the baseline; HEEDS will alter it. To control the level of detail at the contact location, you define the number of gear slices. Where, the number of slices can be set to create imaginary gear layers in a sandwich-like fashion. Once your initial parameters are set, you can generate a model for the entire gear set with just one button. You can watch the model materialize as you watch in Simcenter 3D . The level of fidelity for Gear contact and bearing analysis can also be defined in the transmission builder tool and exported directly into your Simcenter 3D model by simply clicking ‘export all elements.’ Drivers and load cases can now be added, which is done in the Simcenter 3D Motion application. While the user does this, the total time to complete this task is measured in seconds. Now is a good time to create a solution and run the solver to check your setup. Once complete, you should review the outputs and results. Finding any errors in your setup at this stage will prevent you from wasting a lot of time later. Setup Simcenter 3D Motion Gear Design Optimizationn You can load the Simcenter 3D Motion Transmission builder and Simcenter 3D Motion files in the new wizard menu screen. Suppose you wish to optimize the durability of your gear set. In that case, you start by choosing the macro geometry features you want to include and setting your durability test by defining the speed, torque, and required life. Further parameters for this test are also needed, such as the material that can be selected from a menu and the microgeometry convention you wish to follow. Finally, you choose your desired post-processing, select the bearings you want, and set the optimization parameters. Start the design of experiments (DOE) study for your gear design optimization While you are still in the Simcenter 3D Motion Gear Design Optimization tool, initialize the calculation modules to compute the baseline model. This confirms that the model will run in HEEDS and provides HEEDS with the baseline result from which it needs to start. Now, when you open your project in HEEDS , you will find that over 70 design variables for the macro and microgeometry have already been created for cases with just two gear pairs. You will also find that all your output responses have been made, saving you considerable time. All that is left is to set the output responses you want to consider for the objective function and the constraints. You can also set the range to the input parameters if you want to. Getting a gear design optimization result Now, you can run the full DOE in HEEDS and, finally, post-process the results in HEEDS . Conclusion The New Simcenter 3D Motion Gear Design Optimization tool builds on the existing capabilities of the Simcenter Motion 3D Transmission builder with new capabilities that allow you to optimize your design using the power of HEEDS and evaluate non-multibody key performance indicators such as efficiency and durability. You can now develop designs you may never have conceived in a time frame you would have never thought possible in a general-purpose simulation tool. Schedule a meeting with CAEXPERTS and learn how to optimize your gear design with Simcenter 3D Motion Gear Design Optimization ! Reduce time, eliminate rework, and take your designs to a new level of efficiency. Talk to our experts today! WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

After successfully using Simcenter 3D Smart Virtual Sensing to predict loads for strength and fatigue analysis by combining testing and simulation, the well-integrated workflow optimized the efficiency of the entire team. This approach also included the possibility of “measuring the unmeasurable” on a larger scale. Challenges in durability analysis When analyzing potential damage under all possible load scenarios to validate a design, it is essential to obtain accurate data on operational loads. For those who are not experts in durability analysis, designing and validating mechanical structures under static and dynamic loads can be challenging, especially when trying to include operational loads in the study. With smart virtual sensing, operational loads can be obtained for durability analysis. The resulting information on remaining service life is extremely valuable. Despite the specialized tools available for detailed analysis, there is also a need for simpler and more integrated methods for everyday use. The old problem Traditionally, strain gauges are installed on prototypes to perform durability and validation testing. The big challenge is not that critical damage often occurs in areas where it is difficult or impossible to obtain direct formation effects due to geometry limitations. A new approach For load prediction, Simcenter 3D Smart Virtual Sensing can use just a few strain gauges in easily accessible locations to predict operational loads. The question was: could this approach be used continuously to measure unmeasurable loads and predict structural failures? Simcenter 3D Smart Virtual Sensing 2412 is dynamic and has a new feature – the Virtual Damage Sensor . This feature improves structural failure detection, providing a practical solution to a recurring problem. Solution Implementation With the Smart Virtual Damage Sensor solution, strain gauges can be placed in accessible locations to provide the smart virtual sensing tool with the necessary data. This enables data fusion between the physical measurement and the FE model, providing measurements in locations that are difficult to physically measure. Virtual sensors provide detailed results, including strain, stress, velocity, and displacement. In addition, the newly added virtual sensors integrate virtual sensing with durability analysis to provide important damage information, such as remaining service life, accumulated damage history, and damage increments. When combined, these results provide insights into the durability of the structure, indicating when damage is likely to occur and how much useful life is left. The workflow The process for implementing this solution follows these steps: Step 1: Use Simcenter 3D Smart Virtual Sensing Optimal Sensor Placement to determine where to place the physical strain gauges Parallel instrumentation with Simcenter SCADAS RS Step 2: Perform physical testing using Simcenter SCADAS and obtain strain measurements with operational loads. Step 3: Predict operational loads by feeding the measurements and the reduced-order finite element model into Simcenter 3D Smart Virtual Sensing . Step 4: Complete the durability study in Specialist Durability by connecting it to the Smart Virtual Sensing events. Step 5: Perform a durability study and figure out where the potential damage area is. (Step 4 and 5 are a recommended but optional way to find the critical areas). Step 6: Put virtual damage sensors on the potential damage area and run the smart virtual sensing solution to get damage information in the selected locations   The results With this workflow, data on remaining useful life, accumulated damage history, and damage increments can be obtained, allowing for more accurate analysis of the root cause of damage. By following this process, structural damage analysis becomes more efficient and reliable. The Smart Virtual Damage Sensor is a valuable tool for design and validation, offering a practical way to measure damage and assess remaining service life at critical locations. In addition, by making the Virtual Damage Sensor a real-time solution, it is also possible to implement predictive maintenance. This allows potential problems to be identified before they occur, avoiding costly downtime. Optimizing maintenance task scheduling can reduce large safety factors typically included in worst-case scenarios, making structural engineering more accurate and cost-effective. Schedule a meeting with CAEXPERTS and find out how the Simcenter 3D Virtual Damage Sensor can transform your durability analysis, making it more accurate and efficient. Talk to our experts and take your structural engineering to the next level! WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Don’t try this at home – unless you’re simulating it! Thermal Runaway: a recap Thermal runaway of batteries is a dangerous phenomenon where the battery cell overheats uncontrollably. A self-sustaining feedback loop occurs where the battery receives a certain amount of heating, and if left unaddressed, this in turn triggers a series of chemical reactions inside the battery cell. These reactions release even more heat and gases, which can result in huge pressure build up inside the battery. Extremely hot (over 1000oC!) and combustible venting gases are then emitted from the battery cell. When these gases ignite, fire spreads to other battery cells and catastrophic damage can occur to an electric vehicle, property and of course presents a high risk to life. Look at this short video which shows the violent nature of a thermal runaway event: It should be clear that these scenarios should be avoided, and battery systems designed to ensure safe operation if a thermal runaway event occurs. Indeed there are now various national and international regulations that cell makers and electric vehicle manufacturers must adhere to. Time to test? – Accelerated rate calorimetry (ARC) The most intuitive way to understand the behavior of batteries as they undergo a thermal runaway event is to replicate the causes of thermal runaway and see how the battery behaves. In the case of overheating, a common methodology to understand the heat release of the battery is an accelerated rate calorimetry (“ARC”) test. These tests provide clear insights but come with some issues: primarily that the tests themselves are expensive, require access to test facilities and require a physical prototype of the battery cell! Of course, this is where simulation can fit in and allow for rapid design iterations early in the design cycle, with safety in mind. Simcenter STAR-CCM+ already has a wide range of models and functionalities for battery modelling and battery safety, from the 3D cell design right through to the full battery pack and thermal propagation during a runaway event: In version 2502, another layer of functionality will be added – most notably the ability to model detailed thermal runaway at the cellular level with the Homogeneous Multiphase Complex Chemistry (HMMC) model. Thermal runaway chemistry When we consider the inside of a battery cell then there are multiple solids (anode, cathode and separators), as well as liquid electrolyte. When thermal runaway reactions occur, these components can react and decompose to release flammable gases such as hydrogen and methane. This results in multiple phases all reacting with each other e.g multiphase. To capture this complexity, a framework has been developed in which the early stages of a thermal runaway event can be modeled with detailed chemical modeling. This allows designers to explicitly model the fundamental reactions that are triggered during a thermal runaway event. The reactions are considered as a homogeneous mixture, allowing for simple and easy setup in conjunction with our multiphase mixing model. Furthermore, this is all built on top of a proven complex chemistry solver, allowing reactions to be easily defined using standard chemkin file import and accounting for intra- and interphase reactions. This provides unique modeling functionality to deeply understand battery behavior. For example, one can directly configure reactions for SEI decomposition/production, conductive salt decomposition, hydrogen fluoride production, and cathode decomposition; see the example of imported reactions for thermal runaway testing above. Let’s get cookin’ – Heat-Wait-Seek Armed with a new modelling tool, let’s apply it to the simulation of an ARC test and see how it performs. The ARC test involves an initial period of heating the battery called Heat-Wait-Seek (HWS) where the battery is gradually heated before waiting to see if exothermic reactions begin. When those reactions begin, no more heat is applied to the battery, and it is left to continue reacting / self-heating until the onset of thermal runaway. Unveiling the interaction of reactions and phase transition during thermal abuse of Li-ion batteries https://doi.org/10.1016/j.jpowsour.2021.230881 One great thing about having this physics functionality inside Simcenter STAR-CCM+ is that it can leverage the automation capabilities. The ARC testing process can be easily implemented using Simulation Operations and Stages without any scripting. And the results are excellent: As can be seen, the new HMMC model can accurately capture the onset of both the exothermic reaction and thermal runaway. Being able to accurately capture this behavior allows for effective countermeasures or mitigation strategies such as heat shields to be implemented by engineers much earlier in the design process in a safe and cost-effective manner. For example, the predicted heat generation from this simulation can be used as an accurately calculated heat source directly in a larger pack level model, or the predicted vent gas compositions used for a further combustion analysis. An excellent example of how simulation is vital in the battery design cycle. Schedule a meeting with CAEXPERTS and find out how we can help your team design safer, more efficient battery systems using advanced simulation to predict and mitigate thermal runaway events. Contact us now and take your innovation to the next level! WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

The latest update to Simcenter STAR-CCM+ 2502 brings pivotal enhancements across various domains, focusing on boosting simulation speed, enhancing model accuracy, and improving integration across different engineering disciplines. Key advancements include an efficient mesh motion technology for moving objects, faster vehicle thermal management and aerodynamics simulations, streamlined data exchange for E-Machines, and sophisticated methods for accurately modeling battery thermal runaway onset, corrosion and complex non-Newtonian fluid behavior. These developments are designed to help you accelerate development cycles, optimize product performance, and facilitate cross-team collaboration, ultimately driving innovation and efficiency in your projects. Improved battery safety simulations Battery manufacturers face the critical challenge of ensuring safety, particularly the risk of thermal runaway during short circuits or other failures. Traditional modeling tools have struggled to accurately predict these complex chemical and electrochemical reactions. To address this, the latest release of Simcenter STAR-CCM+ 2502 features the “Homogeneous Multiphase Complex Chemistry Model,” designed to provide a detailed simulation of battery cell behaviors under adverse conditions. Although a general model, the homogenous multiphase complex chemistry model can allow designers to explicitly model the fundamental reactions that are triggered during a thermal runaway event, providing detailed insight into the electrochemical and thermal response to a short circuit or nail penetration incident in a battery. This allows engineers to gain deeper insight and design batteries with high degrees of safety without the cost of physical testing. This improved capability ultimately helps in preventing accidents, enhancing consumer trust, and complying with stringent safety regulations. Advanced corrosion analysis Corrosion is a pervasive issue across many industries, leading to significant maintenance costs and equipment downtime. Traditional analysis tools often fail to predict the onset and progression of corrosion effectively, leading to unexpected failures. Simcenter STAR-CCM+ 2502 integrates Corrdesa’s Corrosion Djinn Database for advanced corrosion analysis. High-quality polarization data describes the relationship between the potential drop at the material interface and the specific electric current and are important inputs to the Electrodynamic Potential solver of Simcenter STAR-CCM+ . The Corrdesa Corrosion Djinn material database hosts collection of data, including surface polarization, derived through rigorous experimental quantification. This feature offers engineers robust tools to simulate and predict corrosion under various environmental conditions, using high-fidelity data. As a result, industries can proactively design out potential corrosion issues, extend equipment lifespan, and significantly reduce maintenance costs. Accurate modeling of complex fluids In the food processing industry, accurately predicting the behavior of complex fluids, such as mayonnaise, which exhibit non-Newtonian characteristics, presents significant challenges. These fluids can behave like a solid at lower shear stress levels before moving like a fluid at elevated stress levels. This behavior is complicating production processes and quality control. In response, Simcenter STAR-CCM+ 2502 introduces Generalized Non-Newtonian Fluid Models, namely the Yield Stress Threshold and Yielding Viscosity for Non-Newtonian Cross and Carreau-Yasuda laws. These advanced viscosity models capture the intricate behaviors of such complex Bingham fluids under stress more accurately than ever before. By simulating these fluids’ behaviors, engineers can precisely predict how they will act in the real world, thereby optimizing manufacturing and filling processes. Uniform spray coverage for various applications Achieving uniform spray coverage is imperative in industries ranging from agriculture to automotive manufacturing, where it impacts everything from crop yields to paint finishes. Variability in this process can lead to inefficiency and wastage, posing a substantial logistical challenge. In many such cases the flat fan nozzle Injector provides a uniform, flat spray pattern of a thin, fan-shaped sheet of liquid. In agriculture, flat-fan nozzles are e.g. essential for providing uniform spray coverage in aerial pesticide applications. Similarly, these types of injectors are used for cleaning and degreasing, coating and painting, cooling and humidifying, lubrication, surface Treatment and dust control. The Flat Fan Nozzle Injector model in Simcenter STAR-CCM+ 2502 makes it easy to set-up such injectors quickly and easily. Accurate results are achieved by the Linear Instability Sheet Atomization (LISA) method. This technology ensures uniform application across varied operations, improving resource utilization and process efficiency. Ultimately, this leads to reductions in waste and costs, contributing to more sustainable and eco-friendly production practices. Faster adjoint-based optimization Adjoint optimization methods rely on a series of multiple simulations, in which the adjoint solver is executed at each step. Considering that the adjoint solver is very expensive in terms of computational resources, these optimization studies easily reach the limit of feasibility. The algorithmic improvements made in Simcenter STAR-CCM+ 2502 to the adjoint solver with second order discretization drastically improve the convergence rate, thus lowering significantly the total turnaround time. Furthermore, this improvement reduces the need for falling back to first order adjoint discretization for a robust convergence, hence improving the accuracy of the computed adjoint sensitivities. The reduced simulation time and higher-quality results, enables engineers to explore and realize optimal designs much more efficiently and effectively. Fast and scalable simulations of moving objects Many applications, such as paint dipping and bottle filling, involve the movement of a solid body that affects the motion of a fluid. To capture the motion the overset meshing approach offers both flexibility and accuracy by utilizing a background mesh combined with a body-fitted moving mesh. This configuration ensures high mesh quality near the boundaries of moving objects, leading to precise results. However, this accuracy comes at the cost of increased complexity, which results in higher computational expense and suboptimal scaling. The new Virtual Body approach that is available in the new version of Simcenter STAR-CCM+ 2502 eliminates the need for two separate meshes and provides a more cost-effective, scalable, and easier-to-setup alternative to overset for various validated application. Furthermore, it also offers a more stable solution in scenarios involving tight gaps. Faster sliding mesh simulations on GPUs and CPUs Many applications like external vehicle aerodynamics with rotating wheels, require rigid body motion (RBM) to capture transient, unsteady flow phenomena. This employs the sliding mesh interfaces, also known as non-conformal interfaces. Traditionally, in such scenarios the interface intersection is performed at every time step. Because of the complexity of the intersector algorithm and its high interface data requirement, the performance of the sliding meshes when deployed on large core counts or used with GPUs, has been restricted. Case (cell count) Total sim time (min) No Caching Total sim time (min) Caching Number of CPU/GPUs Speed up Case 1 (120 M) 165.6 149.8 8 x A100 GPUs 10% Case 2 (150 M) 223 187.4 8 x A100 GPUs 16% Case 3 (38 M) 862 470 8 x A100 GPUs 45% Case 4 (140 M) 13 hrs 10.5 hrs 16 x V100 GPUs 19% Case 5 (136 M) 50.7 hrs 44.9 hrs 1600 Cores 12% The new Boundary Interface Caching strategy that is available in the new version of Simcenter STAR-CCM+ 2502 allows for the interface data to be calculated only once and reused for the subsequent time steps, thereby significantly reducing sliding mesh simulation time on both CPUs and GPUs. Faster Vehicle Thermal Management simulations on GPUs The automotive industry is constantly pushed to enhance energy efficiency while managing the heat generated during operation, a demanding aspect of vehicle design. At the same time the benefits of GPUs to solve CFD simulations faster and in a more energy efficient way are without a doubt. With Simcenter STAR-CCM+ 2502 we are further expanding the range of thermal management applications you can tackle on CPUs and GPUs through the porting of more GPU-native solvers: The new GPU-native Actual Flow Dual Stream Heat Exchanger method leverages GPU acceleration to perform complex VTM simulations. Further applications covered include faster CHT simulations of headlamps with the GPU-native segregated and coupled energy solvers for solid shell regions as well as faster Batteries CHT and Electronics cooling analyses thanks to GPU-native Orthotropic, Anisotropic and Transverse Isotropic material property methods. This will increase your throughput and hardware options while a unified solver architecture for CPU and GPU ensures consistent results. As a result, you can perform more thermal management simulations in less time, enhancing productivity and accelerating the development cycles. Native automation of advanced aerodynamics and turbomachinery workflows Complex simulations involving multiple physical phenomena or varied operational stages can be cumbersome to set up, often requiring intricate scripting and setup. The Stages feature within Simcenter STAR-CCM+ streamlines this process. It provides a user-friendly interface for defining and managing simulation stages, cutting down setup time and allowing engineers to focus more on analysis and less on setup. With Simcenter STAR-CCM+ 2502 stages become available for a further extended range of applications: With the support of harmonic balance and harmonic balance turbulence models you can tackle turbomachinery simulation workflows with ease. Stages support for Moving Reference Frame and Rigid Body Motion simplifies workflows with a change from steady state to transient, such as external aerodynamics with rotating parts. The Stages method not only accelerates the simulation workflow but also significantly boosts productivity and mitigates potential setup errors. Streamlined data exchange for E-Machine design Collaboration between electric machine designers and computational fluid dynamics engineers is often hindered by incompatible data formats and systems. The “Simcenter Data Exchange (SCDX)” format, newly implemented in Simcenter STAR-CCM+ 2502 , resolves these issues by ensuring smooth and efficient data transfer across different software tools and teams. This integration capability facilitates a more cohesive workflow, reducing errors, and enabling faster project completion through improved collaboration. These are just a few highlights in Simcenter STAR-CCM+ 2502 . These features will enable you to design better products faster than ever, turning today’s engineering complexity into a competitive advantage. Multiversion support for Simcenter X HPC Facing an urgent CFD project that requires immediate HPC capacity? Questioning massive CAPEX investments for on-premise HPC clusters? Tired the complex IT setup associated with running CFD software on 3rd party cloud-providers? Just not interested in waiting in the queue? Simcenter X HPC enables you to unlock productivity gains with the power of turn-key cloud simulation. Run your Simcenter STAR-CCM+ simulations anytime in the cloud, straight out of Simcenter STAR-CCM+ in 3 clicks. No queuing involved, no IT overhead, no on-premise HPC hardware investments. To make the most out of Simcenter X HPC, with the release of Simcenter STAR-CCM+ 2502 you will have immediate access to the most recent version. Alongside 2502, multiple versions of Simcenter STAR-CCM+ are now available on Simcenter X HPC, including previous versions 2410, 2406, 2306. Use clusters of sizes from 100s to 1000s of cores, instantaneously from a few clicks. Schedule a meeting with CAEXPERTS now and find out how Simcenter STAR-CCM+ can transform your simulation processes, reducing development time and increasing the accuracy of your projects. Talk to our experts and take your engineering to the next level! WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Safety at work should be a priority in any operation, but in emergencies, quick and assertive decision-making can be the difference between life and death. To increase operator safety during activities carried out at height, it is essential to determine the maximum wind speed for safe operation. This is a classic example of an operation using rappelling. In these conditions, the operator faces high-speed winds, which can cause oscillations during work and can result in collisions with other equipment or objects. But how can you anticipate and plan responses to these events? This is where CAE simulation makes all the difference. CAE Simulation The acronym CAE (Computer-Aided Engineering) refers to Computer-Aided Engineering, a technology that uses software to simulate and analyze engineering projects. This tool allows you to predict the behavior of a product before its physical construction, assisting in the development and improvement of projects. CAE simulation is applied in several areas, including structural, fluid, thermal and electromagnetic analysis. The best-known and most widely used techniques are Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) . The benefits of CAE simulation for companies are: Greater efficiency, reliability and quality Cost reduction Reduced developer time in product development Elimination or reduction in the number of test prototypes to be built Increased competitiveness CAE simulation allows for the digital recreation of several scenarios, for example, by analyzing factors such as fall conditions, interaction with the environment, performance of safety equipment and emergency evacuation strategies. With this information, it is possible to improve equipment, enhance protocols and develop more effective training to increase the safety of workers and rescue teams. The Importance of Emergency Planning Emergencies such as falls, leaks or fires can occur even with rigorous preventive measures. The difference lies in how well the team and systems are prepared to deal with these situations. CAE simulation transforms the unpredictable into something controllable, allowing: Faster responses: Equipping teams with elaborate information and ready action plans. Damage reduction: Minimizing impacts on the worker and the operation. Tragedy prevention: Developing strategies to prevent similar situations from occurring again. Simulation The operator, weighing 90 kg, is suspended by a rope, simulating a rappel down a 50-meter tower. The analysis considers the acting forces, such as weight, wind force and turbulent interaction and the tension on the rope. The simulation allows for the inclusion of an air speed curve in relation to height, making the assessment of air flow more accurate, considering turbulence and interaction with the environment. Including the air speed curve in the simulation allows us to assess how wind currents influence the operator's oscillation during rappelling. The intensity and direction of the wind affect the operator's movement, impacting balance and stability. With this analysis, it is possible to predict these effects, helping to understand external forces and their impact on the safety and performance of the operation. In addition, the data obtained allows us to optimize the planning of activities at height and select the most appropriate equipment to reduce risks.   During the simulation, it was possible to determine the force applied to the rope, considering the environmental conditions and the characteristics of the rappelling operation. Factors such as wind speed and sudden movements directly influenced this force. In scenarios with strong winds, with a speed of 15 m/s, the force on the rope reached a peak of 3000 N, which can reach the breaking limit of the rope. This result highlights the importance of evaluating environmental and operational conditions to ensure safety, in addition to the need to carefully choose the materials and equipment used in risky activities. Commitment to life The application of numerical simulations goes beyond innovation; it is a demonstration of commitment to the safety and well-being of workers. In times of emergency, where decisions need to be made in seconds, having the confidence that every detail has been analyzed and planned can save lives. If you would like to explore how CAE simulation can transform workplace safety, optimizing prevention and response to emergencies, get in touch. Let's build safer environments together and protect what is most valuable: people. Schedule a meeting with CAEXPERTS and find out how CAE simulation can transform safety in your workplace! With advanced technology and detailed analysis, we help your company prevent risks, optimize processes and protect lives. Contact us now and take operational safety to the next level! WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Simcenter Amesim software, which allows engineers to virtually assess and optimize systems’ performance, can now be used to recreate the remarkable achievements of the Ingenuity Mars Helicopter, nicknamed “Ginny”, which completed its last flight on the Martian surface a year ago. This mission significantly advanced our knowledge of powered and controlled flight on another planet, serving as a source of inspiration for engineers and space enthusiasts. As NASA Administrator Bill Nelson stated, Ingenuity’s journey represents a groundbreaking milestone in human exploration. “Helicopter Above Perseverance on Mars” – Credit: NASA/JPL-Caltech Ingenuity’s Groundbreaking Flights on Mars When the Perseverance rover touched down on Mars in February 2021, it carried a small companion – the Ingenuity Mars Helicopter. This 4-pound (1.8 kg) robotic rotorcraft was the first powered, controlled aircraft to fly on another planet. Over the course of its mission, Ingenuity far exceeded its original design specifications. Instead of the planned five test flights, Ingenuity went on to complete 72 flights, traveling over 17 kilometers (11 miles) and reaching altitudes of up to 24 meters (79 feet). Ingenuity gained the ability to autonomously select landing sites in treacherous terrain. It also dealt with a malfunctioning sensor, cleaned itself after dust storms, operated from 48 different airfields, and performed three emergency landings. Remarkably, the helicopter even survived the harsh Martian winter. However, the extreme cold of winter posed a significant challenge. Designed to operate during the milder spring season, Ingenuity was unable to power its heaters throughout the frigid Martian nights. This resulted in the flight computer periodically freezing and resetting, a phenomenon known as “power brownouts.” To address this issue, the Ingenuity team had to redesign the helicopter’s winter operations to keep it flying. These flights provided invaluable data and demonstrated the viability of powered flight on Mars, paving the way for future aerial exploration. Ingenuity’s final flight on January 18th, 2024 marked the end of its groundbreaking mission, but the legacy of this little helicopter lives on. Its success has inspired the development of even more ambitious aerial platforms for future Mars exploration. Simulating Ingenuity’s Flights with Simcenter Amesim To celebrate the anniversary of Ingenuity’s last flight, Siemens has developed a system simulation demonstrator that replicates the key aspects of the helicopter’s flight using Simcenter Amesim . Ingenuity flight physics model in Simcenter Amesim Simcenter Amesim is a powerful multiphysics simulation platform that allows engineers to model and analyze complex systems, including flight dynamics, energy management, guidance, navigation, and control of aerial vehicles like Ingenuity. This demonstrator recreates the unique challenges of flying on Mars, including the planet’s thin atmosphere, low gravity, and extreme temperatures. By accurately modeling the physics of Ingenuity’s flight, the energy requirements of its systems, and the control algorithms that guided its movements, the demonstrator provides a realistic simulation of the helicopter’s remarkable achievements. Through this simulation, users can explore the design trade-offs and engineering decisions that went into Ingenuity’s development, gaining a deeper understanding of the technical challenges overcome by the NASA team. Additionally, the demonstrator serves as a valuable tool for testing and validating new aerial platform concepts for future Mars exploration. Experience the Thrill of Ingenuity’s Flights To commemorate the anniversary of Ingenuity’s last flight, we invite you to experience the thrill of this historic achievement through Simcenter Amesim-based system simulation demonstrator. Dive into the details of Ingenuity’s flight physics, energy management, guidance, navigation, and control, and see how this groundbreaking technology can be replicated and advanced using state-of-the-art simulation tools. The demonstrator can be accessed in the software by opening the built-in help feature. If you are not a Simcenter Amesim user, you can start your free trial now. Simcenter Amesim software is part of the Simcenter simulation and test solutions that you can leverage today to drive productivity, achieve better designs faster, and ensure successful space program outcomes. This is particularly crucial due to the increasing complexity of systems in every new generation of aircraft and spacecraft. As engineers strive to push boundaries and achieve innovation, they often encounter unexpected issues and face costly program delays. To address these challenges, a new approach is required, focusing on quicker and more cost-effective processes that not only uphold but also enhance performance and compliance. This entails driving digital transformation to gain a competitive advantage. Want to take your simulations to the next level? Schedule a meeting with CAEXPERTS and find out how Simcenter Amesim can optimize your projects, reducing costs and development time. Contact us now and take your solutions to the next level! WhatsApp: +55 (48) 988144798 E-mail: contato@caexperts.com.br

Simulating the performance of James Webb Space Telescope components Challenges Design a next-generation space telescope Coordinate systems supplied by multiple sources Operate at temperatures near absolute zero Results Standardizing on Femap shortens learning curve Visualization pinpoints potential flaws in components Finding and fixing potential problems long before the telescope is launched NASA Goddard Space Flight Center The NASA Goddard Space Flight Center is home to the United States’ largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system and the universe. Named for American rocketry pioneer Dr. Robert H. Goddard, the center was established in 1959 as NASA’s first space flight complex. Goddard and its several facilities are critical in carrying out NASA’s missions of space exploration and scientific discovery. Building a time machine The use of Femap™ software from Siemens PLM Software is helping NASA develop a time machine. Scheduled for launch in 2018, the James Webb Space Telescope Observatory (JWST) will operate 1.5 million kilometers above the Earth. Its mission is ambitious: examining every phase of cosmic history “from the first luminous glows after the Big Bang to the formation of galaxies, stars and planets to the evolution of our own solar system,” according to the JWST website. The telescope will look back light-years into the past. Considered to be the next generation – not the replacement – of the Hubble Space Telescope, the JWST is an infrared telescope that enables the viewing of more distant, highly redshifted objects. The Hubble is used to study the universe in optical and ultraviolet wavelengths. The JWST will also be larger than Hubble, which is about the size of a large tractor-trailer truck. At 22 by 12 meters, the JWST will be almost as large as a Boeing 737. Fully deployed, the JWST will feature a reflecting mirror with seven times more collecting area than the Hubble. The telescope will be launched into space atop an Ariane 5 rocket from the European Space Agency’s (ESA) launch pad in French Guiana. The JWST will have a hot side and a cold side, with the hot side consisting of the observatory spacecraft, which manages pointing and communication, and a shield that blocks heat and radiation from the sun, Earth and moon. The cold side of the JWST, operating at temperatures near absolute zero, is where the science will happen. Four major instruments will be in operation, including the near-infrared camera or NIRCam, provided by the University of Arizona. Other major instruments include the near-infrared spectrograph (NIRSpec), provided by the ESA, with additional instrumentation provided by the NASA Goddard Space Flight Center (GSFC); the mid-infrared instrument or MIRI, provided jointly by the ESA and NASA’s Jet Propulsion Laboratory (JPL) and the fine guidance sensor/near infrared imager and slitless spectrograph, provided by the Canadian Space Agency. All in all, there are more than 1,000 people in 17 different countries working on JWST, including academic and industrial partners ATK, Ball Aerospace, ITT, Lockheed Martin, Northrop Grumman (the prime contractor) and the Space Telescope Science Institute. Multiple analysis applications feed into Femap Designing, testing, building and assembling JWST is a team effort, taking place on three continents. The instruments now under development are being tested using a variety of computer-aided engineering (CAE) solvers for modal, thermal, thermal distortion and structural analysis. Gluing all this analysis and simulation work together is Femap , the JWST team’s standard application for pre- and postprocessing. “We use Femap as the pre- and postprocessor,” says Emmanuel Cofie, who leads thermal distortion analysis on the ISIM (integrated structural instrument model). “The mechanical design team provides us with CAD files and we use Femap to generate meshes for our mathematical model and, after finite element analysis, to extract results and view the condition and state of the structure under the various load conditions. It is the primary tool we use for visualization of the structure in its operational/launch states before actual environmental testing.” Because there will be only one opportunity for the JWST to succeed, every part and assembly of every system needs to be thoroughly tested on Earth to ensure that all instruments will function flawlessly under expected conditions. Simulating the JWST’s performance on Earth is the only way to determine that the observatory will function once it is in place. It’s a one-of-a-kind, custom job. Using CAE solvers in conjunction with Femap , NASA engineers conduct simulations to ensure each part does not interfere with another and that parts and assemblies have sufficient strength and can withstand extreme heat or cold and vibrations experienced during launch and normal operating conditions. “ Femap is a very usable tool that is at once very affordable and also provides high value,” says Mark McGinnis, thermal distortion working group leader at Goddard. “It enables us to carry out our mission of analyzing the structural and thermal performance of parts and systems. Femap is easy to learn and use, and works well with any solver.” He estimates that the software is used frequently by at least 75 NASA engineers at Goddard. “For example, we will import a back plane sub-assembly model from a contractor and populate it with 18 mirrors to visualize how they come together,” says McGinnis, “We need to be sure the interface grids are coincident as they are supposed to be, and then use it to build the more than 8 million required grids, which makes a very large model from a computing standpoint. We assemble the model using Femap .” Most of the engineers working on the JWST have used Femap as far back as the mid-1990s. Cofie recalls using Femap during the development of Hubble. “We used it for a lot in those days and we continue to use it,” he says. “ Femap helps us understand loading conditions so we can take a structure, run the analysis and see what gets hot and what gets cold. It helps us visualize whether or not a model is feasible.” McGinnis agrees that the visibility Femap provides in postprocessing is a key advantage. “An engineer can easily understand the mathematical results of an analysis conducted with a solver,” he says. “But visualizing analysis results using Femap is an important benefit, showing you exactly what is going on.” Schedule a meeting with CAEXPERTS and find out how advanced simulation can transform your projects! Just as NASA used Femap to ensure the success of the James Webb Space Telescope, we can help your team identify potential failures, optimize performance, and shorten the learning curve. Talk to our experts and take your engineering to the next level! WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br