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The main function of a boiler is to produce heat to heat water or generate steam, which can be used in different industrial processes and in power generation. This equipment can operate with various types of fuel, including fuel oils, natural gas, electricity and biomass. In the case of boilers that use biomass, the heat is generated by burning materials of organic origin, such as pieces of wood (chips), sugarcane bagasse and straw, rice husks and other waste from agriculture. This alternative is considered more sustainable because it uses byproducts that, considering their life cycle, have zero or very low carbon emissions. Figure 1 – Biomass Figure 2 – Operating principle of a biomass boiler Using biomass as an energy source brings significant environmental benefits. As it is a renewable resource, it allows the use of organic waste, such as agricultural and forestry remains, and helps to reduce the emission of greenhouse gases — especially when compared to the use of fossil fuels such as diesel oil. This is because biomass participates in a more balanced carbon cycle: plants absorb carbon dioxide (CO₂) from the atmosphere as they grow, and this same CO₂ is released again during combustion. In addition, because it contains shorter carbon chains, its combustion is more efficient, generating fewer pollutants such as carbon monoxide (CO), nitrogen oxides (NOₓ) and unburned hydrocarbons. Fossil fuels, especially those with longer carbon chains (such as C₈ or C₁₂), are more difficult to break down during combustion, which favors the formation of intermediate species and increases the emission of these pollutants. Thus, the net impact of biomass tends to be much smaller than that of fossil sources. Figure 3 - Carbon cycle The efficiency of biomass combustion inside boilers depends directly on how the fuel is distributed over the grate. In fixed grate systems, it is common for the material to accumulate unevenly, resulting in partially burned layers over other unburned layers. This creates areas with incomplete combustion, compromising the boiler's thermal performance. In addition, this accumulation of unburned fuel can cause accidents due to spontaneous combustion that can occur when it is removed from the boiler hot and comes into contact with oxygen in the air again. Some companies report accidents, for example, when blowing compressed air to unclog the ash collection hopper and with unburned biomass at high temperatures. Combustion modeling using STAR-CCM+ As already shown in the post DEM simulation applied to boilers, initially only the flow of biomass over the grate was evaluated, comparing the cases with fixed and vibrating grates. At this stage, the combustion process was incorporated into the model. Using Simcenter STAR-CCM+ , it is possible to simulate biomass combustion, observing the reduction in particle mass due to carbon volatilization during combustion. The primary air flow, which acts as an oxidizing agent, is also considered, allowing its influence on combustion efficiency and gas flow to be evaluated. Figure 4 – Discrete Element Method (DEM)   By associating the DEM model with the combustion model, it is possible to map biomass combustion. Figure 5 - Computational model of the grate and reaction environment The Simcenter STAR-CCM+ Eddy Break-up combustion model enables detailed simulation of the biomass burning process. It combines a fluid domain, which represents the air where the reactions will occur, and the DEM itself, in addition to other auxiliary models such as turbulence and mass transfer. With this, it is possible to observe the evolution of the combustion process, evaluate the time required for complete combustion, the temperatures reached during the reaction, the products generated (such as CO₂, CO, H₂O, among others) and the mass flow required to maintain combustion in a steady state. Figure 6 - Molar fraction of air, fuel, carbon monoxide and carbon dioxide during the combustion reaction This makes it possible to map the entire thermal system, identifying zones of high and low reactivity, regions with incomplete combustion, areas of material accumulation or oxygen deficiency, in addition to optimizing the air supply and the internal geometry of the boiler.   Video 1 – Air and particle temperature during biomass burning This integration between the DEM flow model and the combustion model allows a complete understanding of the behavior of biomass within the system, promoting improvements in thermal performance, greater efficiency in energy conversion and reduction in pollutant emissions. Video 2 – CO₂ concentration and particle mass during biomass combustion Using Simcenter STAR-CCM+ to simulate biomass flow and combustion allows the entire thermal process to be accurately represented, from fuel movement to complete combustion. This approach makes it possible to identify operational failures, optimize boiler design, and adjust variables such as geometry, vibration, and air supply. This makes it possible to increase energy efficiency, reduce fuel consumption, minimize emissions and waste, and make the plant safer, more reliable, and more sustainable. Simulation thus becomes an essential tool for the modernization and improvement of industrial thermal systems. References:   CARVALHO, Leonardo Lima de. Estudo da dinâmica de escoamento da unidade Microwave Paddle Dryer . 2021. Dissertação (Mestrado em Engenharia Química) – Faculdade de Engenharia Química, Universidade Federal de Uberlândia, Uberlândia, 2021. Available at: https://repositorio.ufu.br/bitstream/123456789/34002/1/EstudoDinamicaEscoamento.pdf .   OLIVEIRA, Luiz. Avaliação numérica do fenômeno de mistura em tambores rotatórios . ENEMP – Congresso Brasileiro de Sistemas Particulados, 2022. Do you want to understand how to optimize the performance of your biomass boiler and reduce emissions using advanced simulations? Schedule a meeting with CAEXPERTS now and find out how applying the combustion model coupled with DEM can transform your operation in efficiency, safety and sustainability. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Simcenter Systems Simulation 2504 has just been released. It contains many exciting new features that will help its users move faster, deal with more complexity, better integrate, and explore new possibilities. Platform update The latest release of Simcenter Systems brings a wave of enhancements designed to accelerate workflows, simplify complex simulations, and boost integration across platforms. From smarter radiation modeling using embedded CFD data to faster simulations, resizable sketch icons, and advanced model validation tools, Simcenter Amesim 2504 and Simcenter Flomaster 2504 empower engineers to build, test, and optimize with greater speed and confidence. With support for FMI 3.0 and license-free FMU export, this update makes collaboration and system integration more seamless than ever. Simcenter Systems 2504 Enhancing modeling efficiency – Resizable icons in Simcenter Amesim sketch Simcenter Amesim streamlines modeling with resizable icons in its sketch environment. This intuitive click-and-drag functionality allows engineers to emphasize key components and subsystems, providing them with the prominence they deserve. Supporting all Simcenter Amesim components, including supercomponents and statecharts, resizing maintains design integrity with preserved aspect ratios. This feature enhances the sketch environment, allowing dynamic presentations and quick adjustments such as copy/paste scaling and reset scaling. With Simcenter Amesim’s resizable icons, engineers can efficiently focus on critical elements, ensuring clarity while modeling complex systems. Speeding up complex models – Simulation acceleration in Simcenter Amesim As systems grow in complexity, simulation models can become cumbersome and time-consuming. Simcenter Amesim has introduced a new adaptive tolerance algorithm to enhance it solver efficiency. This improvement reduces processing times, allowing engineers to gain quicker insights and make rapid decisions. On average, simulations run 19% faster compared to previous versions, helping tackle challenges posed by electrification in both current and future systems. With faster processing, Simcenter Amesim enables engineers to navigate complexity swiftly, boosting productivity and innovation. Ensuring model validation – Test execution manager in Simcenter Amesim Simcenter Amesim introduces the test execution manager to streamline the validation of models and library developments, along with Simcenter Amesim upgrades. This non-regression testing tool efficiently compares simulation results against test cases, ensuring reliability across updates. Engineers benefit from facilitated testing of new developments, seamless upgrading of software versions, and the ability to execute tests both locally and remotely via a web page. The test execution manager keeps your models validated and integrated, supporting continuous development and innovation with confidence. Enhancing model integration – FMI 3.0 co-simulation import in Simcenter Amesim Simcenter Amesim enhances model integration through the support of FMI 3.0 co-simulation import. This feature facilitates the assembly of heterogeneous models using the latest FMI version, offering flexibility with fixed-size and tunable elements and parameters. With this capability, engineers can import a variety of virtual ECUs, including those with arrays, and 3.0 FMUs from tools like Simulink, Dymola, and others. It also enables the mixing of multiple 3.0 and 2.0 FMUs, enhancing compatibility and integration across platforms. Moreover, engineers can apply distinct run settings for each imported FMU, ensuring precise simulation control and effective collaboration. Simplifying model sharing – License-free FMU export in Simcenter Flomaster Simcenter Flomaster introduces a new license option for exporting FMUs that operates without the need for a license server connection, addressing the challenge of using embedded solver FMUs offline. This feature facilitates the easy deployment of FMUs to offline platforms, streamlining workflows when license servers are inaccessible. Additionally, it enables the sharing of models with external partners, enhancing collaboration and integration efforts across different teams and organizations. Electrification As electrification reshapes industries, engineers face growing challenges in battery development, from performance testing to thermal management and aging analysis. The Simcenter Systems 2504 release takes battery simulation to the next level, introducing powerful new tools that make modeling more intuitive, accurate, and aligned with real-world testing. From an enhanced battery cycler to smarter aging models and guided pack design, discover how Simcenter helps you build better batteries faster. Battery Empowering advanced battery testing – Enhanced battery cycler Evaluating battery performance across multiple charge and discharge cycles can be both technically demanding and time-consuming. With the release of Simcenter Systems 2504, we’re introducing an enhanced battery cycler that makes this process significantly easier—and more realistic. Instead of configuring every step manually, engineers can now define entire test sequences through a simple, human-readable text file. Each test can include a range of actions, from basic charging and discharging cycles to custom current profiles, looped sequences, and specific event-based conditions. It’s as close as you can get to operating a real battery test bench—without the hardware. This improvement allows for a much more flexible and intuitive way to run performance assessments and optimization routines, enabling users to simulate complex scenarios and make smarter design decisions, faster. Innovating battery longevity analysis – Electrochemical aging model enhancement Understanding battery aging is vital for engineers as various degradation mechanisms can affect performance and lifespan. Simcenter addresses this challenge with its enhanced battery P2D electrochemical model, which employs advanced pseudo-2D and single-particle modeling capabilities. This innovative model helps identify key degradation mechanisms like positive electrode dissolution, SEI layer growth, and lithium plating. Furthermore, it facilitates the automatic evaluation of effective battery capacity, enhancing both design and operational performance. With this tool, engineers gain valuable insights into battery aging, empowering them to optimize energy storage solutions for increased reliability and efficiency. Energy and thermal management Simplifying complex cavity radiation modeling – Embedded CFD data exchange Simcenter’s Embedded CFD feature revolutionizes thermal comfort management by modeling complex cavity radiation using predictive 3D capabilities in a 1D model. This approach extracts view factors from 3D and translates them into the 1D radiation model. Engineers benefit from automated 3D factor computation and retrieval from Simcenter STAR-CCM+ directly within 1D models. By using user-defined 1D enclosure boundaries, the solution provides automated and efficient resolution of finite radiative fluxes, enhancing system design accuracy and thermal performance. Streamlining battery pack modeling – Battery pack assistant Evaluating battery performance alongside its cooling capabilities presents significant challenges, particularly due to the complex interplay of the physics involved. To streamline this process, Simcenter introduces the battery pack assistant, designed to guide engineers in generating comprehensive multi-physics models. This user-friendly tool offers an intuitive workflow that empowers users to define complex battery systems with visual control over every step. By enabling the simultaneous generation of both battery and cooling models—whether direct or indirect—the battery pack assistant enhances modeling efficiency. Further customization is facilitated through a customizable discretization approach, focusing on specific zones to yield accurate results. The assistant also allows for the generation of an open and easily customizable Simcenter Amesim model. With the battery pack assistant, engineers can confidently navigate the complexities of battery and cooling performance, ensuring optimized designs and improved thermal efficiency. Micro-channel heat exchanger integration – Heat Exchanger Assistant Modeling micro-channel heat exchangers often presents a significant challenge due to the detailed setups required and the need for flexibility to accommodate various configurations. To facilitate this complex process, Simcenter introduces the heat exchanger assistant (HEXA), designed to guide users through the creation of highly detailed and customizable models. The HEXA tool provides a user-friendly workflow that simplifies the design of micro-channel heat exchangers, leading users step-by-step to reduce complexity and errors. Its intuitive sketch generation feature allows for rapid model creation without compromising customization options, enabling even non-experts to build comprehensive models that meet specific project requirements. Additionally, the assistant allows for adaptations to match unique and exotic configurations, ensuring that every design fits perfectly with project specifications. By leveraging HEXA, engineers can efficiently harness the underlying model predictability, enabling easy access to key parameters and enhancing overall design accuracy in heat exchanger modeling. Hydrogen As hydrogen emerges as a key pillar in the shift toward sustainable energy, engineers need robust tools to model, test, and optimize every part of the production and storage process. With Simcenter Systems 2504, the hydrogen capabilities are expanded through a predictive alkaline water electrolyzer component and a dedicated fluid storage library for cryogenic systems. These innovations simplify system design, boost efficiency, and enable data-driven decisions, empowering engineers to lead the way in hydrogen innovation. Enhancing hydrogen production efficiency – Simcenter’s alkaline electrolyzer component Engineers working on hydrogen production face the challenge of assessing the performance of alkaline electrolyzers under varying operating conditions with limited data. Simcenter addresses this with its comprehensive alkaline electrolyzer component, providing a solution that significantly enhances efficiency in green hydrogen production. This component allows engineers to swiftly explore the potential of alkaline electrolyzers across different conditions using a limited experimental dataset for parameter setting. The integration of this predictive AWE component within Simcenter’s suite streamlines the hydrogen production process, enabling quick balance of plant sizing and control design. With these capabilities, engineers can optimize hydrogen systems more effectively, supporting the transition towards sustainable energy solutions. Revolutionizing cryogenic storage design – Simcenter’s fluid storage library and LH₂ dormancy demo In industries like aerospace and automotive, efficient cryogenic fluid storage is essential. To assist engineers, Simcenter introduces its innovative fluid storage library, paired with the liquid hydrogen dormancy demo. This library offers novel components tailored for modeling self-pressurization and boil-off in cryogenic tanks. The LH₂ dormancy demo provides engineers a quick way to harness these components, facilitating system modeling that aligns closely with experimental data. Engineers can now accurately estimate pressure buildup and temperature variations due to heat input. This capability proves invaluable, allowing precise design and optimization of cryogenic storage systems. By integrating these new tools, Simcenter aids engineers in overcoming complex challenges, pushing forward advancements in cryogenic storage across various critical industries. Chassis engineering Streamline your workflow with real-time capable MBS suspension models For engineers working on vehicle dynamics, transitioning complex suspension models from established 3D software to real-time simulations can be a daunting task. Simcenter Amesim addresses this challenge with its new offering: seal-time capable MBS suspension template models, supported by a dedicated graphical user interface (GUI). This innovative solution simplifies the migration process by providing pre-defined suspension system templates that seamlessly integrate 3D CAD data into Simcenter Amesim . Engineers can now preserve the integrity of their initial designs while adapting them for real-time simulation needs, ensuring precision and efficiency in vehicle dynamics. The ready-to-use templates eliminate the time-consuming task of building models from scratch, allowing engineers to focus on optimizing design and functionality. With the real-time capable MBS suspension template models, Simcenter Amesim empowers engineers to enhance their modeling experience, enabling smoother, more reliable transitions to dynamic simulations in vehicle dynamics. Enabling accurate EV and H₂ truck modeling – Vehicle database enhancement In response to the evolving transportation landscape, Simcenter presents its enhanced vehicle model databases to address engineers’ need for precise modeling of new electric vehicles and hydrogen trucks. By utilizing correlated starters and integrating comprehensive test data, engineers gain access to ready-to-use models of vehicles like the Hyundai Ioniq 6, BYD Atto 3, and various hydrogen-powered trucks. This advancement allows for exceptional simulation fidelity, empowering engineers to confidently evaluate and optimize next-generation vehicle solutions. With Simcenter’s enhanced database, the complexities of new vehicle technologies are navigated more effectively, pushing the boundaries of innovation in sustainable transportation. These validated models provide engineers the accuracy required to develop more efficient, reliable transportation solutions, leading to a greener future. Harmonizing chassis design solutions – New framework for tire modeling In the quest to evaluate electric chassis designs across an array of range, comfort, and drivability scenarios, engineers have encountered the challenge of managing diverse tire models within vehicle dynamics solutions. Simcenter addresses this need with its new framework for tire modeling. This innovative approach offers a simplified and harmonized structure, enabling seamless integration and consistency across all tire models. The true value of this framework lies in its contribution to comprehensive chassis design evaluation. With compatibility across various road description formats and dynamic modulation of grip, engineers can effortlessly interface tire modeling software with the complete design process. This ensures that every aspect of tire performance is accurately represented, providing engineers with the tools needed to optimize electric vehicle design and innovate beyond limits. The new version of Simcenter Systems Simulation 2504 is packed with innovations that accelerate simulations, integrate platforms, and expand modeling power in areas such as batteries, barriers, thermal comfort, and more. Want to understand how these improvements can transform your projects and engineering results? Schedule a meeting with CAEXPERTS experts now and find out, in practice, how to make the most of these new possibilities! WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Many applications such as seals, gaskets, valves, and nozzles imply Fluid-Structure Interaction (FSI) in conjunction with mechanical contact between solid bodies. Due to the highly non-linear nature of contacts, we often tend to neglect the respective contact modeling especially in multi-physics applications such as FSI. For a number of applications, being able to model mechanical contact along with fluid-structure interaction is even the key enabler, to do a physical meaningful simulation at all. Solve challenging coupled multi-physics applications in a straightforward manner Sensor & camera nozzle, a clever design For cameras and sensors to produce a sharp image or signal, they require a clean lens. Since many of those installed in automotive are exposed to dirt and debris regular cleaning is a must. This is usually done with the help of a liquid spray from a nozzle. You see below a simple but clever design of a sensor and camera nozzle. It consists of just three parts: a connector, a rubber sleeve, and a nozzle. Design of a sensor and camera cleaning nozzle Modeling mechanical contacts between solid and elastic bodies, introduction of a new model The rubber sleeve seals the assembly and acts as a valve. To illustrate this, a 3D model was created in Simcenter STAR-CCM+ . The connector, as well as the nozzle, are assumed to be rigid, while the sleeve is modeled as an elastic body. The contact between -sleeve and connector- as well as -sleeve and nozzle- is included. This is possible thanks to the ability to now model mechanical contact with any tessellated geometry parts. The animation below shows the assembly process of the three parts: First, the connector is pushed into the rubber sleeve. Next, the rubber sleeve is pressed between the nozzle and the connector, thus sealing the assembly. Mechanical contact modeled with tessellated geometry parts: assembly process example Once installed, the sleeve closes off two radial holes in the connector (see left image). As soon as the cleaning system is activated a pump is being switched on. The pump pressurizes the liquid, and the sleeve deforms because of the liquid pressure. This opens a flow path underneath the sleeve (as shown on the right). A model inspired by Dunlop bicycle valve The bicycle valve developed by Dunlop 1891 works exactly like that. In the image below, you can see the radial holes in the valve body covered by a thin rubber sleeve. Bicycle valve – Developed by Dunlop in 1891 (source:  https://en.wikipedia.org/wiki/Dunlop_valve ) FSI simulation with mechanical contact – an application example The pragmatic approach The model of the sensor and camera nozzle has proven to be very useful to illustrate how the design works. But what about the engineering value? For example, how much liquid will leave the nozzle per unit time considering that the pump of the cleaning system can generate a pressure differential of 1.0 bar? Let’s approach this question in a pragmatic manner. First, a pressure load of 1.0 bar is applied to the inner surface of the sleeve, and the deformation is calculated. Then, the flow path is extracted considering a deformed sleeve. In a subsequent flow simulation, a pressure differential of 1.0 bar is applied, and the flow field is calculated. The video below shows the results of this approach: the average mass flow rate is about 1.93 g/s. Example 1: the pragmatic approach FSI simulation with mechanical contact The above approach is problematic and may lead to wrong engineering decisions. Why? In reality, the deformation of the sleeve impacts the flow, while the flow impacts the deformation of the sleeve. In order to increase the accuracy and the engineering value of the model, the two-way coupling between fluid and structure must be taken into account. Since the flow model and the structure model are part of the same Simcenter STAR-CCM+ simulation this is straightforward and does not even require co-simulation. The video below shows the results using FSI simulation with mechanical contact. The pressure at the inlet is being ramped up from 0.0 bar to 1.0 bar over a period of 1.0s, after that the pressure is kept constant at 1.0 bar. The average mass flow rate between 1.0s and 1.5s is about 1.76 g/s. Example 2: the two-way coupled FSI simulation with mechanical contact The two-way coupled model reveals how significant the impact of the modeling assumption behind the pragmatic approach is. The deformation of the rubber sleeve is very different, and so is the flow field. Not only that, the pragmatic approach also overpredicts the mass flow rate by about 10%. Something particularly fascinating is to observe how the high velocity flow beneath the glove actually sucks the tip of the glove radially inwards. Of course, this is an effect that can not be captured in the pragmatic approach. FSI simulation with mechanical contact, unbeaten accuracy Modeling the complexity of a sensor/camera cleaning nozzle. FSI simulation with mechanical contact The sensor and camera nozzle application demonstrates how the new contact modeling capability adds value to Simcenter STAR-CCM+ in three different ways. First, it enables you to compute how the rubber sleeve deforms during the assembly process. This is useful, but to be fair, you could do that with other products as well. Second, the fact that the model is part of Simcenter STAR-CCM+ means that you used it in a multi-disciplinary fashion. This was demonstrated with the pragmatic approach. A pressure load of 1.0 bar was applied to compute the deformation of the sleeve, or more specifically, to compute the flow path. Next, the flow solution was computed. Here the fact that the structure model and the flow model are part of the same simulation makes this workflow straightforward. For example, there is no need to export and import any data. Third, since the flow model and the structure model are part of the same simulation you can accurately model the two-way coupling between fluid and structure without the need for any co-simulation. To me, this is really what makes this feature so exciting. It is the added value it provides by being part of Simcenter STAR-CCM+ , and the fact that it enables you to solve challenging coupled multi-physics applications in a straightforward manner. There is a bright future ahead of all these autonomous vehicle cameras out there! And the next time you pump up that flat tire, you will definitely think about FSI with mechanical contacts. Schedule a meeting with CAEXPERTS and see how advanced mechanical contact modeling and FSI can revolutionize your designs. Our team is ready to help you overcome complex challenges with precision and efficiency. Let’s innovate together! WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Major producer and designer of heat exchangers increases cooling fan efficiency with Siemens solution Challenges Increase cooling fan efficiency in large industrial plants Decrease cooling fan noise in large industrial plants Locate areas of pressure loss Design completely new cooling system with minimal prototypes Results Developed new cooling solution Located pressure losses Broke industry records for energy efficiency, noise reduction and weight savings "Most importantly, Simcenter FLOEFD gave us the opportunity to really understand the aerodynamics of air-cooled coolers for the first time because the flow and the aerodynamics are more than just a flow through the intake and the fan itself. Guus Bertels, Associate Director of Advanced Design and Analysis , Bronswerk Heat Transfer BV Founded in 1940, Bronswerk Heat Transfer BV specializes in the design and production of heat exchangers and condensers, air-cooled coolers and comprehensive systems. Focusing on high-quality, innovative solutions for heat exchanger issues, Bronswerk Heat Transfer BV has offices and locations in the Netherlands, the Czech Republic and Russia, employing approximately 300 people. Bronswerk Heat Transfer BV designs, produces, and delivers industrial systems of (shell and tube) heat exchangers, cooling equipment, a-frame condensers, air-cooled coolers (ACC) and fans. In addition, Bronswerk Heat Transfer BV supplies and provides maintenance services for process cooling systems around the globe. Bronswerk Heat Transfer BV was recently tasked with increasing the efficiency of cooling fans at large industrial plants while simultaneously decreasing the noise emitted from those fans. In these facilities, fans as large as 33 feet move air across bundles of coils inside a gas or oilfield cooling system. Dozens, even hundreds, of fan systems may be needed to cool the gas or oil, along with untold megawatts of electrical power to run these fans. Fan noise is as important as cost issues when it comes to regulations as large industrial plants are subject to stringent noise regulations. Fans traditionally used in this environment deliver a maximum efficiency of about 50 percent. What would happen if that efficiency could be increased to 80 percent? Or even more? Fewer fans could do the same work with less energy, less noise and lower operational costs. With this vision, the design engineering team at Bronswerk Heat Transfer BV set out to create a new generation of air-cooled cooling systems that would solve age-old problems. Choosing Simcenter FLOEFD Those Bronswerk Heat Transfer BV design engineers selected Simcenter FLOEFD software to develop an oil and gas industrial plant cooling fan that is more energy efficient, quieter and lighter weight than its predecessors. Simcenter FLOEFD enables analysis and validation that are impossible solely with physical measurements. Simcenter FLOEFD is a proven concurrent 3D computational fluid dynamics (CFD) toolset for analysis and validation of their design updates. Simcenter is part of Siemens Xcelerator business platform of software, hardware and services. Bronswerk Heat Transfer BV design engineers have used both CFD tools and physical measurements to characterize the behavior, particularly the aerodynamics, of large air-cooled cooling systems. They found that concurrent CFD often can produce data that would be impossible to acquire with measurements because of physical constraints, the Heisenberg principle, and other factors. Breaking industry records The new Bronswerk Heat Transfer BV cooling solution the design engineers developed includes fans and housings that take their technology cues from gas turbines, aircraft wings and a generous helping of home-grown creativity. Simcenter FLOEFD quickly and accurately validated the practicality of these creative touches. In addition to their purely quantitative output, the CFD simulations helped Bronswerk Heat Transfer BV explore bold ideas without risking project budgets and schedules. “ Simcenter FLOEFD was crucial because I couldn’t have proven it to myself or others that this design could possibly work so that we could start manufacturing prototypes,” says Guus Bertels, associate director of advanced design and analysis, Bronswerk Heat Transfer BV . Physical measurements were essential to the project’s success but couldn’t produce the needed data in every case. With simulation, Bronswerk Heat Transfer BV’s design engineers were able to look at static pressure distributions through a flow field and obtain information on the total pressure, which is a direct measure of the entropy in the system. A loss in total pressure is energy loss, and Simcenter FLOEFD delivered a clear picture of where the losses were. Bronswerk Heat Transfer BV’s Whizz-Wheel®-based cooling systems, which are documented to increase performance by up to 30% , reduce plot space and reduce noise and power consumption, are now breaking all industry records for energy efficiency, noise reduction, and weight savings. “Most importantly, Simcenter FLOEFD gave us the opportunity to really understand the aerodynamics of air-cooled coolers for the first time because the flow and the aerodynamics are more than just a flow through the intake and the fan itself,” says Bertels. Do you want to achieve energy efficiency and noise reduction levels in your industrial cooling systems, like Bronswerk did with Simcenter FLOEFD ? Schedule a meeting with CAEXPERTS experts and find out how we can transform your challenges into innovation and high-impact performance! WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

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