Generative AI for design, broader simulation coverage, dramatic performance gains, and deeper Simcenter ecosystem integration – the Simcenter PhysicsAI 2026.1 release advances AI-powered simulation on every front. Simcenter PhysicsAI 2026.1 (formerly Altair PhysicsAI) is now available, delivering capabilities that empower engineers to unlock the full value of their CAE data with greater speed, accuracy, and intelligence. Built on the foundation of geometric deep learning, Simcenter PhysicsAI trains AI surrogate models on your historical simulation data and delivers data-driven insights up to 1000x faster than traditional solver simulations. In 2026.1, that foundation grows stronger across every dimension: generative AI for early-stage design exploration, extended SPH particle support for demanding impact and large-deformation scenarios, sharper stress and strain hotspot prediction, automated frequency extraction for NVH workflows, up to 5× faster training with up to 50% reduction in peak memory usage, and a deeper native connection to the broader Simcenter ecosystem. Simcenter PhysicsAI Generate: From performance requirements to design concept in seconds Perhaps the most exciting development in the 2026.1 release is the introduction of Simcenter PhysicsAI Generate – a capability that brings generative AI directly into the engineering design process. The challenge it addresses is one that virtually every product development team recognizes: new design requirements arrive with tight timelines, yet every design variant traditionally requires a full physics solver run before any concept can be confirmed. Exploring a broad design space spanning geometry, dimensions, material parameters, and performance targets simultaneously is simply not feasible at the pace modern projects demand. Simcenter PhysicsAI Generate changes that dynamic fundamentally. Powered by diffusion-based generative AI models – it trains on historical designs to learn the deep correlations between geometry, design parameters, and engineering KPIs. Once trained, it produces novel, physics-aware 3D design concepts directly from performance and dimensional requirements, in seconds. Critically, unlike traditional generative tools that apply physics constraints as a post-processing step, Simcenter PhysicsAI Generate produces concepts that are inherently physics-consistent from the outset. Weeks of iterative design exploration can be compressed into a single workflow, with generated concepts that reliably reflect prescribed performance targets from the very first run. Training performance improvements – Up to 5× faster, 50% reduction in peak memory usage Simcenter PhysicsAI 2026.1 is significantly faster and more efficient at using RAM during training. Memory utilization has been fundamentally improved, delivering up to 5× faster training speeds and up to 50% reduced peak memory usage as compared to 2026.0. In one of the benchmarks, peak memory dropped from 175 GiB to 75 GiB, while total training time was cut roughly in half – meaning teams can train larger, more complex models on the same hardware, faster than ever before. Teams using the Simcenter PhysicsAI add-on in Simcenter STAR-CCM+ also benefit from newly available multi-GPU support, enabling even faster model training by distributing the workload across multiple GPUs. For enterprise teams running large-scale CFD or crash models, this translates directly into faster design iteration cycles, reduced infrastructure costs, and the ability to tackle problems that previously strained available resources. Spatial conditioning: Teaching the generator where things matter Building on Simcenter PhysicsAI Generate, 2026.1 also introduces spatial conditioning – the ability to condition generative models on point clouds. Rather than constraining the generator only with scalar design parameters, engineers can now define spatially-distributed constraints as 3D point arrays: attachment point locations, load application zones, manufacturing fixture positions, or any other spatially-meaningful design context. These point clouds are specified in companion JSON files during training, and at generation time, users select node sets for each conditioned point cloud directly in the generation dialog. The result is a generative model with genuine spatial awareness – one that produces concepts respecting real-world geometric constraints, not just abstract performance targets. SPH particle support: AI-accelerated workflows for your most demanding simulations One of the most significant capability expansions in 2026.1 is the addition of Smoothed Particle Hydrodynamics (SPH) particle support. SPH simulations are the method of choice for some of the most demanding physics scenarios in engineering – large-deformation impact events, bird strike analysis, and fluid-structure interaction, to name a few. Until now, SPH particles & point mass elements were not recognized by Simcenter PhysicsAI – limiting its use in explicit simulations. That changes in 2026.1. SPH particles and point mass elements are now fully visible to Simcenter PhysicsAI, enabling it to learn from and predict critical structural integrity indicators – including the number of failed layers, stress, and strain – directly from SPH simulation data. For automotive OEMs, aerospace manufacturers, and defense engineers whose most challenging analyses live in the SPH domain, this is a meaningful step toward AI-accelerated workflows for their hardest problems. Eigen frequency prediction for modal analysis and NVH workflows Modal analysis sits at the heart of NVH and structural dynamics workflows. Understanding how a structure vibrates, where its resonant frequencies lie, and how those modes change across design variants is fundamental to delivering products that are quiet, durable, and dynamically well-behaved. In previous versions of Simcenter PhysicsAI, only mode shapes were predicted, requiring engineers to work around a fundamental missing piece in their AI-assisted simulation pipeline. In 2026.1, that gap is closed. Eigen mode frequency values are now automatically extracted and predicted for modal analysis, with Eigen Model Step Labels automatically associated to each predicted mode shape without any manual intervention. The result is a faster, more accurate normal modes analysis workflow – one where engineers spend less time configuring and more time acting on the insights their models deliver. Native integration with Simcenter Inspire manufacturing solutions The value of AI-driven simulation is maximized when it is embedded directly in the tools engineers use every day, not bolted on as an afterthought. In 2026.1, Simcenter PhysicsAI deepens its integration with the Simcenter Inspire manufacturing solutions ecosystem, enabling seamless data exchange and workflow continuity between casting, molding, forming, extrusion process simulation and AI-powered prediction. For manufacturing-driven industries – automotive, aerospace, heavy equipment – this native connection is a meaningful step toward truly end-to-end workflows, where AI accelerates every stage of the product lifecycle from process design to in-service performance prediction. Constant memory mode: Scaling AI training beyond RAM limits For teams working with extremely large datasets where available RAM is the hard constraint, 2026.1 introduces Constant Memory Mode. When enabled, Simcenter PhysicsAI stores graph data on disk and loads it into RAM only as needed during training – effectively decoupling dataset size from available system memory. To mitigate the I/O overhead inherent in disk-based loading, an asynchronous loading variant is also available, leveraging multiple CPU threads to prefetch data in parallel and recover much of the speed penalty. For organizations with large historical simulation libraries that would otherwise exceed available RAM, this mode removes what has been a genuine barrier to scaling AI-powered workflows. Smarter dataset curation: Better data pipelines A great AI model starts with great data, and the time spent preparing that data is time that cannot be spent on engineering. In 2026.1, the dataset creation and curation workflow has been meaningfully streamlined. Engineers can now down-select results during dataset creation for faster processing, manage multiple samples simultaneously through batch move, copy, and delete operations, and benefit from response-aware outlier detection that updates dynamically based on the selected output. Vector features and custom metadata are now included in outlier analysis and displayed in the results tree and summary views, giving engineers a more complete picture of their data quality at a glance. Collectively, these enhancements make data preparation significantly more efficient and intuitive, reducing the most time-consuming step in building a surrogate AI model. New welcome dashboard: A smarter, ,0faster starting point Sometimes the most impactful improvement is the one that gets engineers to value faster. The new Welcome Dashboard in 2026.1 delivers a clean, intuitive entry point to the Simcenter PhysicsAI, making it straightforward to create new projects, open existing ones, resume recent work, access tutorials, and browse built-in examples – all from a single, well-organized screen. Accessible directly from the familiar Simcenter PhysicsAI ribbon, the dashboard reduces the friction of getting started, particularly for new users or teams onboarding Simcenter PhysicsAI for the first time. Improved stress and strain hotspot prediction for structural analysis Finding stress hotspots accurately is not just an academic exercise – it is the difference between a design that passes fatigue life requirements and one that fails in the field. In 2026.1, Simcenter PhysicsAI predicts stresses, strains, and other element-bound fields directly on the elements themselves, bypassing interpolation entirely. A new “Preserve Output Bindings” discretization option ensures that the element or nodal definition of the original field results is faithfully maintained throughout the prediction pipeline. The outcome is sharper, more trustworthy hotspot maps – the kind of accuracy that gives structural engineers the confidence to act on AI predictions rather than simply validate them. Custom input visualization: Transparency that builds trust in AI predictions As AI models become more deeply embedded in engineering workflows, transparency becomes essential. Engineers need to understand not just what the AI predicts, but what information it is working with. In 2026.1, users can now visualize custom input features directly within the dataset and testing GUIs – whether those inputs are global scalars, nodal scalars, or vector fields. This gives engineers a clear, visual window into the data that drives the model, making it easier to validate inputs, catch data quality issues early, and build the kind of trust in AI predictions that supports confident decision-making. New geometric similarity score: Predict with confidence, act with certainty How do you know whether an AI prediction can be trusted? Simcenter PhysicsAI features a geometric similarity score – an indicator based on geometry and discretization that assesses how similar a new design is to the training dataset. Engineers can instantly assess the novelty of a design and whether a full solver run is warranted, enabling confident AI-driven design exploration while reducing the risk of acting on out-of-distribution results. In 2026.1, that capability has been significantly strengthened. Previously, similarity scores ranged from −∞ to 1 – a range that was mathematically valid but intuitively difficult to interpret. The new similarity score is strictly bounded between 0 and 1, computed using a mathematically rigorous piecewise smooth curve as a function of the Euclidean distance between the feature encodings of the prediction sample and the nearest training sample. Equally important, the score is now feature-aware: each continuous input feature – shell thickness, meshed geometry, and others – receives its own individual similarity score alongside an aggregate score. This granularity helps engineers quickly identify which aspects of a new design are well-represented by the training data and which might warrant additional caution or supplementary simulation – making AI predictions not just fast, but genuinely trustworthy. Simcenter PhysicsAI 2026.1 – A solution that keeps raising the bar Taken together, the updates in Simcenter PhysicsAI 2026.1 tell a coherent story: a solution maturing rapidly across every dimension that matters to engineering organizations. Physics coverage is broader, reaching into SPH-based explicit models and modal dynamics. AI capabilities are more powerful, with generative design and spatial conditioning pushing the frontier of what is possible. Computational performance is dramatically improved, making larger problems tractable on existing hardware. And integration with the broader Simcenter ecosystem is deepening – bringing AI-powered prediction closer to the tools and workflows where engineering decisions are actually made. Whether you are a NVH engineer predicting modal behavior across hundreds of design variants, a crash analyst working with SPH-heavy impact models, or a design team looking to harness generative AI for early-stage concept creation, Simcenter PhysicsAI 2026.1 has something substantive to offer. The future of engineering simulation is not just faster solvers – it is AI that learns from your data, speaks the language of physics, and delivers answers at the speed of design. That future is here, and it keeps getting better. If you want to unlock the full potential of Simcenter PhysicsAI 2026.1 and accelerate your development processes using artificial intelligence, schedule a consultation with CAEXPERTS. Our team includes engineers trained and qualified to provide support, implementation, and application services for Altair solutions, helping your company integrate AI-driven simulation into your engineering workflows. We collaborate with your team on initial projects to maximize return on investment, helping you get the best performance out of the tools and achieve faster, more accurate, and reliable results. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Mention oil and most people will think about friction, after all if you want something to move freely then you add oil to the surfaces. When we think about oil in cars, most people will think about engines, gears and their smooth operation. But oil has dual benefit: by virtue of its high thermal conductivity and high specific heat capacity it makes a very effective coolant. Whether that’s the cooling jets stopping piston crowns from melting, the gearbox oil carrying away the waste heat from a gear mesh, or oil sprayed onto eMotors. Simulating these applications of oil with CFD is challenging, and while Simcenter STAR-CCM+ allowed to tackle those through Hybrid Multiphase for quite some time, this can be a computationally relatively costly endeavor, especially in early design phases. With version 2606 Simcenter STAR-CCM+ adds a massive leap in capability to the Smoothed Particle Hydrodynamics (SPH) solver so that you can iterate faster without losing fidelity. As a key leading application, in this blog we will focus on the vital role oil plays in electric motors. Understanding heat generation in electric motors Electric motors convert electric power to mechanical power incredibly efficiently (94 percent or higher) but losses still exist. A 200kW EV motor loses approximately ~12kW, mostly as heat. What exactly happens if we don’t manage that heat properly? High temperatures are particularly bad for the windings. Copper’s resistance increases with temperature, leading to increased energy losses and further heat generation. The winding insulation also has a thermal rating, and exceeding it leads to premature degradation. The flux density of permanent magnets also reduces with temperature, impacting torque output. The heat originates from two primary sources: Joule losses in the windings and iron losses in the core. Joule losses occur when current flows through the motor windings. A simple demonstration of heat generation through Joule (aka Ohmic) losses Because these losses are proportional to current squared, they can rapidly escalate. To mitigate this, there’s a growing trend toward higher voltage architectures (400V or 800V), which reduce current-related losses—though this comes at the cost of significantly more expensive components. Iron losses, meanwhile, result from both eddy currents and hysteresis in the stator and rotor cores. Eddy currents are induced electrical currents within the magnetic core that oppose the original change in flux, leading to energy dissipation as heat. Hysteresis losses occur as the core material continuously reorients itself to follow the rapidly changing magnetic field direction, with the energy required for this reorientation also converting to heat. Finally there are also small friction losses from the bearings and rotor movement. Keeping our cool, efficiently Now that we’ve learned where the heat comes from and all the problems it can create, what can we do about it? In practice, whilst a simple motor like an alternator can be air-cooled with an open back design, EV motors rely on liquid cooling to keep temperatures under control. Water-glycol jackets operate in the same way as those in a cylinder head and water has a much higher thermal conductivity and specific heat capacity than oil. However, as oil is dielectric it can be sprayed directly onto the hottest parts of the motor, making it an order of magnitude more effective than a water jacket. Gear oil is also convenient to use as it can additionally lubricate the bearings and other transmission components in an Electric Drive Unit (EDU). The perfect solution then? Well, the continuous strive for drivetrain efficiency demands lighter weight: less system mass means less energy required to accelerate and decelerate, lower overall power consumption and key for most buyers: a higher range figure. Increasing the system power density means proportionally less material, which means less heat capacity and less thermal inertia, the hottest parts get hotter faster, with no ability to act as a sink and distribute the heat. This places increasing demands on the cooling system to absorb and distribute heat. Unfortunately, lightweighting applies to the oil volume too. Reducing the volume of liquids also reduces dynamic mass (great!), but at the cost of cooling system capacity. This means that engineers need to make sure that every precious drop of coolant is used as effectively as possible to extract maximum performance from the cooling system. If we consider a thermal abuse loadcase where the motor is outputting high torque and low power (imagine driving a heavily laden vehicle up a steep hill), the aim is to identify areas starved of coolant and also predict the overall rise in system temperature. If we focus on spray cooling as is typical in most current generation EVs, various configurations of stationary and rotating jets are employed to cool the end windings. However, the challenge is that the time scales of flow and thermal phenomena are very different, whilst we might be resolving details of the oil jets in the order of milliseconds, reaching thermal equilibrium can take minutes. SPH and thermal simulation – coupled physics made easy SPH is a wonderful tool for capturing violent oil flows in drivetrains. Capturing the fluid-thermal interaction adds another layer of complexity. Typically solving this problem with SPH simulation relied on either simulating a short duration and then extrapolating the heat transfer over time, or mapping between separate simulations, with manual export of Heat Transfer Coefficients (HTCs) each time the data is exchanged. This might be OK for a handful of simulations, but it becomes tedious and error prone when trying to do it for a full design study. It’s possible to improve the situation with some script stitching, but these days shorter EV development times are seen as a competitive advantage. There has to be a better way. Simcenter STAR-CCM+ 2606 addresses this challenge by enabling the SPH solver to couple directly with the Simcenter STAR-CCM+ Energy Solver for conjugate heat transfer simulation. You now have access to the advanced physics and boundary conditions available in the Energy solver alongside your SPH simulation in a single environment. This allows full modelling of the fluid temperature evolution, heat transfer at the walls and solid temperature evolution in a fully coupled simulation. Both simulations are set up in the same Simcenter STAR-CCM+ environment for a familiar and consistent workflow. Comparison of convective Heat Transfer Coefficient as a function of inlet velocity between Simcenter STAR-CCM+ SPH and experiment. Source Kekila et al, 2019, NREL/CP-5400-74284 Alternatively, Simulation Operations can be used to stagger the fluid and thermal simulations and capture longer timescales. What would have required scripts can now be done easily in a few clicks in Simcenter STAR-CCM+ SPH. This capability delivers more reliable predictions for cooling simulations, eliminates manual data transfer and allows seamless post-processing without needing to switch tools. Extending SPH with multiphysics and coupled thermal-electromagnetics- CFD Iron losses are often assumed to be constant in a thermo-fluid-dynamic simulation, whereas in reality, they are strongly dependent on temperature. Capturing this effect would typically require a complex mapping procedure between different tools. In Simcenter STAR-CCM+, it is possible to activate the electromagnetic solver and integrate it into the simulation operations loop. This allows losses to be updated based on the new temperature distribution as the oil circulates and the temperature evolves—all within Simcenter STAR-CCM+. Asymmetric cooling oil distribution is driven by the winding angle and the resulting impact on cooling (HTC). Individually aligning the outer oil jets is one way to solve this problem, a task made much easier with optimization The simulation now captures the combined effects of the problem. The introduction noted that the oil should be used as efficiently as possible to extract maximum performance from the cooling system. Based on the results obtained, it is possible to analyze the system's behavior and adjust the number of jets—as well as their location, diameter, and angle—to optimize coil wetting and maximize heat transfer. With a meshless approach to fluid simulation, implementing and iterating on these types of changes becomes much simpler. Simcenter HEEDS can also be used to automatically apply these changes during a study and optimize wetting behavior. SPH simulation-based optimization of nozzle orientation for selected designs to obtain optimized wetting. Source: InDesA SPH simulation of optimized nozzle angles for maximum surface wetting and cooling efficiency. Source: InDesA Simulation should go beyond the oil While the focus has shifted toward electric motors, the efficiency and reliable performance of any vehicle powertrain—regardless of the motor type—depend on oil. Ensuring a design delivers sufficient oil to the right locations in the proper quantities to prevent system failures relies on simulation. Obtaining accurate predictions requires tightly coupled flow and energy solvers. To generate these predictions quickly enough to keep pace with the design cycle, seamless integration and built-in optimization capabilities are essential. Do you want to unlock the full potential of Simcenter STAR-CCM+ to enhance thermal simulation and optimize cooling in your designs? Schedule a meeting with CAEXPERTS and leverage the expertise of our engineers to apply the best simulation and optimization strategies to your project. We collaborate with your team on initial projects to maximize return on investment, helping your company extract peak performance from the tool and achieve faster, more accurate, and reliable results. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Simcenter EDEM 2026.1 (formerly Altair EDEM) is now available, bringing engineers powerful capabilities to enhance their particle simulation workflows. Automate your simulation setup and reuse models across workflows with minimal effort, enabling you to explore the possibilities of particle behavior in diverse scenarios. Analyze coating thickness on particle surfaces up to 100x faster, significantly accelerating your design iterations and helping you go faster from concept to solution. Develop and maintain custom physics models faster with a unified approach that simplifies handling complexity in your particle systems. These enhancements streamline your engineering process, reduce setup time, and improve computational efficiency. Discover the complete range of enhancements in Simcenter EDEM 2026.1 and see how these capabilities can support your next project. Develop and maintain custom physics models faster than ever Developing custom physics models in DEM simulations has traditionally meant managing two separate codebases: one for CPU solvers and another for GPU solvers. This duplication creates a maintenance burden, doubles your testing effort, and introduces opportunities for inconsistencies between implementations. With Simcenter EDEM 2026.1, you now have access to a Unified Custom Model API that eliminates this complexity. You write your custom physics code once, and it runs seamlessly on both CPU and GPU solvers without any duplication. You benefit from consistent behavior across both solver types, making debugging significantly more efficient and reducing the risk of solver-specific errors. The streamlined file structure frees you to focus on physics innovation rather than managing code complexity. You reduce development time substantially by eliminating redundant coding and testing cycles. This unified approach means faster iteration, easier maintenance, and greater confidence in your custom model implementations across your entire simulation environment. Ready to accelerate your custom physics development? Explore the Unified Custom Model API. Automate simulation setup and reuse models across workflows with minimal effort Setting up simulation variants in DEM workflows often means repeating the same configuration steps over and over, which consumes valuable engineering time and limits your ability to explore design alternatives efficiently. When every parameter change requires manual intervention through the GUI, running design of experiments or parametric studies becomes a bottleneck that slows down innovation. The new Simcenter EDEM 2026.1 release introduces a human-readable JSON input file format that fundamentally changes how you interact with your simulation models. You can now edit simulation configurations using any script that can modify JSON (including Python) or any standard text editor, eliminating the need to rebuild models from scratch. This approach enables you to automate design of experiments by programmatically generating multiple simulation variants without manual rework. You gain the flexibility to reuse and adapt existing simulations by simply modifying text files rather than clicking through complex setup procedures. The JSON format also allows you to seamlessly integrate EDEM into custom workflows and AI-driven processes using standard tools and libraries. You’ll accelerate your simulation throughput while maintaining full control over model configurations through an accessible, scriptable interface. Explore how JSON-based simulation input files can streamline your DEM workflow and unlock new automation possibilities. Analyze coating thickness on particle surfaces up to 100x faster Spray coating simulations are critical for optimizing pharmaceutical tablet coating and food seasoning processes, but slow analysis times have traditionally created bottlenecks in process development. Engineers often wait hours for coating thickness results on particle surfaces, which delays optimization cycles and slows down production decisions when time-to-market is crucial. The new release of Simcenter EDEM 2026.1 addresses this challenge with significantly accelerated spray coating performance for polyhedral particles. With this enhancement, you can now complete tablet coating or seasoning simulations in minutes instead of hours, transforming your workflow efficiency. You’ll optimize spray parameters faster, enabling you to reduce material waste and improve coating uniformity across your product batches. The performance boost allows you to run more design iterations within the same timeframe, giving you the confidence to fine-tune production processes based on comprehensive analysis rather than limited data. This means you can explore a wider range of operating conditions and make better-informed decisions about nozzle positioning, spray rates, and process parameters. Faster results directly translate to shorter development cycles and quicker paths to production optimization. Ready to accelerate your coating analysis workflow? Explore the enhanced spray coating performance capabilities and discover how much faster you can optimize your processes. If you want to unlock the full potential of Simcenter EDEM 2026.1 and accelerate your development processes with more efficient DEM simulations, schedule a consultation with CAEXPERTS. Our team consists of engineers trained and qualified to provide support, implementation, and application services for Altair solutions; we collaborate with your team on initial projects to maximize return on investment and help your company achieve peak performance from the tool, delivering faster, more accurate, and reliable results. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

HEEDS is a powerful optimization software that interfaces with all commercial design (CAD) and simulation (CAE) tools; Multidisciplinary; Multiphysical; Multiscale; Process automation; Distributed Execution; Insight & Discovery; Portal to: ANSYS; Abaqus; CATIA; CREO; EXCEL; DYNA; MATLAB; SolidWorks; python HEEDS HEEDS is a powerful design space exploration and optimization software package that interfaces with all commercial computer-aided design (CAD) and computer-aided engineering (CAE) tools to drive product innovation. HEEDS accelerates the product development process by automating analysis workflows (Process Automation), maximizing available hardware and software computational resources (Distributed Execution), and efficiently exploring the design space for innovative solutions (Efficient Search), while evaluating new concepts ensuring that the performance requirements are met ( Insight & Discovery ). Contact an Expert Process automation Distributed Execution Efficient Search Insight & Discovery HEEDS enables automated workflows to make it easier to drive product development processes. With an extensive list of interfaces designed for commercial CAD and CAE tools, HEEDS quickly and easily integrates many technologies without the need for custom scripts . Data is automatically shared across different modeling and simulation products to assess performance tradeoffs and design robustness. HEEDS leverages existing hardware investments by making efficient use of all available hardware resources . Utilize Windows and Linux-based workstations or clusters , on-premises or offsite, as well as cloud computing resources to accelerate the development of innovative products. For example, geometry modifications can be automated on a Windows® operating system laptop , a structural deformation simulation can be performed on a Linux workstation, and a computational fluid dynamics (CFD) simulation can be performed on multiple computer cores. a Linux cluster , or in the cloud. Unlike most traditional optimization tools, which require highly specialized technical knowledge and model simplification to enable efficient search, all designers and engineers can use HEEDS to achieve innovation. HEEDS includes proprietary Design Space Exploration functionality to efficiently find design concepts that meet or exceed performance requirements. HEEDS automatically adapts its search strategy as it learns more about the design space to find the best possible solution within the allotted time frame. It's easy to use, designed to meet deadlines, and capable of delivering significant value! HEEDS provides the ability to easily compare performance across a broad spectrum of designs that exhibit desirable characteristics and robustness. The software helps users visualize project performance trade-offs between competing objectives and constraints with a variety of charts, tables and images to gain insights and discover innovative solutions. This facilitates the development of production-ready designs; enabling a truly digital twin! ⇐ Back to Tools

Simcenter 3D - Minimize noise and optimize the sound quality of products. quickly gain insights into a project's acoustic performance, coupled vibroacoustics, and aeroacoustics. FEM/BEM solvers; Meshing for Acoustics; Nastran Advanced; Acoustic Transfer Vector; Acoustics HPC; Ray Acoustics – SIEMENS Simcenter 3D Acoustic Simulation Simcenter™ 3D software offers a comprehensive solution to minimize noise and optimize product sound quality. Dedicated acoustic modeling features, efficient solvers , and easy-to-interpret visualization tools allow you to quickly gain insight into a design's acoustic performance for decoupled acoustic, coupled vibroacoustics, and aeroacoustics applications. Solution Benefits Accelerate acoustic generation and modeling Deliver high-fidelity vibroacoustic simulations in the most efficient way Faster design analysis iterations with CAD-CAE test associativity Gain instant insights with specific acoustic post-processing Providing a platform for multidisciplinary simulation Accelerate acoustic simulation model creation from complex geometries, whether structural mesh model, CAD geometry or from scratch Use fast and efficient FEM/BEM solvers to provide acoustic calculations faster Effectively solve acoustics, vibroacoustics, and flow-induced noise issues from a single interface Simulate acoustic performance for indoor, outdoor or mixed interiors Accelerate various acoustic RPM calculations involving engines, gearboxes, and rotating components Perform realistic acoustic simulation: anechoic boundary condition, porous finishing materials (hard and soft frames), acoustic source, lightning noise and more Advanced features such as surface wrapping, convex meshing, mesh thickening, and the ability to create hybrid (hexa-tetra) meshes help speed up acoustic meshing processes more than traditional preprocessors. The availability of multiple material models for structure and fluid and the wide range of boundary conditions and structural and acoustic loads allow you to configure your analysis efficiently. Simcenter 3D increases realism in your simulations by providing support for loading or font creation from test data and predecessor simulations of multibody or computational fluid dynamics (CFD). Simcenter Nastran® software is used to quickly solve complex indoor and outdoor acoustics problems, thanks to key features such as Automatically Blended Layer (AML) technology and Finite Element Adaptive Ordering (FEMAO), which allows using small fluid meshes with an ideal number of Degrees of Freedom (DoF) per frequency. Simcenter 3D connects seamlessly to computer-aided design (CAD), computer-aided engineering (CAE), and even test data. Any design modification can be easily introduced into the structural and/or acoustic model, eliminating multiple conversions between file formats and recreating models. Simcenter 3D provides intuitive, easy-to-interpret post-processing tools for investigating noise such as sound pressure level (SPL), acoustic power, or directivity. Path, modal, and panel contribution analysis helps you quickly identify important noise sources and their propagation. The Simcenter 3D acoustics solution is part of a larger multidisciplinary simulation environment and is integrated with the Simcenter 3D Engineering Desktop at the core for centralized pre- and post-processing for all Simcenter 3D solutions. This integrated environment helps you achieve faster CAE processes and streamline multidisciplinary simulations that integrate acoustics and other disciplines, such as gear noise analysis from motion solutions, or NVH and vibroacoustics analysis that require structural or flow-induced loads. Sectors Industry applications Aerospace and Defense Automotive and transport Consumer goods Industrial machinery Marinho As noise can affect health and a silent product is often perceived as superior quality, companies are adopting efficient processes and tools to optimize the noise performance of their products. With Simcenter 3D, aviation engineers can predict cabin noise generated by turbulent boundary layers (TBL) in the fuselage or by aeroacoustic noise coming from the environmental control system (ECS). External noise can be solved using Edge Boundary Element Method (BEM) and FEM solvers . Spacecraft engineers can reduce the risk of their acoustic verification tests by virtually evaluating them in Simcenter 3D. During vehicle development and enhancement programs, Simcenter 3D capabilities can provide noise, vibration, and harshness (NVH) engineers with valuable insight into acoustic, vibroacoustic, and aeroacoustic noise contributions in the vehicle cabin and external environment. Building high-quality, powerful speakers, quiet vacuums and washing machines, and other noiseless consumer goods requires advanced noise engineering and sound characterization capabilities provided by Simcenter 3D. Simcenter's 3D acoustic modules provide the capabilities needed to evaluate the noise radiated by the machine, including capturing the effect of encapsulations with sound treatments. The acoustic capabilities of Simcenter 3D can be used to study complex underwater radiation from ship hulls, propellers, and submarine hull reflections of sonar waves. Módulos Simcenter 3D Meshing for Acoustics software helps create meshes for FEM and BEM acoustic analysis. The module provides advanced, easy-to-use functionality for creating an acoustic fluid mesh for both indoor and outdoor acoustic applications from an existing structural mesh or CAD geometry. Simcenter Nastran Advanced Acoustics software provides support for standard loads and boundary conditions and key technologies such as AML and FEMAO to quickly solve acoustic simulations. It is suitable for studying component acoustic radiation and pass-by noise from complete vehicles, transmission loss from pipeline systems such as intakes and exhausts or mufflers, and transmission loss from panels. Simcenter 3D Acoustic Transfer Vector software supports acoustic transfer vector (ATV) computation, expressing the sensitivity of the pressure response in a virtual microphone per unit normal velocity at field points on a radiating surface. It can be reused to quickly predict the acoustic response to any surface vibrations. Likewise, vibroacoustic transfer vectors (VATV) express the sensitivity of microphone pressures to the unitary force applied at points in a structure. Furthermore, VATV can be quickly reused to predict the acoustic response to any force load. Modal participation factors (MPFs) can also be used with ATVs in the context of modal acoustic transfer vector (MATV). Simcenter 3D Aero-Vibro-Acoustics software supports the creation of aeroacoustic sources close to turbulent noise emitting flows and allows to calculate their acoustic response in the external or internal environment; for example, for noise from heating, ventilation, and air conditioning (HVAC) and environmental control system (ECS) ductwork, train boogies and pantographs, cooling fans, ship and aircraft propellers, and much more. The product also allows defining the wind loads that act on the structural panels, leading to a vibroacoustic response; for example, in a car or airplane cabin. Simcenter 3D Load Identification allows to obtain accurate dynamic loads of a structure. Operational loads are very important for accurate response prediction, but are often impossible or difficult to measure directly. This product offers several ways to identify operating forces from measured data, either by the mounting stiffness method or the inverse matrix method. For example, in an inverse matrix method, operational vibration data can be measured under operating conditions and transfer func tions (FRFs) can be measured under controlled laboratory conditions or obtained from simulations. This data is then combined into a reverse load identification case. In addition, Simcenter 3D Load Identification supports a modal expansion solution to create enriched vibration results in a complete FE model based on measured vibrations at just a few points. Finally, a second method for deriving structural surface vibrations is provided through inverse numerical acoustics, in which pressure responses measured at just a few points close to the structure are used together with acoustic transfer vectors to identify total surface vibrations. The obtained vibration field can then be used for acoustic radiation analysis. The Simcenter 3D Environment for BEM Acoustics software supports the generation of a ready-to-run acoustic or vibroacoustic simulation model for direct BEM and indirect BEM and provides comprehensive post-processing tools to analyze the acoustic or vibroacoustic results. The Simcenter 3D Acoustics BEM solver is used to predict the acoustic response in closed and unbounded domains using a mesh only for the boundary of the fluid domain. The vibroacoustic analysis is supported by coupling the acoustic fluid with a structural modal model. Structural vibrations can also be imposed on the BEM fluid using weak vibroacoustic coupling. Simcenter 3D Acoustics Accelerated BEM software provides hierarchical matrix (H-Matrix) BEM and fast multipole (FM) BEM solvers to extend the computational limits of standard solvers . These solvers are suitable for outdoor acoustics of large structures such as vehicles and large engines, aircraft, ships, submarines, as well as high frequency applications such a ultrasonic sensors. Simcenter 3D Acoustics' time domain BEM software enables BEM solutions to resolve transient acoustic and vibroacoustic phenomena. In opposition to frequency domain based BEM solvers , Simcenter 3D Acoustics Time Domain BEM Solver offers the possibility to solve problems involving short term excitation impulsive signals in time domain. This BEM solver is suitable for applications such as parking sensor design and door slam analysis, for example. Simcenter 3D Acoustics HPC software allows you to run acoustic FEM or BEM calculations in multiprocessing mode on the parallel hardware of your choice. Parallel calculation sequences are implemented using the message passing interface (MPI) communication standard. In the case of FEM vibroacoustics, this product incorporates Simcenter Nastran's Distributed Memory Parallelization (DMP) feature. Simcenter 3D Ray Acoustics is used to predict acoustic responses up to very high frequencies and very large geometries, in closed and unlimited domains. Unlike finite element method (FEM) or boundary element method (BEM) acoustic solvers , ray acoustic solutions are not based on a fine domain discretization. Therefore, the solution is not limited by an upper frequency limit or the size of the model and the resolution is done orders of magnitude faster compared to FEM or BEM. Simcenter 3D Ray Acoustics integrates an engineering environment into Simcenter 3D to generate and post-process a ray acoustic model, as well as a ray acoustic solver , which is the CSTB ICARE solver. Module benefits: Start from a structural FEM model or CAD geometry Accelerate the acoustic meshing process for complex geometries Main features: Hybrid polygon-based thickening, hole filling, and rib removal tools Interior and exterior surface wrapping technology based on CAD or CAE model input Easy creation of convex outer boundary surface to build FEM meshes for outdoor acoustics Dominant hexadecimal hybrid hexa and tetra mesher for fluid volumes facilitating efficient solution Shell mesh thickening (reverse of mid-surface) to derive boundary surfaces of fluid cavities, which is useful for muffler and other fluid FEM meshes Module benefits: Runs vibroacoustic simulations (SOL108/SOL111) for indoor or outdoor noise Study outdoor acoustics with lean FEM models thanks to built-in AML technology Efficiently simulate broadband acoustic problems using the adaptive FEMAO solver Main features: Supports standard loads and boundary conditions, as well as specific acoustic boundary conditions such as duct modes and acoustic diffuse field (random) loads Pressure loads on structural surfaces from other acoustic or CFD analysis Porous and temperature-dependent fluid materials, average convective flow effects, frequency-dependent surface impedance, and transfer admittance between pairs of surfaces Calculate sound pressure, intensity, and power for virtual microphones located inside or outside the mesh fluid volume Module benefits: Use ATV to calculate the noise of rotating machines with loads of several revolutions per minute (RPM) up to 100 times faster Use VATV to quickly assess cabin noise due to various flow-induced pressure loads load cases such as wind loads and turbulent boundary layers Main features: ATV results are efficiently stored in a Nastran (op2) or Sysnoise (ssndb) result file ATV can be interpolated when used in a forced response context Evaluate acoustic pressure and power and panel, network, and mode contributions to ATV response Module benefits: Conservative mapping of CFD pressure results to acoustic or structural mesh Equivalent aeroacoustic surface dipole sources Equivalent aeroacoustic fan sources for tonal and broadband noise Wind loads, using semi-empirical turbulent boundary layer models or pressure loads mapped from CFD results Derive aeroacoustic sources based on lean surface pressure for stationary and rotating surfaces Provides easy-to-use, scalable load preparation for aerovibroacoustic wind noise simulations Import binary files with load data directly into Simcenter Nastran for response calculation Main features: Conservative mapping of CFD pressure results to acoustic or structural mesh Equivalent aeroacoustic surface dipole sources Equivalent aeroacoustic fan sources for tonal and broadband noise Wind loads, using semi-empirical turbulent boundary layer models or pressure loads mapped from CFD results Module benefits: Determine operating forces or vibrations that are difficult or impossible to measure directly Get a more realistic simulation by applying more accurate loading Combine measured loading data with FE simulations Main features: Assembly method for estimating assembly forces by combining operational vibration data on each side of the assembly and assembly stiffness data Inverse matrix method by combining operational measurements and transfer functions based on all measured data or a combination of operational measurements and simulation data Simple application and reuse of forces or vibrations identified in the simulation model Module benefits: Provide a user-friendly interface to simplify the creation of acoustic BEM models for standard and accelerated BEM solvers Supports pure acoustic issues as well as weak or fully coupled vibroacoustic response via modal-based framework definition Leverage dedicated post-processing capabilities to improve engineering insight and user productivity Main features: Provide all standard structural and acoustic loads and boundary conditions to accurately describe your vibroacoustic issues Prepare deterministic and random acoustic and vibro-acoustic analysis Standard post-processing of acoustic results such as acoustic pressure and power and structural vibrations Dedicated diagnostic graphs showing panel contributions and structural modal contributions to acoustic pressure or power Module benefits: BEM solvers , fast and efficient to solve purely acoustic and vibroacoustic problems A multitude of acoustic and structural loads and boundary conditions are supported for an accurate description of your vibroacoustic simulation model Automatic BEM model corrections for free and seam edges Main features: Direct and indirect decoupled acoustic solutions Indirect, loosely coupled and strongly coupled vibroacoustic solutions Deterministic and random acoustic and vibroacoustic analysis Returns standard acoustic and structural response results Provides structural panel contributions and modal contributions to acoustic pressure or power Solutions Guide | Simcenter 3D for acoustic simulation Module benefits: Provides faster calculations for large BEM models (larger geometry and/or higher frequencies) Requires less system memory than standard BEM Supports uncoupled acoustic response as well as coupled vibro-acoustic response simulation Main features: Includes a fast iterative multipole solver as well as a direct hierarchical H-Matrix solver Both solvers support parallel computing, including up to four processes for free, or using more than four processes, when combined with Simcenter 3D Acoustics High Performance Computing (HPC) software Supports the convection effect of a medium (uniform) flow on acoustic wave propagation Module benefits: Allows accurate modeling of transient infinite domain problem Provides solutions to purely acoustic and vibroacoustic problems Provides fast and efficient time-domain solver , also for large models Main features: Dedicated Simcenter 3D Acoustics Transient BEM solver environment for time-domain BEM calculations, i ncluding two analysis types: acoustic transient and vibro-acoustic transient Supports various loads and boundary conditions: Acoustic transient: acoustic monopole, plane wave, infinite plane, acoustic absorber, transfer admittance Transient vibro-acoustics: force applied to the structure (with defined mode representation), pre-computed vibrations, infinite plane, acoustic absorber, transfer admittance, panel Solutions guide | Simcenter 3D for acoustic simulation Module benefits: Accelerates acoustic calculations using multithreading , shared memory parallelization (SMP), multiprocessing, and DMP This product supports high performance computing for Simcenter 3D Acoustics FEM and BEM solvers Main features: Solvers can run in high-performance computing mode on multi-node clusters as well as on multi-core workstations Allows you to solve high frequency problems with DMP for which near linear parallel speed can be expected Module benefits: Solve high-frequency acoustic simulations for large models in a fraction of the time required with FEM or BEM solvers A coarse mesh can be used as it captures model geometry, simplifying model creation Standard acoustic loads and boundary conditions are supported for accurate description of the simulation model Advanced results and post-processing to explore ray path arrivals or sound quality criteria Main features: Returns acoustic results in both frequency and time domains Simulates ray propagation of acoustic waves with adaptive beam-tracking technology Accurately simulates reflections on curved surfaces despite coarse mesh discretization Capture multi-order diffraction effects and creeping waves Captures late reflections and diffusion effects with particle tracking technology Supports standard acoustic loads including point source directivity ___________________________________________________________________________ Simcenter 3D Meshing for Acoustics ___________________________________________________________________________ Simcenter Nastran Advanced Acoustics ___________________________________________________________________________ Simcenter 3D Acoustic Transfer Vector ___________________________________________________________________________ Simcenter 3D Aero-Vibro-Acoustics ___________________________________________________________________________ Simcenter 3D Load Identification ___________________________________________________________________________ Simcenter 3D Environment for BEM Acoustics ___________________________________________________________________________ Simcenter 3D Acoustics BEM solver ___________________________________________________________________________ Simcenter 3D Acoustics Accelerated BEM solver ___________________________________________________________________________ Simcenter 3D Acoustics Time Domain BEM solver ___________________________________________________________________________ Simcenter 3D Acoustics HPC ___________________________________________________________________________ Simcenter 3D Ray Acoustics ⇐ Back to Simcenter

Fulwave solvers based on integral methods to solve Maxwell's electromagnetic equations (Method of Moments – MoM) and asymptotic methods based on Uniform Diffraction Theory (UTD) and Iterative Physical Optics (IPO) – EMC; EMI; Time and frequency, linear and non-linear, finite and boundary elements. Electromagnetic Compatibility Use predefined virtual experiments to evaluate the simulated performance of electric motors. Experiments produce output quantities, waveforms, fields, and graphs. Industry 4.0 factories, incorporating wireless IIoT systems, operate in a complex and noisy electromagnetic environment, as there is an increasing number of electronic devices and electrical cables and wires in vehicles, as well as a significant expansion of antennas and new types of wireless devices. Therefore, it becomes increasingly challenging to ensure that a device continues to function correctly by being immune and not interfering with surrounding devices causing possible failures. Contact an Expert Analyzes Method of Moments Uniform Theory of Diffraction Iterative Physical Optics Simcenter 3D High Frequency addresses a broad frequency spectrum to cover all major analysis needs. Users can select the most appropriate one from a variety of dedicated solvers . These include full-wave solvers based on integral methods for solving Maxwell's electromagnetic equations (Method of Moments – MoM) and asymptotic methods based on Uniform Diffraction Theory (UTD) and Iterative Physical Optics (IPO). Efficiently solve full 2.5D and 3D field problems. Solver acceleration options are incorporated to facilitate direct handling of ultra-large scale system-level models such as complete aircraft, satellites, ships and cars. MoM solves Maxwell's equations discretely without making any approximation: the problem is discretized and transformed into a system of linear equations. Both standard (direct) and fast (iterative with multilevel fast multipole algorithm) solution approach are available. Different boundary conditions are managed: Electric Field Integral Equation (EFIE), Impedance Boundary Conditions (IBC), Combined Field Integral Equation (CFIE) and Poggio-Miller-Chang-Harrington-Wu-Tsai (PMCHWT). Preconditioners (eg Multi-Resolution, SPLU, ILUT) accelerate the convergence of the iterative solution approach. Low-frequency stabilization methods (S-PEEC formulation) solve the problem of low-frequency breakage (very ill-conditioned linear system). The multiport approach minimizes the computational load for evaluating active solutions. MoM is suitable when precision is required for complex problems (in terms of geometries and materials) and when the interaction between the radiation source and the scattering structure is strong. The Uniform Theory of Diffraction (UTD) is a “ray” method, based on an asymptotic solution of Maxwell's equations. The UTD is applicable when a radiant source interacts with a scattering structure whose dimensions are much larger than the field's wavelengt h (eg ships, vehicles or scene settings such as airports, factories, cities, etc.). Under these assumptions, as well as in the case of optics, electromagnetic scattering can be described as the combination of discrete contributions (reflections and diffractions of different orders) from a number of “hot spots” distributed in the structure (edge, wedge, vertex), according to the relatively simple geometrical laws relating to the propagation of rays. UTD manages real materials characterized through transmission and reflection coefficients. Iterative Physical Optics (IPO) is a current-based high-frequency iterative technique. The IPO is applicable in the evaluation of the interaction between a radiant source and a scattering structure whose dimensions are larger than the field wavelength (for example, antenna reflectors, radomes, vehicles, etc.). The application of the equivalence theorem for the description of the scattering mechanism and adoption of the iterative process allows the reconstruction of interactions between objects in complex scenarios without resorting to ray-tracing . Computational resources are optimized by exploiting state-of-the-art technologies: GPU computing, far-field fast approximation algorithm, and iterative relaxation techniques. Thin sheets and impedance boundary condition formulations are available. Simcenter 3D Simcenter 3D High Frequency Simcenter includes distinctive low- and high-frequency electromagnetic simulation capabilities for the unique demands of each domain. Expand your insight into electromechanical component performance, power conversion, antenna design and location, electromagnetic compatibility (EMC) and electromagnetic interference (EMI). A variety of dedicated solvers (time and frequency based, linear and non-linear, finite and boundary element) provide a transformative CAE process, with simulations ranging from quick initial analysis to inherent realism for final verification. Complementarily, Simcenter 3D High Frequency allows analyzing the electromagnetic performance of electrical harnesses, which are imported directly from the CAPITAL software , world leader in wire harness engineering tools. In Simcenter 3D, automatic features work on generating 3D geometry from CAPITAL and assigning properties. The integrated multi-conductor transmission line network (MTLN) solver, combined with Simcenter 's electromagnetic solver – 3D High Frequency–, allows you to perform any wiring harness analysis such as emission, susceptibility, and cross talk within the harness and between the whips. ⇐ Back to Disciplines