SAP has announced updates to its data analytics technology via SAP Datasphere — a tool that creates a business data fabric architecture to unify distributed and siloed data landscapes. Improvements include the automatic creation of knowledge graphs which can help organization better understand data and leverage generative AI. The tool creates ontology that describes the relationships of data based on inherent business context from sources like SAP S/4HANA. The knowledge graph then enables the data to be processed as a semantic web of relationships enabling tools data analytical tools to draw more insights and information.

For instance, it can be linked to a large language model, or SAP’s AI-copilot Joule, to help answer user inquiries while limiting AI hallucinations. The release also includes a new vector engine for SAP HANA Cloud which enables the ability to simplify data architectures and store or compare vectors using SQL. The method to install SAP and non-SAP data sources (such as SAP Analytics Cloud, Collibra AI Governance and Confluent) into SAP Datasphere has also been simplified.

A knowledge graph made using SAP Datasphere. (Image: SAP.)

Aras improves its PLM platform

PLM and digital thread company Aras announced the latest release of Aras Innovator. Highlights from the release include new digital thread capabilities such as simplified user interactions to view, edit, change and interrelate items. There is also a new workflow to connect to authoring tools and other enterprise solutions. Aras Innovator also has a fully integrated low-code development environment to extend applications and develop bespoke tools. For instance, new widgets and carts simplify the creation and navigation of apps like dashboards and reports. The release also introduces Aras Advanced 3D which helps to visualize and interact with large CAD assemblies within a single session. It can also perform advanced searches, filters, clash detection, analyses, measurements, sectioning, geometry manipulation and IP protection.

Prostep launches OpenCLM 3.0

Prostep has released the latest version of its digital thread solution OpenCLM 3.0. The aim of OpenCLM is to make it easy to track developing projects and enact change management. The highlight of this release is the simplification of how to integrate the tool into an organization’s IT ecosystem. Improved dashboard and graphing tools also make it clearer and more concise to visualize information. The new release enables the control of data access based on a user’s role. This means that although all the data on OpenCLM can be described as a single source of truth, the individuals accessing that data will get a tailored view of that truth to best fit their day-to-day operations.

Dassault Systems connects Geovia to its 3DExperience platform

In an announcement about the latest version of its mining software Geovia, Dassault Systèmes said the tool will now be seamlessly integrated into the 3DExperience PLM platform. This will provide organizations with a single source of truth across the mining value chain from pit to port. The release also includes a new Strategic Mine Planner role and Underground Mine Designer role. The first complements the Pit Optimizer role, enabling users to optimize robust and reliable plans for capacity and ecological responsibility. Meanwhile, the Underground Mine Designer role helps engineers use generative parametric modeling to generate and evaluate designs using automated processes to optimize for compliance and safety.

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Cadence Design Systems has announced that it will acquire BETA CAE Systems International. The aim is to expand the electronics-focused multiphysics capabilities of Cadence’s Intelligent Systems Design tools by expanding into the realm of structural analysis. Due to the industry’s move towards digital transformations and the added convergence between mechanical and electrical products, this purchase rings similar to others in the engineering simulation field: a structural simulation company merging with electronics design automation (EDA) companies. In this case, Cadence’s portfolio of electromagnetics, electro thermal and computational fluid dynamics (CFD) tools will be enhanced by BETA CAE’s structural analysis tools.

Noesis Solutions releases a solver-agnostic AI-powered simulation tool

Many simulation organizations are embracing the use of AI tools, but most are focused on producing tools tailored to their own software portfolios. Noesis Solutions, however, is releasing nvision, an AI-powered surrogate modelling tool that is open and solver-agnostic. This will help simulation engineers using numerous and disparate simulation tools to use AI functionalities to reduce the time to results without reducing accuracy. If the user has historical simulation data, they can use it to build a model to help get near real-time results from simulations that could traditionally take hours, days or even weeks to run.

Maplesoft releases Maple 2024 leans into AI

The mathematical software tool Maple has just announced its 2024 release. This version offers engineers AI technologies, like an AI Formula Assistant, to improve efficiency and report writing. Users can also build their own AI tools inside Maple and link it to their systems. The AI tools offered will help engineers produce formulas, solve equations, explain systems and understand Maple commands, reducing time spend on training and producing reports. The release also has a new algorithm to solve multivariate polynomial systems, integral equations, summations, matroid theory and more.

The mathematical software Maple has released its 2024 version. (Image: Maplesoft.)

Coreform Cubit 2024.3 released

Coreform has released the 2024.3 version of its Cubit simulation technology. Key highlights include faster performance, improved Python integration, feature enhancements and bugfixes. The release also includes improvements to the documentation of Direct Accelerated Geometry Monte Carlo (DAGMC) neutronics.

Siemens updates model-based RAMS software

Siemens Digital Industries Software has released the 3.8.7 version of MADE, a model-based reliability, maintainability and safety analysis (RAMS) software. The tool helps organizations perform RAMS assessments using digital twins. The release includes user experience and workflow improvements and faster digital twin creations due to its improved PLM integrations via Teamcenter and API protocols. The functional hazard assessment (FHA) process has also been redesigned in this release. Other improvements include the precision and ease of use of mission profile definition (MPD), alignments to ARP 4761 rev A for functional hazard analysis (FHA), new taxonomies and customizations for failure modes, effects and criticality analysis (FMECA) reports, new prognostics and health management (PHM) module for sensor testing, costing and updates and more.

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Simens Digital Industries Software has announced the release of Simcenter Star-Ccm+ 2402. The update to the CFD software focuses on speeding up results via more GPU options. The release also offers more accurate simulations for turbomachinery and coupled fluid-structure interactions. Now, engineers can also perform volumetric photon Monte Carlo simulations to model and assess the absorption and scattering of radiation as it interacts with media.

Volumetric photon Monte Carlo simulation. (Image: Siemens.)

Modelon releases a new library for advanced automotive simulations

Modelon has released a new library to help engineers model and simulate battery thermal management and climate control systems on EVs. Some systems the library will help model include heat pumps and refrigerant-coolant systems. The library will help engineer size components such as electric motors, battery packs, cables and more based on operational and systems requirements.

Modelon has also expanded its libraries for driver-in-the-loop capabilities. Notable to this expansion is the ability to couple with simulation environments like rFpro.

Intel 18A processor technology now supported by Ansys and Siemens

Ansys and Siemens have announced that their design technology can now support Intel 18A process technology with RibbonFET transistors and backside power delivery.

For Siemens users, this means that the Calibre nmPlatform tool for integrated circuit (IC) design verification and the Analog FastSPICE (AFS) platform for analog, radio frequency, custom digital and mixed-signal circuit verification can now be used to design Intel 18A and 16 process technologies.

For Ansys users, they can assess the Intel 18A processor technology using RedHawk-SC and Totem for power integrity signoff of digital and analog designs. Users can also use PathFinder for electrostatic discharge and Raptor for high-speed signals including on-chip electromagnetic coupling.

Intel Foundry works with Ansys and Siemens on EMIB 2.5D technology

Like above, both Ansys and Siemens are now able to perform signoff, and other functions, for Intel’s embedded multi-die interconnected bridge (EMIB) 2.5D chip assembly technology. For instance, engineers can use Ansys RedHawk-SC Electrothermal to perform multiphysics thermal analyses on this IC technology. Meanwhile, users of Siemens Xpedition Substrate Integrator software, Xpedition Package Designer software, Hyperlync software and Calibre nmPlatform can use these tools for EMIB floor planning, prototyping, signoff and more.

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Dassault Systèmes’ workflow assesses the spread of disease in hospitals. Notice how viruses spread over dividers and equipment. (Image: Dassault Systèmes.)

Using the workflow, Dassault Systèmes was able to create a virtual twin of the hospital’s dialysis unit which consisted of an open space capable of holding 50 patients a week. Healthcare providers were then able to see how particles circulate in the air to better understand the importance of ventilation and masks. The simulations showed viruses floating over patient dividers and equipment to spread throughout the room.

The twin was made on the simple, and free, space optimization tool HomeByMe—using building blueprints and 3D scans. The twin was then input into SIMULIA to simulate transmissions based on different respiratory, airflow and medical equipment layout scenarios. This means that the same tool used by laypeople to help sell homes and optimize Feng Shui can be used by healthcare workers to design layouts and select equipment.

“Dassault Systèmes had already worked on projects at other hospitals in Paris and understood our mission to offer the highest level of care. Its solutions allowed us to visualize the production of respiratory particles, follow their trajectory, and see how they could spread from patient to patient,” said Dr. Guillaume Mellon, attending physician and head of the Infection Prevention and Control team at Saint-Louis Hospital AP-HP. “This incredibly innovative educational experience made our health professionals more aware of respiratory cross-transmission risks in the hospital. The entire experience exceeded my expectations.”

It’s true that engineers modeled the particle flow in the room, but with the success of this trial run it’s hard to not see Dassault Systèmes, or someone else, making this workflow into a simplified simulation app targeting healthcare providers.

“Virtual twins are poised to transform daily patient care and infection prevention in the coming years,” said Claire Biot, vice president of Life Sciences and Healthcare Industry at Dassault Systèmes.  “We’ve already completed projects with a number of major hospitals that successfully demonstrated how our virtual twin technology can help identify and optimize safety measures.”

By giving healthcare providers this level of insight into the selection and layout of equipment it will put more pressure on engineers within the industry to ensure that their medical device designs are optimized to reduce transmissions. This will require engineers to perform CFD simulations of their designs within operational environments to ensure their products surpass the performance of the competition. This will be especially important for those designing partitions and large equipment which will affect the flow of air within a room.

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(Image: Bigstock.)

But there is a significant challenge with the abbreviation MBD. With 26 letters in the English alphabet, there are 17,576 possible abbreviations with three letters. This gives engineers plenty of options to differentiate the numerous concepts in the field. However, despite those permutations MBD has no less than four, perhaps more, engineering definitions. Here is a guide.

Model-based definition (MBD)

A quick google search of MBD may return inks to an old engineering.com article and posts from engineering software companies such as PTC and Autodesk defining the term as model-based definition.

Model-based definition is a feature in various CAD, PDM and PLM software that enables users to annotate and associate part information with a 3D model. Some of the information that might be included with this version of MBD includes geometric dimensioning and tolerancing (GD&T), material properties, bills of materials (BOMs), configurations, data, notes and more.

In essence, the 3D geometry acts as a single source of truth for everything an organization needs to know about a part. In the past, much of this data was associated with 2D engineering drawings and paper documents. However, as 3D models are better equipped at modeling real-world assets, and digital records are easier to maintain, MBD is a considerable improvement.

MBD is often used interchangeably with product information modeling (PIM) or digital product definition (DPD). It is also associated with numerous industry standards including ASME Y14.41, ISO 16792, ISO 1101 and AS9100.

Model-based design (MBD), or is it model-based development?

A Google search of the term MBD may also bring up pages from the engineering software companies Synopsys and MathWorks that define the acronym as model-based design. If that isn’t confusing enough, PTC, IEEE, systems engineering company Array of Engineers and automotive systems engineering company dSPACE use the term model-based development on their websites to describe the very same process.

Whether you call it mode-based design or development, this version of MBD can be traced back to the early history of systems design, systems engineering and process control. It involves producing a model of a complex system using flow charts, mathematical equations and simple simulations.

The model-based design process. (Image: Synopsys.)

Early in development, the goal of model-based design is to quickly iterate system setups via virtual tests. At this stage, the simulations help engineers explore the design space, verify and validate final products, enhance functional safety and generate software to control the system. As this is all done digitally, systems development can be done faster and safer than if various physical prototypes were used.

After deployment of a physical system, MBD simulations are still useful. For instance, they can then be used as a digital twin to help optimize, predict maintenance and upgrade physical assets.

Multibody dynamics (MBD)

In the engineering simulation and computer-aided engineering (CAE) world, people might know MBD to stand for multibody dynamics. For example, simulation software companies such as Hexagon, COMSOL, Altair and Ansys, as well as outlets like ScienceDirect, MIT and more, have website pages devoted to this definition.

A multibody dynamics simulation of aircraft landing gear using Adams software. (Image: Hexagon.)

Multibody dynamics simulations assess mechanical systems made up of rigid or elastic parts. Using equations of motion, multibody dynamics simulation software numerically assesses the kinematics of each part in the system based on their mass, center of mass, inertia and properties after the application of internal and external forces or torques. The motions multibody dynamics simulations might describe span the translational and rotational movements of aircraft parts, construction equipment, robots, vehicles or any other system with moving parts. Some assessments engineers can perform using multibody dynamics include the study of noise, vibration and harshness (NVH), vehicle performance, electronic control systems and more.

Much like model-based design and model-based definition, multibody dynamics is often used early in the product development cycle to virtually test the performance of a design before any physical assets are produced. Multibody dynamics simulations can also be used as part of a digital twin to monitor and assess real-world assets. However, unlike model-based design digital twins, which traditionally assess industrial systems, multibody dynamics digital twins assess a real-world systems’ motion.

More MBD?

Other definitions of MBD exist for various engineers in different industries. Some examples include:

• Molecular beam deposition in materials science.
• Market-based dynamics in economics and systems engineering.
• Minimum bounding dimension in geometry.
• Motherboard in electronics.

If you can think of more engineering terms abbreviated to MBD, list them below.

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A local Von Mises stress simulation using finite element analysis. (Image: Bigstock.)

Traditionally, CAE has been used at the end of development to verify that a final, or near final, design is meeting expectations. However, modern product development processes have started to use CAE early in development via iterative design processes such as simulation-driven design or design for manufacturing. The aim of these processes is to find design flaws and manufacturing issues early in development when they can be easily and affordably fixed. In doing so, engineers can avoid problems before manufacturing or final testing when solving issues is more time consuming and expensive.

Engineering simulations have also started to enter engineering workflows after a product is in the field. At this point, data from the real-world asset can be collected using sensors and the Internet of Things (IoT) to be assessed by CAE tools. These assessments can help predict issues, schedule preventative maintenance and optimize performance. When this setup is created, the simulation is often referred to as a digital twin of the real-world asset it is assessing.

CAE tools have also become more of a necessity in recent years as product development has become more complex. Rarely do new products perform only one task; now they are often smart, connected to the IoT, collaborative, automated and more. This has forced engineers to simultaneously assess, test and verify more physical phenomena, to ensure interactions do not affect performance, via multiphysics simulations.

In the past, simulations of a product’s structure, heat transfer and electromagnetics would have been assessed by separate models. Multiphysics models combine these assessments into a single simulation. This has forced many CAE users to expand their areas of expertise to other physical phenomena, as well as work together to ensure the physics of a system is optimally captured.

The challenge of added complexity in products is further compounded by the fact that development times are shrinking as consumers want newer technologies. As a result, simulation has become a popular tool to reduce, or even eliminate, the need for physical testing. This enables products to launch faster and at a lower cost.

Suppliers of CAE software include Ansys, Altair, Autodesk, COMSOL, Dassault Systèmes, Hexagon, Maplesoft, MathWorks, PTC, Siemens Digital Industries Software and more. CAE is often associated with computer-aided design (CAD) and computer-aided manufacturing (CAM) as there is a lot of overlap and communications between these technologies. For instance, the geometry made in CAD software is a popular starting point for 3D engineering simulations. As such, the suppliers of CAD and CAM tools also include many of the organizations listed above.

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At this week’s 3DEXPERIENCE World, engineering design software companies Dassault Systèmes and Cadence announced that they are integrating the AI-driven Cadence OrCAD X and Allegro X with the extended 3DEXPERIENCE Works portfolio for SOLIDWORKS’ existing and future customers. In doing so, electrical and mechanical engineers gain a cloud-enabled integrated workflow for the product development of mechatronic systems. This workflow can optimize these designs for performance, manufacturability, cost, compliance, reliability and supply chain resilience.

Ansys releases a cloud-based method to access Fluent CFD simulations

After the release of Ansys 2024 R1, the simulation leader announced the release of Fluent Web UI, a cloud-based method to access, control, monitor, run and speed-up Ansys Fluent CFD simulations. According to the release, engineers will have access to native GPU and cloud-based high-performance computing (HPC) to speed up time-to-result by a factor of 10. The software option also comes with a streamlined user interface that simplifies workflows for the aerospace and automotive sector.

Ansys Fluent Web UI enables engineers to work on CFD simulations on any device on the cloud. (Image: Ansys.)

Intact.Simulation Compatible with Rhino 8

The latest version of the automated mechanical design and simulation software Intact.Simulation will now be compatible with the visual programming interface Rhino Grasshopper V2.0 via the 3D modeling tool Rhino 8. Other improvements include an automatic simulation feature that triggers when parameters are changed. The release also includes a new list of input materials, boundary conditions and loads.

Improving Automotive Car Simulators with VR

The driving simulator company VI-grade is partnering with virtual reality company Varjo to connect VR and XR (extended reality) headsets into the driving simulator experience. The collaboration will help engineers design human-machine interfaces in the automotive industry. It will also provide more realistic simulations, AI-based traffic behavior and sensor fusion between the headset, simulator and digitally simulated environment. The announcement notes that Varjo’s XR-3 and XR-4 headsets will connect with VI-WorldSim version 2024.1.

By using VR and XR, engineers can enhance driving simulators to design better cars and automotive systems. (Image: VI-grade.)

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What is the meaning of a finite element?

To solve an FEM analysis, the geometry of the problem must be broken down into smaller, simpler geometries called finite elements. This process is often called meshing, as it turns the larger geometry into a grid, or mesh, of smaller parts.

A mesh of finite elements (left) depicts the geometry of a part. A structural simulation (right) derived from the mesh shows how the part will react to an applied force. (Image: Bigstock.)

Once boundary conditions and material properties are selected, the differential equations that describe the physics of the system can be mimicked within each finite element using algebraic equations. This system of equations can then be solved iteratively until the value of an error function is minimized.

Smaller finite elements—also known as a finer mesh—will yield better estimates of the physics and capture local phenomena. However, the trade-off is that the simulation will be harder to solve computationally. To ensure a solution can be found that is both timely and accurate, the number and size of finite elements need to be optimized.

To get around these issues, simulation users will often create a mesh with finer elements near complex geometries and coarser elements where results are not expected to change much from element to element. These variable finite element sizes produce accurate results in areas of interest without making the simulation computationally expensive or time consuming.

When should FEM be used and what alternatives exist?

FEM can be used to simulate many physics problems, including computational fluid dynamics (CFD). However, for CFD the finite difference method (FDM) or finite volume method (FVM) are often selected instead. CFD problems tend to require a larger number of elements—making FEM too computationally expensive. FDM and FVM, however, use lower order approximations within each cell, making these methods more attractive in CFD scenarios.

On the other hand, FEM is more attractive in problems requiring fewer finite elements as it generally returns a higher quality of results and can accommodate geometries of higher complexity.

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The Ansys 2024 R1 release focuses on user experience improvements and additional AI features. SimAI was previously announced to offer a cloud-based generative AI workflow where simulation results can be used to predict other designs in minutes. The release includes other AI improvements in the form of Ansys optiSLang AI+, Granta MI AI+ and CFD AI+. Ansys Discovery is also getting speed boosts in the form of cloud-based, burst compute. Tests have been able to run thousands of simulations in 10 minutes without bogging down workstations. The user experience improvements enable engineers to customize their workflow based on accessibility. It also has three standard modes:

• Classic mode for those used to previous releases.
• Dark mode for reduced eyestrain.
• Light mode for improved visibility.

Screen shots of user interface modes from Ansys 2024 R1 include: dark mode (left), light mode (middle) and classic mode (right). (Image: Ansys.)

Cadence releases AI-enhanced thermal design and analysis platform for ECAD/MCAD

Cadence, the electronic systems design software company, has just released Celsius Studio, an AI-enhanced platform for thermal design and analysis that marries both mechanical CAD (MCAD) and electrical CAD (ECAD) models. Celsius Studio can perform thermal analyses of 2.5D and 3D-IC packages as well as assess the performance of electronic cooling systems for PCB and electronic assemblies.

What sets Celsius Studio apart is its generative AI optimization and modeling tools as well as its ability to unify the work of electrical, thermal and mechanical engineers into one multiphysics platform. This means that these engineers can use the same MCAD/ECAD geometry without simplifying, translating or manipulating the model. This news follows the 2022 acquisition of Future Facilities and its electronics cooling technology, which Celsius Studio now makes accessible to electrical and mechanical engineers.

Cadence releases a complete AI thermal design and analysis tool for electronic systems. (Image: Cadence.)

Avnet releases toolbox for over-the-air antenna to bits simulation.

Avnet, a product development and prototyping company, has released Avnet RFSoC Explorer Toolbox version 3.0 which can help engineers simulate over-the-air antenna to bits communications with the 5G mmWave Phased Array Antenna Modules (PAAM) Development platform. This will enable engineers to quickly develop and digitally prototype 5G mmWave systems using the Avnet RFSoC Explorer on the MATLAB dashboard.

Cadence offers dedicated hardware and software for CFD and multiphysics analysis

Cadence has just released its Millennium Enterprise Multiphysics Platform consisting of CFD and multiphysics optimized supercomputers and software. The new platform is available on the cloud and on-premises to provide GPU accelerated HPC for generative AI, digital twins and multiphysics simulation. The new platform is targeting the automotive and aerospace markets to help accelerate the design and optimization of turbomachinery, electric vehicles and green technologies.

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The 2312 release of Simcenter Mechanical simulation focuses on making workflows more collaborative between design, simulation and physical testing. As part of this release, Siemens Digital Industries Software announced Simcenter E-Machine Design software to help engineers design electric machines. The tool brings together the functionalities of Simcenter SPEED, Motorsolve and MAGNET, enabling engineers to replicate physical electric machine experiments within a digital space. Engineers will benefit from E-Machine Design’s template-based design workflow. This enables engineers to model numerous electric machines without being a finite element expert. The aim here is to reduce development time and reduce the barriers to using simulation tools. The tool also helps engineers reduce the operational temperatures of electric machines and simulate axial flux.

Ansys and DXOMARK partnership expands their optical simulation workflows

A new partnership between Ansys and DXOMARK offers engineers an end-to-end workflow for virtual camera systems by combining Ansys Lumerical, Ansys Zemax OpticStudio, Ansys Speos and DXOMARK Analyzer. This workflow will bridge the gap between physical measurements and simulation by using the image quality analysis capabilities of Analyzer and augmenting them with Ansys’ portfolio of optical simulation software. The idea is to first run simulations in Zemax OpticStudio to optimize lens designs, and then simulate complex micro-components in Lumerical. Results are then passed onto Speos to build a virtual model of the camera. Speos Sensor System Exporter is then used to pass results to Analyzer to assess image noise, flare, dynamic ranges and distortions. This workflow is targeting the autonomous vehicle and medical markets to help develop new optical products and systems.

Simulation of stray light effects from a lens. (Image: Ansys.)

Rescale adds quantum computing to its cloud-based HPC offerings

Rescale, a supplier of pay-as-you-go, cloud-based, on-demand HPC resources, has partnered with IonQ to give engineers access to quantum computing technology. Currently, the Rescale platform connects engineers to top-of-the-line HPC tools designed to compute simulations and AI problems. With this new partnership, quantum computers, such as the 29-qubit IonQ Forte, will be on the platform. This will help engineers solve some problems once thought incalculable or computationally expensive. Rescale and IonQ note the industries likely to benefit from this announcement include product development, healthcare, life sciences, materials research and more.

Siemens changes how to share circuit thermal models for 3D CFD analysis

Siemens has announced Boundary Condition Independent Reduce Order Models (BCI-ROM), a new feature in Simcenter Flotherm for electronics cooling simulation. The tool enables engineers to simplify and obfuscate their integrated circuit designs while maintaining the ability for others to run CFD simulations with the part. This will help protect intellectual properties, enhance supply chain collaboration and ensure the accuracy of electronic systems by enabling engineers throughout the part life cycle to use the model. For instance, a chip’s ROM can be sent to customers so they can assess the thermal performance of their designs without knowing the chip’s specifics. This will protect the chip manufacturer from IP theft.

An engineer performs a 3D CFD simulation on electronic components. (Siemens.)

Ansys and Humanetics to expand crash test dummy simulations

Ansys has agreed to buy a minority stake in Humanetics, which will improve collaboration between the two organizations. Humanetics provides engineers with physical and digital anthropomorphic test devices (ATD) — colloquially known as crash test dummies. Digital ATDs are often used in simulations to assure the safety and ergonomics of products. The partnership will aim to further these assessments via digital twin technology by linking physical and digital ATDs together. This will help engineers design products, improve testing and inform the decision-making process.

Autodesk releases Moldflow 2024

The 2024 release of Autodesk Moldflow includes improvements to Moldflow Adviser, Insight and Synergy. Changes in this update include an updated user interface for Study Duplication features, the decoupling of the material database installation from the release and improvements of the general solver in the areas of Dual Domain warpage, shrinkage, sink marks and thermal expansion predictions.

Markforged’s new tool blends simulation and AI to optimize print strength

Markforged has recently released Performance Advisor, a tool which automatically suggests optimal print settings to improve the strength of additive manufactured parts. The tool does this, without user-specified use cases, by assessing the geometry’s eigenmodes — or how the part naturally vibrates. Performance Advisor notes the regions of the part most susceptible to deformation and stress and then uses machine learning to suggest print settings to address these issues. This tool is not meant to replace simulation in cases where use cases are known and well understood. But when engineers are early in the development process, this tool can speed up the time to print a physical prototype.

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