Like other product design engineers, medical device engineers need to know the traditional mechanical properties of a material they plan to use to ensure it’s up to the task. But that’s not enough. They also need to know how the body will react to the device and how the device will react to the body.
Working with the right data is critical to an efficient workflow, but with all the different stakeholders involved in product design and development, how do you know where the right data is?
To conduct a CAE simulation, there are three important steps to an analysis: pre-processing, solving and post-processing. This post discusses the FEA pre-processing step, specifically the importance of a good quality mesh.
The old, siloed approach to product design and development is being replaced by streamlined workflows where an array of hardware and software needs to work together to foster innovation.
Ansys launched a research survey last year to find out how engineering organizations are using HPC resources for engineering simulation.
Many organizations are beginning to implement plans to return to the office. The COVID-19 pandemic has everyone rethinking office spaces, especially the all too common open-office space.
3D electromagnetic problems become more complex in multiphysics simulations such as noise-vibration and harshness (NVH).
Engineers understand that the individual components they design and simulate are part of larger assemblies, which are part of larger systems, which are part of an ecosystem.
Simulation-based digital twins, especially when implementing new data center technology, streamline data center design and operations management.
In his post, author Boris Marovic writes about the leading role of simulation in the Ingenuity 21 space program.
Learn how engineers improve manufacturing procedures and minimize tooling and material costs on-demand.
The convergence of mechatronic and system-based engineering with advances in data management, artificial intelligence (AI), machine-learning (ML) and increasingly connected manufacturing is challenging traditional industrial product development and manufacturing processes.
The Digital Twin provides a collaborative framework and the necessary design tools to drive informed, real-time decisions regarding thermal risk and capacity utilization. 6SigmaDCX Release 15 streamlines data center design and management with new big data features, faster model creation and automation across the board.
Thanks to Simon Fischer, here’s the first ever Guinness served in perfection – by a CFD simulation tool. Hey, its five o-clock somewhere right?
One of the software tools used to design the weather station on the Perseverance rover was Simcenter FLOEFD.
Webinar on out-of-the-box, CAD-integrated simulation.
Can you create better designs based on experience or based on simulation data?
This e-book outlines the necessity for unlocking your data center’s business potential.
Our vision is a world where all data centers can realize their business potential. To make this vision a reality, we are pioneering the concept of the Digital Twin for data center design and management.
You may not know it, but today data centers are crucial: they underpin daily life throughout society. Every time you use common tools on the Internet like Google, Facebook, or YouTube, a data center somewhere is involved in this process.
Innovative manufacturers are taking advantage of advances in simulation technology and development processes to beat their competitors to market with higher quality, longer lasting products.
Deploying any change within your data center can seem daunting. But with a data center Digital Twin you can undertake virtual testing of those changes, using physics-based simulation, ensuring nothing goes into a live environment that hasn’t already been assessed for performance.
Webinar on automated simulation processes for use by designers.
Why CFD inside CAD is more than just pretty colors.
Learn how design engineers using CATIA V5 can efficiently use Simcenter to understand their product's performance earlier.
Using NX Open built into Simcenter 3D, users can use automate simulation processes called templates. These template are made up of all the simulation knowledge that is needed for the complex analysis to ensure that high quality products are created, even by less experienced users
See how Creo users can use simulation
A component’s fatigue life is affected by multiple factors such as material, geometry, stress range, load frequency, manufacturing process, and atmospheric conditions. It is a difficult question to figure out by hand, which makes it an ideal task for computational simulation.
ESRD provides a few tips and links to help you become more acquainted with StressCheck® Professional and its latest features.
ESRD’s CAE Handbook contains 95+ high-quality, expert-built digital handbook solutions. This demo shows how a 3D attachment lug assembly is solved in multi-body contact, and post-processing of the data of interest is automatically reported.
Could OnScale's Multiphysics simulation have been the key to solving the global supply disturbance amounting to $400 million per hour? Read the article in Digital Engineering.
An online community for Next-Generation Simulation usage and expansion: Are you being left behind?
Capturing high level modelling and idealization decisions in order to create a fit-for-purpose analysis model
This paper provides an aerospace industry perspective on the Digital Twin and the significant benefits and rationale to accelerate embracing the fourth industrial revolution referred to as digital transformation.
Renowned researcher Bert Blocken, Ph.D., was recently recognized by Engineering.com alongside other pioneering minds, such as Elon Musk and Ansys CEO Ajei Gopal, for his groundbreaking academic research activities in computational fluid dynamics, wall function development and analysis of basic flow phenomena.
This webinar explores the steps to take with any CAD model to ensure that it’s simulation ready.
A video tutorial as outlined in the StressCheck v11 Getting Started Guide. Import 3D geometry, automesh, apply boundary conditions, solve a linear p-extension, and perform the four key quality checks.
In this video, you can see how the user is able to navigate on the performance map, evaluating the behavior of the design on specific operating conditions, for different values and views (pressure field, velocity field, etc.). Then, the user can upload a new geometry, and get the instantaneous predictions of the model on the whole range of operating conditions.
When issuing a prediction, one can question human or artificial intelligence on how much she/it is sure about the prediction. Without going into detail on the dramatic consequences of overconfident artificial agents in such situations as Autonomous Driving, this article will focus on the Neural Concept’s core competence: building predictive models that are surrogates of more resource-intensive CAE models.
Model Order Reduction (MOR) techniques are interpolation methods exploiting existing data sets (input and output) delivered from an existing model or experimental setup. This paper presents the major idea behind reduction methods along with potential applications for crash and safety simulations.
For many years we have taken for granted the constant improvement in capabilities, performance and connectivity of the electronic devices that are now ubiquitous — from the next-generation wearable, cell phone or computer to smart home devices and virtual assistants that know what we want before we do.
Watch this video as presented by Mr. Jürgen Bruns from Volkswagen AG, at the 8th BEFORE REALITY Conference.
Watch this video presentation by Mr. Jean-Christophe Carniel from Groupe PSA, at the 8th BEFORE REALITY Conference.
Making geometry models suitable for CFD meshing is often a time-consuming bottleneck in CFD analysis. Here we will discuss why this is so and some ways to alleviate the problems.
Systems Thinking is central to the design of complex systems and to the implementation of your long-term Digital Thread strategy. This Executive Brief describes the risks associated with product complexity and provides you with a practical guide to implement a Systems Thinking approach.
In this nTop Live, Andrew Sartorelli, Product Manager at nTopology, shows you how to import topology optimization results from Altair Optistruct® and automatically reconstruct the geometry to produce a manufacturable part.
Digital Engineering's Beth Stackpole writes that a focus on post-processing capabilities and creative use of emerging technologies takes the democratization of simulation to the next level boosting accessibility of analysis-driven insight.
In the recent nTop Platform 2.24 update, we introduced the topology optimization overhang constraint for Additive Manufacturing. In this blog post, we take a deeper look at the unique capabilities of this new feature and how it allows you to create optimization workflows that are different from every other solution currently in the market.
During new vehicle development the current design is frozen and released and important attributes are analyzed virtually. After such a release, a vast amount of data is available and CAE models need to be created or updated as fast as possible with high quality. The process of collecting, checking and preparing all data was cumbersome and a significant amount of time was also needed to check and correct the received models which could have been based on incorrect input.
The auto industry has been moving from a physical test-based development process to more of a virtual one. All aspects of the vehicle’s design and performance targets are being driven by the use of CAE simulations. Taking the data from one format like CAD and putting them into various formats that physics-based solvers can use is key. Honda R&D America's Mr. Eric Dehoff presents at the 8th BEFORE REALITY Conference.
Simulation-led workflows now dominate early-stage device design and have edged into bench testing and validation. By Desktop Engineering's Beth Stackpole.
Field-Driven Design is a methodology enabled by the unique capabilities of nTop Platform. Field-Driven Design is a radically better way to generate & control complex part geometry for engineering, manufacturing, and product development. This whitepaper describes the general concepts of Field-Driven Design, how to create and use fields in nTop Platform, and how to use this unique design methodology to unlock new applications.
In this short video presentation, Rev-Sim Co-Founder, Malcolm Panthaki provides an update on just how much the Democratizing Simulation initiative has grown in two short years.
In this Digital Engineering article, author Kenneth Wong writes that while designer-friendly tools are on the rise, some make make the establishment uneasy.
Over the past 12 months, nTop Platform has evolved into an advanced engineering product development platform. Engineering teams are using our software to tackle the most challenging problems. With 2020 soon coming to a close, now is the perfect time for an end-of-the-year retrospective. Here are the nTop highlights of the year.
Crash simulations are relative complex processes, considering all required steps, from model import and simplification, mesh generation, material description, to boundary conditions, contacts and initial conditions setup. Starting from a detailed CAD model, BETA CAE Systems provides all the necessary tools for Aerospace crash simulations pre- and post- processing.
Self-driving is becoming more and more realistic. Every day, thousands of autonomous vehicles are being tested on the roads by companies like Waymo, Cruise, Uber, Tesla, and some of those companies have accumulated millions of miles of road testing data, enhancing and validating their autonomous “brain”, with the hope that in the near future, full automation can be achieved.
“Siloed or simulation tool-specific SPDM is simply not scalable with the increasing demands for more and more simulation as part of the overall design process,” contends Pawel Chadzynski, senior director, product marketing at Aras. “When simulation data is in multiple spreadsheets owned by individual experts, you can’t scale up the volume of simulation needed for the complexity of products. You just can’t do it with existing infrastructure.”
This NAFEMS and Rev-Sim co-hosted webinar will help to establish a fundamental understanding of Systems Thinking as a critical complement to the Reductionist design approach. As part of the discussion, we will explore the need for pervasive simulation across the entire product lifecycle as a critical tool for the design, manufacture and maintenance of tomorrow’s interconnected multidisciplinary products.
For simulation to have a broader financial impact on an enterprise, SPDM needs to be implemented and deployed seamlessly within the broader enterprise, especially as required to support implementations of Digital Threads and Digital Twins. This NAFEMS and Rev-Sim co-hosted webinar explores how these platform concepts advance the use and impact of analysis and simulation in the coming decade.
Systems thinking, model-based concepts and simulation methods and processes are closely connected. The support of pervasive engineering analysis & simulation technologies are vital in making these concepts feasible. This NAFEMS and Rev-Sim co-hosted webinar will examine how these concepts interact and how the resulting benefits are critical to the enterprise.
Recent advances in data science techniques in support of data driven models, especially in the application of AI, machine learning (deep learning) and predictive analytics, have brought these concepts to the fore in every area of industry. This webinar will discuss where we are, including some successful case studies, and how these technologies are being used to advance significantly the engineering analysis and simulation capabilities and approaches over the next 10 years.
The more that systems thinking becomes an integral part of how design processes are performed, the more our engineers will examine critically the interaction of the various subsystems and components inherent to an overall system, rather than in an isolated manner. This webinar will look at how model-based design and model-based development can work alongside generative design, powered by pervasive simulation for the entire product team. Is this the next major step that is needed in our industry to design, validate and support our products with advanced integrated systems that have been increasing exponentially in complexity?
This paper outlines what Machine Learning (ML) and Artificial Intelligence (AI) is in the context of virtual manufacturing and CAE, and how ML models can shorten the simulation lifecycle dramatically across all industries.
Learn how Akselos provides breakthrough digital twin technology that delivers unique solutions to the challenges that the oil & gas industry is facing. A truly transformational digital twin technology for best-in-class structural integrity management throughout all phases of FPSO lifecycle.
If you look into the future for your company, you need new or better business outcomes. That should be the driver for your company. A company does not need PLM or a Digital Twin. A company might want to reduce its time to market, improve collaboration between all stakeholders. These objectives can be realized by different ways of working and an IT-infrastructure to allow these processes to become digital and connected.
The vision for Generative Design is that it could enable a significant paradigm shift in the design processes used today by enabling designs to be computer-generated based on a proper specification of rules, requirements, and constraints. This overturns the current practice of design, where designs must first be created so they can be evaluated against their performance requirements.
Generative Design is the use of algorithmic methods to quickly and automatically, or iteratively, transform requirements, constraints, uncertainties, and design space to create/drive viable designs or outcomes. Requirements, constraints, and uncertainties may include factors from multiple areas including: design, performance, manufacturing, usability, aesthetics, ergonomics, and cost.
This presentation introduces approaches and platform characteristics that increase the smoothness of the information flow across domains, and between system designers and simulation engineers, through the realization of a custom, domain-independent, system-centric digital thread. This provides a single source of truth for the specifications of all systems of interest and related data.
A True Digital Twin replicates the proposed physical space, and includes all mechanical, robotic, sensor, vision, AI, and computer systems, while simultaneously incorporating real human action and interaction. Humans experience the system in virtual reality (VR), with concurrent motion capture driving their avatars in real time. The avatars interact with virtual objects and their physical “stand ins”, which are also motion-tracked. All aspects of the system, including hardware, software, AI training data/models, and human interaction, are developed, tested and optimized virtually using a proprietary software platform.
The objective of this book is to provide prudent, actionable, vendor independent, information and best-practices on how to approach an SDM project and achieve a first successful SDM deployment as well as identifying pitfalls to avoid based on facts and data from 20 years of SDM project experiences.
In an effort to expedite the development of innovative, sustainable engines, drive enterprise-wide collaboration, and support environmental sustainability initiatives, Cummins is leveraging Ansys Minerva, powered by Aras. Learn more! #digitaltransforamationplatform #SPDM
This paper provides an assessment of the Generative Design workflow in Autodesk Fusion 360. This assessment is based on the capability assessment model related to the Key Capability Areas of Generative Design for General Applicability and their associated criteria outlined in the intrinSIM Market Report entitled “A Vision for Generative Design”.
“A Vision for Generative Design” is a software independent intrinSIM market research paper that explores the potential paradigm shift enabled by Generative Design and what is required to enable that design paradigm shift. This market research paper looks at the key capability areas required to support a paradigm shift and proposes a capability assessment model with detailed assessment criteria for each of the key capability areas.
The term “generative design” has been used in architecture and civil engineering for more than a decade. It is now gaining currency in the mechanical design (MCAD) world.
CAD programs are ideal for design engineers who need to express their concepts, whether the shape of an automotive part or the housing of a smartphone, in detailed 3D geometry. Dassault Systèmes’ SolidWorks and CATIA, Autodesk Inventor, Siemens PLM Software’s Solid Edge and PTC’s Creo Parametric exemplify such programs.
In today’s design environment, it’s increasingly necessary to combine multiple file types in a single project. If you need to work with parametric, direct and facet modeling within the same project, some CAD platforms require you to move design data across multiple pieces of software.
Generative design replicates natural world's evolutionary approach with cloud computing to provide thousands of solutions to one engineering problem.
Generative design is opening new opportunities for solving design problems — and turning traditional workflows upside down, moving simulation ahead of model creation. Understanding the basics of the technology can help you decide if it’s time to share your AEC or MCAD workload with generative design tools.
To complement this issue on generative design, Ian Symington, NAFEMS Technical Officer, reached out to members of the NAFEMS Vendor Network nafe.ms/vendor to get their thoughts on the topic.
Topology Optimization that accounts for Additive Manufacturing constraints is a solid beginning for Generative Design. But Generative Design is more than this and may include multiple forms of Design Optimization.
A presentation by CIMdata's Dr. Keith Meintjes at the 2018 CAASE conference.
A Digital Engineering Webcast from November, 2018.
This presentation illustrates the Generative Design requirements assessment using the ASSESS assessment model and intrinSIM quantification method.
From CAASE 20: The vision for Generative Design is to enable a significant paradigm shift in the current design processes through the creation of algorithmically-generated designs by Design Engineers in the early concept design stage.
Generative Design is an innovation that significantly alters this way of thinking. It leverages topology optimization, artificial intelligence, and advanced simulation which automatically creates multiple viable design alternatives by specifying simple design criteria.
Generative Design is a holistic methodology that augments the capabilities of engineers with digital tools, enabling them to innovate faster. In this 20+ page guide, we explain how you can use nTop Platform as a powerful Generative Design toolbox that gives you complete control over every aspect of your design workflows.
Generative Design is getting a lot of attention — but what is it exactly? Here is why the current Generative Design concepts fall short and how nTop’s alternative approach enables you to unlock its full potential today.
Future Facilities company and data center digital twins overview video series.
A six-part video series on data center digital twins.
Success within a data center starts with effective communication between teams, and a planning process that is as agile as it is reliable. Because data center managers must respond to problems as they arise, they are often forced risk resilience and efficiency by making decisions based on inadequate data.
An overview video of data center digital twins.
6SigmaRoom is the industry’s leading data center CFD tool. It is part of the 6SigmaDCX software suite, which integrates IT and engineering operations in capacity planning.
Our vision is a world where all data centers can realize their business potential. To make this vision a reality, we are pioneering the concept of the Digital Twin for data center design and management.
Renumbering (ordering) of the cells in the Finite Volume Method (FVM) can affect the performance of the linear solver and thus the speed of the simulation.
Professor Kozo Fujii recently shared preliminary results of a large-eddy simulation of an axial fan that were computed on overset structured grids. Decomposition techniques were then used to compute the fan’s acoustic signature. A journal article and conference presentation are currently in-work and will contain more detail on the simulations and a broader range of results.
Computational fluid dynamics (CFD) can be used to influence decisions early in the design process. In order to assess the state-of-the-art of CFD and its predictive capability for medical devices, the U.S. Food and Drug Administration (FDA) developed two benchmark models for validation.
In this webinar, Yamaichi Special Steel explains how they combined the advanced capabilities of nTop Platform with their own custom software (Cognitive Additive & OptiBot) to create a generative design workflow tailored to their needs.
Titanium is the blank canvas on which advanced additive designs can be placed.
In this speaker series, experts in the field of Design for Additive Manufacturing will discuss applications for metal 3D printing and the constant trade off between engineering requirements and design for the manufacturing process.