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NAFEMS Americas and Digital Engineering (DE) teamed up (once again) to present CAASE, the (now Virtual) Conference on Advancing Analysis & Simulation in Engineering, on June 16-18, 2020! CAASE20 brought together the leading visionaries, developers, and practitioners of CAE-related technologies in an open forum, unlike any other, to share experiences, discuss relevant trends, discover common themes, and explore future issues, including: -What is the future for engineering analysis and simulation? -Where will it lead us in the next decade? -How can designers and engineers realize its full potential? What are the business, technological, and human enablers that will take past successful developments...more
NAFEMS Americas and Digital Engineering (DE) teamed up (once again) to present CAASE, the (now Virtual) Conference on Advancing Analysis & Simulation in Engineering, on June 16-18, 2020! CAASE20 brought together the leading visionaries, developers, and practitioners of CAE-related technologies in an open forum, unlike any other, to share experiences, discuss relevant trends, discover common themes, and explore future issues, including: -What is the future for engineering analysis and simulation? -Where will it lead us in the next decade? -How can designers and engineers realize its full potential? What are the business, technological, and human enablers that will take past successful developments...more
NAFEMS Americas and Digital Engineering (DE) teamed up (once again) to present CAASE, the (now Virtual) Conference on Advancing Analysis & Simulation in Engineering, on June 16-18, 2020! CAASE20 brought together the leading visionaries, developers, and practitioners of CAE-related technologies in an open forum, unlike any other, to share experiences, discuss relevant trends, discover common themes, and explore future issues, including: -What is the future for engineering analysis and simulation? -Where will it lead us in the next decade? -How can designers and engineers realize its full potential? What are the business, technological, and human enablers that will take past successful developments...more
Digital Twin – An Engineers’ Perspective Abstract The term “Digital Twin” was defined by Dr. Michael Grieves at the University of Michigan around 2001. He defines “Digital Twin” as a digital replica of physical assets, processes and systems that have been manufactured. He promoted the idea of comparing a Digital Twin to its engineering design to better understand what was produced versus what was designed, tightening between design and execution. Digital Twin starts with the existence of a physical part –as early as a prototype exists, and they last until product end-of-life. We can put the digital twin life into three major phases: twins for designs, twins for manufacturing and twins for...more
Blog: How Do I Switch It On? Excuse me, how do I switch it on? 19 March 2013 by Tony Abbey, NAFEMS Training Manager One of the most enjoyable aspects of the training that I carry out is the travelling involved. I have been very fortunate to teach in many countries around the world and to visit many interesting places. Often this involves flying into an airport, picking up a rental car and then heading off to my hotel on the first night. One of the great blessings has been the introduction of SatNav or GPS navigation aids. I always carry my own with me and like to have a backup iPhone or similar just in case. Finding a city centre, or very rural, hotel on a dark rainy night is now a lot...more
These slides were presented at the " Digital Tools for Transforming the Aerospace Industry " Seminar, held in Middleburg Heights, USA on 3-4 September, 2025....more
What, exactly, is Scientific Machine Learning, and how can it enhance traditional simulation? What role does it play in building surrogate models like Neural Operators or Physics-Informed Neural Networks? This webinar explores the transformative potential of Scientific Machine Learning, a powerful approach that fuses the rigour of physics-based modelling with the adaptive power of data-driven algorithms. Discover how this synergy is bridging the gap between complex simulations and real-time decision-making, unlocking new potential in product development. The webinar will focus on enabling you to augment , not replace, your established simulation workflows. create highly accurate surrogate...more
Overview Modeling and simulation (M&S) are a well-established part of the engineering design process. M&S are also gaining traction in other product life cycle processes through concepts like certification-by-analysis and digital twins. These advancements and the widespread influence of M&S continue to add relevance to the question of how much to trust computational model predictions. The answer to this question can be extremely challenging to determine and strongly depends on the application. Even if there is Verification, Validation, and Uncertainty Quantification (VVUQ) evidence to build credibility in the model predictions, this information is often difficult to convey to the model end-users...more
“Digital twin” is currently a term applied in a wide variety of ways. Some differences are variations from sector to sector, but definitions within a sector can also vary significantly. Within engineering, claims are made regarding the benefits of using digital twinning for design, optimisation, process control, virtual testing, and lifetime estimation. In many of its usages, the distinction between a model and a digital twin is not made clear. "When I use a word, it means whatever I want it to mean": Humpty Dumpty in Alice’s Adventures Through The Looking Glass, Lewis Carroll. The danger of this variety and vagueness is that a poor or inconsistent definition and explanation of a digital twin...more
In this webinar the sources of error in numerical simulation and methods used for controlling them will be discussed. It is shown that when the size of the numerical errors in the quantities of interest (QoI) are not known then it is not possible to certify that a design is in compliance with the design rules. Therefore error estimation in terms of the QoI is an essential technical requirement. Error estimation is possible only when the mathematical model is properly formulated. This webinar will also highlight the differences between finite element modeling and numerical simulation. The creative aspects of formulating mathematical models and objective methods for ranking their performance are...more
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