At present, a very substantial unrealized potential exists in numerical simulation. Simulation technology has matured to the point where management can realistically expect the reliability of predictions based on numerical simulations to match the reliability of observations in physical experimentation. This will require management to upgrade simulation practices through exercising simulation governance.
Digital transformation is a multifaceted concept with plenty of room for interpretation. Its common theme emphasizes the proactive adoption of digital technologies to reshape business practices with the goal of gaining a competitive edge. The scope, timeline, and resource allocation of digital transformation projects depend on the specific goals and objectives. Here, we address digital transformation in the engineering sciences, focusing on numerical simulation.
The idea of a digital twin originated at NASA in the 1960s as a “living model” of the Apollo program. When Apollo 13 experienced an oxygen tank explosion, NASA utilized multiple simulators and extended a physical model of the spacecraft to include digital simulations, creating a digital twin. This twin was used to analyze the events leading up to the accident and investigate ideas for a solution. The term “digital twin” was coined by NASA engineer John Vickers much later. While the term is commonly associated with modeling physical objects, it is also employed to represent organizational processes. Here, we consider digital twins of physical entities only.
Models, developed under the discipline of VVUQ, can be relied on to make correct predictions within their domains of calibration. However, model development projects lacking the discipline of VVUQ tend to produce wrong models.
Certification by Analysis (CbA) uses validated computer simulations to demonstrate compliance with regulations, replacing some traditional physical tests. CbA allows for exploring a wide range of design scenarios, accelerates innovation, lowers expenses, and upholds rigorous safety standards. The key to CbA is reliability. This means that the data generated by numerical simulation should be as trustworthy as if they were generated by carefully conducted physical experiments. To achieve that goal, it is necessary to control two fundamentally different types of error; the model form error and the numerical approximation error, and use the models within their domains of calibration.
In engineering sciences, we classify mathematical models as ‘proper’ or ‘improper’ rather than ‘scientific’ or ‘pseudoscientific’. A model is said to be proper if it is consistent with the relevant mathematical theorems that guarantee the existence and, when applicable, the uniqueness of the exact solution. Otherwise, the model is improper. At present, the large majority of models used in engineering practice are improper. Following are examples of frequently occurring types of error, with brief explanations.
Mathematical models have become indispensable sources of information on which technical and business decisions are based. It is therefore vitally important for decision-makers to know whether relying on the predictions of mathematical models is justified. When properly used, numerical simulation can be a major corporate asset. However, it can become a major corporate liability if the reliability of predictions is not guaranteed. Learn more in our latest blog post.
In this final post of our “S.A.F.E.R. Numerical Simulation for Structural Analysis in the Aerospace Industry” series, we will profile the stress analysis software product StressCheck, what makes it different from other FEA software and the applications for which it is used in A&D engineering.[…]
In mid-May 2023, ESRD’s Co-Founder and Chairman Dr. Barna Szabó delivered a keynote presentation at the ASME VVUQ 2023 Symposium in Baltimore, Maryland, USA. Dr. Szabó’s presentation, entitled “Simulation Governance: An Idea Whose Time Has Come”, will focus on the goals and means of Simulation Governance with reference to mechanical/aerospace engineering practice. We are pleased to announce that the recording of the keynote presentation is now available.
Learn how Simulation Governance was introduced, how it came to be one of the Big Issues of NAFEMS, and how ESRD’s leadership and other world-renowned simulation experts are using this powerful function for enhancing reliability of modern numerical simulation […]
The software provides a highly reliable and user-friendly production stress analysis tool that will replace the Finite Element Method (FEM) tools and failure criteria the experts currently employ for analyzing bonded joints. The software includes an FEM-based handbook format, which allows non-experts to utilize models prepared by specialists. The handbook problems include built-in failure criteria, geometric and material nonlinearities, and the modern FEM technology provides better error control and the treatment of very large aspect ratios.”
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