Why model V&V?

The scientific method of formulating a hypothesis, developing an experiment and collecting information, and reaching a conclusion either in favor of the hypothesis or that contradicts it, has traditionally been based on physical experiments and measurements. Compared to the 4,000+ years of scientific history, science-based predictive Modeling and Simulation (M&S) is recent. Only since the late 1980’s, or for the past twenty years or so, have scientists started to be confident in their ability to understand and model moderately complex phenomena or applications.

The consequence is that physical experiments that have traditionally supported the decision-making process in physics and engineering are progressively being replaced by numerical simulations. The availability of increasingly faster, cheaper, and massively parallel computing resources are feeding this trend, together with the development of more powerful computing languages and user-friendly visualization tools. It also goes hand-in-hand with the economic imperative of reducing time-to-market cycles and research and development costs, a promise that many industries claim the increased reliance on M&S can fulfill.

One dramatic example where M&S replaced testing is the certification by Boeing Aerospace of their 777 aircraft, which was to a great extent based on simulations in the late 1990’s even though the U.S. Federal Aviation Administration still required full-scale testing for its own accreditation. Accrediting the aircraft involved performing large-scale computational fluid dynamics simulations of its flutter characteristics. Another example is the Nuclear Test Ban Treaty (NTBS) enforced in the United States since 1992, which makes nuclear testing impossible. Mathematical models, computer codes, and numerical simulations have been developed at national laboratories of the U.S. Department of Energy, such as LANL, to study the performance, reliability, and provide the annual certification of these very complex systems.