Continuing from my prior post, another example of the role that digital manufacturing and simulation plays comes from the Automobili Lamborghini Advanced Composite Structures Laboratory (ACSL) at the University of Washington in Seattle (USA), which blends aerospace and automotive composite development. Working with Boeing and the US Federal Aviation Administration (FAA), the ACSL improves certification of new composite materials and structures, often based on proven virtual testing principles pioneered for Lamborghini automobiles.

ACSL and Boeing collaborated on advanced analysis methods for predicting the crash performance of the all-composite monocoque of Lamborghini’s Aventador automobile. Aventador passed its crash-test certification on the first try; previous models required two or three tests. At $1 million per crash, savings were substantial, even without factoring in time and cost saved by not building additional test vehicles. See figure above.

A Complete Paradigm Shift

While such programs go beyond industry standards in employing virtual testing, Dr. R. Byron Pipes, John Bray Distinguished Professor in the College of Engineering at Purdue University (USA), believes they don’t go far enough.

Current trends in virtual testing of new composites is only an incremental improvement, Pipes believes, not the complete paradigm shift needed to unshackle composite development. “We are still struggling with empirical-based manufacturing and (physical) testing-based certification,” he said. “It costs $100 million per material to qualify composites to fly on a new airframe. Once certified, materials changes are economically impossible.”

Dr. Pipes describes composite development today as dominated by experiments and only aided by analysis. “We have the computational power to change this paradigm and replace thousands of (physical) tests with robust multi-scale simulation of manufacturing and performance,” he said. “Only then will we enable innovations in materials composition and processing without repeated costly recertification.”

Reducing Uncertainty

Today, manufacturers physically test every element before it is assembled and every part before it goes on an airplane, contributing to unsustainable development cycles and costs. “You will never totally escape the need for (physical) testing to validate models, but we must address the issue of certainty in simulation results, or rather, how to manage uncertainty,” Dr. Pipes said. “Simulation tools can guide understanding of uncertainty in design and also how it propagates.”[su_ pullquote align=”left”] Using virtual simulations, Cobham Life Support reduced destructive tests on a NASA fuel tank by 50%, saving $500,000.[/su_pullquote]

To demonstrate the potential of the approach, Dr. Pipes cites the US National Nuclear Security Administration (NNSA).

Due to the US moratorium on nuclear device testing, NNSA, a division of the US Department of Energy, cannot conduct full-scale physical performance testing. “About 15 to 20 years ago, we defined a road map of what was needed to achieve simulation-based certification,” said Dr. Mark Anderson, technical advisor to the NNSA from Los Alamos National Laboratory, a US government- supported research agency. Key elements of this road map include: transition to a validated predictive capability based on multi-scale, physics-based computer simulation and quantification of uncertainty in NNSA’ simulation tools.

Balancing Physical and Virtual

Dr. Anderson believes composites modeling can be advanced by adapting the NNSA approach. “For most industries, what would be the most appropriate is a balance between the historical testing-based approach and this simulation/uncertainty quantification based approach,” Anderson said. He notes that although significant theory has gone into composite industry models, many still use a simple mathematical description that fits empirical test data.

Uncertainty quantification (UQ) involves managing both parametric uncertainty and model-form uncertainty. “There is an investment to be made up front, both in time and money,” Dr. Anderson said. “But by building simulation capability, it is possible to reduce testing costs from $500,000 to $100,000, for example.” He notes that US-based automotive maker General Motors has used UQ in crash-test simulations and that NASA is incorporating it into the space agency’s simulation tools to aid with tests it cannot perform physically, such as reactions in a space environment or full-structure tests that are beyond the scope of its current budget.

The result is the potential for “robust design” – high performance without the overdesign needed to compensate for uncertainty. Robust design factors uncertainty directly into the model, producing designs that are less sensitive to uncertainty, with less bet-hedging overdesign.

This excerpt was originally published in Dassault Systèmes’ Compass magazine, and was used with permission. Read the full article here.