New computer simulation method can equip engineers, doctors with more, better information
Sandia National Laboratories researchers have created a method of processing 3D images for computer simulations that could have beneficial implications for several industries, including health care, manufacturing and electric vehicles.
At Sandia, the method could prove vital in certifying the credibility of high-performance computer simulations used in determining the effectiveness of various materials for weapons programs and other efforts, said Scott A. Roberts, Sandia’s principal investigator on the project. Sandia can also use the new 3D-imaging workflow to test and optimize batteries used for large-scale energy storage and in vehicles.
“It’s really consistent with Sandia’s mission to do credible, high-consequence computer simulation,” he said. “We don’t want to just give you an answer and say, ‘trust us.’ We’re going to say, ‘here’s our answer and here’s how confident we are in that answer,’ so that you can make informed decisions.”
The researchers shared the new workflow, dubbed by the team as EQUIPS for Efficient Quantification of Uncertainty in Image-based Physics Simulation, in a paper published today in the journal Nature Communications.
“This workflow leads to more reliable results by exploring the effect that ambiguous object boundaries in a scanned image have in simulations,” said Michael Krygier, a Sandia postdoctoral appointee and lead author on the paper. “Instead of using one interpretation of that boundary, we’re suggesting you need to perform simulations using different interpretations of the boundary to reach a more informed decision.”
EQUIPS can use machine learning to quantify the uncertainty in how an image is drawn for 3D computer simulations. By giving a range of uncertainty, the workflow allows decision-makers to consider best- and worst-case outcomes, Roberts said.
Read about how the workflow EQUIPS decision-makers with better information in the complete news release.