The breakthroughs developed by the researchers and their collaborators over the last decade builds upon the realization that the data provides, for any object, a detailed field map that can be represented as a weighted sum of various distances from a given point.
"Unlike existing analysis techniques that can be error prone and require models that take far longer to create, Scan and Solve compresses the entire analysis into a series of automated, efficient steps," says Michael Freytag, whose doctoral thesis details the Scan and Solve approach.
In their analysis of Michelangelo's David, the researchers were able to predict the stresses that the statue endures on a daily basis by using the Scan and Solve software with original shape data.
The analysis matched well with the statue's known crack damage, indicating that the method could help archivists by serving as a predictor for what areas of an ancient artifact may need to be bolstered to prevent damage, even if the statue has not yet shown fatigue.
The same approach could work for a bone or car part or any other heavily used component, potentially aiding engineers as they develop protections for those objects.
However, the research breakthrough is not only the predictive capabilities, said NSF Program Director Judy Vance who supported the research effort.
"For engineers designing new structures and components, the Scan and Solve claim to fame is the ability to go directly from scan data to analysis model without any intermediate steps that produce accumulating errors," said Vance. "This approach produces improved results that can be computed in less time providing a smooth link between the gathering of data and the analysis of data."
Now that digitized data are becoming commonplace, the researchers see Scan and Solve as a new way to bring the power of software-driven engineering tools such as computer-aided design to art, architecture, medicine an
|Contact: Josh Chamot|
National Science Foundation