{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T01:50:26Z","timestamp":1783561826216,"version":"3.55.0"},"reference-count":26,"publisher":"ASME International","issue":"6","license":[{"start":{"date-parts":[[2020,7,9]],"date-time":"2020-07-09T00:00:00Z","timestamp":1594252800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.asme.org\/publications-submissions\/publishing-information\/legal-policies"}],"content-domain":{"domain":["asmedigitalcollection.asme.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Design space exploration (DSE) is the process whereby a designer seeks to understand some results across a set of design variations. Structural DSE of turbomachinery compressor blades is often challenging because the large number of design variables make it difficult to learn the effect that each variable has upon the stress contours. Principal component analysis (PCA) of the stress contours is used as a way to understand how the stress contours change over the design space. Two methods are introduced to address the challenge of understanding how the stress changes over a large number of variables. First, a two-point correlation is applied to relate the design variables to the scores of each principal component. Second, a coupling of the stress and coordinate location of each node in PCA is developed which also indicates how the stress variations relate to geometric variations. These provide insight to how design variables influence the stress. It is shown how these methods use PCA as DSE tools to better explore the structural design space of compressor blades. Better DSE can improve compressor blades and the computational cost needed for their design.<\/jats:p>","DOI":"10.1115\/1.4047428","type":"journal-article","created":{"date-parts":[[2020,7,9]],"date-time":"2020-07-09T11:30:36Z","timestamp":1594294236000},"update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":12,"title":["Structural Design Space Exploration Using Principal Component Analysis"],"prefix":"10.1115","volume":"20","author":[{"given":"Spencer","family":"Bunnell","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, Brigham Young University, Provo, UT 8460"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steven","family":"Gorrell","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, Brigham Young University, Provo, UT 8460"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Salmon","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, Brigham Young University, Provo, UT 8460"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Thelin","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, Brigham Young University, Provo, UT 8460"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Ruoti","sequence":"first","affiliation":[{"name":"Pratt & Whitney, East Hartford, CT 06118"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"33","published-online":{"date-parts":[[2020,7,9]]},"reference":[{"key":"2020070907300839100_CIT0001","doi-asserted-by":"crossref","DOI":"10.1115\/GT2018-77188","article-title":"Rapid Visualization of Compressor Blade Finite Element Models Using Surrogate Modeling","author":"Bunnell","year":"2018"},{"issue":"1","key":"2020070907300839100_CIT0002","doi-asserted-by":"crossref","first-page":"011007","DOI":"10.1115\/1.4029217","article-title":"Real-Time Visualization of Finite Element Models Using Surrogate Modeling Methods","volume":"15","author":"Heap","year":"2015","journal-title":"ASME J. 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