{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T17:57:51Z","timestamp":1761155871110,"version":"3.41.2"},"reference-count":21,"publisher":"ASME International","issue":"1","content-domain":{"domain":["asmedigitalcollection.asme.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2015,3,1]]},"abstract":"<jats:p>Parametric finite element analysis (FEA) models are commonly used in iterative design processes to obtain an optimum model given a set of loads, constraints, objectives, and design parameters to vary. In some instances, it is desirable for a designer to obtain some intuition about how changes in design parameters can affect the FEA solution of interest, before simply sending the model through the optimization loop. For example, designers who wish to explore the design space and understand how each variable changes the output in a visual way, looking at the whole model and not just numbers or a response surface of a single FEA node. This could be accomplished by running the FEA on the parametric model for a set of part family members, but this can be very time consuming and only gives snapshots of the model's real behavior. This paper presents a method of visualizing the FEA solution of the parametric model as design parameters are changed in real-time by approximating the FEA solution using parametric FEA modeling, surrogate modeling methods, and visualization methods. The implementation develops a parametric FEA mode that includes mesh morphing algorithms that allow the mesh to change parametrically along with the model geometry. This allows the surrogate models assigned to each individual node to use the nodal solution of multiple finite element analyses as regression points to approximate the FEA solution. The surrogate models can then be mapped to their respective geometric locations in real-time. The results of the FEA calculations are updated in real-time as the parameters of the design model change allowing real-time visualization.<\/jats:p>","DOI":"10.1115\/1.4029217","type":"journal-article","created":{"date-parts":[[2014,11,22]],"date-time":"2014-11-22T17:30:45Z","timestamp":1416677445000},"update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":11,"title":["Real-Time Visualization of Finite Element Models Using Surrogate Modeling Methods"],"prefix":"10.1115","volume":"15","author":[{"given":"Ryan C.","family":"Heap","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602 e-mail:"}]},{"given":"Ammon I.","family":"Hepworth","sequence":"additional","affiliation":[{"name":"Research Staff Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602 e-mail:"}]},{"given":"C.","family":"Greg Jensen","sequence":"additional","affiliation":[{"name":"Professor Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602 e-mail:"}]}],"member":"33","reference":[{"issue":"2","key":"2019100601480315700_B1","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/S0045-7949(96)00354-9","article-title":"A Combined Dynamic-Static Finite Element Model for the Calculation of Dynamic Stresses at Critical Locations","volume":"65","year":"1997","journal-title":"Comput. Struct."},{"issue":"3","key":"2019100601480315700_B2","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1109\/84.788632","article-title":"Generating Efficient Dynamical Models for Microelectromechanical Systems From a Few Finite-Element Simulation Runs","volume":"8","year":"1999","journal-title":"J. Microelectromech. Syst."},{"issue":"1","key":"2019100601480315700_B3","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/S0022-460X(02)01278-6","article-title":"A New Eigensolution of Structures Via Dynamic Condensation","volume":"266","year":"2003","journal-title":"J. Sound Vib."},{"issue":"3","key":"2019100601480315700_B4","first-page":"251","article-title":"Probability-Based Least Square Support Vector Regression Metamodeling Technique for Crashworthiness Optimization Problems","volume":"7","year":"2011","journal-title":"Comput. Mech."},{"volume-title":"Computational Approaches for Aerospace Design: The Pursuit of Excellence","year":"2005","key":"2019100601480315700_B5"},{"key":"2019100601480315700_B6","doi-asserted-by":"crossref","unstructured":"Gano, S. E., Kim, H., and Ii, D. E. B., 2006, \u201cComparison of Three Surrogate Modeling Techniques: Datascape[Textregistered], Kriging, and Second Order Regression,\u201d 11th AIAA\/ISSMO Multidisciplinary Analysis and Optimization Conference, Lockheed Martin\u2014Integrated Systems and Solutions, pp. 1\u201318.","DOI":"10.2514\/6.2006-7048"},{"issue":"3","key":"2019100601480315700_B7","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1108\/03321641111110870","article-title":"Interactive Visualization of Transient 3D Electromagnetic and n-Dimensional Parameter Spaces in Virtual Reality","volume":"30","year":"2011","journal-title":"COMPEL: Int. J. Comput. Math. Electr. Electron. Eng."},{"edition":"3rd ed.","volume-title":"Finite Element Analysis: Theory and Application With ansys","year":"2008","key":"2019100601480315700_B8"},{"issue":"4","key":"2019100601480315700_B9","first-page":"370","article-title":"Review of Metamodeling Techniques in Support of Engineering Design Optimization","volume":"129","year":"2006","journal-title":"ASME J. Mech. Des."},{"key":"2019100601480315700_B10","doi-asserted-by":"crossref","unstructured":"Shepard, D., 1968, \u201cA Two-Dimensional Interpolation Function for Irregularly-Spaced Data,\u201d Proceedings of the 1968 23rd ACM National Conference, ACM, pp. 517\u2013524.","DOI":"10.1145\/800186.810616"},{"volume-title":"Mastering cadcam","year":"2005","key":"2019100601480315700_B11"},{"issue":"7","key":"2019100601480315700_B12","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1016\/j.compind.2011.05.008","article-title":"Metamodeling Development for Reliability-Based Design Optimization of Automotive Body Structure","volume":"62","year":"2011","journal-title":"Comput. Ind."},{"issue":"1","key":"2019100601480315700_B13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00158-001-0160-4","article-title":"Comparative Studies of Metamodelling Techniques Under Multiple Modelling Criteria","volume":"23","year":"2001","journal-title":"Struct. Multidiscip. Optim."},{"issue":"5\u20138","key":"2019100601480315700_B14","first-page":"229","article-title":"Isogeometric Analysis Using t-Splines","volume":"199","year":"2010","journal-title":"Comput. Methods Appl. Mech. Eng."},{"volume-title":"ansys Software Help Documentation","year":"2012","key":"2019100601480315700_B15"},{"volume-title":"isight Software Help Documentation","year":"2012","key":"2019100601480315700_B16"},{"issue":"8","key":"2019100601480315700_B17","doi-asserted-by":"crossref","first-page":"1905","DOI":"10.1029\/JB076i008p01905","article-title":"Multiquadratic Equations of Topography and Other Irregular Surfaces","volume":"76","year":"1971","journal-title":"J. Geophys. Res."},{"key":"2019100601480315700_B18","article-title":"Motivation for Using Radial Basis Functions to Solve PDEs"},{"key":"2019100601480315700_B19","doi-asserted-by":"crossref","unstructured":"Mak, M. W., and Li, C. K., 1999, \u201cElliptical Basis Function Networks and Radial Basis Function Networks for Speaker Verification: A Comparative Study,\u201d Proceedings of the International Joint Conference on Neural Networks, pp. 3034\u20133039.","DOI":"10.1109\/IJCNN.1999.836039"},{"key":"2019100601480315700_B20","unstructured":"Selin, E., 2012, \u201cApplication of Parametric Nurbs Geometry to Mode Shape Identification and the Modal Assurance Criterion,\u201d M.S. thesis, Brigham Young University, Provo, UT."},{"key":"2019100601480315700_B21","doi-asserted-by":"crossref","unstructured":"Choudhury, A., Nair, P. B., and Keane, A. J., 2002, \u201cA Data Parallel Approach for Large-Scale Gaussian Process Modeling,\u201d Proceedings of the Second SIAM International Conference on Data Mining, pp. 95\u2013111.","DOI":"10.1137\/1.9781611972726.6"}],"container-title":["Journal of Computing and Information Science in Engineering"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/asmedigitalcollection.asme.org\/computingengineering\/article-pdf\/doi\/10.1115\/1.4029217\/6100692\/jcise_015_01_011007.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/asmedigitalcollection.asme.org\/computingengineering\/article-pdf\/doi\/10.1115\/1.4029217\/6100692\/jcise_015_01_011007.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T20:35:27Z","timestamp":1747168527000},"score":1,"resource":{"primary":{"URL":"https:\/\/asmedigitalcollection.asme.org\/computingengineering\/article\/doi\/10.1115\/1.4029217\/370602\/RealTime-Visualization-of-Finite-Element-Models"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,3,1]]},"references-count":21,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2015,3,1]]}},"URL":"https:\/\/doi.org\/10.1115\/1.4029217","relation":{},"ISSN":["1530-9827","1944-7078"],"issn-type":[{"type":"print","value":"1530-9827"},{"type":"electronic","value":"1944-7078"}],"subject":[],"published":{"date-parts":[[2015,3,1]]},"article-number":"011007"}}