Pub Date : 2023-01-01DOI: 10.7712/120223.10377.20026
Atefeh Soleymani, Hashem Jahangir, Denise-Penelope N. Kontoni, Mina Naseri Nasab
{"title":"ARTIFICIAL INTELLIGENCE-BASED UNCERTAINTY QUALIFICATION OF THE MECHANICAL PROPERTIES OF SUSTAINABLE CONCRETE SPECIMENS","authors":"Atefeh Soleymani, Hashem Jahangir, Denise-Penelope N. Kontoni, Mina Naseri Nasab","doi":"10.7712/120223.10377.20026","DOIUrl":"https://doi.org/10.7712/120223.10377.20026","url":null,"abstract":"","PeriodicalId":486785,"journal":{"name":"4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135213495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.7712/120223.10372.19964
Oumaima Belcadi, Nicolas Desilles, Christophe Gautrelet, Fatima Ezzahra Arrakhiz, Leila Khalij, Emmanuel Pagnacco, Hassan El Minor
{"title":"MECHANICAL CHARACTERIZATION OF POLYPROPYLENE COMPOSITES REINFORCED WITH ARGAN NUT SHELL PARTICLES","authors":"Oumaima Belcadi, Nicolas Desilles, Christophe Gautrelet, Fatima Ezzahra Arrakhiz, Leila Khalij, Emmanuel Pagnacco, Hassan El Minor","doi":"10.7712/120223.10372.19964","DOIUrl":"https://doi.org/10.7712/120223.10372.19964","url":null,"abstract":"","PeriodicalId":486785,"journal":{"name":"4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134884170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.7712/120223.10329.19599
Romain Espoeys, Loïc Brevault, Mathieu Balesdent, Sophie Ricci, Paul Mycek
{"title":"MULTI-FIDELITY SEQUENTIAL BAYESIAN OPTIMIZATION AND RELIABILITY ASSESSMENT METHOD FOR THE DESIGN OF COMPLEX SYSTEMS","authors":"Romain Espoeys, Loïc Brevault, Mathieu Balesdent, Sophie Ricci, Paul Mycek","doi":"10.7712/120223.10329.19599","DOIUrl":"https://doi.org/10.7712/120223.10329.19599","url":null,"abstract":"","PeriodicalId":486785,"journal":{"name":"4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134884466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the recent rise of neural operators, scientific machine learning offers new solutions to quantify uncertainties associated with high-fidelity numerical simulations. Traditional neural networks, such as Convolutional Neural Networks (CNN) or Physics-Informed Neural Networks (PINN), are restricted to the prediction of solutions in a predefined configuration. With neural operators, one can learn the general solution of Partial Differential Equations, such as the elastic wave equation, with varying parameters. There have been very few applications of neural operators in seismology. All of them were limited to two-dimensional settings, although the importance of three-dimensional (3D) effects is well known. In this work, we apply the Fourier Neural Operator (FNO) to predict ground motion time series from a 3D geological description. We used a high-fidelity simulation code, SEM3D, to build an extensive database of ground motions generated by 30,000 different geologies. With this database, we show that the FNO can produce accurate ground motion even when the underlying geology exhibits large heterogeneities. Intensity measures at moderate and large periods are especially well reproduced. We present the first seismological application of Fourier Neural Operators in 3D. Thanks to the generalizability of our database, we believe that our model can be used to assess the influence of geological features such as sedimentary basins on ground motion, which is paramount to evaluating site effects.
{"title":"FOURIER NEURAL OPERATOR SURROGATE MODEL TO PREDICT 3D SEISMIC WAVES PROPAGATION","authors":"Fanny Lehmann, Filippo Gatti, Michaël Bertin, Didier Clouteau","doi":"10.7712/120223.10339.20362","DOIUrl":"https://doi.org/10.7712/120223.10339.20362","url":null,"abstract":"With the recent rise of neural operators, scientific machine learning offers new solutions to quantify uncertainties associated with high-fidelity numerical simulations. Traditional neural networks, such as Convolutional Neural Networks (CNN) or Physics-Informed Neural Networks (PINN), are restricted to the prediction of solutions in a predefined configuration. With neural operators, one can learn the general solution of Partial Differential Equations, such as the elastic wave equation, with varying parameters. There have been very few applications of neural operators in seismology. All of them were limited to two-dimensional settings, although the importance of three-dimensional (3D) effects is well known. In this work, we apply the Fourier Neural Operator (FNO) to predict ground motion time series from a 3D geological description. We used a high-fidelity simulation code, SEM3D, to build an extensive database of ground motions generated by 30,000 different geologies. With this database, we show that the FNO can produce accurate ground motion even when the underlying geology exhibits large heterogeneities. Intensity measures at moderate and large periods are especially well reproduced. We present the first seismological application of Fourier Neural Operators in 3D. Thanks to the generalizability of our database, we believe that our model can be used to assess the influence of geological features such as sedimentary basins on ground motion, which is paramount to evaluating site effects.","PeriodicalId":486785,"journal":{"name":"4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135213475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.7712/120223.10336.19750
Chao Liu, Xinlei Zhou, Xizhao Wang
{"title":"PREDICTION UNCERTAINTY FLATTENING FOR PERFORMANCE IMPROVEMENT OF DEEP LEARNING","authors":"Chao Liu, Xinlei Zhou, Xizhao Wang","doi":"10.7712/120223.10336.19750","DOIUrl":"https://doi.org/10.7712/120223.10336.19750","url":null,"abstract":"","PeriodicalId":486785,"journal":{"name":"4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135213479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.7712/120223.10324.19770
Bibhas Paul, A. S. Nisha, C. S. Manohar
{"title":"BAYESIAN UPDATING OF GLOBAL RESPONSE SENSITIVITY INDICES IN AN INSTRUMENTED STRUCTURE","authors":"Bibhas Paul, A. S. Nisha, C. S. Manohar","doi":"10.7712/120223.10324.19770","DOIUrl":"https://doi.org/10.7712/120223.10324.19770","url":null,"abstract":"","PeriodicalId":486785,"journal":{"name":"4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135213488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"ABSTENTION IN REGRESSION","authors":"Cristina Garcia-Cardona, Jamaludin Mohd-Yusof, Tanmoy Bhattacharya","doi":"10.7712/120223.10366.19843","DOIUrl":"https://doi.org/10.7712/120223.10366.19843","url":null,"abstract":"","PeriodicalId":486785,"journal":{"name":"4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135213520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.7712/120223.10357.19880
Augustin Persoons, Conradus Van Mierlo, Pierre Beaurepaire, David Moens
{"title":"ROBUST DESIGN OPTIMIZATION UNDER EPISTEMIC UNCERTAINTY USING ADAPTIVE KRIGING AND EXTREME VALUE DISTRIBUTIONS","authors":"Augustin Persoons, Conradus Van Mierlo, Pierre Beaurepaire, David Moens","doi":"10.7712/120223.10357.19880","DOIUrl":"https://doi.org/10.7712/120223.10357.19880","url":null,"abstract":"","PeriodicalId":486785,"journal":{"name":"4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135213528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.7712/120223.10325.19795
Daniel Andrés Arcones, Martin Weiser, Faidon-Stelios Koutsourelakis, Jörg F. Unger
{"title":"EVALUATION OF MODEL BIAS IDENTIFICATION APPROACHES BASED ON BAYESIAN INFERENCE AND APPLICATIONS TO DIGITAL TWINS","authors":"Daniel Andrés Arcones, Martin Weiser, Faidon-Stelios Koutsourelakis, Jörg F. Unger","doi":"10.7712/120223.10325.19795","DOIUrl":"https://doi.org/10.7712/120223.10325.19795","url":null,"abstract":"","PeriodicalId":486785,"journal":{"name":"4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135213453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.7712/120223.10335.19568
Matieyendou Lamboni
{"title":"NEW DEPENDENT MEASURES OF ASSOCIATION BETWEEN DYNAMIC MODEL OUTPUTS AND INPUTS USING KERNELS","authors":"Matieyendou Lamboni","doi":"10.7712/120223.10335.19568","DOIUrl":"https://doi.org/10.7712/120223.10335.19568","url":null,"abstract":"","PeriodicalId":486785,"journal":{"name":"4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135213463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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