Articles citing this article

The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).

Cited article:

Uncertainty Quantification on Foam Modeling: The Interplay of Relative Permeability and Implicit-texture Foam Parameters

G. B. de Miranda, R. W. dos Santos, G. Chapiro and B. M. Rocha
Transport in Porous Media 152 (1) (2025)
https://doi.org/10.1007/s11242-024-02137-1

Ratcheting fluid pumps: Using generalized polynomial chaos expansions to assess pumping performance and sensitivity

Zain Moin, Laura A. Miller and Nicholas A. Battista
Physics of Fluids 36 (12) (2024)
https://doi.org/10.1063/5.0237403

Derivative-Enhanced Rational Polynomial Chaos for Uncertainty Quantification

Karanvir S. Sidhu and Roni Khazaka
IEEE Transactions on Circuits and Systems I: Regular Papers 71 (4) 1832 (2024)
https://doi.org/10.1109/TCSI.2024.3350509

Polynomial-chaos-based conditional statistics for probabilistic learning with heterogeneous data applied to atomic collisions of Helium on graphite substrate

Christian Soize and Quy-Dong To
Journal of Computational Physics 496 112582 (2024)
https://doi.org/10.1016/j.jcp.2023.112582

Uncertainty quantification analysis of bifurcations of the Allen–Cahn equation with random coefficients

Christian Kuehn, Chiara Piazzola and Elisabeth Ullmann
Physica D: Nonlinear Phenomena 470 134390 (2024)
https://doi.org/10.1016/j.physd.2024.134390

Space‐time stochastic Galerkin boundary elements for acoustic scattering problems

Heiko Gimperlein, Fabian Meyer and Ceyhun Özdemir
International Journal for Numerical Methods in Engineering 125 (15) (2024)
https://doi.org/10.1002/nme.7497

An approximation theory framework for measure-transport sampling algorithms

Ricardo Baptista, Bamdad Hosseini, Nikola Kovachki, Youssef Marzouk and Amir Sagiv
Mathematics of Computation (2024)
https://doi.org/10.1090/mcom/4013

Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees)

Paul Novello, Gaël Poëtte, David Lugato, Simon Peluchon and Pietro Marco Congedo
Journal of Computational Physics 498 112700 (2024)
https://doi.org/10.1016/j.jcp.2023.112700

Probabilistic-learning-based stochastic surrogate model from small incomplete datasets for nonlinear dynamical systems

Christian Soize and Roger Ghanem
Computer Methods in Applied Mechanics and Engineering 418 116498 (2024)
https://doi.org/10.1016/j.cma.2023.116498

Algorithm 1040: The Sparse Grids Matlab Kit - a Matlab implementation of sparse grids for high-dimensional function approximation and uncertainty quantification

Chiara Piazzola and Lorenzo Tamellini
ACM Transactions on Mathematical Software 50 (1) 1 (2024)
https://doi.org/10.1145/3630023

Energy stable and structure-preserving schemes for the stochastic Galerkin shallow water equations

Dihan Dai, Yekaterina Epshteyn and Akil Narayan
ESAIM: Mathematical Modelling and Numerical Analysis 58 (2) 723 (2024)
https://doi.org/10.1051/m2an/2024012

Surrogate recycling for structures with spatially uncertain stiffness

Karl-Alexander Hoppe, Kevin Josef Li, Bettina Chocholaty, Johannes D. Schmid, Simon Schmid, Kian Sepahvand and Steffen Marburg
Journal of Sound and Vibration 570 117997 (2024)
https://doi.org/10.1016/j.jsv.2023.117997

Exact and Approximate Moment Derivation for Probabilistic Loops With Non-Polynomial Assignments

Andrey Kofnov, Marcel Moosbrugger, Miroslav Stankovič, Ezio Bartocci and Efstathia Bura
ACM Transactions on Modeling and Computer Simulation 34 (3) 1 (2024)
https://doi.org/10.1145/3641545

Probabilistic Prequalification Scheme of a Distribution System Operator for Supporting Market Participation of Multiple Distributed Energy Resource Aggregators

Chang Min Jeong, Hee Seung Moon and Seung Wan Kim
IEEE Transactions on Energy Markets, Policy and Regulation 2 (4) 465 (2024)
https://doi.org/10.1109/TEMPR.2024.3386722

Emulator-based Bayesian inference on non-proportional scintillation models by compton-edge probing

David Breitenmoser, Francesco Cerutti, Gernot Butterweck, Malgorzata Magdalena Kasprzak and Sabine Mayer
Nature Communications 14 (1) (2023)
https://doi.org/10.1038/s41467-023-42574-y

A fully Bayesian sparse polynomial chaos expansion approach with joint priors on the coefficients and global selection of terms

Paul-Christian Bürkner, Ilja Kröker, Sergey Oladyshkin and Wolfgang Nowak
Journal of Computational Physics 488 112210 (2023)
https://doi.org/10.1016/j.jcp.2023.112210

The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory

Sergey Oladyshkin, Timothy Praditia, Ilja Kroeker, Farid Mohammadi, Wolfgang Nowak and Sebastian Otte
Neural Networks 166 85 (2023)
https://doi.org/10.1016/j.neunet.2023.06.036

Deriving task specific performance from the information processing capacity of a reservoir computer

Tobias Hülser, Felix Köster, Kathy Lüdge and Lina Jaurigue
Nanophotonics 12 (5) 937 (2023)
https://doi.org/10.1515/nanoph-2022-0415

Bayesian calibration with summary statistics for the prediction of xenon diffusion in UO2 nuclear fuel

Pieterjan Robbe, David Andersson, Luc Bonnet, Tiernan A. Casey, Michael W.D. Cooper, Christopher Matthews, Khachik Sargsyan and Habib N. Najm
Computational Materials Science 225 112184 (2023)
https://doi.org/10.1016/j.commatsci.2023.112184

Gaussian active learning on multi-resolution arbitrary polynomial chaos emulator: concept for bias correction, assessment of surrogate reliability and its application to the carbon dioxide benchmark

Rebecca Kohlhaas, Ilja Kröker, Sergey Oladyshkin and Wolfgang Nowak
Computational Geosciences 27 (3) 369 (2023)
https://doi.org/10.1007/s10596-023-10199-1

Multigroup-like MC resolution of generalised Polynomial Chaos reduced models of the uncertain linear Boltzmann equation (+discussion on hybrid intrusive/non-intrusive uncertainty propagation)

Gaël Poëtte
Journal of Computational Physics 474 111825 (2023)
https://doi.org/10.1016/j.jcp.2022.111825

Convergence of a stochastic collocation finite volume method for the compressible Navier–Stokes system

Eduard Feireisl and Mária Lukáčová-Medviďová
The Annals of Applied Probability 33 (6A) (2023)
https://doi.org/10.1214/23-AAP1937

Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems

Lianghao Cao, Thomas O'Leary-Roseberry, Prashant K. Jha, J. Tinsley Oden and Omar Ghattas
Journal of Computational Physics 486 112104 (2023)
https://doi.org/10.1016/j.jcp.2023.112104

Structure damage identification in dams using sparse polynomial chaos expansion combined with hybrid K-means clustering optimizer and genetic algorithm

Li YiFei, Hoang-Le Minh, S. Khatir, Thanh Sang-To, Thanh Cuong-Le, Cao MaoSen and Magd Abdel Wahab
Engineering Structures 283 115891 (2023)
https://doi.org/10.1016/j.engstruct.2023.115891

Bayesian inference with correction of model bias for Thermo-Hydro-Mechanical models of large concrete structures

D. Rossat, J. Baroth, M. Briffaut, F. Dufour, A. Monteil, B. Masson and S. Michel-Ponnelle
Engineering Structures 278 115433 (2023)
https://doi.org/10.1016/j.engstruct.2022.115433

Empirical Assessment of Non-Intrusive Polynomial Chaos Expansions for High-Dimensional Stochastic CFD Problems

Nikhil Iyengar, Dushhyanth Rajaram and Dimitri Mavris
Aerospace 10 (12) 1017 (2023)
https://doi.org/10.3390/aerospace10121017

Surface damage evolution of artillery barrel under high-temperature erosion and high-speed impact

Shuli Li, Liqun Wang and Guolai Yang
Case Studies in Thermal Engineering 42 102762 (2023)
https://doi.org/10.1016/j.csite.2023.102762

Global sensitivity analysis using multi-resolution polynomial chaos expansion for coupled Stokes–Darcy flow problems

Ilja Kröker, Sergey Oladyshkin and Iryna Rybak
Computational Geosciences 27 (5) 805 (2023)
https://doi.org/10.1007/s10596-023-10236-z

Multi-parameter identification of concrete dam using polynomial chaos expansion and slime mould algorithm

Li YiFei, Cao MaoSen, H.Tran-Ngoc, Samir Khatir and Magd Abdel Wahab
Computers & Structures 281 107018 (2023)
https://doi.org/10.1016/j.compstruc.2023.107018

Polynomial chaos expansion surrogate modeling of passive cardiac mechanics using the Holzapfel–Ogden constitutive model

J.O. Campos, R.M. Guedes, Y.B. Werneck, L.P.S. Barra, R.W. dos Santos and B.M. Rocha
Journal of Computational Science 71 102039 (2023)
https://doi.org/10.1016/j.jocs.2023.102039

A spectral surrogate model for stochastic simulators computed from trajectory samples

Nora Lüthen, Stefano Marelli and Bruno Sudret
Computer Methods in Applied Mechanics and Engineering 406 115875 (2023)
https://doi.org/10.1016/j.cma.2022.115875

Bayesian updating for predictions of delayed strains of large concrete structures: influence of prior distribution

D. Rossat, J. Baroth, M. Briffaut, F. Dufour, A. Monteil, B. Masson and S. Michel-Ponnelle
European Journal of Environmental and Civil Engineering 27 (4) 1763 (2023)
https://doi.org/10.1080/19648189.2022.2095441

Global sensitivity analysis of a coupled multiphysics model to predict surface evolution in fusion plasma–surface interactions

Pieterjan Robbe, Sophie Blondel, Tiernan A. Casey, Ane Lasa, Khachik Sargsyan, Brian D. Wirth and Habib N. Najm
Computational Materials Science 226 112229 (2023)
https://doi.org/10.1016/j.commatsci.2023.112229

An Adaptive Sampling and Domain Learning Strategy for Multivariate Function Approximation on Unknown Domains

Ben Adcock, Juan M. Cardenas and Nick Dexter
SIAM Journal on Scientific Computing 45 (1) A200 (2023)
https://doi.org/10.1137/22M1472693

Behavioral theory for stochastic systems? A data-driven journey from Willems to Wiener and back again

Timm Faulwasser, Ruchuan Ou, Guanru Pan, Philipp Schmitz and Karl Worthmann
Annual Reviews in Control 55 92 (2023)
https://doi.org/10.1016/j.arcontrol.2023.03.005

Finite-Horizon Robustness Analysis of an Automatic Landing System Under Probabilistic Uncertainty

Luca L. Evangelisti and Harald Pfifer
Journal of Guidance, Control, and Dynamics 1 (2023)
https://doi.org/10.2514/1.G007518

Metamodel-assisted hybrid optimization strategy for model updating using vibration response data

Li YiFei, Cao MaoSen, Tran N. Hoa, S. Khatir, Hoang-Le Minh, Thanh SangTo, Thanh Cuong-Le and Magd Abdel Wahab
Advances in Engineering Software 185 103515 (2023)
https://doi.org/10.1016/j.advengsoft.2023.103515

Global Sensitivity Analysis and Uncertainty Quantification for Background Solar Wind Using the Alfvén Wave Solar Atmosphere Model

Aniket Jivani, Nishtha Sachdeva, Zhenguang Huang, Yang Chen, Bart van der Holst, Ward Manchester, Daniel Iong, Hongfan Chen, Shasha Zou, Xun Huan and Gabor Toth
Space Weather 21 (1) (2023)
https://doi.org/10.1029/2022SW003262

A polynomial chaos efficient global optimization approach for Bayesian optimal experimental design

André Gustavo Carlon, Cibelle Dias de Carvalho Dantas Maia, Rafael Holdorf Lopez, André Jacomel Torii and Leandro Fleck Fadel Miguel
Probabilistic Engineering Mechanics 72 103454 (2023)
https://doi.org/10.1016/j.probengmech.2023.103454

Approximating the first passage time density from data using generalized Laguerre polynomials

Elvira Di Nardo, Giuseppe D’Onofrio and Tommaso Martini
Communications in Nonlinear Science and Numerical Simulation 118 106991 (2023)
https://doi.org/10.1016/j.cnsns.2022.106991

Arbitrary multi-resolution multi-wavelet-based polynomial chaos expansion for data-driven uncertainty quantification

Ilja Kröker and Sergey Oladyshkin
Reliability Engineering & System Safety 222 108376 (2022)
https://doi.org/10.1016/j.ress.2022.108376

Learning "Best" Kernels from Data in Gaussian Process Regression. With Application to Aerodynamics

Jean-Luc Akian, Luc Bonnet, HOUMAN OWHADI and Eric Savin
SSRN Electronic Journal (2022)
https://doi.org/10.2139/ssrn.4158385

A Polynomial-Chaos-Based Multifidelity Approach to the Efficient Uncertainty Quantification of Online Simulations of Automotive Propulsion Systems

Hang Yang, Alex Gorodetsky, Yuji Fujii and K. W. Wang
Journal of Computational and Nonlinear Dynamics 17 (5) (2022)
https://doi.org/10.1115/1.4053559

Surrogate modeling for efficiently, accurately and conservatively estimating measures of risk

John D. Jakeman, Drew P. Kouri and J. Gabriel Huerta
Reliability Engineering & System Safety 221 108280 (2022)
https://doi.org/10.1016/j.ress.2021.108280

A Comparative Study of Polynomial-Type Chaos Expansions for Indicator Functions

Florian Bourgey, Emmanuel Gobet and Clément Rey
SIAM/ASA Journal on Uncertainty Quantification 10 (4) 1350 (2022)
https://doi.org/10.1137/21M1413146

Uncertainty Quantification Framework for Predicting Material Response with Large Number of Parameters: Application to Creep Prediction in Ferritic-Martensitic Steels Using Combined Crystal Plasticity and Grain Boundary Models

Amirfarzad Behnam, Timothy J. Truster, Ramakrishna Tipireddy, Mark C. Messner and Varun Gupta
Integrating Materials and Manufacturing Innovation 11 (4) 516 (2022)
https://doi.org/10.1007/s40192-022-00277-0

Stochastic Galerkin Methods for Linear Stability Analysis of Systems with Parametric Uncertainty

Bedřich Sousedík and Kookjin Lee
SIAM/ASA Journal on Uncertainty Quantification 10 (3) 1101 (2022)
https://doi.org/10.1137/21M1415595

Learning “best” kernels from data in Gaussian process regression. With application to aerodynamics

J.-L. Akian, L. Bonnet, H. Owhadi and É. Savin
Journal of Computational Physics 470 111595 (2022)
https://doi.org/10.1016/j.jcp.2022.111595

Multigroup-Like Mc Resolution of Generalised Polynomial Chaos Reduced Models of the Uncertain Linear Boltzmann Equation

gael poette
SSRN Electronic Journal (2022)
https://doi.org/10.2139/ssrn.4051364

Uncertainty quantification for ecological models with random parameters

Jody R. Reimer, Frederick R. Adler, Kenneth M. Golden and Akil Narayan
Ecology Letters 25 (10) 2232 (2022)
https://doi.org/10.1111/ele.14095

A polymorphic uncertainty model for the curing process of transversely fiber-reinforced plastics

Eduard Penner, Ismail Caylak and Rolf Mahnken
Mathematics and Mechanics of Complex Systems 10 (1) 21 (2022)
https://doi.org/10.2140/memocs.2022.10.21

Bi-fidelity reduced polynomial chaos expansion for uncertainty quantification

Felix Newberry, Jerrad Hampton, Kenneth Jansen and Alireza Doostan
Computational Mechanics 69 (2) 405 (2022)
https://doi.org/10.1007/s00466-021-02096-0

A Homotopy Bayesian Approach for Inverse Problems

Xiao-Mei Yang, Zhi-Liang Deng and Harendra Singh
Mathematical Problems in Engineering 2022 1 (2022)
https://doi.org/10.1155/2022/9680613

Surrogate assisted active subspace and active subspace assisted surrogate—A new paradigm for high dimensional structural reliability analysis

Navaneeth N. and Souvik Chakraborty
Computer Methods in Applied Mechanics and Engineering 389 114374 (2022)
https://doi.org/10.1016/j.cma.2021.114374

Bayesian inversion using adaptive Polynomial Chaos Kriging within Subset Simulation

D. Rossat, J. Baroth, M. Briffaut and F. Dufour
Journal of Computational Physics 455 110986 (2022)
https://doi.org/10.1016/j.jcp.2022.110986

A General Framework of Rotational Sparse Approximation in Uncertainty Quantification

Mengqi Hu, Yifei Lou and Xiu Yang
SIAM/ASA Journal on Uncertainty Quantification 10 (4) 1410 (2022)
https://doi.org/10.1137/21M1391602

Uncertainty consideration in CFD-models via response surface modeling: Application on realistic dense and light gas dispersion simulations

Ronald Zinke, Kevin Wothe, Dmitry Dugarev, Oliver Götze, Florian Köhler, Sebastian Schalau and Ulrich Krause
Journal of Loss Prevention in the Process Industries 75 104710 (2022)
https://doi.org/10.1016/j.jlp.2021.104710

Variational inference with NoFAS: Normalizing flow with adaptive surrogate for computationally expensive models

Yu Wang, Fang Liu and Daniele E. Schiavazzi
Journal of Computational Physics 467 111454 (2022)
https://doi.org/10.1016/j.jcp.2022.111454

Nonlinear Vibrations of Simply Supported Cylindrical Panels with Uncertain Parameters: An Intrusive Application of the Generalized Polynomial Chaos Expansion

Anna Elizabete F. Palla and Frederico M. A. Silva
Journal of Vibration Engineering & Technologies 10 (8) 2917 (2022)
https://doi.org/10.1007/s42417-022-00527-7

Hyperbolicity-preserving and well-balanced stochastic Galerkin method for two-dimensional shallow water equations

Dihan Dai, Yekaterina Epshteyn and Akil Narayan
Journal of Computational Physics 452 110901 (2022)
https://doi.org/10.1016/j.jcp.2021.110901

Numerical Analysis of the Monte-Carlo Noise for the Resolution of the Deterministic and Uncertain Linear Boltzmann Equation (Comparison of Non-Intrusive gPC and MC-gPC)

Gaël Poëtte
Journal of Computational and Theoretical Transport 51 (1-3) 1 (2022)
https://doi.org/10.1080/23324309.2022.2063900

Analysis of the Equilibrium Phase in Immune-Controlled Tumors Provides Hints for Designing Better Strategies for Cancer Treatment

Kevin Atsou, Sokchea Khou, Fabienne Anjuère, Véronique M. Braud and Thierry Goudon
Frontiers in Oncology 12 (2022)
https://doi.org/10.3389/fonc.2022.878827

A non-Gaussian stochastic model from limited observations using polynomial chaos and fractional moments

Ruijing Zhang and Hongzhe Dai
Reliability Engineering & System Safety 221 108323 (2022)
https://doi.org/10.1016/j.ress.2022.108323

Global Sensitivity Analysis and Uncertainty Quantification for Simulated Atrial Electrocardiograms

Benjamin Winkler, Claudia Nagel, Nando Farchmin, Sebastian Heidenreich, Axel Loewe, Olaf Dössel and Markus Bär
Metrology 3 (1) 1 (2022)
https://doi.org/10.3390/metrology3010001

Efficient uncertain keff computations with the Monte Carlo resolution of generalised Polynomial Chaos based reduced models

Gaël Poëtte and Emeric Brun
Journal of Computational Physics 456 111007 (2022)
https://doi.org/10.1016/j.jcp.2022.111007

Uncertainty propagation in pore water chemical composition calculation using surrogate models

Pierre Sochala, Christophe Chiaberge, Francis Claret and Christophe Tournassat
Scientific Reports 12 (1) (2022)
https://doi.org/10.1038/s41598-022-18411-5

Efficient uncertainty propagation for photonics: Combining Implicit Semi-analog Monte Carlo (ISMC) and Monte Carlo generalised Polynomial Chaos (MC-gPC)

Gaël Poëtte
Journal of Computational Physics 450 110807 (2022)
https://doi.org/10.1016/j.jcp.2021.110807

A local hybrid surrogate‐based finite element tearing interconnecting dual‐primal method for nonsmooth random partial differential equations

Martin Eigel and Robert Gruhlke
International Journal for Numerical Methods in Engineering 122 (4) 1001 (2021)
https://doi.org/10.1002/nme.6571

Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark

Nora Lüthen, Stefano Marelli and Bruno Sudret
SIAM/ASA Journal on Uncertainty Quantification 9 (2) 593 (2021)
https://doi.org/10.1137/20M1315774

Data-driven polynomial chaos expansions for characterization of complex fluid rheology: Case study of phosphate slurry

Nabil El Moçayd and Mohammed Seaid
Reliability Engineering & System Safety 216 107923 (2021)
https://doi.org/10.1016/j.ress.2021.107923

A note on stochastic polynomial chaos expansions for uncertain volatility and Asian option pricing

Y.-T. Lin, Y.-T. Shih, C.-S. Chien and Q. Sheng
Applied Mathematics and Computation 393 125764 (2021)
https://doi.org/10.1016/j.amc.2020.125764

Emulation of Stochastic Simulators Using Generalized Lambda Models

Xujia Zhu and Bruno Sudret
SIAM/ASA Journal on Uncertainty Quantification 9 (4) 1345 (2021)
https://doi.org/10.1137/20M1337302

Hyperbolicity-Preserving and Well-Balanced Stochastic Galerkin Method for Shallow Water Equations

Dihan Dai, Yekaterina Epshteyn and Akil Narayan
SIAM Journal on Scientific Computing 43 (2) A929 (2021)
https://doi.org/10.1137/20M1360736

Stability analysis of a hyperbolic stochastic Galerkin formulation for the Aw-Rascle-Zhang model with relaxation

Stephan Gerster, Michael Herty and Elisa Iacomini
Mathematical Biosciences and Engineering 18 (4) 4372 (2021)
https://doi.org/10.3934/mbe.2021220

Uncertainty quantification for the random viscous Burgers’ partial differential equation by using the differential transform method

Marc Jornet
Nonlinear Analysis 209 112340 (2021)
https://doi.org/10.1016/j.na.2021.112340

Convergence Analysis and Adaptive Order Selection for the Polynomial Chaos Approach to Direct Optimal Control under Uncertainties

Lilli Frison and Christian Kirches
SIAM Journal on Control and Optimization 59 (1) 509 (2021)
https://doi.org/10.1137/17M1133038

Development of hybrid dimension adaptive sparse HDMR for stochastic finite element analysis of composite plate

Amit Kumar Rathi and Arunasis Chakraborty
Composite Structures 255 112915 (2021)
https://doi.org/10.1016/j.compstruct.2020.112915

Global sensitivity analysis for stochastic simulators based on generalized lambda surrogate models

Xujia Zhu and Bruno Sudret
Reliability Engineering & System Safety 214 107815 (2021)
https://doi.org/10.1016/j.ress.2021.107815

Non-intrusive polynomial chaos methods for uncertainty quantification in wave problems at high frequencies

Nabil El Mocayd, M Shadi Mohamed and Mohammed Seaid
Journal of Computational Science 53 101344 (2021)
https://doi.org/10.1016/j.jocs.2021.101344

Uncertainty quantification for random Hamiltonian systems by using polynomial expansions and geometric integrators

Marc Jornet
Chaos, Solitons & Fractals 151 111208 (2021)
https://doi.org/10.1016/j.chaos.2021.111208

Flow-driven spectral chaos (FSC) method for long-time integration of second-order stochastic dynamical systems

Hugo Esquivel, Arun Prakash and Guang Lin
Journal of Computational and Applied Mathematics 398 113674 (2021)
https://doi.org/10.1016/j.cam.2021.113674

A Global Sensitivity Analysis Framework for Hybrid Simulation with Stochastic Substructures

Nikolaos Tsokanas, Xujia Zhu, Giuseppe Abbiati, Stefano Marelli, Bruno Sudret and Božidar Stojadinović
Frontiers in Built Environment 7 (2021)
https://doi.org/10.3389/fbuil.2021.778716