Pregled bibliografske jedinice broj: 1158723
Application of physics-informed neural networks to inverse problems in unsaturated groundwater flow
Application of physics-informed neural networks to inverse problems in unsaturated groundwater flow // Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 16 (2022), 21-36 doi:10.1080/17499518.2021.1971251 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1158723 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Application of physics-informed neural networks to
inverse problems in unsaturated groundwater flow
Autori
Đepina, Ivan ; Jain, Saket ; Mar Valsson, Sigurdur ; Gotovac, Hrvoje
Izvornik
Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards (1749-9518) 16
(2022);
21-36
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Physics-informed ; Neural network ; Richards ; Unsaturated ; Inverse ; Infiltration ; Groundwater
Sažetak
This paper investigates the application of Physics- Informed Neural Networks (PINNs) to inverse problems in unsaturated groundwater flow. PINNs are applied to the types of unsaturated groundwater flow problems modelled with the Richards partial differential equation and the van Genuchten constitutive model. The inverse problem is formulated here as a problem with known or measured values of the solution to the Richards equation at several spatio-temporal instances, and unknown values of solution at the rest of the problem domain and unknown parameters of the van Genuchten model. PINNs solve inverse problems by reformulating the loss function of a deep neural network such that it simultaneously aims to satisfy the measured values and the unknown values at a set of collocation points distributed across the problem domain. The novelty of the paper originates from the development of PINN formulations for the Richards equation that requires training of a single neural network. The results demonstrate that PINNs are capable of efficiently solving the inverse problem with relatively accurate approximation of the solution to the Richards equation and estimates of the van Genuchten model parameters.
Izvorni jezik
Engleski
Znanstvena područja
Građevinarstvo
POVEZANOST RADA
Ustanove:
Fakultet građevinarstva, arhitekture i geodezije, Split
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Emerging Sources Citation Index (ESCI)
- Scopus