Abstract

This work presents an explicit methodology for estimating source terms in the diffusion equation based on the classical integral transform technique (CITT), employing eigenfunction expansions. This work extends the application of a recently developed methodology to more general three-dimensional cases. Given the high computational costs associated with these calculations, the study introduces essential enhancements for solving the related inverse problems more efficiently and proposes an automatic criterion for selecting the truncation order in the inverse problem solution, aiming at regularization based on the discrepancy principle. The results, based on simulated measurements for transient three-dimensional diffusion problems, demonstrate the effective improvements achieved, yielding consistently good results across the tested scenarios, including varying noise levels and different functional forms of the sought source terms. Accurate source term detection via an explicit computationally fast approach. Three-dimensional transient source terms are successfully handled. Selection of expansion truncation order for regularization is handled automatically. Computational efficiency is achieved through automatic truncation.

References

1.
Woodbury
,
K.
,
Najafi
,
H.
,
Monte
,
F.
, and
Beck
,
J.
,
2023
,
Inverse Heat Conduction: Ill‐Posed Problems
,
Wiley
, Hoboken, NJ.
2.
Özişik
,
M.
, and
Orlande
,
H.
,
2021
,
Inverse Heat Transfer: Fundamentals and Applications
,
CRC Press
, Boca Raton, FL.
3.
Orlande
,
H. R. B.
,
2012
, “
Inverse Problems in Heat Transfer: New Trends on Solution Methodologies and Applications
,”
ASME J. Heat Mass Transfer-Trans. ASME
,
134
(
3
), p.
031011
.10.1115/1.4005131
4.
Kaipio
,
J.
, and
Somersalo
,
E.
,
2006
,
Statistical and Computational Inverse Problems
(Applied Mathematical Sciences),
Springer
,
New York
.
5.
Kulacki
,
F. A.
,
2018
,
Handbook of Thermal Science and Engineering
,
Springer
,
New York
.
6.
Tikhonov
,
A. N.
, and
Arsenin
,
V. I.
,
1977
,
Solutions of Ill-Posed Problems
(Scripta Series in Mathematics),
Winston and Distributed Solely by Halsted Press
, Washington, D.C.
7.
Kirsch
,
A.
,
2021
,
An Introduction to the Mathematical Theory of Inverse Problems
,
Springer International Publishing
, Cham, Switzerland.
8.
Colton
,
D.
, and
Kress
,
R.
,
2019
,
Inverse Acoustic and Electromagnetic Scattering Theory
,
Springer International Publishing
, Cham, Switzerland.
9.
Kaipio
,
J. P.
, and
Fox
,
C.
,
2011
, “
The Bayesian Framework for Inverse Problems in Heat Transfer
,”
Heat Transfer Eng.
,
32
(
9
), pp.
718
753
.10.1080/01457632.2011.525137
10.
Alifanov
,
O.
,
1994
,
Inverse Heat Transfer Problems
(International Series in Heat and Mass Transfer), 1st ed.,
Springer
,
Berlin, Germany
.
11.
Knupp
,
D.
,
2021
, “
Integral Transform Technique for the Direct Identification of Thermal Conductivity and Thermal Capacity in Heterogeneous Media
,”
Int. J. Heat Mass Transfer
,
171
, p.
121120
.10.1016/j.ijheatmasstransfer.2021.121120
12.
Czél
,
B.
,
Woodbury
,
K. A.
, and
Gróf
,
G.
,
2014
, “
Simultaneous Estimation of Temperature-Dependent Volumetric Heat Capacity and Thermal Conductivity Functions Via Neural Networks
,”
Int. J. Heat Mass Transfer
,
68
, pp.
1
13
.10.1016/j.ijheatmasstransfer.2013.09.010
13.
Wang
,
C.
,
Heng
,
Y.
,
Luo
,
J.
, and
Wang
,
X.
,
2024
, “
A Fast Bayesian Parallel Solution Framework for Large-Scale Parameter Estimation of 3D Inverse Heat Transfer Problems
,”
Int. Commun. Heat Mass Transfer
,
155
, p.
107409
.10.1016/j.icheatmasstransfer.2024.107409
14.
Koleva
,
M. N.
, and
Vulkov
,
L. G.
,
2024
, “
Inverse Boundary Conditions Interface Problems for the Heat Equation With Cylindrical Symmetry
,”
Symmetry
,
16
(
8
), p.
1065
.10.3390/sym16081065
15.
Engl
,
H. W.
,
Hanke
,
M.
, and
Neubauer
,
G.
,
1996
,
Regularization of Inverse Problems
(Mathematics and Its Applications),
Springer
,
Dordrecht, Netherlands
.
16.
Pacheco
,
C. C.
,
2024
, “
An Online Database of Benchmark Problems for Verification of Inverse Problems Computer Codes
,”
Heat Transfer Eng.
,
45
(
12–13
), pp.
1070
1080
.10.1080/01457632.2023.2241175
17.
Huang
,
C.-H.
,
Li
,
J.-X.
, and
Kim
,
S.
,
2008
, “
An Inverse Problem in Estimating the Strength of Contaminant Source for Groundwater Systems
,”
Appl. Math. Modell.
,
32
(
4
), pp.
417
431
.10.1016/j.apm.2006.12.009
18.
Li
,
J.
,
Wu
,
Z.
,
He
,
H.
, and
Lu
,
W.
,
2022
, “
Comparative Analysis of Groundwater Contaminant Sources Identification Based on Simulation Optimization and Ensemble Kalman Filter
,”
Environ. Sci. Pollut. Res.
,
29
(
60
), pp.
90081
90097
.10.1007/s11356-022-21974-5
19.
Yoon
,
S.
,
Lee
,
S.
,
Zhang
,
J.
,
Zeng
,
L.
, and
Kang
,
P.
,
2023
, “
Inverse Estimation of Multiple Contaminant Sources in Three-Dimensional Heterogeneous Aquifers With Variable-Density Flows
,”
J. Hydrol.
,
617
, p.
129041
.10.1016/j.jhydrol.2022.129041
20.
Lugão
,
B.
,
Knupp
,
D.
, and
Rodriges
,
P.
,
2022
, “
Direct and Inverse Simulation Applied to the Identification and Quantification of Point Pollution Sources in Rivers
,”
Environ. Modell. Software
,
156
, p.
105488
.10.1016/j.envsoft.2022.105488
21.
Zhu
,
Y.
,
Chen
,
Z.
, and
Asif
,
Z.
,
2021
, “
Identification of Point Source Emission in River Pollution Incidents Based on Bayesian Inference and Genetic Algorithm: Inverse Modeling, Sensitivity, and Uncertainty Analysis
,”
Environ. Pollut.
,
285
, p.
117497
.10.1016/j.envpol.2021.117497
22.
Mehrabanian
,
K.
, and
Abbas Nejad
,
A.
,
2023
, “
A New Approach for the Heat Source Estimation in Cancerous Tissue Treatment With Hyperthermia
,”
Int. J. Therm. Sci.
,
194
, p.
108593
.10.1016/j.ijthermalsci.2023.108593
23.
Mital
,
M.
, and
Scott
,
E. P.
,
2007
, “
Thermal Detection of Embedded Tumors Using Infrared Imaging
,”
ASME J. Biomech. Eng.
,
129
(
1
), pp.
33
39
.10.1115/1.2401181
24.
Wu
,
J.
,
Liu
,
Z.
,
Yuan
,
S.
,
Cai
,
J.
, and
Hu
,
X.
,
2020
, “
Source Term Estimation of Natural Gas Leakage in Utility Tunnel by Combining CFD and Bayesian Inference Method
,”
J. Loss Prev. Process Ind.
,
68
, p.
104328
.10.1016/j.jlp.2020.104328
25.
Guo
,
J.
,
Le Masson
,
P.
,
Rouquette
,
S.
,
Loulou
,
T.
, and
Artioukhine
,
E.
,
2007
, “
Estimation of a Source Term in a Two-Dimensional Heat Transfer Problem: Application to an Electron Beam Welding, Theoretical and Experimental Validations
,”
Inverse Probl. Sci. Eng.
,
15
(
7
), pp.
743
763
.10.1080/17415970701198688
26.
Zeng
,
L.
,
Gao
,
J.
,
Lv
,
L.
,
Zhang
,
R.
,
Chen
,
Y.
,
Zhang
,
X.
,
Huang
,
Z.
, and
Zhang
,
Z.
,
2020
, “
Markov-Chain-Based Inverse Modeling to Fast Localize Hazardous Gaseous Pollutant Sources in Buildings With Ventilation Systems
,”
Build. Environ.
,
169
, p.
106584
.10.1016/j.buildenv.2019.106584
27.
Wang
,
X.
,
Zhang
,
D.
, and
Zhang
,
L.
,
2020
, “
Estimation of Moving Heat Source for an Instantaneous Three-Dimensional Heat Transfer System Based on Step-Renewed Kalman Filter
,”
Int. J. Heat Mass Transfer
,
163
(
4
), p.
120435
.10.1016/j.ijheatmasstransfer.2020.120435
28.
Qian
,
W.
,
He
,
K.
, and
Wang
,
Q.
,
2008
, “
Inverse Estimation of Heat Source Term in Three-Dimensional Transient Heat Conduction Problem
,”
Chin. J. Theor. Appl. Mech.
,
40
(
256
), p.
611
.10.6052/0459-1879-2008-5-2007-256
29.
Reis
,
L. A. D.
,
Orlande
,
H. R. B.
, and
Lesnic
,
D.
,
2014
, “
A Comparison of the Iterative Regularization Technique and of the Markov Chain Monte Carlo Method: Estimation of the Source Term in a Three-Dimensional Heat Conduction Problem
,”
10th World Congress on Computational Mechanics
, São Paulo, Brazil, July 8--13, pp.
2375
2393
.10.5151/meceng-wccm2012-18836
30.
Zhang
,
P.
,
Meng
,
P.
,
Yin
,
W.
, and
Liu
,
H.
,
2023
, “
A Neural Network Method for Time-Dependent Inverse Source Problem With Limited-Aperture Data
,”
J. Comput. Appl. Math.
,
421
, p.
114842
.10.1016/j.cam.2022.114842
31.
Massard
,
H.
,
Orlande
,
H. R. B.
, and
Fudym
,
O.
,
2012
, “
Estimation of Position-Dependent Transient Heat Source With the Kalman Filter
,”
Inverse Probl. Sci. Eng.
,
20
(
7
), pp.
1079
1099
.10.1080/17415977.2012.712520
32.
Gasperazzo
,
G. R.
, and
Colaço
,
M. J.
,
2024
, “
Transient Source Terms Estimate in Advection-Diffusion Problems Using the Method of Fundamental Solutions and an Eulerian–Lagrangian Transformation
,”
Heat Transfer Eng.
,
45
(
12–13
), pp.
1158
1171
.10.1080/01457632.2023.2241171
33.
Dalla
,
C. E. R.
,
da Silva
,
W. B.
,
Dutra
,
J. C. S.
, and
Colaço
,
M. J.
,
2024
, “
Online Estimation of Inlet Contaminant Concentration Using Eulerian–Lagrangian Method of Fundamental Solutions and Bayesian Inference
,”
Comput. Math. Appl.
,
164
, pp.
131
138
.10.1016/j.camwa.2024.04.019
34.
Margotto
,
B. H. M.
,
Colaço
,
M. J.
,
Kopperschmidt
,
C. E. P.
,
Bozzoli
,
F.
,
Pagliarini
,
L.
,
Cattani
,
L.
,
da Silva
,
W. B.
,
Hamada
,
M.
, and
Nagano
,
H.
,
2024
, “
Estimation of Internal Heat Flux on Pulsating Heat Pipes Using Kalman Filter: Numerical and Experimental Results
,”
J. Phys.: Conf. Ser.
,
2685
(
1
), p.
012071
.10.1088/1742-6596/2685/1/012071
35.
Neto
,
A. S.
,
Becceneri
,
J.
, and
Campos Velho
,
H.
,
2023
,
Computational Intelligence Applied to Inverse Problems in Radiative Transfer
,
Springer International Publishing
, Cham, Switzerland.
36.
Negreiros
,
A. R.
,
Knupp
,
D. C.
,
Abreu
,
L. A. S.
, and
Silva Neto
,
A. J.
,
2020
, “
Explicit Reconstruction of Space- and Time-Dependent Heat Sources With Integral Transforms
,”
Numer. Heat Transfer, Part B
,
79
(
4
), pp.
216
233
.10.1080/10407790.2020.1850148
37.
Özışık
,
M.
,
1993
,
Heat Conduction
,
Wiley
, Hoboken, NJ.
38.
Cotta
,
R. M.
,
Knupp
,
D. C.
, and
Quaresma
,
J. N. N.
,
2018
,
Analytical Methods in Heat Transfer
,
Springer International Publishing
,
Cham
, Switzerland, pp.
61
126
.
39.
Cotta
,
R. M.
,
2020
,
Integral Transforms in Computational Heat and Fluid Flow
,
CRC Press, Boca Raton, FL
.
40.
Mikhailov
,
M. D.
, and
Özışık
,
M. N.
,
1984
,
Unified Analysis and Solutions of Heat and Mass Diffusion
,
Dover, Mineola, NY
.
41.
Naveira-Cotta
,
C. P.
,
Cotta
,
R. M.
, and
Orlande
,
H. R.
,
2011
, “
Inverse Analysis With Integral Transformed Temperature Fields: Identification of Thermophysical Properties in Heterogeneous Media
,”
Int. J. Heat Mass Transfer
,
54
(
7–8
), pp.
1506
1519
.10.1016/j.ijheatmasstransfer.2010.11.042
42.
Abreu
,
L. A. S.
,
Orlande
,
H. R. B.
,
Naveira-Cotta
,
C. P.
,
Quaresma
,
J. N. N.
,
Cotta
,
R. M.
,
Kaipio
,
J.
, and
Kolehmainen
,
V.
,
2011
, “
Identification of Contact Failures in Multi-Layered Composites
,”
ASME
Paper No. DETC2011-47511.10.1115/DETC2011-47511
43.
Abreu
,
L. A. S.
,
Orlande
,
H. R. B.
,
Kaipio
,
J.
,
Kolehmainen
,
V.
,
Cotta
,
R. M.
, and
Quaresma
,
J. N. N.
,
2014
, “
Identification of Contact Failures in Multilayered Composites With the Markov Chain Monte Carlo Method
,”
ASME J. Heat Mass Transfer-Trans. ASME
,
136
(
10
), p.
101302
.10.1115/1.4027364
44.
Knupp
,
D. C.
, and
Abreu
,
L. A. S.
,
2016
, “
Explicit Boundary Heat Flux Reconstruction Employing Temperature Measurements Regularized Via Truncated Eigenfunction Expansions
,”
Int. Commun. Heat Mass Transfer
,
78
, pp.
241
252
.10.1016/j.icheatmasstransfer.2016.09.012
45.
Cotta
,
R. M.
,
Abreu
,
L. A.
,
Pontes
,
P. C.
,
Naveira-Cotta
,
C. P.
,
Knupp
,
D. C.
,
Orlande
,
H. R. B.
, and
Colaço
,
M. J.
,
2024
, “
Computational-Analytical Integral Transform and CPU-Intensive Simulations in Heat and Fluid Flow
,” 9th Thermal and Fluids Engineering Conference (
TFEC
), Corvallis, OR, Apr. 21--24, pp.
1
16
.10.1615/TFEC2024.kl.051359
46.
Abreu
,
L. A. S.
,
Orlande
,
H. R. B.
,
Colaço
,
M. J.
,
Kaipio
,
J.
,
Kolehmainen
,
V.
,
Pacheco
,
C. C.
, and
Cotta
,
R. M.
,
2018
, “
Detection of Contact Failures With the Markov Chain Monte Carlo Method by Using Integral Transformed Measurements
,”
Int. J. Therm. Sci.
,
132
, pp.
486
497
.10.1016/j.ijthermalsci.2018.06.006
47.
de Oliveira
,
A. J. P.
,
Abreu
,
L. A. S.
, and
Knupp
,
D. C.
,
2023
, “
Explicit Scheme Based on Integral Transforms for Estimation of Source Terms in Diffusion Problems in Heterogeneous Media
,”
J. Eng. Exact Sci.
,
9
(
10
), p.
17811
.10.18540/jcecvl9iss10pp17811
48.
de Oliveira
,
A. J. P.
,
Knupp
,
D. C.
, and
Abreu
,
L. A. S.
,
2025
, “
Integral Transforms for Explicit Source Estimation in Non-Linear Advection-Diffusion Problems
,”
Appl. Math. Comput.
,
487
, p.
129092
.10.1016/j.amc.2024.129092
49.
Morozov
,
V. A.
,
1966
, “
On the Solution of Functional Equations by the Method of Regularization
,”
Dokl. Akad. Nauk SSSR
,
167
(
3
), pp.
510
512
.https://www.mathnet.ru/links/c191c4fa0eaa60cfcacd68ca9571427f/dan32161.pdf
50.
W. R.
Inc
.,
2023
,
Mathematica, Version 13.3
,
W. R. Inc
.,
Champaign, IL
.
51.
Blackwell
,
J.
,
Kraśny
,
M. J.
,
O'Brien
,
A.
,
Ashkan
,
K.
,
Galligan
,
J.
,
Destrade
,
M.
, and
Colgan
,
N.
,
2022
, “
Proton Resonance Frequency Shift Thermometry: A Review of Modern Clinical Practices
,”
J. Magn. Reson. Imaging
,
55
(
2
), pp.
389
403
.10.1002/jmri.27446
52.
Stauffer
,
P. R.
,
Snow
,
B. W.
,
Rodrigues
,
D. B.
,
Salahi
,
S.
,
Oliveira
,
T. R.
,
Reudink
,
D.
, and
Maccarini
,
P. F.
,
2014
, “
Non-Invasive Measurement of Brain Temperature With Microwave Radiometry: Demonstration in a Head Phantom and Clinical Case
,”
Neuroradiology J.
,
27
(
1
), pp.
3
12
.10.15274/NRJ-2014-10001
53.
Nunes
,
F. S.
,
Orlande
,
H. R.
, and
Nowak
,
A. J.
,
2022
, “
An Inverse Analysis of the Brain Cooling Process in Neonates Using the Particle Filter Method
,”
Int. J. Numer. Methods Heat Fluid Flow
,
32
(
12
), pp.
3908
3934
.10.1108/HFF-04-2022-0207
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