Use neural network in photoacoustic measurement of thermoelastic properties of aluminum foil
Само за регистроване кориснике
2022
Аутори
Đorđević, Кatarina Lj.Galović, Slobodanka
Popović, Marica N.
Nešić, Mioljub V.
Stanimirović, Ivanka P.
Stanimirović, Zdravko
Markushev, Dragan D.
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
The objective of this paper is to present methodology of the precise and reliable determination of thermal diffusivity and linear coefficient of thermal expansion of the photoacoustic signal recorded (obtained) using open photoacoustic cell where thickness of the sample served as a control parameter. The methodology was based on the application of neural networks that were trained on numerical experiments and optimized by adding Gaussian noise to the training base that corresponded in percentage to maximum measurement uncertainty. By comparing the predictions of the neural network with theoretical fitting curve for experimental results for the aluminum sample that was 197 μm thick, it was shown that the proposed methodology achieves high precision in the determination of thermoelastic and geometrical properties of the sample.
Кључне речи:
Aluminum / Inverse problem / Linear coefficient of thermal expansion / Minimum volume cell / Neural networks / Photoacoustic / Thermal diffusivityИзвор:
Measurement, 2022, 199, 111537-Финансирање / пројекти:
- Министарство науке, технолошког развоја и иновација Републике Србије, институционално финансирање - 200017 (Универзитет у Београду, Институт за нуклеарне науке Винча, Београд-Винча) (RS-MESTD-inst-2020-200017)
DOI: 10.1016/j.measurement.2022.111537
ISSN: 0263-2241
Scopus: 2-s2.0-85133764127
Колекције
Институција/група
VinčaTY - JOUR AU - Đorđević, Кatarina Lj. AU - Galović, Slobodanka AU - Popović, Marica N. AU - Nešić, Mioljub V. AU - Stanimirović, Ivanka P. AU - Stanimirović, Zdravko AU - Markushev, Dragan D. PY - 2022 UR - https://vinar.vin.bg.ac.rs/handle/123456789/10364 AB - The objective of this paper is to present methodology of the precise and reliable determination of thermal diffusivity and linear coefficient of thermal expansion of the photoacoustic signal recorded (obtained) using open photoacoustic cell where thickness of the sample served as a control parameter. The methodology was based on the application of neural networks that were trained on numerical experiments and optimized by adding Gaussian noise to the training base that corresponded in percentage to maximum measurement uncertainty. By comparing the predictions of the neural network with theoretical fitting curve for experimental results for the aluminum sample that was 197 μm thick, it was shown that the proposed methodology achieves high precision in the determination of thermoelastic and geometrical properties of the sample. T2 - Measurement T1 - Use neural network in photoacoustic measurement of thermoelastic properties of aluminum foil VL - 199 SP - 111537 DO - 10.1016/j.measurement.2022.111537 ER -
@article{ author = "Đorđević, Кatarina Lj. and Galović, Slobodanka and Popović, Marica N. and Nešić, Mioljub V. and Stanimirović, Ivanka P. and Stanimirović, Zdravko and Markushev, Dragan D.", year = "2022", abstract = "The objective of this paper is to present methodology of the precise and reliable determination of thermal diffusivity and linear coefficient of thermal expansion of the photoacoustic signal recorded (obtained) using open photoacoustic cell where thickness of the sample served as a control parameter. The methodology was based on the application of neural networks that were trained on numerical experiments and optimized by adding Gaussian noise to the training base that corresponded in percentage to maximum measurement uncertainty. By comparing the predictions of the neural network with theoretical fitting curve for experimental results for the aluminum sample that was 197 μm thick, it was shown that the proposed methodology achieves high precision in the determination of thermoelastic and geometrical properties of the sample.", journal = "Measurement", title = "Use neural network in photoacoustic measurement of thermoelastic properties of aluminum foil", volume = "199", pages = "111537", doi = "10.1016/j.measurement.2022.111537" }
Đorđević, К. Lj., Galović, S., Popović, M. N., Nešić, M. V., Stanimirović, I. P., Stanimirović, Z.,& Markushev, D. D.. (2022). Use neural network in photoacoustic measurement of thermoelastic properties of aluminum foil. in Measurement, 199, 111537. https://doi.org/10.1016/j.measurement.2022.111537
Đorđević КL, Galović S, Popović MN, Nešić MV, Stanimirović IP, Stanimirović Z, Markushev DD. Use neural network in photoacoustic measurement of thermoelastic properties of aluminum foil. in Measurement. 2022;199:111537. doi:10.1016/j.measurement.2022.111537 .
Đorđević, Кatarina Lj., Galović, Slobodanka, Popović, Marica N., Nešić, Mioljub V., Stanimirović, Ivanka P., Stanimirović, Zdravko, Markushev, Dragan D., "Use neural network in photoacoustic measurement of thermoelastic properties of aluminum foil" in Measurement, 199 (2022):111537, https://doi.org/10.1016/j.measurement.2022.111537 . .