PROŠEK, Andrej ;MAVKO, Borut . Response Surface Generation with Optimal Statistical Estimator. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 46, n.1, p. 14-23, july 2017. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/article/response-surface-generation-with-optimal-statistical-estimator/>. Date accessed: 23 nov. 2024. doi:http://dx.doi.org/.
Prošek, A., & Mavko, B. (2000). Response Surface Generation with Optimal Statistical Estimator. Strojniški vestnik - Journal of Mechanical Engineering, 46(1), 14-23. doi:http://dx.doi.org/
@article{.,
author = {Andrej Prošek and Borut Mavko},
title = {Response Surface Generation with Optimal Statistical Estimator},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {46},
number = {1},
year = {2000},
keywords = {response surface; optimal statistical estimator; peak cladding temperature; nuclear safety; },
abstract = {In the field of nuclear engineering the response surface is used to solve some problems related to nuclear safety. The main purpose of the study was to develop a tool suitable for response surface generation of complex and non-linear phenomena and to demonstrate its applicability for the response surface generation of peak cladding temperature during a small-break loss-of-coolant accident in a nuclear power plant. The optimal statistical estimator, adapted for use in multi-dimensional space, was used for response surface generation. For assessing the adequacy and predictive capability of the optimal statistical estimator two statistics were built in, and the possibility to set the width of the Gaussian curve. The performance of the optimal statistical estimator was tested with the results from 59 different calculations of the small-break lossof-coolant accident. The application of the optimal statistical estimator shows several advantages when compared to the more commonly used regression analysis. The results showed that the response surface for the peak cladding temperature was adequately predicted by the optimal statistical estimator but not with regression analysis. Furthermore, an ability to automate the response surface generation provides the possibility of using the optimal statistical estimator for an uncertainty evaluation of any kind of time dependent phenomena and transients},
issn = {0039-2480}, pages = {14-23}, doi = {},
url = {https://www.sv-jme.eu/article/response-surface-generation-with-optimal-statistical-estimator/}
}
Prošek, A.,Mavko, B. 2000 July 46. Response Surface Generation with Optimal Statistical Estimator. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 46:1
%A Prošek, Andrej %A Mavko, Borut %D 2000 %T Response Surface Generation with Optimal Statistical Estimator %B 2000 %9 response surface; optimal statistical estimator; peak cladding temperature; nuclear safety; %! Response Surface Generation with Optimal Statistical Estimator %K response surface; optimal statistical estimator; peak cladding temperature; nuclear safety; %X In the field of nuclear engineering the response surface is used to solve some problems related to nuclear safety. The main purpose of the study was to develop a tool suitable for response surface generation of complex and non-linear phenomena and to demonstrate its applicability for the response surface generation of peak cladding temperature during a small-break loss-of-coolant accident in a nuclear power plant. The optimal statistical estimator, adapted for use in multi-dimensional space, was used for response surface generation. For assessing the adequacy and predictive capability of the optimal statistical estimator two statistics were built in, and the possibility to set the width of the Gaussian curve. The performance of the optimal statistical estimator was tested with the results from 59 different calculations of the small-break lossof-coolant accident. The application of the optimal statistical estimator shows several advantages when compared to the more commonly used regression analysis. The results showed that the response surface for the peak cladding temperature was adequately predicted by the optimal statistical estimator but not with regression analysis. Furthermore, an ability to automate the response surface generation provides the possibility of using the optimal statistical estimator for an uncertainty evaluation of any kind of time dependent phenomena and transients %U https://www.sv-jme.eu/article/response-surface-generation-with-optimal-statistical-estimator/ %0 Journal Article %R %& 14 %P 10 %J Strojniški vestnik - Journal of Mechanical Engineering %V 46 %N 1 %@ 0039-2480 %8 2017-07-07 %7 2017-07-07
Prošek, Andrej, & Borut Mavko. "Response Surface Generation with Optimal Statistical Estimator." Strojniški vestnik - Journal of Mechanical Engineering [Online], 46.1 (2000): 14-23. Web. 23 Nov. 2024
TY - JOUR AU - Prošek, Andrej AU - Mavko, Borut PY - 2000 TI - Response Surface Generation with Optimal Statistical Estimator JF - Strojniški vestnik - Journal of Mechanical Engineering DO - KW - response surface; optimal statistical estimator; peak cladding temperature; nuclear safety; N2 - In the field of nuclear engineering the response surface is used to solve some problems related to nuclear safety. The main purpose of the study was to develop a tool suitable for response surface generation of complex and non-linear phenomena and to demonstrate its applicability for the response surface generation of peak cladding temperature during a small-break loss-of-coolant accident in a nuclear power plant. The optimal statistical estimator, adapted for use in multi-dimensional space, was used for response surface generation. For assessing the adequacy and predictive capability of the optimal statistical estimator two statistics were built in, and the possibility to set the width of the Gaussian curve. The performance of the optimal statistical estimator was tested with the results from 59 different calculations of the small-break lossof-coolant accident. The application of the optimal statistical estimator shows several advantages when compared to the more commonly used regression analysis. The results showed that the response surface for the peak cladding temperature was adequately predicted by the optimal statistical estimator but not with regression analysis. Furthermore, an ability to automate the response surface generation provides the possibility of using the optimal statistical estimator for an uncertainty evaluation of any kind of time dependent phenomena and transients UR - https://www.sv-jme.eu/article/response-surface-generation-with-optimal-statistical-estimator/
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author = {Prošek, A., Mavko, B.},
title = {Response Surface Generation with Optimal Statistical Estimator},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {46},
number = {1},
year = {2000},
doi = {},
url = {https://www.sv-jme.eu/article/response-surface-generation-with-optimal-statistical-estimator/}
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TY - JOUR AU - Prošek, Andrej AU - Mavko, Borut PY - 2017/07/07 TI - Response Surface Generation with Optimal Statistical Estimator JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 46, No 1 (2000): Strojniški vestnik - Journal of Mechanical Engineering DO - KW - response surface, optimal statistical estimator, peak cladding temperature, nuclear safety, N2 - In the field of nuclear engineering the response surface is used to solve some problems related to nuclear safety. The main purpose of the study was to develop a tool suitable for response surface generation of complex and non-linear phenomena and to demonstrate its applicability for the response surface generation of peak cladding temperature during a small-break loss-of-coolant accident in a nuclear power plant. The optimal statistical estimator, adapted for use in multi-dimensional space, was used for response surface generation. For assessing the adequacy and predictive capability of the optimal statistical estimator two statistics were built in, and the possibility to set the width of the Gaussian curve. The performance of the optimal statistical estimator was tested with the results from 59 different calculations of the small-break lossof-coolant accident. The application of the optimal statistical estimator shows several advantages when compared to the more commonly used regression analysis. The results showed that the response surface for the peak cladding temperature was adequately predicted by the optimal statistical estimator but not with regression analysis. Furthermore, an ability to automate the response surface generation provides the possibility of using the optimal statistical estimator for an uncertainty evaluation of any kind of time dependent phenomena and transients UR - https://www.sv-jme.eu/article/response-surface-generation-with-optimal-statistical-estimator/
Prošek, Andrej, AND Mavko, Borut. "Response Surface Generation with Optimal Statistical Estimator" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 46 Number 1 (07 July 2017)
Strojniški vestnik - Journal of Mechanical Engineering 46(2000)1, 14-23
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
In the field of nuclear engineering the response surface is used to solve some problems related to nuclear safety. The main purpose of the study was to develop a tool suitable for response surface generation of complex and non-linear phenomena and to demonstrate its applicability for the response surface generation of peak cladding temperature during a small-break loss-of-coolant accident in a nuclear power plant. The optimal statistical estimator, adapted for use in multi-dimensional space, was used for response surface generation. For assessing the adequacy and predictive capability of the optimal statistical estimator two statistics were built in, and the possibility to set the width of the Gaussian curve. The performance of the optimal statistical estimator was tested with the results from 59 different calculations of the small-break lossof-coolant accident. The application of the optimal statistical estimator shows several advantages when compared to the more commonly used regression analysis. The results showed that the response surface for the peak cladding temperature was adequately predicted by the optimal statistical estimator but not with regression analysis. Furthermore, an ability to automate the response surface generation provides the possibility of using the optimal statistical estimator for an uncertainty evaluation of any kind of time dependent phenomena and transients