Uncertainty analysis of the PBMR turbo machines / H.P. van der Linde.
The aim of this study was to quantify the amount of uncertainty that surrounds the design of the PBMR turbo machines. The PBMR plant is a first-of-a-kind engineering effort in which a closed loop intercooled Brayton cycle is used to extract nuclear energy from a pebble bed reactor. Until the plant h...
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ndltd-NWUBOLOKA1-oai-dspace.nwu.ac.za-10394-47042014-04-16T03:56:32ZUncertainty analysis of the PBMR turbo machines / H.P. van der Linde.Uncertainty analysis of the pebble bed modular reactor turbo machinesVan der Linde, Hendrik PetrusThe aim of this study was to quantify the amount of uncertainty that surrounds the design of the PBMR turbo machines. The PBMR plant is a first-of-a-kind engineering effort in which a closed loop intercooled Brayton cycle is used to extract nuclear energy from a pebble bed reactor. Until the plant has been successfully operated, uncertainty will exist as to the performance of key components: The Monte Carlo method was selected for the uncertainty analysis. The analysis tools used for the study were Matlab and Flownex. Flownex is widely used in industry. It is a fast solving network CFD code that solves conservation of mass, energy and momentum equations. In order to automate the process of solving thousands of steady-states, another code developed in Matlab was used. Matlab was also used to process the data. Six turbo machine variables were selected as evaluating criteria. These included the rotational speed of the turbo units, the surge margin of the compressors, the grid power produced and the net cycle efficiency. Four steady state operating points, which are spread within the plant operating envelope, were evaluated. Plant parameters influencing the six turbo machine variables were identified and the degree to which they contribute to the uncertainty was justified. The uncertain parameters include pressure drop, to which the reactor and turbo machine intake and diffusers are the main contributors. Other uncertain parameters include leakage flows, turbo machine efficiency and flow area, reactor outlet temperature, manifold pressure and cooling water temperature. The Monte Carlo results indicate that the PBMR design is fairly robust with regard to the turbo machine parameters. An adjustment with regard to the design surge margin of the Low Pressure Compressor can be made as a result of this study. This recommendation will further enhance the robustness of the PBMR plant while at the same time quantifying the uncertainty surrounding the design of the turbo machines. Abbreviated results of this study were presented at the HTR 2004 conference in Beijing, China.Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2006.North-West University2011-09-07T09:27:15Z2011-09-07T09:27:15Z2005Thesishttp://hdl.handle.net/10394/4704en |
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The aim of this study was to quantify the amount of uncertainty that surrounds the design of the PBMR turbo machines. The PBMR plant is a first-of-a-kind engineering effort in which a closed loop intercooled Brayton cycle is used to extract nuclear energy from a pebble bed reactor. Until the plant has been successfully operated, uncertainty will exist as to the performance of key components:
The Monte Carlo method was selected for the uncertainty analysis. The analysis tools used for the study were Matlab and Flownex. Flownex is widely used in industry. It is a fast solving network CFD code that solves conservation of mass, energy and momentum equations. In order to automate the process of solving thousands of steady-states, another code developed in Matlab was used. Matlab was also used to process the data.
Six turbo machine variables were selected as evaluating criteria. These included the rotational speed of the turbo units, the surge margin of the compressors, the grid power produced and the net cycle efficiency. Four steady state operating points, which are spread within the plant operating envelope, were evaluated.
Plant parameters influencing the six turbo machine variables were identified and the degree to which they contribute to the uncertainty was justified. The uncertain parameters include pressure drop, to which the reactor and turbo machine intake and diffusers are the main contributors. Other uncertain parameters include leakage flows, turbo machine efficiency and flow area, reactor outlet temperature, manifold pressure and cooling water temperature.
The Monte Carlo results indicate that the PBMR design is fairly robust with regard to the turbo machine parameters. An adjustment with regard to the design surge margin of the Low Pressure Compressor can be made as a result of this study. This recommendation will further enhance the robustness of the PBMR plant while at the same time quantifying the uncertainty surrounding the design of the turbo machines. Abbreviated results of this study were presented at the HTR 2004 conference in Beijing, China. === Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2006. |
author |
Van der Linde, Hendrik Petrus |
spellingShingle |
Van der Linde, Hendrik Petrus Uncertainty analysis of the PBMR turbo machines / H.P. van der Linde. |
author_facet |
Van der Linde, Hendrik Petrus |
author_sort |
Van der Linde, Hendrik Petrus |
title |
Uncertainty analysis of the PBMR turbo machines / H.P. van der Linde. |
title_short |
Uncertainty analysis of the PBMR turbo machines / H.P. van der Linde. |
title_full |
Uncertainty analysis of the PBMR turbo machines / H.P. van der Linde. |
title_fullStr |
Uncertainty analysis of the PBMR turbo machines / H.P. van der Linde. |
title_full_unstemmed |
Uncertainty analysis of the PBMR turbo machines / H.P. van der Linde. |
title_sort |
uncertainty analysis of the pbmr turbo machines / h.p. van der linde. |
publisher |
North-West University |
publishDate |
2011 |
url |
http://hdl.handle.net/10394/4704 |
work_keys_str_mv |
AT vanderlindehendrikpetrus uncertaintyanalysisofthepbmrturbomachineshpvanderlinde AT vanderlindehendrikpetrus uncertaintyanalysisofthepebblebedmodularreactorturbomachines |
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1716665142822830080 |