Segregated targeting for multiple resource networks using decomposition algorithm
A generalized decomposition technique is presented for determining optimal resource usage in segregated targeting problems with single quality index (e.g., concentration, temperature, etc.) through pinch analysis. The latter problems are concerned with determining minimal resource requirements of pr...
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oai:animorepository.dlsu.edu.ph:faculty_research-17972020-10-24T01:48:02Z Segregated targeting for multiple resource networks using decomposition algorithm Bandyopadhyay, Santanu Sahu, Gopal Chandra Foo, Dominic Chwan Yee Tan, Raymond R. A generalized decomposition technique is presented for determining optimal resource usage in segregated targeting problems with single quality index (e.g., concentration, temperature, etc.) through pinch analysis. The latter problems are concerned with determining minimal resource requirements of process networks characterized by the existence of multiple zones, each consisting of a set of demands and using a unique external resource. However, all the zones share a common set of internal sources. The decomposition algorithm allows the problem to be decomposed into a sequence of subproblems, each of which can in turn be solved using any established graphical or algebraic targeting methodology to determine the minimum requirement of respective resource. This article presents a rigorous mathematical proof of the decomposition algorithm, and then demonstrates its potential applications with case studies on carbon-constrained energy sector planning, interplant water integration, and energy-based multisector fuel allocation. © 2009 American Institute of Chemical Engineers. 2010-05-01T07:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/798 Faculty Research Work Animo Repository |
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A generalized decomposition technique is presented for determining optimal resource usage in segregated targeting problems with single quality index (e.g., concentration, temperature, etc.) through pinch analysis. The latter problems are concerned with determining minimal resource requirements of process networks characterized by the existence of multiple zones, each consisting of a set of demands and using a unique external resource. However, all the zones share a common set of internal sources. The decomposition algorithm allows the problem to be decomposed into a sequence of subproblems, each of which can in turn be solved using any established graphical or algebraic targeting methodology to determine the minimum requirement of respective resource. This article presents a rigorous mathematical proof of the decomposition algorithm, and then demonstrates its potential applications with case studies on carbon-constrained energy sector planning, interplant water integration, and energy-based multisector fuel allocation. © 2009 American Institute of Chemical Engineers. |
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Bandyopadhyay, Santanu Sahu, Gopal Chandra Foo, Dominic Chwan Yee Tan, Raymond R. |
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Bandyopadhyay, Santanu Sahu, Gopal Chandra Foo, Dominic Chwan Yee Tan, Raymond R. Segregated targeting for multiple resource networks using decomposition algorithm |
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Bandyopadhyay, Santanu Sahu, Gopal Chandra Foo, Dominic Chwan Yee Tan, Raymond R. |
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Bandyopadhyay, Santanu |
title |
Segregated targeting for multiple resource networks using decomposition algorithm |
title_short |
Segregated targeting for multiple resource networks using decomposition algorithm |
title_full |
Segregated targeting for multiple resource networks using decomposition algorithm |
title_fullStr |
Segregated targeting for multiple resource networks using decomposition algorithm |
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Segregated targeting for multiple resource networks using decomposition algorithm |
title_sort |
segregated targeting for multiple resource networks using decomposition algorithm |
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Animo Repository |
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2010 |
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https://animorepository.dlsu.edu.ph/faculty_research/798 |
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