Loading…

Comparison of the Performances of Different Reduced Forms of a Condenser Model

Symbolic manipulation uncovers hidden constraints for a model and facilitates model reduction for solution. The present work points out possible pitfalls of this procedure and finds possible solutions. The performances of different reduced forms of a condenser model are compared under step and impul...

Full description

Saved in:
Bibliographic Details
Published in:Chemical engineering & technology 2017-09, Vol.40 (9), p.1630-1637
Main Authors: Ahuja, Sanjeev, Arya, Raj Kumar
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c3544-945c576602535c335756689cf6301a9f38d6bd2af84980ac424d9512cd36dda3
cites cdi_FETCH-LOGICAL-c3544-945c576602535c335756689cf6301a9f38d6bd2af84980ac424d9512cd36dda3
container_end_page 1637
container_issue 9
container_start_page 1630
container_title Chemical engineering & technology
container_volume 40
creator Ahuja, Sanjeev
Arya, Raj Kumar
description Symbolic manipulation uncovers hidden constraints for a model and facilitates model reduction for solution. The present work points out possible pitfalls of this procedure and finds possible solutions. The performances of different reduced forms of a condenser model are compared under step and impulse perturbations. The system does not need to be at steady state before perturbation. Some symbolically manipulated models cause inconsistent reinitialization and convergence and introduce significant computational errors. Physically unreasonable system behavior thus emerges, which worsens with increasing model complexity. Nevertheless, the less symbolically manipulated models present realistic and accurate behaviors. Another approach to model reduction is the reformulation of a model through a physical insight. A physically reformulated model proposed for the system leads to accurate and physically reasonable system behavior. To facilitate solution, different reduced forms of a condenser model are obtained by symbolic manipulations and physical reformulation. Their performances are compared for realistic initialization, evolution, and convergence under step and impulse perturbations. The performance worsens with increasing model complexity, but the less symbolically manipulated and physically reformulated models show accurate behaviors.
doi_str_mv 10.1002/ceat.201600114
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_1931776230</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1931776230</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3544-945c576602535c335756689cf6301a9f38d6bd2af84980ac424d9512cd36dda3</originalsourceid><addsrcrecordid>eNqFkM1LAzEQxYMoWKtXzwuet04-d3Msa6tC_UB6DzGZ4JZ2U5Mt4n_v1ooePQ0z7_fmwSPkksKEArBrh7afMKAKgFJxREZUMloKyuQxGYHmUFaSqlNylvMKBmZYRuSxiZutTW2OXRFD0b9h8YwpxLSxncO8v920IWDCri9e0O8c-mI-yN-SLZrYeewypuIhelyfk5Ng1xkvfuaYLOezZXNXLp5u75vponRcClFqIZ2slAImuXScy0oqVWsXFAdqdeC1V6-e2VALXYN1ggmvJWXOc-W95WNydXi7TfF9h7k3q7hL3ZBoqOa0qhTjMFCTA-VSzDlhMNvUbmz6NBTMvjKzr8z8VjYY9MHw0a7x8x_aNLPp8s_7BT0vbfE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1931776230</pqid></control><display><type>article</type><title>Comparison of the Performances of Different Reduced Forms of a Condenser Model</title><source>Wiley-Blackwell Read &amp; Publish Collection</source><creator>Ahuja, Sanjeev ; Arya, Raj Kumar</creator><creatorcontrib>Ahuja, Sanjeev ; Arya, Raj Kumar</creatorcontrib><description>Symbolic manipulation uncovers hidden constraints for a model and facilitates model reduction for solution. The present work points out possible pitfalls of this procedure and finds possible solutions. The performances of different reduced forms of a condenser model are compared under step and impulse perturbations. The system does not need to be at steady state before perturbation. Some symbolically manipulated models cause inconsistent reinitialization and convergence and introduce significant computational errors. Physically unreasonable system behavior thus emerges, which worsens with increasing model complexity. Nevertheless, the less symbolically manipulated models present realistic and accurate behaviors. Another approach to model reduction is the reformulation of a model through a physical insight. A physically reformulated model proposed for the system leads to accurate and physically reasonable system behavior. To facilitate solution, different reduced forms of a condenser model are obtained by symbolic manipulations and physical reformulation. Their performances are compared for realistic initialization, evolution, and convergence under step and impulse perturbations. The performance worsens with increasing model complexity, but the less symbolically manipulated and physically reformulated models show accurate behaviors.</description><identifier>ISSN: 0930-7516</identifier><identifier>EISSN: 1521-4125</identifier><identifier>DOI: 10.1002/ceat.201600114</identifier><language>eng</language><publisher>Frankfurt: Wiley Subscription Services, Inc</publisher><subject>Consistent initialization ; Constraint modelling ; Differential‐algebraic equations ; Dynamic simulation ; Emergent behavior ; Index reduction ; Model reduction ; Perturbation methods ; Steady state</subject><ispartof>Chemical engineering &amp; technology, 2017-09, Vol.40 (9), p.1630-1637</ispartof><rights>2017 WILEY‐VCH Verlag GmbH &amp; Co. KGaA, Weinheim</rights><rights>2017 WILEY-VCH Verlag GmbH &amp; Co. KGaA, Weinheim</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3544-945c576602535c335756689cf6301a9f38d6bd2af84980ac424d9512cd36dda3</citedby><cites>FETCH-LOGICAL-c3544-945c576602535c335756689cf6301a9f38d6bd2af84980ac424d9512cd36dda3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Ahuja, Sanjeev</creatorcontrib><creatorcontrib>Arya, Raj Kumar</creatorcontrib><title>Comparison of the Performances of Different Reduced Forms of a Condenser Model</title><title>Chemical engineering &amp; technology</title><description>Symbolic manipulation uncovers hidden constraints for a model and facilitates model reduction for solution. The present work points out possible pitfalls of this procedure and finds possible solutions. The performances of different reduced forms of a condenser model are compared under step and impulse perturbations. The system does not need to be at steady state before perturbation. Some symbolically manipulated models cause inconsistent reinitialization and convergence and introduce significant computational errors. Physically unreasonable system behavior thus emerges, which worsens with increasing model complexity. Nevertheless, the less symbolically manipulated models present realistic and accurate behaviors. Another approach to model reduction is the reformulation of a model through a physical insight. A physically reformulated model proposed for the system leads to accurate and physically reasonable system behavior. To facilitate solution, different reduced forms of a condenser model are obtained by symbolic manipulations and physical reformulation. Their performances are compared for realistic initialization, evolution, and convergence under step and impulse perturbations. The performance worsens with increasing model complexity, but the less symbolically manipulated and physically reformulated models show accurate behaviors.</description><subject>Consistent initialization</subject><subject>Constraint modelling</subject><subject>Differential‐algebraic equations</subject><subject>Dynamic simulation</subject><subject>Emergent behavior</subject><subject>Index reduction</subject><subject>Model reduction</subject><subject>Perturbation methods</subject><subject>Steady state</subject><issn>0930-7516</issn><issn>1521-4125</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNqFkM1LAzEQxYMoWKtXzwuet04-d3Msa6tC_UB6DzGZ4JZ2U5Mt4n_v1ooePQ0z7_fmwSPkksKEArBrh7afMKAKgFJxREZUMloKyuQxGYHmUFaSqlNylvMKBmZYRuSxiZutTW2OXRFD0b9h8YwpxLSxncO8v920IWDCri9e0O8c-mI-yN-SLZrYeewypuIhelyfk5Ng1xkvfuaYLOezZXNXLp5u75vponRcClFqIZ2slAImuXScy0oqVWsXFAdqdeC1V6-e2VALXYN1ggmvJWXOc-W95WNydXi7TfF9h7k3q7hL3ZBoqOa0qhTjMFCTA-VSzDlhMNvUbmz6NBTMvjKzr8z8VjYY9MHw0a7x8x_aNLPp8s_7BT0vbfE</recordid><startdate>201709</startdate><enddate>201709</enddate><creator>Ahuja, Sanjeev</creator><creator>Arya, Raj Kumar</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope></search><sort><creationdate>201709</creationdate><title>Comparison of the Performances of Different Reduced Forms of a Condenser Model</title><author>Ahuja, Sanjeev ; Arya, Raj Kumar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3544-945c576602535c335756689cf6301a9f38d6bd2af84980ac424d9512cd36dda3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Consistent initialization</topic><topic>Constraint modelling</topic><topic>Differential‐algebraic equations</topic><topic>Dynamic simulation</topic><topic>Emergent behavior</topic><topic>Index reduction</topic><topic>Model reduction</topic><topic>Perturbation methods</topic><topic>Steady state</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ahuja, Sanjeev</creatorcontrib><creatorcontrib>Arya, Raj Kumar</creatorcontrib><collection>CrossRef</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Chemical engineering &amp; technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ahuja, Sanjeev</au><au>Arya, Raj Kumar</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparison of the Performances of Different Reduced Forms of a Condenser Model</atitle><jtitle>Chemical engineering &amp; technology</jtitle><date>2017-09</date><risdate>2017</risdate><volume>40</volume><issue>9</issue><spage>1630</spage><epage>1637</epage><pages>1630-1637</pages><issn>0930-7516</issn><eissn>1521-4125</eissn><abstract>Symbolic manipulation uncovers hidden constraints for a model and facilitates model reduction for solution. The present work points out possible pitfalls of this procedure and finds possible solutions. The performances of different reduced forms of a condenser model are compared under step and impulse perturbations. The system does not need to be at steady state before perturbation. Some symbolically manipulated models cause inconsistent reinitialization and convergence and introduce significant computational errors. Physically unreasonable system behavior thus emerges, which worsens with increasing model complexity. Nevertheless, the less symbolically manipulated models present realistic and accurate behaviors. Another approach to model reduction is the reformulation of a model through a physical insight. A physically reformulated model proposed for the system leads to accurate and physically reasonable system behavior. To facilitate solution, different reduced forms of a condenser model are obtained by symbolic manipulations and physical reformulation. Their performances are compared for realistic initialization, evolution, and convergence under step and impulse perturbations. The performance worsens with increasing model complexity, but the less symbolically manipulated and physically reformulated models show accurate behaviors.</abstract><cop>Frankfurt</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/ceat.201600114</doi><tpages>8</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0930-7516
ispartof Chemical engineering & technology, 2017-09, Vol.40 (9), p.1630-1637
issn 0930-7516
1521-4125
language eng
recordid cdi_proquest_journals_1931776230
source Wiley-Blackwell Read & Publish Collection
subjects Consistent initialization
Constraint modelling
Differential‐algebraic equations
Dynamic simulation
Emergent behavior
Index reduction
Model reduction
Perturbation methods
Steady state
title Comparison of the Performances of Different Reduced Forms of a Condenser Model
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T04%3A23%3A17IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Comparison%20of%20the%20Performances%20of%20Different%20Reduced%20Forms%20of%20a%20Condenser%20Model&rft.jtitle=Chemical%20engineering%20&%20technology&rft.au=Ahuja,%20Sanjeev&rft.date=2017-09&rft.volume=40&rft.issue=9&rft.spage=1630&rft.epage=1637&rft.pages=1630-1637&rft.issn=0930-7516&rft.eissn=1521-4125&rft_id=info:doi/10.1002/ceat.201600114&rft_dat=%3Cproquest_cross%3E1931776230%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c3544-945c576602535c335756689cf6301a9f38d6bd2af84980ac424d9512cd36dda3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1931776230&rft_id=info:pmid/&rfr_iscdi=true