{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/42510"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/42510","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Using computer simulation to reduce costs at a recirculating aquaculture facility","abstract":"The Recirculating Aquaculture System can be considered as a dynamic system in which the system variables change instantaneously during the growing period. This effort uses a combination of discrete and continuous simulation to model this system. Changing the values of a certain set of variables (regressors) result in changes to another set of variables (responses). So the inter relationship between the regressors and responses are first defined. Then the changes to the regressors are defined as a function of time. The computer program then simulates time from the beginning to the end of the growing period. By attaching cost factors, the cost of running the system during the growing period can be obtained. In a real facility, some of the regressors can be changed by the operator, affecting the overall cost. So, in this model, different values for this subset of regressors are tried out using a proprietary heuristic called \"Optquest\" to arrive at a low cost configuration. Some of the responses are also constrained while trying to minimize the cost, e.g., ammonia level. The output of the model gives a cost savings of about $10,000 over a period of 8 months for a facility with 12 tanks by suggesting optimal values for the water replenishment rate, water recirculation rate, oxygen supply rate and feeds per day.","abstract_html":"The Recirculating Aquaculture System can be considered as a dynamic system in which the system variables change instantaneously during the growing period. This effort uses a combination of discrete and continuous simulation to model this system. Changing the values of a certain set of variables (regressors) result in changes to another set of variables (responses). So the inter relationship between the regressors and responses are first defined. Then the changes to the regressors are defined as a function of time. The computer program then simulates time from the beginning to the end of the growing period. By attaching cost factors, the cost of running the system during the growing period can be obtained. In a real facility, some of the regressors can be changed by the operator, affecting the overall cost. So, in this model, different values for this subset of regressors are tried out using a proprietary heuristic called "Optquest" to arrive at a low cost configuration. Some of the responses are also constrained while trying to minimize the cost, e.g., ammonia level. The output of the model gives a cost savings of about $10,000 over a period of 8 months for a facility with 12 tanks by suggesting optimal values for the water replenishment rate, water recirculation rate, oxygen supply rate and feeds per day.","abstract_has_math":false,"creators":["Simon, John"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Industrial and Systems Engineering","degree_department":"Industrial and Systems Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Boardman, Gregory D.","Taaffe, Michael R."],"committee_members":["McLean, Ewen W.","Taylor, Daniel B.","Koelling, C. Patrick"],"year":2005,"date_issued":"2005-04-26","date_published":"2005-04-26","updated_at":"2026-07-22T22:20:05Z","subjects":["aquaculture","Simulation"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-05062005-000324"],"render_values":[{"text":"etd-05062005-000324","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/42510","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Boardman, Gregory D.","Taaffe, Michael R."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["McLean, Ewen W.","Taylor, Daniel B.","Koelling, C. 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This effort uses a combination of discrete and continuous simulation to model this system. Changing the values of a certain set of variables (regressors) result in changes to another set of variables (responses). So the inter relationship between the regressors and responses are first defined. Then the changes to the regressors are defined as a function of time. The computer program then simulates time from the beginning to the end of the growing period. By attaching cost factors, the cost of running the system during the growing period can be obtained. In a real facility, some of the regressors can be changed by the operator, affecting the overall cost. So, in this model, different values for this subset of regressors are tried out using a proprietary heuristic called \"Optquest\" to arrive at a low cost configuration. Some of the responses are also constrained while trying to minimize the cost, e.g., ammonia level. The output of the model gives a cost savings of about $10,000 over a period of 8 months for a facility with 12 tanks by suggesting optimal values for the water replenishment rate, water recirculation rate, oxygen supply rate and feeds per day."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:title","label":"Title","values":["Using computer simulation to reduce costs at a recirculating aquaculture facility"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Boardman, Gregory D.","Taaffe, Michael R."],"dc:contributor.committeemember":["McLean, Ewen W.","Taylor, Daniel B.","Koelling, C. Patrick"],"dc:contributor.department":["Industrial and Systems Engineering"],"dc:creator":["Simon, John"],"dc:date.accessioned":["2014-03-14T21:35:40Z"],"dc:date.available":["2014-03-14T21:35:40Z","2008-05-24"],"dc:date.issued":["2005-04-26"],"dc:description.abstract":["The Recirculating Aquaculture System can be considered as a dynamic system in which the system variables change instantaneously during the growing period. This effort uses a combination of discrete and continuous simulation to model this system. Changing the values of a certain set of variables (regressors) result in changes to another set of variables (responses). So the inter relationship between the regressors and responses are first defined. Then the changes to the regressors are defined as a function of time. The computer program then simulates time from the beginning to the end of the growing period. By attaching cost factors, the cost of running the system during the growing period can be obtained. In a real facility, some of the regressors can be changed by the operator, affecting the overall cost. So, in this model, different values for this subset of regressors are tried out using a proprietary heuristic called \"Optquest\" to arrive at a low cost configuration. Some of the responses are also constrained while trying to minimize the cost, e.g., ammonia level. 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