{"id":{"repo_id":"uoit","oai_identifier":"oai:ontariotechu.scholaris.ca:10155/1566"},"canonical_url":"https://search.dev.ndltd.org/etd/uoit/oai:ontariotechu.scholaris.ca:10155/1566","repository":{"repo_id":"uoit","name":"Ontario Institute of Technology","base_url":"https://ontariotechu.scholaris.ca/server/oai/request"},"display":{"title":"Optimized clean hydrogen production using nuclear small modular reactor and concentrated solar power as a renewable energy source","abstract":"According to current predictions, hydrogen will serve as a key fuel and energy source by decreasing greenhouse gas (GHG) emissions. In this research an integral Pressurized Water Reactor-type Small Modular Reactor (iPWR-type SMR), connected to a molten-salt based Concentrated Solar Power (CSP) plant, producing electricity and hydrogen is investigated specifically, by modeling and simulations of a Nuclear-Renewable Hybrid Energy System (N-RHES). Optimization of design and functional variables/parameters, as complexity in system engineering, are considered as scenarios. The major results of this research is that multi-objective optimization provides recommended, operational scenarios to obtain preferred results in spite of variability of sunshine in terms of objectives, which are maximizing total profit and total heat equivalent. This research carried out based on modeling and simulations on MATLAB and Genetic Algorithms (GAs) for optimization is key for real life applications. Moreover, in terms of SMR safety-in-design, important time slots are given and explained in this thesis.","abstract_html":"According to current predictions, hydrogen will serve as a key fuel and energy source by decreasing greenhouse gas (GHG) emissions. In this research an integral Pressurized Water Reactor-type Small Modular Reactor (iPWR-type SMR), connected to a molten-salt based Concentrated Solar Power (CSP) plant, producing electricity and hydrogen is investigated specifically, by modeling and simulations of a Nuclear-Renewable Hybrid Energy System (N-RHES). Optimization of design and functional variables/parameters, as complexity in system engineering, are considered as scenarios. The major results of this research is that multi-objective optimization provides recommended, operational scenarios to obtain preferred results in spite of variability of sunshine in terms of objectives, which are maximizing total profit and total heat equivalent. This research carried out based on modeling and simulations on MATLAB and Genetic Algorithms (GAs) for optimization is key for real life applications. Moreover, in terms of SMR safety-in-design, important time slots are given and explained in this thesis.","abstract_has_math":false,"creators":["Ciftcioglu, Mustafa"],"institution":"University of Ontario Institute Technology","degree_name":"Master of Applied Science (MASc)","degree_level":null,"degree_discipline":"Nuclear Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Tokuhiro, Akira","Genco, Filippo"],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-12-01","date_published":"2022-12-01","updated_at":"2026-07-24T05:35:30Z","subjects":["Hydrogen production","Small modular reactors","Renewable energy","Thermochemical cycles","Multi-objective optimization"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10155/1566","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Tokuhiro, Akira","Genco, Filippo"]},{"key":"dc:creator","label":"Author","values":["Ciftcioglu, Mustafa"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2023-01-10T17:14:35Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2023-01-10T17:14:35Z"]},{"key":"dc:date.issued","label":"Date","values":["2022-12-01"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Nuclear Engineering"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Applied Science (MASc)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Ontario Institute Technology"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Hydrogen production","Small modular reactors","Renewable energy","Thermochemical cycles","Multi-objective optimization"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10155/1566"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["According to current predictions, hydrogen will serve as a key fuel and energy source by decreasing greenhouse gas (GHG) emissions. In this research an integral Pressurized Water Reactor-type Small Modular Reactor (iPWR-type SMR), connected to a molten-salt based Concentrated Solar Power (CSP) plant, producing electricity and hydrogen is investigated specifically, by modeling and simulations of a Nuclear-Renewable Hybrid Energy System (N-RHES). Optimization of design and functional variables/parameters, as complexity in system engineering, are considered as scenarios. The major results of this research is that multi-objective optimization provides recommended, operational scenarios to obtain preferred results in spite of variability of sunshine in terms of objectives, which are maximizing total profit and total heat equivalent. This research carried out based on modeling and simulations on MATLAB and Genetic Algorithms (GAs) for optimization is key for real life applications. Moreover, in terms of SMR safety-in-design, important time slots are given and explained in this thesis."]},{"key":"dc:title","label":"Title","values":["Optimized clean hydrogen production using nuclear small modular reactor and concentrated solar power as a renewable energy source"]}]}],"canonical_facts":{"dc:contributor.advisor":["Tokuhiro, Akira","Genco, Filippo"],"dc:creator":["Ciftcioglu, Mustafa"],"dc:date.accessioned":["2023-01-10T17:14:35Z"],"dc:date.available":["2023-01-10T17:14:35Z"],"dc:date.issued":["2022-12-01"],"dc:description.abstract":["According to current predictions, hydrogen will serve as a key fuel and energy source by decreasing greenhouse gas (GHG) emissions. In this research an integral Pressurized Water Reactor-type Small Modular Reactor (iPWR-type SMR), connected to a molten-salt based Concentrated Solar Power (CSP) plant, producing electricity and hydrogen is investigated specifically, by modeling and simulations of a Nuclear-Renewable Hybrid Energy System (N-RHES). Optimization of design and functional variables/parameters, as complexity in system engineering, are considered as scenarios. The major results of this research is that multi-objective optimization provides recommended, operational scenarios to obtain preferred results in spite of variability of sunshine in terms of objectives, which are maximizing total profit and total heat equivalent. This research carried out based on modeling and simulations on MATLAB and Genetic Algorithms (GAs) for optimization is key for real life applications. Moreover, in terms of SMR safety-in-design, important time slots are given and explained in this thesis."],"dc:identifier.uri":["https://hdl.handle.net/10155/1566"],"dc:language.iso":["en"],"dc:subject":["Hydrogen production","Small modular reactors","Renewable energy","Thermochemical cycles","Multi-objective optimization"],"dc:title":["Optimized clean hydrogen production using nuclear small modular reactor and concentrated solar power as a renewable energy source"],"dc:type":["Thesis"],"thesis:degree_discipline":["Nuclear Engineering"],"thesis:degree_name":["Master of Applied Science (MASc)"],"thesis:institution_name":["University of Ontario Institute Technology"]},"updated_at":"2026-07-24T05:35:30Z"}