A Framework for Coupling and Quantifying Sustainability and Resilience in Intelligent Buildings
A Master of Science thesis in Engineering Systems Management by Deena Ahmed Al Qurneh entitled, “A Framework for Coupling and Quantifying Sustainability and Resilience in Intelligent Buildings”, submitted in July 2020. Thesis advisors is Salwa Beheiry, Dr. Maruf Mortula. Soft copy is available (Thes...
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| Format: | doctoralThesis |
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2020
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| Online Access: | http://hdl.handle.net/11073/19716 |
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| _version_ | 1864513442473312256 |
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| author | Al Qurneh, Deena Ahmed |
| author_facet | Al Qurneh, Deena Ahmed |
| author_role | author |
| dc.contributor.none.fl_str_mv | Beheiry, Salwa Mortula, Maruf |
| dc.creator.none.fl_str_mv | Al Qurneh, Deena Ahmed |
| dc.date.none.fl_str_mv | 2020-08-11T08:19:34Z 2020-08-11T08:19:34Z 2020-07 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | 35.232-2020.23 http://hdl.handle.net/11073/19716 |
| dc.language.none.fl_str_mv | en_US |
| dc.subject.none.fl_str_mv | Sustainability Resilience Intelligent Buildings Net Present Value |
| dc.title.none.fl_str_mv | A Framework for Coupling and Quantifying Sustainability and Resilience in Intelligent Buildings |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/doctoralThesis |
| description | A Master of Science thesis in Engineering Systems Management by Deena Ahmed Al Qurneh entitled, “A Framework for Coupling and Quantifying Sustainability and Resilience in Intelligent Buildings”, submitted in July 2020. Thesis advisors is Salwa Beheiry, Dr. Maruf Mortula. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form). |
| format | doctoralThesis |
| id | aus_aa2226eeb00be1226b4c790903c086c3 |
| identifier_str_mv | 35.232-2020.23 |
| language_invalid_str_mv | en_US |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/19716 |
| publishDate | 2020 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | A Framework for Coupling and Quantifying Sustainability and Resilience in Intelligent BuildingsAl Qurneh, Deena AhmedSustainabilityResilienceIntelligent BuildingsNet Present ValueA Master of Science thesis in Engineering Systems Management by Deena Ahmed Al Qurneh entitled, “A Framework for Coupling and Quantifying Sustainability and Resilience in Intelligent Buildings”, submitted in July 2020. Thesis advisors is Salwa Beheiry, Dr. Maruf Mortula. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).The concepts of sustainability and resilience have become increasingly important. Sustainability is often related to implementing best practices in many facets of the construction industry and resilience typically refers to the adaptability and endurance of systems in harsh conditions. Both concepts are studied over the life cycles of buildings. On the other hand, smart buildings are growing in use and scope and tend to be more dependent on technology and complex systems. Therefore, they also tend to be more prone to unexpected failure. While the two concepts of sustainability and resilience are interrelated, there is limited research that quantifies and/or combines them, and none studying how the two behave when developers aim to apply both in smart buildings. Hence, this study constructed a framework that developed a financial model where the Net Present Value (NPV) was used to study the implications and limitations of the investment in both concepts, i.e. the NPV was measured using direct and indirect costs and benefits resulting from having sustainability and resilience integrated in smart buildings. Thus, translating the benefits of this integration into monetary values. Sustainability was essentially quantified via translating the costs and benefits of the three main components: environmental, social and economic. While resilience was measured via the impact frequency of faults and the absence of detection tools on the calculated NPV. The two were then coupled by measuring the costs and benefits of installing and maintaining resilience tools in sustainably designed smart buildings and studying this impact on the resultant NPV. The designed model was also applied on four case studies of selected smart buildings in Dubai. The results of the study indicate that integrating the targeted sustainable approaches in smart buildings, with tools that improve resilience, yield a higher NPV. However, to maintain the positive effect on the NPV and to minimize the cost of failure, fault detection and diagnosis tools need to be assimilated in the initial smart and sustainable buildings design.College of EngineeringMultidisciplinary ProgramsMaster of Science in Engineering Systems Management (MSESM)Beheiry, SalwaMortula, Maruf2020-08-11T08:19:34Z2020-08-11T08:19:34Z2020-07info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2020.23http://hdl.handle.net/11073/19716en_USoai:repository.aus.edu:11073/197162025-06-26T12:28:55Z |
| spellingShingle | A Framework for Coupling and Quantifying Sustainability and Resilience in Intelligent Buildings Al Qurneh, Deena Ahmed Sustainability Resilience Intelligent Buildings Net Present Value |
| status_str | publishedVersion |
| title | A Framework for Coupling and Quantifying Sustainability and Resilience in Intelligent Buildings |
| title_full | A Framework for Coupling and Quantifying Sustainability and Resilience in Intelligent Buildings |
| title_fullStr | A Framework for Coupling and Quantifying Sustainability and Resilience in Intelligent Buildings |
| title_full_unstemmed | A Framework for Coupling and Quantifying Sustainability and Resilience in Intelligent Buildings |
| title_short | A Framework for Coupling and Quantifying Sustainability and Resilience in Intelligent Buildings |
| title_sort | A Framework for Coupling and Quantifying Sustainability and Resilience in Intelligent Buildings |
| topic | Sustainability Resilience Intelligent Buildings Net Present Value |
| url | http://hdl.handle.net/11073/19716 |