Civil Engineering

Permanent URI for this collectionhttps://hdl.handle.net/10679/9157

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    Feature extraction for enhancing data-driven urban building energy models
    (European Council on Computing in Construction (EC3), 2023) Bolluk, Muhammed Said; Seyis, Senem; Aydoğan, Reyhan; Computer Science; Civil Engineering; KAZAZOĞLU, Senem Seyis; AYDOĞAN, Reyhan; Bolluk, Muhammed Said
    Building energy demand assessment plays a crucial role in designing energy-efficient building stocks. However, most studies adopting a data-driven approach feel the deficiency of datasets with building-specific information in building energy consumption estimation. Hence, the research objective of this study is to extract new features within the climate, demographic, and building use type categories and increase the accuracy of a non-parametric regression model that estimates the energy consumption of a building stock in Seattle. The results show that adding new features to the original dataset from the building use type category increased the regression results with a 6.8% less error and a 30.8% higher R2 Score. Therefore, this study shows that building energy consumption estimation can be enhanced via new feature extraction equipped with domain knowledge.
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    Field reconnaissance on seismic performance and functionality of Turkish industrial facilities affected by the 2023 Kahramanmaras earthquake sequence
    (Springer, 2024-01) Sağbaş, Gülşah; Garjan, Ramin Sheikhi; Sarıkaya, Mahmut Kerem; Deniz, Derya; Civil Engineering; DENİZ, Derya; Sağbaş, Gülşah; Garjan, Ramin Sheikhi; Sarıkaya, Mahmut Kerem
    On February 6th, 2023, an earthquake sequence with moment magnitudes (Mw) of 7.8 and 7.5 rocked southern and eastern Turkiye, affecting 15 million-residents and a significant portion of Turkiye’s industrial community. In the days following the earthquake sequence, a reconnaissance team was organized to visit the industrial districts in the five provinces of the earthquake region. While performance and functionality of 131 industrial facilities were inspected using the proposed data-collection protocols, 18 interviews with industrial representatives were conducted. The inspection and interview results show that the earthquake sequence had a significant impact on industrial facilities, resulting in enormous economic losses and business disruptions lasting three months to two years. While the sequence imposed severe demands on the facilities, their poor performance is mostly due to discrepancies between seismic design code requirements and building practice. The most affected facilities were found to be those built before 2000, as well as precast reinforced concrete structures with pin-supported roofs. As a result, these types of facilities in earthquake-prone areas are strongly advised to be re-evaluated. Furthermore, various nonstructural building components, such as claddings and equipment/machinery, were substantially damaged at the majority of the assessed sites, causing lengthy interruptions. To reduce future seismic losses and disruptions to industry, the proposed protocols and findings of this field study can be utilized to support further resilience studies on the development of business continuity plans and risk management approaches for industrial facilities.
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    Multi-criteria decision-making model for risk management in modular construction projects
    (Taylor & Francis, 2024) Khodabocus, Sabah Fatima; Seyis, Senem; Civil Engineering; KAZAZOĞLU, Senem Seyis; Khodabocus, Sabah Fatima
    The modular sector needs a precise guide to determine the most efficient risk management approaches. The main research objective of this study is to develop a multi-criteria decision-making model to find the most efficient risk management approach according to the relevant risk criteria. The risk criteria and risk management approaches for modular construction projects were also identified and classified within this scope. A systematic literature review, semi-structured interviews, and open-ended questionnaires were performed for identification and classification purposes. For ranking and quantifying the identified risks and risk approaches, as well as developing the decision-making model, the Delphi method and the Analytical Hierarchy Process (AHP) were conducted. A two-round Delphi method, with eleven experts, was conducted to achieve efficient performance scores of the identified risk management approaches. The percentage standard deviation decreased, Relative Importance Index (RII), Cronbach’s alpha, and Kendall’s coefficient of concordance (Kendall’s W) were calculated to ensure the outputs’ reliability, validity, and agreement level. The AHP method opted to quantify the Delphi method outputs, solve the multi-criteria decision-making process, and develop the multi-criteria decision-making model for risk management of modular construction projects. Triangulation results show that the critical risk categories are supply chain, health and safety, stakeholders, and governmental support. Lean principles such as the Last Planner System, Value Stream Mapping, Just in Time, and Kaizen are top-rated risk management approaches. This research’s novelty is identifying and analyzing crucial risk categories, providing the relevant risk management approaches ranked according to efficiency performance, and presenting a decision-making model as a guideline for risk management of modular construction projects.
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    Conference ObjectPublicationOpen Access
    Two-part bio-based self-healing repair agent for cement-based mortar
    (International Center for Numerical Methods in Engineering, 2020) Tezer, Mustafa Mert; Bundur, Zeynep Başaran; Civil Engineering; BUNDUR, Zeynep Başaran; Tezer, Mustafa Mert
    Factors affecting durability of concrete structures are generally associated with each other. Due to its brittle nature, concrete can crack under stress and these cracks are one of the main reasons for a decrease in service life in concrete structures. Therefore, it is crucial to detect and recover microcracks, then to repair them as they were developed to wider cracks. Recent research in the field of concrete materials suggested that it might be possible to develop a smart cement-based material that is capable of remediate cracks by triggering biogenic calcium carbonate (CaCO3) precipitaton. This paper summarizes a study undertaken to investigate the self-healing efficiency of Sporosarcina pasteurii (S. pasteurii) cells immobilized on both diatomaceous earth and pumice, to remediate flexural cracks on mortar in early ages (28 days after mixing). To obtain a two-phase bio additive, half of the minerals were saturated with a nutrient medium consisting of urea, corn-steep liqueur(CSL) and calcium acetate and the cells with immobilized to the other half without nutrients. Screening of the healing process was done with ultrasonic pulse velocity (UPV) testing and stereomicroscopy. With this approach, the cracks on mortar surface were sealed and the water absorption capacity of the so-called self-healed mortar decreased compared to its counterpart cracked mortar samples.