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Al-Humaidi, H M (2007) A fuzzy logic approach to model delays in construction projects, Unpublished PhD Thesis, , Ohio State University.
Al-Kaabi, N S (2006) A fuzzy-based construction safety advisor (CSA) for construction safety in the United Arab Emirates, Unpublished PhD Thesis, , The Ohio State University.
Bu-Qammaz, A S A S (2015) Risk management model for international public construction joint venture projects in Kuwait, Unpublished PhD Thesis, , Ohio State University.
El-khawas, I N (1997) The optimal design of buildings: A life-cycle approach to energy efficiency, Unpublished PhD Thesis, , The Ohio State University.
Ellis, R A (1980) An analysis of the impact of public participation activities in water and transportation projects, Unpublished PhD Thesis, , Ohio State University.
Fereshtehnejad, S (2018) Multi-hazard lifecycle methods for aging structures and infrastructure systems, Unpublished PhD Thesis, , Ohio State University.
Garrett, C C (1991) Roadway infrastructure management and investment behavior studies for developing countries: A multicriteria approach to road improvement decision-making, Unpublished PhD Thesis, , The Ohio State University.
Godby, C J (2002) A computational study of lexicalized noun phrases in English, Unpublished PhD Thesis, , The Ohio State University.
Halfawy, M M R (1998) A multi-agent collaborative framework for concurrent design of constructed facilities, Unpublished PhD Thesis, , The Ohio State University.
Hauenstein, A D (1966) Construction: A taxonomy and syllabus of production practices with implications for industrial arts, Unpublished PhD Thesis, , The Ohio State University.
Jin, R (2013) A statistical modeling approach to studying the effects of alternative and waste materials on green concrete properties, Unpublished PhD Thesis, , Ohio State University.
- Type: Thesis
- Keywords: sustainability; feedback; pollution; recycling; reuse; experiment; regression analysis; questionnaire survey; simulation
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/1648131011
- Abstract:
The sustainability movement of the construction industry involves the application of environmentally friendly materials and recycling of waste streams. As the most widely consumed construction material worldwide, concrete consumes an astronomical amount of energy and concrete materials (e.g., cement, sand, and aggregates) to produce and becomes waste when it is demolished. In this research, “green” concrete is defined as concrete produced by using alternative or recycled waste materials that can save energy, reduce environmental pollution, reuse waste streams, improve concrete properties, and/or are locally available. These alternative cementitious and aggregate materials are defined as “green” concrete materials. Despite that the various types of “green” concrete materials have been studied previously in academia, there is not sufficient information on how those “green” concrete materials are used in concrete production and how the old concrete is recycled in the U. S. construction industry. This research started with the investigation of the current implementation of “green” concrete and old concrete recycling in the U. S. construction industry using the face-toface and online questionnaire survey approach. The survey identified the commonly used “green” concrete materials (e.g., fly ash, ground-granulated blast-furnace slag, silica fume, and lightweight aggregate) in the concrete industry and explored the current practice of old concrete recycling. The data collected from questionnaire surveys to industry practitioners links the academia research and industry concern. Based on the feedback collected from the survey, the “green” concrete materials, including the newly emerged Portland limestone cement (PLC), the most commonly used supplementary cementitious material fly ash Class F, and the locally available lightweight aggregate Haydite in Ohio, were selected for the follow-up experimental study. During the experiment, these “green” concrete materials were used to replace conventional materials (i.e. , Portland cement and pea gravel) by different percentages. In total 36 batches of concrete with different mixtures were casted. The tested concrete properties include slump, air content, and density of fresh concrete, as well as compressive and tensile strength of hardened concrete at different curing ages. The test results provided the knowledge of how these selected “green” concrete materials affected concrete properties. Through the literature review, this research found that the statistical modeling, as a potential approach to simulating the relationships between concrete properties and variables such as mixture design and curing age, had not been widely applied in the research of “green” concrete. Therefore, this research applied the multivariate regression analysis to predict the “green” concrete properties based on seven independent predicator variables in concrete mixture and curing age. Up to 17 types of regression models were proposed for the simulation, including both linear and non-linear formats. The best-fit model was identified in “green” concrete analysis based on R2, error analysis, analysis of variance, and Durbin-Watson value s. One additional batch of concrete was tested for model validation. The comprehensive list of independent predicator variables enabled the established regression model as a potential tool to predict concrete properties in “green” concrete research and practice. Compared with other methods, this statistical approach is economical and can provide relatively accurate results.
Mahmood, N A (2021) Real-time site safety risk assessment and intervention for on-foot building construction workers using RFID-based multi-sensor intelligent system, Unpublished PhD Thesis, , The Ohio State University.
Pan, N-F S (2001) Fuzzy reasoning expert scheduling system (FRESS) for highway construction subject to rain impact: A case study in Taiwan, Unpublished PhD Thesis, , Ohio State University.
Sadoun, B I (1992) A modeling methodology for energy-conserving site design, Unpublished PhD Thesis, , The Ohio State University.
Sarma, K C (2001) Fuzzy discrete multicriteria cost optimization of steel structures using genetic algorithm, Unpublished PhD Thesis, , The Ohio State University.
Sirca, G F (2019) Analysis of full-scale in-service civil engineering structures, Unpublished PhD Thesis, , The Ohio State University.
Stanbury, J A C (1992) An exploratory empirical study of the international consulting engineering design services industry: A United States perspective, Unpublished PhD Thesis, , Ohio State University.
Tseng, C-H (2006) Safety performance analyzer for constructed environments (SPACE), Unpublished PhD Thesis, , The Ohio State University.
Vargas, C A (1998) Investigating construction falls using fault tree analysis and developing a prototype tool to reduce falls using expert system and computer-assisted instruction methods, Unpublished PhD Thesis, , The Ohio State University.
Wee, S (1993) A prototype of an expert system for pavement maintenance and rehabilitation strategy in the state of Ohio (espresso), Unpublished PhD Thesis, , The Ohio State University.
Yang, F (2022) Ascending the pagoda: A ground-up exploration of the ancient construction methods of dayanta using virtual reality, Unpublished PhD Thesis, , The Ohio State University.
Yoo, W S (2007) An information-based decision making framework for evaluating and forecasting a project cost and completion date, Unpublished PhD Thesis, , Ohio State University.
Young, D R (1968) The development of a construction industry interest inventory, Unpublished PhD Thesis, , The Ohio State University.
Yu, B (2007) Essays on structural analysis of procurement auctions, Unpublished PhD Thesis, , The Ohio State University.