Abstracts – Browse Results
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Abraham, D M (1990) A state-based framework using indicators for construction monitoring and evaluation, Unpublished PhD Thesis, , University of Maryland, College Park.
Ahrari, A (2012) A decision support system for dynamic integrated project scheduling and equipment operation planning, Unpublished PhD Thesis, , University of Maryland, College Park.
Akar, G (2009) Analysis of activity choice: The role of activity attributes and individual schedules, Unpublished PhD Thesis, , University of Maryland, College Park.
Al-Fadhala, M M (2002) Uncertainty-based condition assessment of existing concrete structures, Unpublished PhD Thesis, , University of Maryland, College Park.
Al-Wazeer, A A-R (2007) Risk-based bridge maintenance strategies, Unpublished PhD Thesis, , University of Maryland, College Park.
Avetisyan, H G (2013) Sustainable infrastructure modeling and policy analyses: Construction, energy and transportation industries, Unpublished PhD Thesis, , University of Maryland, College Park.
Bai, L (2013) RFID sensor-driven structural condition monitoring in integrated building information modeling environment, Unpublished PhD Thesis, , University of Maryland, College Park.
Bender, W J (2000) A risk-based cost control methodology for constructing complex structures with the mobile offshore base as a case study, Unpublished PhD Thesis, , University of Maryland, College Park.
Chelson, D E (2010) The effects of building information modeling on construction site productivity, Unpublished PhD Thesis, , University of Maryland, College Park.
Chen, C-H (2003) Integrated management of highway maintenance and traffic, Unpublished PhD Thesis, , University of Maryland, College Park.
Cheung, M (2017) The antecedents of safety leadership, Unpublished PhD Thesis, , University of Maryland, College Park.
Chung, B (2007) An analysis of success and failure factors for ERP systems in engineering and construction firms, Unpublished PhD Thesis, , University of Maryland, College Park.
Ding, Q (2018) Using social media to evaluate public acceptance of infrastructure projects, Unpublished PhD Thesis, , University of Maryland, College Park.
Eldukair, Z A R (1988) Safety assessment and optimization of construction operations based on fuzzy sets, Unpublished PhD Thesis, , University of Maryland, College Park.
Erfani, A (2023) Data-driven risk modeling for infrastructure projects using artificial intelligence techniques, Unpublished PhD Thesis, , University of Maryland, College Park.
Hao, J X (2007) Infrastructure investment and economic development, Unpublished PhD Thesis, , University of Maryland, College Park.
Hickey, P J (2023) A study of gender diversity in u.S. Architecture, engineering, and construction (AEC) industry leadership, Unpublished PhD Thesis, , University of Maryland, College Park.
Hsu, S-C (2013) A complexity-based approach to intra-organizational team selection, Unpublished PhD Thesis, , University of Maryland, College Park.
Hu, M (2022) Influence of project design team characteristics on construction cost of sustainable buildings, Unpublished PhD Thesis, , University of Maryland, College Park.
Ingraham, A T (2001) Bidder-auctioneer cheating in sealed-bid auctions, Unpublished PhD Thesis, , University of Maryland, College Park.
Jang, W S (2007) Embedded system for construction material tracking using combination of radio frequency and ultrasound signal, Unpublished PhD Thesis, , University of Maryland, College Park.
Karimi, S (2021) A systematic methodology for evaluating and balancing acceptance risks with pay factors for highway construction materials, Unpublished PhD Thesis, , University of Maryland, College Park.
Lessani, A (2016) Decision analysis in construction claims, Unpublished PhD Thesis, , University of Maryland, College Park.
Lu, R (2010) Impacts of local item dependence of testlet items with the multistage tests for pass-fail decisions, Unpublished PhD Thesis, , University of Maryland, College Park.
McCahill, D F (1990) A practical model for simulation of earthwork construction, with applications for scheduling, Unpublished PhD Thesis, , University of Maryland, College Park.
Mohieldin, Y A (1989) Analysis of construction processes with nonstationary work task durations, Unpublished PhD Thesis, , University of Maryland, College Park.
Moore, W B (1989) Modeling the impact of large construction projects on surrounding communities, Unpublished PhD Thesis, , University of Maryland, College Park.
Neely, L E (2017) Project scheduling disputes: Expert characterization and estimate aggregation, Unpublished PhD Thesis, , University of Maryland, College Park.
Negahban, S (2008) Utilization of enterprise resource planning tools by small to medium size construction organizations: A decision-making model, Unpublished PhD Thesis, , University of Maryland, College Park.
Nyakaana Blair, A M A (1999) Risk analysis of cost and schedule of complex engineering systems, Unpublished PhD Thesis, , University of Maryland, College Park.
Ordonez Arizaga, J F (2007) A methodology for project risk analysis using Bayesian belief networks within a Monte Carlo simulation environment, Unpublished PhD Thesis, , University of Maryland, College Park.
Owoyemi, J A (2018) Performance evaluation of higway transportation design-build project delivery: A case study, Unpublished PhD Thesis, , University of Maryland, College Park.
Parvan, K (2012) Estimating the impact of building information modeling (BIM) utilization on building project performance, Unpublished PhD Thesis, , University of Maryland, College Park.
Quadri, H A (2019) Value engineering decisioneering: A risk management tool in the project management office- case study of electricity distribution companies in Nigeria, Unpublished PhD Thesis, , University of Maryland, College Park.
Salgado, C A (2005) Construction project organizational structuring, Unpublished PhD Thesis, , University of Maryland, College Park.
Shafahi, A (2016) Mathematical model and framework for multi-phase project optimization, Unpublished PhD Thesis, , University of Maryland, College Park.
Sharma, D K (2012) Design of availabilty payment mechanism for public private partnerships, Unpublished PhD Thesis, , University of Maryland, College Park.
Sundararajan, S K (2004) Project performance-based optimal capital structure for privately financed infrastructure projects, Unpublished PhD Thesis, , University of Maryland, College Park.
Tatari, M O (2009) Empirical analysis of construction enterprise information systems: Assessing the critical factors and benefits, Unpublished PhD Thesis, , University of Maryland, College Park.
Vecino, G A (2016) The feasibility of using web-based technology for the management of dredging projects, Unpublished PhD Thesis, , University of Maryland, College Park.
Yang, N (2010) Optimization of highway work zone decisions considering short-term and long-term impacts, Unpublished PhD Thesis, , University of Maryland, College Park.
Zeng, Y (2010) Risk management for enterprise resource planning system implementations in project-based firms, Unpublished PhD Thesis, , University of Maryland, College Park.
Zhao, Y (2023) Sustainability, acceptance risk analysis and machine learning in assessing mechanical properties and the impact of highway materials in transportation infrastructure, Unpublished PhD Thesis, , University of Maryland, College Park.
- Type: Thesis
- Keywords: population; sustainability; highway; natural resources; pipeline; specification; learning; life cycle; quality assurance; rehabilitation; service life; risk analysis; machine learning; Monte Carlo simulation; simulation; economic impact; pavement design
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/2832227931
- Abstract:
Improving the performance and extending the service life of transportation infrastructure is a long standing goal of Federal Highway Administration (FHWA) and the transportation community. Accurate prediction of the mechanical properties of highway materials are indispensable for enhancing the sustainability and resilience of transportation infrastructure since it provides accurate inputs for pavement mechanistic-empirical (ME) design and prediction of pavement distresses, helping to optimally allocate the maintenance needs and reduce testing frequencies which account for costly expenditures. Accurate prediction of materials properties can also reduce the acceptance risks during quality assurance (QA) without conducting extensive testing. Concrete plays an important role in the construction of transportation infrastructure. Developing an empirical and/or statistical model for accurately predicting compressive strength remains challenging and requires extensive experimental work. Thus, the objective of the study was to improve the prediction of concrete compressive strength using ML algorithms. A ML pipeline was proposed in which a two-layer stacked model was developed by combining seven individual ML models. Feature engineering was implemented, and feature importance was evaluated to provide better interpretability of the data and the model. This study promotes a more thorough assessment of alternative ML algorithms for predicting material properties.In addition, the quality of highway materials and construction translate directly to performance. To develop a statistically sound QA specification, the risks to the agency and contractor must be well understood. In this study, a Monte Carlo simulation model was developed to systematically assess the acceptance risks and the implications on pay factors (PF). The simulation was conducted using typical acceptance quality characteristics (AQCs), such as strength, for Portland cement (PCC) pavements. The analysis indicated that specific combinations of contractor and agency sample sizes and population characteristics have a greater impact on acceptance risks and may provide inconsistent PF. The proposed methodology aids both agencies and producers to better understand and evaluate the impact of sample sizes and population characteristics on the acceptance risks and PF.Finally, the use of recycled materials is a key element in generating sustainable pavement designs to save natural resources, reduce energy, greenhouse gas (GHG) emissions and costs. This study proposed a methodological life cycle assessment (LCA) framework to quantify the environmental and economic impacts of using recycled materials in pavement construction and rehabilitation. The LCA was conducted on two roadway projects with innovative recycled materials, such as construction and demolition waste (CDW) and rock dust. The proposed LCA framework can be used elsewhere to quantify the environmental and economic benefits of using recycled materials in pavements.