Abstracts – Browse Results
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Akcamete, A (2011) A formal approach for managing facility change information and capturing change history as part of building information models (BIMs), Unpublished PhD Thesis, , Carnegie Mellon University.
Al-Dughaither, K A (1996) International construction financing strategies: Influential factors and decision-making, Unpublished PhD Thesis, , Carnegie Mellon University.
Amekudzi, A (1999) Uncertainty analysis of national highway performance measures in the context of evolving analysis models and data, Unpublished PhD Thesis, , Carnegie Mellon University.
Atasoy, G (2013) Visualizing and interacting with construction project performance information, Unpublished PhD Thesis, , Carnegie Mellon University.
Bello, M A (2012) Minimizing impediments to design for construction safety (DFCS) implementation on capital projects, Unpublished PhD Thesis, , Carnegie Mellon University.
Ben-Alon, L (2020) Natural buildings: Integrating earthen building materials and methods into mainstream construction, Unpublished PhD Thesis, , Carnegie Mellon University.
Coffelt, D P, Jr. (2008) Roof management improvement: Improving infrastructure management decision making through a consideration of total life cycle cost and deterioration, Unpublished PhD Thesis, , Carnegie Mellon University.
Dayanand, N (1996) Scheduling payments in projects: An optimization framework, Unpublished PhD Thesis, , Carnegie Mellon University.
Ergen, E (2005) Formalization of life-cycle data management of engineered-to-order components using advanced tracking technologies, Unpublished PhD Thesis, , Carnegie Mellon University.
Gordon, C (2006) A formalism and a framework for planning of sensor-based construction inspections, Unpublished PhD Thesis, , Carnegie Mellon University.
He, R (2023) Modeling of sustainable materials management systems: Hybrid science-based, data-driven approaches, Unpublished PhD Thesis, , Carnegie Mellon University.
- Type: Thesis
- Keywords: complexity; decision support; sustainability; circular economy; climate change; forecasting; innovation; learning; materials management; policy; waste disposal; waste management; neural network; quantification; machine learning
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/2805814234
- Abstract:
Fueled by growing waste generation, worsening impacts of climate change, and tightening resource constraints, societies are beginning to pivot to a circular economy, of which sustainable materials management (SMM) is a crucial component. Under this SMM paradigm, solid waste management systems (SWMS) need to serve the dual purposes of waste disposal and resource valorization in technologically feasible, economically beneficial, environmentally responsible, and socially benign ways. This requires innovative holistic approaches for understanding the flows and stocks of resources, deploying appropriate treatment and valorization technologies, and mobilizing social and financial capital. To advance the scientific understanding of SMM and to tackle the dilemma of coupling between complex science and scarce data, this dissertation leverages system dynamics perspectives and data-driven quantification capabilities to develop novel science-based, data-driven models for supporting real-world SMM decisions.As a prerequisite of SMM, a hybrid demand forecast framework is built by integrating empirical evidence-informed future scenarios into a stocks dynamics model to project future stocks and flows of materials. This adaptable framework is applied to forecast the U.S. copper demand and stocks from 2016 to 2070, which reveals a stabilizing trend of per capita in-use stock and growing trends of consumption and end-of-life (EOL) copper generation. By analyzing various U.S.-specific future scenarios, the recovery of EOL materials is identified as a main sustainability challenge. To understand the mechanisms of EOL recovery and the potential of data-driven modeling, a comprehensive global knowledge base is built by reviewing and compiling data on municipal solid waste (MSW) generation, characterization, and management practices. A total of 1,720 records from various reputable sources, including NGO databases, governmental reports, and peer-reviewed articles are collected to build statistical models that predict MSW generation, composition, and management practices using 18 socioeconomic variables. This knowledge base not only systemizes sub-domains of SWMS knowledge into a comprehensive framework, but also highlights pervasive data and knowledge gaps. To address the need for decision support in the new era of SMM while facing the challenge of insufficient data, a novel hybrid machine learning model is built by imposing the holistic decision-making context of SWMS on a traditional neural network architecture. The hybrid model is capable of learning various technical, economic, and behavioral aspects of SWMS using the relatively small and heterogeneous dataset in the knowledge base. In comparison, the hybrid model not only outperforms traditional machine learning models with similar complexity in prediction errors and convergence rates, but also offers superior interpretability for policy decision support.In summary, this dissertation is intended to empower SMM decision makers with a suite of hybrid tools for forecasting material flows and stocks, revealing the data landscape of EOL streams, and modeling the entire decision-making context of SWMS. From the methodology innovation standpoint, this dissertation pioneers and contributes to the nascent research field of integrating sustainability science with data science.
Herabat, P (1997) A functional specification for a decision support system to select bridge analysis tools, Unpublished PhD Thesis, , Carnegie Mellon University.
Kiliccote, H (1997) A standards processing framework, Unpublished PhD Thesis, , Carnegie Mellon University.
Kiziltas, S (2008) An automated approach for developing integrated model-based construction project histories to support estimation of activity production rates, Unpublished PhD Thesis, , Carnegie Mellon University.
Lee, K J (2013) A formal and ontological approach to embed commissioning test protocol into building information model, Unpublished PhD Thesis, , Carnegie Mellon University.
Lee, S H (2009) Computational fieldwork support for efficient operation and maintenance of mechanical, electrical and plumbing systems, Unpublished PhD Thesis, , Carnegie Mellon University.
Ochoa Franco, L A (2004) Life cycle assessment of residential buildings, Unpublished PhD Thesis, , Carnegie Mellon University.
Pradhan, A R (2009) An approach for fusing data from multiple sources to support construction productivity analyses, Unpublished PhD Thesis, , Carnegie Mellon University.
Reich, Y (1991) Building and improving design systems: A machine learning approach, Unpublished PhD Thesis, , Carnegie Mellon University.
Reinhardt, J (2003) Navigational models for effective and efficient interaction with integrated product and process models on construction sites, Unpublished PhD Thesis, , Carnegie Mellon University.
Resendiz-Carrillo, D (1990) Risk-based framework for the selection of socially optimal dam safety goals, Unpublished PhD Thesis, , Carnegie Mellon University.
Rivard, H (1997) A building design representation for conceptual design and case-based reasoning, Unpublished PhD Thesis, , Carnegie Mellon University.
Sharrard, A L (2007) Greening construction processes using an input-output-based hybrid life cycle assessment method, Unpublished PhD Thesis, , Carnegie Mellon University.