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Doctor of Philosophy with a Major in Building Construction

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search.filters.applied.f.advisor: Ashuri, Baabak × search.filters.applied.f.isSeriesOfPublicationTitle: Building Construction and Facility Management Graduate Program ×

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Now showing 1 - 7 of 7
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    Industry 4.0 And Short-Term Outlook for AEC Industry Workforce
    (Georgia Institute of Technology, 2021-12-13) Quintana, Emilio
    Technology is uniquely transforming our society to a significant degree. This transformation has been described as Industry 4.0 and encompasses machine learning, computerization, automation, artificial intelligence, and robotics. Industry 4.0 is currently impacting the United States’ workplace and is projected in continue uniquely changing our society over the next twenty years or so. Looking specifically at the AEC industry, this paper researches how the AEC industry workplace could be impacted by Industry 4.0 over the next several years. The hypothesis that jobs more at risk for automation should see low or negative growth and lower wages over the next several years was tested by using U.S. Bureau of Labor Statistics (BLS) occupational wage data and growth projections to create an opportunity value for each occupation, and then evaluating the relationship between the opportunity value and probability of automation. A statistical significance was found between the two variables. The hypothesis that certain skills are particularly associated with high growth/high wage jobs versus low growth/low wage jobs was tested by scraping important skills/qualities from the individual occupational webpages hosted by the U.S. Bureau of Labor Statistics, and then comparing the approximately top 80% of skills scraped between the two groups. Certain skills/qualities were found to be particularly associated with each group. Finally, the occupations associated with the AEC industry were compared with the findings from the first two hypotheses. The discoveries were that the AEC industry is potentially more susceptible to Industry 4.0 than other industries. This research is of significance because research into how the AEC industry workplace will be impacted by Industry 4.0 over the next several years was not found in the research background, and it has implications on potential career choices, skill requirements, and areas of research and development. Recommendations for future work include utilizing new data sources, Monte Carlo simulations, cohort analysis, and cluster analysis to make more specific forecasts on Industry 4.0’s impact on the AEC industry.
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    Changes in quality management approaches for design-build highway projects
    (Georgia Institute of Technology, 2018-04-27) Lee, Jung Hyun
    The purpose of this study is to determine changes in quality management approaches of design-build (DB) highway projects compared to those in design-bid-build (DBB) projects. Identifying the existing challenges in the quality management procedures in DB environment requires conducting a content analysis. This involved reviewing regulations, FHWA policy documents, quality manuals, and state DOT solicitation documents. To obtain a deeper understanding of the state of the practice in state DOTs and to identify best practices in handling the identified challenges, this study conducted structured interviews of DOT personnel and industry experts. The results indicate that responsibility for quality assurance is being transferred to design-build teams. The findings of this study show six areas of changes in DB highway projects: (1) acceptance approaches; (2) selection criteria; (3) independent assurance procedures; (4) non-conformance reports; (5) cost mechanisms; and (6) pay factor adjustment.
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    Challenges and opportunities in environmental planning and permitting on transportation design-build projects
    (Georgia Institute of Technology, 2013-07-03) Hannon, David
    Environmental planning and permitting for transportation projects is often seen as one of the top reasons for project delay. On design-build projects, this process is often treated as the critical path to advertising the project and on all transportation projects many critical phases of the project such as right of way acquisition, final design, and construction cannot begin until the environmental planning process is complete. The objective of this research is to identify challenges to the environmental planning and permitting process and opportunities for managing those challenges. To identify these challenges and opportunities, a synthesis of transportation and design-build research was done along with interviews with agencies leaders at seven State Departments of Transportation (DOTs). Once these challenges and opportunities were identified, example environmental planning documents and requests for proposals were reviewed from various State DOTs to document their usage. Additionally follow up interviews were conducted with environmental planning experts with experience on design-build projects from six of the State DOTs that were previously interviewed. This research contributes to the state of knowledge through providing comprehensive information on environmental planning and permitting challenges that must be managed on design-build transportation projects and opportunities for managing these challenges. Managing the identified challenges by utilizing these opportunities provides transportation agencies with opportunities to make the environmental planning and permitting process on design-build projects more efficient. This research contributes to the state of practice of transportation agencies through providing opportunities for streamlining environmental analysis and permitting that is vital to transportation agencies who strive to accelerate the delivery of design-build projects.
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    Testing the impact of using cumulative data with genetic algorithms for the analysis of building energy performance and material cost
    (Georgia Institute of Technology, 2012-11-14) Dingwall, Austin Gregory
    The demand for energy and cost efficient buildings has made architects and contractors more aware of the resources consumed by the built environment. While the actual economic and environmental costs of future construction can never be completely predicted, energy simulations and cost modeling have become accepted ways to guide the design and construction process by comparing possible outcomes. These tools are now commonplace in the construction industry, and researchers are continuing to develop new and innovative strategies to optimize building design and construction. Previous research has proven that genetic algorithms are effective methods to evaluate and optimize building design in situations that contain a large number of possible solutions. The technique makes a computationally difficult multi-optimization process possible but is still a reactive and time consuming process that focuses on evaluation rather than solution generation. This research presented in this paper builds upon established multi-objective optimization techniques that use an energy simulator to estimate a conceptual building’s energy use as well as construction cost. The study compares simulations of a simplified model of a 3-story inpatient hospital located in Atlanta, Georgia using a defined set of variables. A combined global minimum of annual energy consumption and total construction is sought after using a method that utilizes a genetic algorithm. The second phase of this research uses a modified approach that combines the traditional genetic algorithm with a seeding method that utilizes previous results. A new set of simulations were established that duplicates the initial trials using a slightly modified set of design variables. The simulation was altered, and the phase one trials were utilized as the first generation of simulated solutions. The objective of this thesis is to explore one method of making energy use and cost estimating more accessible to the construction industry by combining simulation optimization and indexing. The results indicate that this study’s proposed augmented approach has potential benefits to building design optimization, although more research is required to validate this hypothesis in its entirety. This study concludes that the proposed approach can potentially reduce the time needed for individual optimization exercises by creating a cumulative, robust catalog of previous computations that will inform and seed future analyses. The research was conducted in five general stages. The first part defines the research problem and scope of research to be conducted. In the second part, the concepts of genetic algorithms and energy simulation are explored in a comprehensive literature review. The remaining parts explain the trial simulations performed in this study. Part three explains the experiment’s methodology, and part four describes the simulation results. The fifth and final part looks at what the possible conclusions that can be made from analyzing the study’s results.
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    Creating a framework for the successful implementation of energy retrofit projects: a detailed case study of energy retrofits in Atlanta's Chastain Park
    (Georgia Institute of Technology, 2012-04-10) Pope, Bryan Christopher
    This paper seeks to develop a framework for the successful implementation of energy retrofit projects in all settings, including those with the non-traditional structure and unique needs of some non-profit organizations. This will be accomplished using researched strategies for overcoming commonly associated challenges along with experiences gained through a real-life case study involving a multi-facility retrofit project in Atlanta's largest public park, Chastain Park. The framework includes the application of research based solutions for common challenges as well as specific strategies for the translation of collected data into an actual scope of work, methods for the collection of bids and selection of contractor(s), the importance of and methods for communicating amongst stakeholders, and the need for a dedicated project manager on site at all times.
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    Economic evaluation of flexible partitions
    (Georgia Institute of Technology, 2010-05-27) Phometsi, Mothusi
    Corporate Real Estate (CRE) investors are often confronted with a need for flexibility in buildings. They often embark on costly renovations to accommodate changing use requirements. When new needs arise, landlords and tenants often risk loss due to inability to easily switch to configurations that can meet those needs. The main cause for this problem is lack of a planning model that can allow buildings to easily evolve over time allowing decision-makers to hedge investment positions against risk due to uncertainty. The emergence of Real Options (RO) theory in the 1970's has led to debates in search of a better planning model for real projects. The success of RO application in building construction (BC) hinges on the development of models that can be used to assess economic performance of flexible design options (FDO) in building systems. For building interior spaces, there is currently no model that can value flexibility of partition systems. The purpose of this study is to present a model that can be used to value flexibility in mutually exclusive partition systems over a project's life span. The proposed model uses decision tree representation, stochastic forecasting and random sampling of decision-path scenarios to generate cumulative risk profiles of partition systems' life cycle costs with expected median value, standard deviation and variance to inform decision making under uncertainty. The research processes include: assumptions, decision-making structure for identification of uncertain variable, model representation, spreadsheet programming, Monte Carlo simulation, and validation. The model will enable application of RO "in" BC projects.
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    Statistical analysis of residential housing prices in an up and down real estate market: a general framework and study of Cobb County, GA
    (Georgia Institute of Technology, 2009-11-17) Corsini, Kenneth Richard
    The recent economic recession has had a significant impact on residential real estate both nationally and regionally. Our research is focused specifically on Cobb County, Georgia and the impact that the declining economy has had on home buying and property values in this area. Specifically, this research aims to identify changes in the residential market in terms of significant characteristics of housing and their corresponding effect on home values.