Doctor of Philosophy with a Major in Building Construction

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Doctor of Philosophy with a Major in Building Construction

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https://hdl.handle.net/1853/72547

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Degree Series

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School of Building Construction

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Now showing 1 - 10 of 23

Product Model Exchange Standards for Cast-in-Place Reinforced Concrete: Implementation Methods, Value Considerations, and Application to Design Indicators

(Georgia Institute of Technology, 2022-04-27) Garcia Bottia, Leonardo

Building Information Modeling (BIM) has changed the way information in design and construction is communicated by allowing the possibility of exchanging project models and data together. To optimize the process, standards have been developed to define what is required in each exchange and how to represent it. For several years Cast-in-Place (CIP) reinforced concrete (RC), one of the most important construction materials worldwide, has been subject to considerable efforts toward the development of its standards. However, the monolithic nature of the material and its complex supply chain makes it difficult for this development to be properly carried out. This dissertation presents the results of a study with four key aims: (1) identify how exchange standards for CIP RC fit into current engineering and construction practices, (2) develop the requirements and methods for implementation, (3) study the value considerations of implementing the standards in practice, and (4) apply the information available in exchange standards to enhance the design and construction processes through the estimation of design indicators. This research is developed in the context of the undergoing efforts of the American Concrete Institute (ACI) to develop industry-wide standards for CIP RC concrete. To map the current engineering practices and challenges regarding CIP RC model exchanges, the dissertation presents the results of an ethnographic-action study performed to allow a description of current behaviors, the acquisition of qualitative data regarding the advantages of implementing BIM standards on a practical level, and to inform of potential additional requirements for standardization. To assist the implementation of standards in practice, this dissertation presents a set of methods for implementation that adapt to current tools and practices. To study the value considerations of implementing exchange standards, the same CIP RC processes captured in the ethnographic study are reproduced using the methods developed for model exchange standards. Finally, the study presents the results of a logistic regression model developed to use the parametrized information made available through these exchanges, to estimate indicators that improve the design and construction processes. In conclusion, this research provides recommendations to further develop CIP RC modeling and exchange standards, studies how design and construction practice aligns with new CIP RC standard workflows, provides methods for implementation, and develops a model useful to predict design indicators during early stages using the valuable information embedded in CIP RC exchange standards.
Mitigation of Business Risk Exposure in Public Higher Education Facilities Management Using Key Performance Indicators: Analysis of the University System of Georgia

(Georgia Institute of Technology, 2021-05-25) Maddox, Anthony J.

The post-secondary education sector has sustained significant student growth, which has led to the expansion of institutional buildings and infrastructure. With increased growth and expansion experienced in previous years, appropriate operational funding has not always matched growth. This lack of funding can cause an increase of deferred maintenance and capital renewal, which results in an increase in Business Risk Exposure (BRE) to the organization. The objective of this study is to examine the facilities operational and capital funding of the University System of Georgia institutions. Funding will be compared to counterparts within a Facilities Performance Indicator (FPI) report in order to understand if operational funding is adequate or below comparable institutions. This report is comprised of educational institutions across the United States volunteering current facility information, created annually by the Association of Physical Plant Administrators (APPA).
Conceptual framework for incorporating access for maintainability considerations in BIM coordination

(Georgia Institute of Technology, 2020-05-05) Sierra Aparicio, Monica Viviana

Access to perform maintainability tasks has been addressed by facility managers as one of the common struggles they face once the construction project is delivered. The development of Building Information Modeling (BIM) has proved the potential to foresee, identify, and remove the physical barriers for maintenance teams in order to allow a better compliance of their tasks and to ensure that equipment is timely and effectively reviewed. Also, rule-based software might enhance the revision of the Americans with Disabilities Act (ADA) compliance checks, easing the decision-making process in regard to end-user accessibility. Tools such as Solibri have rule templates for a few ADA checks. Yet, there is not a framework that can provide complete operational constraints and foresees the avoidance of accessibility concerns during the design phase. The objective of this study is to develop a proof of concept that addresses access for maintainability requirements during the coordination procedure, ensuring a welcoming and equitable environment for everybody. In order to introduce accessibility preconditions to an automated rule generator, the interpretation and reduction of the regulation needs to be done first. Afterward, the decoded restrictions are introduced into a Dynamo script, which will make them visible on the clash detection tool during the coordination procedure. Later on, the proposed framework will be tested on a case study. The proposal might contribute to the reduction of the project’s lifecycle costs by considering maintainability restrictions earlier in the design process. Moreover, inputs related to disabled individuals’ daily struggles might be further developed by fining tune the proof of concept. Therefore, those issues might be included as a driver, following a human-centered design process. Furthermore, the incorporation of those constraints will contribute to the execution of a resilient building, capable of satisfying its occupants displacement requirements.
DECISION SUPPORT FRAMEWORK FOR TRANSFORMING URBAN BUILDINGS AT MULTIPLE SCALES

(Georgia Institute of Technology, 2020-04-25) Chang, Soowon

Due to the increasing population, cities are requiring more energy. Among urban elements, buildings account for about 40% of energy demands and 30% of carbon dioxide emissions globally. To address the increase of energy demands and environmental responsibility, existing buildings should be transformed into highly energy efficient forms. This research explores how to support decisions that affect performance-driven smart and resilient urban systems focusing on building renovations. The research scope covers the redevelopment of existing built forms at multiple scales. Since urban objects influence urban patterns at other scales, both individual and collective performances of buildings at larger scales should be evaluated to support proper redevelopment decisions. In addition, the transformation of existing buildings will encounter different problems and challenges at different scales in urban areas. On an individual building level, the selection of different envelope options can project the future architectural environment of buildings. On a block level, the performance will be changed along with combinations of building typologies such as land use, height, floor area, etc., and therefore changes to building typologies should be managed collectively to improve the performance. When PV are applied in buildings and hourly electricity demands are recognized, the dynamic energy flows on a community level will become complex to manage. In this respect, this research is devised to identify and address redevelopment problems at different scales: individual buildings, block, and community. On the individual building level, this research studies how to support decision-making when optimizing the selection of building envelopes by using a Genetic Algorithm (GA). Based on the findings from optimizing at each scale, an interdependence of building parameters and multiple performance is observed. Therefore, decision frameworks across multiple scales are extrapolated to support community-driven and building-driven decisions. On the block level, this research explores how existing building typologies influence multiple performance indicators in a collective manner to support reconfiguring decisions using a Bayesian Multilevel Modeling. On the community level, this study addresses how the community can optimize block boundaries for resiliently managing the energy demand and supply of groups of buildings by using K-nearest neighbors (KNN) and community clustering algorithms. This research will contribute to making appropriate decisions for investment, regulations, or guidelines when renovating physical building assets at different scales in urban areas. The research findings will consolidate theoretical understandings about the relationships between building design and construction parameters considering multiple performance indicators at multiple scales in urban areas. Since many cities are at the tipping point trying to become more resilient, increasingly focusing on sustainability, economic feasibility, and human well-being, a better understanding of the impact of built forms at multiple scales will support urban development decisions for the future smart and connected communities.
Clash Resolution Optimization based on Component and Clash Dependent Networks

(Georgia Institute of Technology, 2020-04-25) Hu, Yuqing

Effective coordination across multi-disciplines is crucial to make sure that the locations of building components meet physical and functional constraints. Building information modeling (BIM) has been increasingly applied for coordination and one of its most widely used applications is automatic clash detection. The realistic visualization function of BIM helps reduce ambiguity and expedites clash detection. However, many project participants criticize automatic clash detection, as many detected clashes are irrelevant with no significant impact on design or construction work, thereby decreasing the precision of clash results and the benefits of BIM. In addition, clash detection consists of discovering problems, but it does not entail solving these clashes. Even though some studies discussed automatic clash detection, they rarely discussed the dependence relationships between building components. However, a building is an inseparable whole, and the dependent relationships among building components propagate the impact of clashes. Relocating one object to correct one clash may result in other objects violating spatial constraints, which may directly cause new clashes or indirectly cause them through relocating other components. Therefore, figuring out the dependency among clash objects with peripheral building components is useful to optimizing clash solutions by avoiding change propagation. Algorithms are designed to automatically capture dependency relations from models to construct a component dependency network. The network is used as an input to distinguish irrelevant clashes for improving clash detection quality by analyzing the relations between clash components and the relations between clash components with their nearby components. The feasibility to harness the clash component network and graph theory are also explored to generate the clash component change list for minimizing clash change impact from a holistic perspective. In addition, this study demonstrates how to use BIM information to refine clash management, and specifically focus on designing a hybrid clash correction sequence to minimize potential iterative adjustments. The contributions of this study exist at three levels. The most straightforward contribution is that this research proposed a method to improve clash detection quality as well as to provide decision support for clash resolution, which can help project teams to focus on important clashes and improve design coordination efficiency. In addition, this research proposes a new perspective to view clashes, switching the clash management focus and inspiring researchers to focus on finding global optimal solutions for all clashes other than a single clash. The third level is that even though this research focuses on clash management, the optimization algorithms based on graph theory can be used in other interdependent systems to improve design and construction performance.
Decision support system for the integration of sustainable parameters in single-family housing project delivery

(Georgia Institute of Technology, 2019-07-26) Tijo, Silvia Juliana

The implementation of sustainable practices in building construction has a direct impact on the financial, environmental, and social dimensions of sustainable development. Powering and heating buildings consumes enormous amounts of energy, and the residential and commercial building sector remains the largest end-use sector for energy in the U.S. The fact that actual energy consumption of this sector is two-fifths of the total energy consumption in the United States represents a significant economic opportunity for the country. In spite of the progress in performance and affordability of sustainable technologies, materials, and systems, the residential sector is behind in adopting these in single-family homes. Several building aspects must undergo evaluation under a holistic approach to achieving the technical and economic success of the project, but the fragmentation of the industry and the required expertise level for using existing simulating tools represent a barrier for this purpose. In residential projects, the selection of design and construction parameters occurs mostly during the early stages of the pre-construction process, while the majority of the building simulation tools require information from late stages of the process. During the early stages, the designer cannot easily predict the impact of decisions on building performance and cost. Furthermore, existing methodologies do not integrate project goals in early stages (i.e., pre-design, conceptual design, and schematic design) of the pre-construction process. Without these methodologies, selecting sustainable parameters for housing delivery and implementing sustainable principles is difficult, and consequently jeopardizes reaching sustainable goals for the building. The result of this research is a decision support system (DSS) that uses the analytic hierarchy process (AHP) and system dynamics (SD) to assist decision makers in the selection of construction parameters for sustainable housing. The proposed DSS integrates a set of project goals in the process of selecting alternatives, allowing a balance between the preferences of the decision maker and the solution that better fits those preferences. The approach focuses more on using DSS to support design exploration rather than finding optimal solutions. Given the iterative nature of the design process and the fragmentation of the construction industry, the proposed DSS provides information about costs, duration, and environmental impact of the alternatives at early stages of the project development. Therefore, an objective comparison of different design alternatives under identical conditions can take place, and the decision maker can learn from the effects of new decisions over other parameters that are interrelated. The outcomes of the research can help developers, architects, and home-owners to define sustainable parameters at early stages of the project delivery when the impact of their decisions is higher, and the cost of implementing changes is lower than in the later stages.
Sustainable energy technology, adoption, rebound, and resilience

(Georgia Institute of Technology, 2019-01-22) Hashemi Toroghi, Shahaboddin

While in the United States, centralized generation and distribution network are the basis of the current electric infrastructure, the recent surge in uptake of solar photovoltaic (PV) systems introduces a new avenue to decentralize this system. Furthermore, PV systems can substitute the grid electricity and increase the share of renewable energy sources. While by 2018, five states in the U.S. (California, Hawaii, Nevada Massachusetts, and Vermont) could reach 10% threshold for the share of solar sources in generating electricity, at the country level this share is still less than 3%; whereas in some other countries, such as Germany and Japan, it has already reached more than 6%. This dissertation examines the diffusion of PV systems from three perspectives, addressing three gaps in knowledge: an empirical study of the diffusion of PV systems in Georgia, a method to estimate renewable rebound effect, and a framework to quantify the resilience capacity of an electric infrastructure system with emergency electricity generators, including PV systems. Three studies present the primary contributions of this research. Study 1 examines the diffusion of PV systems in Georgia, identifies characteristics of adopters and patterns of adoption, and forecasts the future adoption of PV systems. Study 2 introduces a new approach to estimate the direct rebound effect, subsequent of a major adoption of PV systems. Study 3 presents a state-of-the-art framework that quantifies the resilience capacity of an electric infrastructure system with emergency electricity generators. The findings of the study 1 provides a benchmark for the future adoption of PV systems and highlights the impact of socio-economic and location-based factors in the diffusion of PV systems in Georgia. These findings can be used to shape a more effective policy, aiming to increase the share of PV systems, or evaluate the effectiveness of a policy. The finding of the study 2 opens a new avenue to compute the rebound effect and can support development of a policy to mitigate the renewable rebound effect in a targeted region. The finding of the study 3 can help system designers to customize the design of a resilient system based on its characteristics. The introduced framework can further be used to investigate improvement of the resilience capacity in an electric infrastructure system by increasing the penetration of PV systems, or other decentralized electricity generators in a region.
If these walls could talk: Automated performance measurement for building modeling decisions using data analytics

(Georgia Institute of Technology, 2018-01-10) Yarmohammadi, Saman

Building information modeling (BIM) is instrumental in documenting design, enhancing customer experience, and improving product functionality in capital projects. However, high-quality building models do not happen by accident, but rather because of a managed process that involves several participants from different disciplines and backgrounds. Throughout this process, the different priorities of design modelers often result in conflicts that can negatively impact project outcomes. There is a need for effective management of the modeling process to prevent such unwanted outcomes. Effective management of this process requires an ability to closely monitor the modeling process and correctly measure the modelers' performance. Nevertheless, existing methods of performance monitoring in building design practices lack an objective measurement system to quantify modeling progress. The widespread utilization of BIM tools presents a unique opportunity to retrieve granular design process data and conduct accurate performance measurements. This research improves upon previous efforts by presenting a novel application programming interface (API)-enabled approach to automatically collect detailed design development data directly from BIM software packages and efficiently calculate several modeling performance measures. The primary objective of this research is to create and examine the feasibility of a proposed automated design performance monitoring framework. The proposed framework provides the following capabilities: (a) non-intrusive and cost-effective data acquisition for capturing design development events in real time, (b) scalable and high-speed ingestion for the storage of design modeling data, (c) objective measurement of designer performance and estimating levels of effort required to complete design tasks, and (d) identifying optimal design teams using empirical performance information. In chapter 3, the utilization of modeling development information embedded in design log files that are produced by Autodesk Revit is proposed as a rich source of performance data. To this end, generalized suffix tree (GST) data structures are utilized to find common, frequent command sequences among Revit users. In addition to identifying the common command execution patterns, the average time it takes the selected modelers to execute command sequences is calculated. The obtained results demonstrate that there is a statistically significant difference between the modelers in terms of the time it takes them to conduct similar modeling tasks. Chapter 4 utilizes modeling software solution’s APIs to automatically collect and store timestamped design development information. The proposed passive data recording approach allows for the real-time capture of comprehensive user interface (UI) interaction and model element modification events. The proposed framework is also implemented as an Autodesk Revit plugin. An experiment is then conducted to verify the accuracy of this plugin. Throughout this experiment, manual recordings of model development events were compared against the automatically generated plugin output. Chapter 5 outlines the details of an approach to identify the optimal design modeling team configuration based on automatically collected performance data. To this end, an experiment is conducted to capture data using the developed Revit plugin. Experiment participants’ individual production rates are estimated to establish the validity of the proposed approach to identify the optimal design team configurations. The presented approach uses the earliest due date (EDD) sequencing rule in combination with the critical path method (CPM) to calculate the maximum lateness for different design team arrangements. The primary contributions of this study to the state of knowledge are as follows: (a) proposing a tailored string mining algorithm that is capable of extracting meaningful information from timestamped design development data, (b) developing a framework based on APIs to automatically collect design modeling data, and (c) creating a mathematical model to estimate design modeling project completion times based on individual performance data and project requirements. This study contributes to the state of practice by (a) allowing design project managers to gain an unprecedented insight into the evolution of a building model using the information embedded in design log files, (b) helping design managers to acquire progress information without the need to manually record and report data, and (c) enabling design managers to identify an optimal modeling team arrangement based on automatically captured, quantitative performance information.
The effect of military construction transformation on project cost and schedule within the United States Army Corps of Engineers South Atlantic Division

(Georgia Institute of Technology, 2017-11-07) Westcott, Matthew

The United States Corps of Engineers (USACE) has been the primary Construction Agent of the United States Army and Air Force. Its members are considered the experts in project delivery for the Department of Defense (DoD). In 2006, the Base Realignment and Closure Program (BRAC) and the Global War on Terrorism (GWOT) led to increased workload which caused the USACE to adopt the Design-Build project delivery process as a primary means of project delivery in an effort to leverage the method’s ability to deliver projects at a lower cost and faster delivery time as compared to conventional methods. The focused use of the Design-Build process was to become the primary business practice of USACE after the BRAC/GWOT period, replacing the traditional Design-Bid-Build process that had dominated the USACE landscape for 50 years. The USACE Commander’s intent behind the Design-Build incorporation was to realize a 15% cost savings and a 30% reduction in delivery time over the traditional method. This measure of success would serve as a guide to the USACE for future business practices. Military Construction Transformation, or MILCON Transformation, was the name designated to the Design-Build process when it was approved as the primary form of project delivery in the USACE in 2006. Since then, the four-year spike in project workload brought about during the BRAC and initial GWOT period has been diminished, and the business practice has taken some time to incorporate refinements based on lessons learned during the BRAC/GWOT period. In 2009 the Engineer Inspector General (EIG) was commissioned to measure the performance standards given by the USACE Commander, but after conducting only interviews of district chiefs across the USACE, the EIG was unable to quantify any project data that was relatable to the Commander’s metric (EIG, 2009). Independent studies evaluating the performance of Design-Build in various domains of the public sector have been conducted in the past, however a measurement of this specificity has yet to be conducted. The scope of this thesis is to evaluate the MILCON Transformation performance of the of the South Atlantic Division during 2002-2014. Project data was gathered from the USACE-internal automated information system, Enterprise Data Warehouse (EDW). Only MILCON, vertical construction project data was collected from EDW, and four hypothesis based off cost and time were developed for testing. Five project milestones for 304 projects that qualified for evaluation were evaluated using 180 separate Welch’s T-tests to test for a statistically significant difference between Design-Bid-Build and Design-Build. Of the 180 T-tests conducted, 37 were in support of the alternate hypothesis, which stated that there was a statistically significant difference with 95% confidence between the two project delivery models. Projects were analyzed in three different ways. First, projects were distributed between the two project delivery populations and all performance metrics regarding cost and time were analyzed from the Division level. Next, projects were analyzed by building type, to find out if there were any specific types of buildings where Design-Build performed better than Design-Bid-Build. Finally, projects were analyzed by District, where projects from each of the 5 Districts within the South Atlantic Division were analyzed to determine if any one District executed Design-Build more successfully than another District. From this analysis, it was found that the 15% reduction of cost by use of Design-Build was realized from a Division level. However, in no circumstance was the target 30% reduction in time realized for the Division, any District, or any specific building type. Results were then presented to a focus group of leaders within the USACE South Atlantic Division to gather insight on why the USACE Commanders goals were not completely met. Since literature pointed to Design-Build as being a source of lower cost and time in the public sector, data results warranted further insight as to why the USACE struggled to gain full value from the Design-Build delivery model. The focus group validated the data and findings while attributing discovered performance metrics to operational tempo, manpower, and conservative management. From these results, the researcher submits recommendations on how the USACE can realize greater value from the use of Design-Build.
Analyzing uncertainty in the price of materials and financial risk management strategies

(Georgia Institute of Technology, 2017-05-11) Ilbeigi, Mohammad

Significant volatility and unprecedented uncertainty in the price of asphalt cement is a serious challenge for both contractors and state DOTs with regards to proper cost estimating and budgeting of transportation projects. Previous studies indicate that owner organizations often overpay for projects under fixed-price contracts that transfer the material price risk to contractors due to increased risk premiums and hidden contingencies in contractors’ submitted bid prices. A common method widely used by state DOTs for handling the issue of extra risk premiums in submitted bid prices and avoiding overpayment to contractors is to offer price adjustment clauses (PACs) in contracts. A PAC is a risk sharing contractual mechanism that guarantees an adjustment in payment to contractors based on the size and direction of the material price change. Although uncertainty in the price of asphalt cement is a serious challenge for both contractors and state DOTs and many transportation agencies utilize PACs to control consequences of material price volatility, there is little knowledge about analyzing uncertainties in the price of asphalt cement and actual performance of PACs. This dissertation aims to analyze uncertainty in the price of asphalt cement and examine performance of PACs in highway construction projects. After a comprehensive review of the existing body of knowledge about uncertainties in the price of critical materials in transportation projects and PACs, time series analysis is conducted and four univariate time series forecasting models are created to forecast future price of asphalt cement. The results of the time series forecasting show that all four time series models can predict the future values of asphalt cement price with proper accuracy but among the four models, the ARIMA and Holt Exponential Smoothing models are the most accurate prediction models with less than 2% error. Then, ARCH/GARCH time series analysis is conducted to quantify and forecast level of uncertainties in the price of asphalt cement. The results of this step can help transportation agencies systematically measure, analyze and forecast the uncertainties in the price of asphalt cement and implement their risk management strategies at the right time. In next step, impacts of offering PACs on submitted bid prices for major asphalt line items are analyzed using multivariate regression analysis. Finally, effects of offering PACs on dispersion of submitted bid prices and number of bidders are analyzed using system monitoring processes.