Browsing by Author "de la Garza, Jesus M."
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- Anonymous Indoor Positioning System using Depth Sensors for Context-aware Human-Building InteractionBallivian, Sergio Marlon (Virginia Tech, 2019-05-24)Indoor Localization Systems (ILS), also known as Indoor Positioning Systems (IPS), has been created to determine the position of individuals and other assets inside facilities. Indoor Localization Systems have been implemented for monitoring individuals and objects in a variety of sectors. In addition, ILS could be used for energy and sustainability purposes. Energy management is a complex and important challenge in the Built Environment. The indoor localization market is expected to increase by 33.8 billion in the next 5 years based on the 2016 global survey report (Marketsandmarkets.com). Therefore, this thesis focused on exploring and investigating "depth sensors" application in detecting occupants' indoor positions to be used for smarter management of energy consumption in buildings. An interconnected passive depth-sensor-based system of occupants' positioning was investigated for human-building interaction applications. This research investigates the fundamental requirements for depth-sensing technology to detect, identify and track subjects as they move across different spaces. This depth-based approach is capable of sensing and identifying individuals by accounting for the privacy concerns of users in an indoor environment. The proposed system relies on a fixed depth sensor that detects the skeleton, measures the depth, and further extracts multiple features from the characteristics of the human body to identify them through a classifier. An example application of such a system is to capture an individuals' thermal preferences in an environment and deliver services (targeted air conditioning) accordingly while they move in the building. The outcome of this study will enable the application of cost-effective depth sensors for identification and tracking purposes in indoor environments. This research will contribute to the feasibility of accurate detection of individuals and smarter energy management using depth sensing technologies by proposing new features and creating combinations with typical biometric features. The addition of features such as the area and volume of human body surface was shown to increase the accuracy of the identification of individuals. Depth-sensing imaging could be combined with different ILS approaches and provide reliable information for service delivery in building spaces. The proposed sensing technology could enable the inference of people location and thermal preferences across different indoor spaces, as well as, sustainable operations by detecting unoccupied rooms in buildings.
- Automated 2D Detection and Localization of Construction Resources in Support of Automated Performance Assessment of Construction OperationsMemarzadeh, Milad (Virginia Tech, 2012-12-10)This study presents two computer vision based algorithms for automated 2D detection of construction workers and equipment from site video streams. The state-of-the-art research proposes semi-automated detection methods for tracking of construction workers and equipment. Considering the number of active equipment and workers on jobsites and their frequency of appearance in a camera's field of view, application of semi-automated techniques can be time-consuming. To address this limitation, two new algorithms based on Histograms of Oriented Gradients and Colors (HOG+C), 1) HOG+C sliding detection window technique, and 2) HOG+C deformable part-based model are proposed and their performance are compared to the state-of-the-art algorithm in computer vision community. Furthermore, a new comprehensive benchmark dataset containing over 8,000 annotated video frames including equipment and workers from different construction projects is introduced. This dataset contains a large range of pose, scale, background, illumination, and occlusion variation. The preliminary results with average performance accuracies of 100%, 92.02%, and 89.69% for workers, excavators, and dump trucks respectively, indicate the applicability of the proposed methods for automated activity analysis of workers and equipment from single video cameras. Unlike other state-of-the-art algorithms in automated resource tracking, these methods particularly detects idle resources and does not need manual or semi-automated initialization of the resource locations in 2D video frames.
- Automated Vision-Based Tracking and Action Recognition of Earthmoving Construction OperationsHeydarian, Arsalan (Virginia Tech, 2012-04-30)The current practice of construction productivity and emission monitoring is performed by either manual stopwatch studies which are significantly labor intensive and subject to human errors, or by the use of RFID and GPS tracking devices which may be costly and impractical. To address these limitations, a novel computer vision based method for automated 2D tracking, 3D localization, and action recognition of construction equipment from different camera viewpoints is presented. In the proposed method, a new algorithm based on Histograms of Oriented Gradients and hue-saturation Colors (HOG+C) is used for 2D tracking of the earthmoving equipment. Once the equipment is detected, using a Direct Linear Transformation followed by a non-linear optimization, their positions are localized in 3D. In order to automatically analyze the performance of these operations, a new algorithm to recognize actions of the equipment is developed. First, a video is represented as a collection of spatio-temporal features by extracting space-time interest points and describing each with a Histogram of Oriented Gradients (HOG). The algorithm automatically learns the distributions of these features by clustering their HOG descriptors. Equipment action categories are then learned using a multi-class binary Support Vector Machine (SVM) classifier. Given a novel video sequence, the proposed method recognizes and localizes equipment actions. The proposed method has been exhaustively tested on 859 videos from earthmoving operations. Experimental results with an average accuracy of 86.33% and 98.33% for excavator and truck action recognition respectively, reflect the promise of the proposed method for automated performance monitoring.
- Bookkeeping Procedures for the Application of the Concept of Pre-Allocation of Total FloatAmbani, Nikhil (Virginia Tech, 2004-11-05)With the increasing complexity in construction projects, monitoring project schedule and managing projects effectively is becoming increasingly important. Most projects being deadline oriented, timely completion becomes a must. Like every industry, the construction industry too lays a lot of emphasis on timely completion which makes it necessary to monitor the project schedule very closely. A schedule overrun is never predicted at the start of the project but during the course of the project, even the slightest change can result in delays. As per the current scheduling practices, float is considered free. It is an expiring resource and hence the party to the use the float first owns the float. The concept endorsed by the court for analyzing delay claims is the proximate cause concept. As per this concept, the party which is the immediate cause to a particular delay is held responsible for that delay irrespective of what has happened before in the project. Due the ambiguous nature of its interpretation, the present concept on float management has now become one the primary reasons for disputes amongst the participating parties. Parties in contract are always trying to appropriate float to suit their interests. This is why total float management has gained this level of importance in today's industry. To handle this issue of total float management more efficiently, Dr. Prateapusanond (2003) proposes a new concept of total float management as an effort towards a more fair and equitable system. This concept respects the dynamic nature of construction projects and recognizes float to be an asset for both parties. The new concept proposes to allocate float in the ratio 50:50 between the parties at the start of the project. This pre-allocated float owned by each party is called the Allowable Total Float (ATF). The implementation of this concept ensures that the parties are now aware that consumption of float in a way that it affects critical activities will expose them potential damages. This concept is an effort towards a more fair and equitable system for total float management. It appears impressive on paper but its practicality and applicability remains a major concern. This research is aimed at testing the practicality of the proposed concept of pre-allocation of total float. It introduces bookkeeping procedures that will facilitate the application of the concept of Pre-allocation of total float. These procedures have been developed and tested on certain case studies to make sure that they are robust. Once their ability to handle scheduling issues is determined, the bookkeeping procedure along with the concept of pre-allocation of total float is applied to a real construction project. This research presents an in depth analysis of the nature of the proposed concept of pre-allocation of total float, the scheduling issues which this concept does not address to, and certain assumptions which could be used in conjunction with the present concept to make it robust in nature.
- Case studies of employee participation programs in construction and their effects on absenteeismCox, Robert F. (Virginia Tech, 1994-11-05)In recent years, the construction industry has shown a steady decline in productivity and worker morale, while experiencing an increase in absenteeism (Maloney, 1991; CII, 1982). This has had a tremendous economic and motivational impact. This dilemma coupled with the fast-paced growth of competition has led many construction companies to look for new ways to improve overall performance and reduce absenteeism. For over twenty years construction researchers have proposed various employee participation programs (EPP’s) as a possible management method to counter the decline in productivity. The suggested modern styles of management included applications such as: quality circles, goal setting, participative decision making, work crew selection, work teams, and more recently, Total Quality Management / Continuous Improvement Programs. While these past research efforts proposed such approaches, they are still not considered standard practices for the industry. Some leading edge contractors are working towards adaptation of these new management methods in hopes of leading their competition. This research studies four construction firms and their efforts to implement Employee Participation Programs (EPP’s) as part of their movement towards improving quality management. Each of the four cases utilized a “top-down” implementation approach which began with the management, executive, office staff, and supervisory personnel (company level). At the time of this study, the case companies had not established EPP’s at the field level of their organizations. The research investigates employee participation programs and their effects on absenteeism. The research utilized F-Tests (analysis of variance), factor analyses, T-tests, and regression analyses in support of its findings. The overall results show that EPP’s can have a negative influence on the variation in absenteeism behaviors. The findings indicate that the EPP’s affects over time increase as the program matures. The study concluded that employee perception of their significance and their proximity to the participation played a major role in the overall effects on absenteeism. The study found that the decision / problem environment was the single best predictor of changes in absence behaviors. Significant absenteeism trends were identified in Post-EPP measurement periods. The outcomes of this study were secured through the development and pilot use of the Employee Participation Program Profile Classification System (EPP-PCS).
- Categorizing Accelerated Bridge Construction Projects for Improving Decision-MakingLinares Garcia, Daniel Antonio (Virginia Tech, 2018-08-23)Accelerated Bridge Construction, also known as ABC, is a methodology that seeks to improve project development of bridges by reducing the overall project schedule and the impact on the traveling public by implementing innovative technologies and strategies in any phase of project development. However, ABC may incur additional direct costs for the project and some risks are associated because of the accelerated constraints implied in this methodology. On the positive side, the opportunity costs and reductions of traffic disruptions costs may overcome the additional costs associated with ABC. Decision-making methodologies for assessment of ABC as an alternative to traditional construction are of great interest for project developers. The topics of research about ABC are diverse but focus mainly on the means and methods, technical aspects, applications, innovations, and decision-making of ABC. Decision-making is of great concern for project developers, especially government organizations, to sustain project goals of serviceability and to validate the additional expenditures in a project. In addition, project developers improve their decisions and project outcomes by reviewing success and failure cases for completed projects in the past. This study seeks to improve the decision-making processes in ABC by finding a more direct correlation of projects to compare by means of a categorization of these ABC projects. Smaller groups in this categorization will help narrow the scope of the characteristics of the projects to consider and to find more relevant lessons learned from the smaller groups of the categorization. To develop the categorization in this study, the data source used is the completed ABC projects database from the Federal Highway Administration (FHWA). The statistical categorization methodology for this study is the Agglomerate Hierarchy Clustering which developed a determined number of cluster based on the closeness among data parameters with "n" number of dimensions of analysis. The number of dimensions for the analysis in this study was established as 13 parameters collected from the database and these were considered critical decision-making parameters and consequential parameters to reflect project decisions and consequences of those decisions. The results of this study rendered 3 categories, and into these categories, 5 sub-categories were distributed according to the same analysis developed. The sub-categories show similarities between the projects according to the parameters established, so the sub-categories help narrow the scope of projects for project developers. As a complement to the categorization, a project matching tool for external projects was also developed to help decision-makers to test their projects according to the analysis in this study and also help developers narrow their review of cases in search for lessons learned. Uses of this study include the prediction of information of parameters according to the variables and ranges in this categorization, and the narrowing of study cases to review. Stakeholders interested can be government organizations seeking to establish the viability of an ABC project, or to improve their project outcomes at any stage of development. Other stakeholders can be designers and contractors that also need to improve their projects at any stage of development.
- Comparative Analysis of Current Performance-Based Maintenance Methods to Improve Virginia HighwaysArcella, Joseph Louis (Virginia Tech, 2013-04-12)This research was completed in two phases; phase-one involved a mini-scan study of the highway maintenance industry to identify the current state-of-practice in performance-based maintenance contracting (PBMC). Phase one gathered information on domestic and foreign agencies currently using performance-based maintenance on highways. Phase two used the mini-scan study information to build, compare and analyze agency timelines (i.e., VDOT to others). Timelines included major milestones at each agency; milestones which enabled innovation in the field of performance-based contracting. The purpose of comparing VDOT to other agencies was to provide VDOT with industry best practices as well as recommendations for future contract evolutions. Timelines were constructed for Florida DOT, Main Roads of Western Australia, England\'s Highways Agency and New Zealand Transport Agency. Connection links were made between VDOT and the other four agencies based on similarities in procurement laws and maintenance milestones (i.e., 1st Design-Build project). The timeline linkages and collection of information on benefits associated with PBMC (compared to traditional method-based maintenance) were used to make five recommendations for VDOT\'s future maintenance program. VDOT recommendations were: Use performance-based contracting on secondary roads, use area-wide contracts to cover addition facilities, shift VDOT TAMS focus from lowest-cost to a best-value approach similar to England\'s Managing-Agent Contractor, devise a strategic network of highways to prioritize maintenance, use key performance indicators to align Maintenance Division objectives with overall VDOT organization. Recommendations also considered the current restrictions imposed by Virginia procurement laws.
- Comparison of Large Scale Renewable Energy Projects for the United States Air ForceHughes, Jeffrey S. (Virginia Tech, 2012-10-02)This thesis focused on the performance of large-scale renewable energy projects for the United States Air Force. As global energy demands continue to rise, the need to find ways to save energy and produce alternative sources of energy will increase. The Federal Government has begun to address the challenge of energy production and energy security in recent years. In order to increase both the energy production and energy security for the Air Force, there is a trend to increase the amount of renewable energy produced on military installations. The goal of this research was to compare the estimated and actual performance of these large-scale on-site renewable energy projects at Air Force installations. The variables considered for this research were the execution methods and the renewable energy sources. The performance of each project was evaluated against factors identified in previous sustainable construction studies. The study found that actual performance of third party owned and operated projects differed from the expected performance by less than the Air Force owned and operated projects, and that performance of renewable energy projects differed from the expected performance by less than high performance buildings from previous studies. The study also found factors that contributed to the gap between the expected and actual performance including optimistic modeling, unusual weather, operational issues and higher than expected maintenance of the projects. The results of this research were an initial step in understanding the actual performance of large-scale renewable energy projects.
- A Comprehensive Practice of Total Float Pre-Allocation and Management for the Application of A CPM-Based Construction ContractPrateapusanond, Apirath (Virginia Tech, 2003-12-05)Many construction contracts require contractors to use the Critical Path Method (CPM) scheduling technique as a management tool. In such projects, many participating parties commonly attempt to appropriate float time shown in the CPM schedules in order to advance their own interests. Under current scheduling practices, float time is considered "free" and therefore does not belong to any one party in the construction process. As a result of this conception, when a project delay occurs, float ownership and its utilization can become a major source of dispute. This ambiguous interpretation of total float ownership can be clarified by improving contract language with regard to scheduling specifications in the area of total float management. The purpose of this research dissertation is to introduce a comprehensive practice of float pre-allocation and management terms, for the application of scheduling specifications in the CPM-based construction contract. The proposed concept for managing "total float" involves pre-allocating a set amount of total float on the same non-critical path of activities to the two contractual parties - owner and contractor. For the sake of equity, this research adopts an equal (50-50) allocation concept, which allocates to each party one-half of the total float. This new concept for pre-allocating and managing "total float" involves recommending contract clauses to direct its use and to explain the manner in which responsibility for any resulting delay will be assigned. Six examples of factual situations are provided to illustrate the assigning of responsibility for delays. The features of proposed concept are then compared to those of other theories presently being used. Such a comparison provides insight as to which features have not worked well in the past - and how those of the proposed concept can change this. A Delphi survey is used to validate the total float pre-allocation concept of equal allocation. The survey shows that the concept could significantly increase involved parties' awareness of total float consumption and thus help resolve any potential disputes regarding it. This dissertation considers suggestions obtained from the survey and recommends them for future study. The simple step of inserting new scheduling language into the construction contract documents assures that all participants will become more aware of the fact that when they consume floats, they introduce the potential of increasing project completion times.
- Controlling the cost of workers' compensation in construction: making the pieces fitDecker, Lisa (Virginia Tech, 1995-05-03)The costs related to workers compensation in the construction industry are rising every year, with no end in sight. Construction professionals can no longer afford to wait for others to solve the problem through new legislation or rate control. Controlling workers’ compensation costs is a puzzle that can be solved by contractors if they have all of the “pieces” and a guide. This thesis supplies the “pieces” by educating the reader on the terminology, intricacies, and problems of the workers’ compensation system. It also serves as the guide to solving the puzzle by discussing management techniques that are currently being used to control workers’ compensation costs, and their effectiveness. Costs are not the only concern of construction professionals as they turn their attention to workers’ compensation. It is mandatory that every company that is eligible have an Experience Modification Rating (EMR) that is applied to its premiums to adjust for its actual insurance performance. The EMR has gained a new function, however. Owners are using the EMR as a prequalifier in bidding, suggesting that the EMR is an accurate predictor of a contractor’s safety performance. This assertion is not entirely true. This thesis addresses the inadequacy of the EMR as an indicator of safety performance and suggests alternative measures of a contractor’s safety. The management techniques cited, and the assertions made with regard to the EMR, in this thesis are based on the opinions of the forty-two (42) contractors and over one thousand six hundred (1600) construction workers who participated in a study conducted by the Construction Industry Institute’s (CII) Workers Compensation Task Force. The findings of this thesis were made a part of the task force’s CII Source Document.
- Data-driven customer energy behavior characterization for distributed energy managementAfzalan, Milad (Virginia Tech, 2020-07-01)With the ever-growing concerns of environmental and climate concerns for energy consumption in our society, it is crucial to develop novel solutions that improve the efficient utilization of distributed energy resources for energy efficiency and demand response (DR). As such, there is a need to develop targeted energy programs, which not only meet the requirement of energy goals for a community but also take the energy use patterns of individual households into account. To this end, a sound understanding of the energy behavior of customers at the neighborhood level is needed, which requires operational analytics on the wealth of energy data from customers and devices. In this dissertation, we focus on data-driven solutions for customer energy behavior characterization with applications to distributed energy management and flexibility provision. To do so, the following problems were studied: (1) how different customers can be segmented for DR events based on their energy-saving potential and balancing peak and off-peak demand, (2) what are the opportunities for extracting Time-of-Use of specific loads for automated DR applications from the whole-house energy data without in-situ training, and (3) how flexibility in customer demand adoption of renewable and distributed resources (e.g., solar panels, battery, and smart loads) can improve the demand-supply problem. In the first study, a segmentation methodology form historical energy data of households is proposed to estimate the energy-saving potential for DR programs at a community level. The proposed approach characterizes certain attributes in time-series data such as frequency, consistency, and peak time usage. The empirical evaluation of real energy data of 400 households shows the successful ranking of different subsets of consumers according to their peak energy reduction potential for the DR event. Specifically, it was shown that the proposed approach could successfully identify the 20-30% of customers who could achieve 50-70% total possible demand reduction for DR. Furthermore, the rebound effect problem (creating undesired peak demand after a DR event) was studied, and it was shown that the proposed approach has the potential of identifying a subset of consumers (~5%-40% with specific loads like AC and electric vehicle) who contribute to balance the peak and off-peak demand. A projection on Austin, TX showed 16MWh reduction during a 2-h event can be achieved by a justified selection of 20% of residential customers. In the second study, the feasibility of inferring time-of-use (ToU) operation of flexible loads for DR applications was investigated. Unlike several efforts that required considerable model parameter selection or training, we sought to infer ToU from machine learning models without in-situ training. As the first part of this study, the ToU inference from low-resolution 15-minute data (smart meter data) was investigated. A framework was introduced which leveraged the smart meter data from a set of neighbor buildings (equipped with plug meters) with similar energy use behavior for training. Through identifying similar buildings in energy use behavior, the machine learning classification models (including neural network, SVM, and random forest) were employed for inference of appliance ToU in buildings by accounting for resident behavior reflected in their energy load shapes from smart meter data. Investigation on electric vehicle (EV) and dryer for 10 buildings over 20 days showed an average F-score of 83% and 71%. As the second part of this study, the ToU inference from high-resolution data (60Hz) was investigated. A self-configuring framework, based on the concept of spectral clustering, was introduced that automatically extracts the appliance signature from historical data in the environment to avoid the problem of model parameter selection. Using the framework, appliance signatures are matched with new events in the electricity signal to identify the ToU of major loads. The results on ~1500 events showed an F-score of >80% for major loads like AC, washing machine, and dishwasher. In the third study, the problem of demand-supply balance, in the presence of varying levels of small-scale distributed resources (solar panel, battery, and smart load) was investigated. The concept of load complementarity between consumers and prosumers for load balancing among a community of ~250 households was investigated. The impact of different scenarios such as varying levels of solar penetration, battery integration level, in addition to users' flexibility for balancing the supply and demand were quantitatively measured. It was shown that (1) even with 100% adoption of solar panels, the renewable supply cannot cover the demand of the network during afternoon times (e.g., after 3 pm), (2) integrating battery for individual households could improve the self-sufficiency by more than 15% during solar generation time, and (3) without any battery, smart loads are also capable of improving the self-sufficiency as an alternative, by providing ~60% of what commercial battery systems would offer. The contribution of this dissertation is through introducing data-driven solutions/investigations for characterizing the energy behavior of households, which could increase the flexibility of the aggregate daily energy load profiles for a community. When combined, the findings of this research can serve to the field of utility-scale energy analytics for the integration of DR and improved reshaping of network energy profiles (i.e., mitigating the peaks and valleys in daily demand profiles).
- Decentralized HVAC Operations: Novel Sensing Technologies and Control for Human-Aware HVAC OperationsJung, Wooyoung (Virginia Tech, 2020-04-13)Advances in Information and Communication Technology (ICT) paved the way for decentralized Heating, Ventilation, and Air-Conditioning (HVAC) HVAC operations. It has been envisioned that development of personal thermal comfort profiles leads to accurate predictions of each occupant's thermal comfort state and such information is employed in context-aware HVAC operations for energy efficiency. This dissertation has three key contributions in realizing this envisioned HVAC operation. First, it presents a systematic review of research trends and developments in context-aware HVAC operations. Second, it contributes to expanding the feasibility of the envisioned HVAC operation by introducing novel sensing technologies. Third, it contributes to shedding light on viability and potentials of comfort-aware operations (i.e., integrating personal thermal comfort models into HVAC control logic) through a comprehensive assessment of energy efficiency implications. In the first contribution, by developing a taxonomy, two major modalities – occupancy-driven and comfort-aware operations – in Human-In-The-Loop (HITL) HVAC operations were identified and reviewed quantitatively and qualitatively. The synthesis of previous studies has indicated that field evaluations of occupancy-driven operations showed lower potentials in energy saving, compared to the ones with comfort-aware operations. However, the results in comfort-aware operations could be biased given the small number of explorations. Moreover, required data representation schema have been presented to foster constructive performance assessments across different research efforts. In the end, the current state of research and future directions of HITL HVAC operations were discussed to shed light on future research need. As the second contribution, moving toward expanding the feasibility of comfort-aware operations, novel and smart sensing solutions have been introduced. It has been noted that, in order to have high accuracy in predicting individual's thermal comfort state (≥90%), user physiological response data play a key part. However, the limited number of applicable sensing technologies (e.g., infrared cameras) has impeded the potentials of implementation. After defining required characteristics in physiological sensing solutions in context of comfort-aware operations (applicability, sensitivity, ubiquity, and non-intrusiveness), the potentials of RGB cameras, Doppler radar sensors, and heat flux sensors were evaluated. RGB cameras, available in many smart computing devices, could be a ubiquitous solution in quantifying thermoregulation states. Leveraging the mechanism of skin blood perfusion, two thermoregulation state quantification methods have been developed. Then, applicability and sensitivity were checked with two experimental studies. In the first experimental study aiming to see applicability (distinguishing between 20 and 30C with fully acclimated human bodies), for 16 out of 18 human subjects, an increase in their blood perfusion was observed. In the second experimental study aiming to evaluate sensitivity (distinguishing responses to a continuous variation of air temperature from 20 to 30C), 10 out of 15 subjects showed a positive correlation between blood perfusion and thermal sensations. Also, the superiority of heat flux data, compared to skin temperature data, has been demonstrated in predicting personal thermal comfort states through the developments of machine-learning-based prediction models with feature engineering. Specifically, with random forest classifier, the median value of prediction accuracy was improved by 3.8%. Lastly, Doppler radar sensors were evaluated for their capability of quantifying user thermoregulation states leveraging the periodic movement of the chest/abdomen area induced by respiration. In an experimental study, the results showed that, with sufficient acclimation time, the DRS-based approach could show distinction between respiration states for two distinct air temperatures (20 and 30C). On the other hand, in a transient temperature without acclimation time, it was shown that, some of the human subjects (38.9%) used respiration as an active means of heat exchange for thermoregulation. Lastly, a comprehensive evaluation of comfort-aware operations' performance was carried out with a diverse set of contextual and operational factors. First, a novel comfort-aware operation strategy was introduced to leverage personal sensitivity to thermal comfort (i.e., different responses to temperature changes; e.g., sensitive to being cold) in optimization. By developing an agent-based simulation framework and thorough diverse scenarios with different numbers and combinations of occupants (i.e., human agents in the simulation), it was shown that this approach is superior in generating collectively satisfying environments against other approaches focusing on individual preferred temperatures in selection of optimized setpoints. The energy implications of comfort-aware operations were also evaluated to understand the impact from a wide range of factors (e.g., human and building factors) and their combinatorial effect given the uncertainty of multioccupancy scenarios. The results demonstrated that characteristics of occupants' thermal comfort profiles are dominant in impacting the energy use patterns, followed by the number of occupants, and the operational strategies. In addition, when it comes to energy efficiency, more occupants in a thermal zone/building result in reducing the efficacy of comfort-driven operation (i.e., the integration of personal thermal comfort profiles). Hence, this study provided a better understanding of true viability of comfort-driven HVAC operations and provided the probabilistic bounds of energy saving potentials. These series of studies have been presented as seven journal articles and they are included in this dissertation.
- A Decison Support System for Multi-Objective Multi-Asset Roadway Asset ManagementShoghli, Omidreza (Virginia Tech, 2014-08-12)The limited available budget along with old aging infrastructure in nation magnifies the role of strategic decision making for maintenance of infrastructure. The challenging objective is to maintain the infrastructure asset systems in a state of good repair and to improve the efficiency and performance of the infrastructure systems while protecting and enhancing the natural environment. Decision makers are in need of a decision support system to consider these multiple objectives and criteria to effectively allocate funding and achieve the highest possible return on investment on their infrastructure. The research proposes and validates a framework for such decisions. The proposed model aims at finding optimal techniques for maintenance of multiple roadway asset items while taking into account time, cost, level of service and environmental impacts. Therefore, the goal is to answer what are the optimal combinations of maintenance techniques for roadway assets while more than one objective is being optimized. In other words, the main objective is to develop a decision support system for selecting and prioritizing necessary actions for MRandR (Maintenance, Repair and Rehabilitation) of multiple asset items in order for a roadway to function within an acceptable level of service, budget, and time while considering environmental impacts. To achieve these desirable outcomes, this model creates a two-stage framework for a sustainable infrastructure asset management. First a multi-objective problem based on the multi colony ant colony optimization is analyzed. The objectives of the problem are: (i) Minimizing maintenance costs, (ii) Minimizing maintenance time, (iii) Minimizing environmental impacts and (iv) Maximizing level of service improvement. In the second stage, the results of the multi objective optimization will be prioritized using a Multi Criteria Decision Making (MCDM) process. The proposed approach will simultaneously optimize four conflicting objectives along with using a multi criteria decision-making technique for ranking the resulted non-dominated solutions of multi objective optimization. The results of implementation of the proposed model on a section of I-64 highway are presented for a sub-set of asset items. Moreover, the proposed model is validated using a scalable test problem as well as comparison with existing examples. Results reveal the capability of the model in generation of optimal solutions for the selection of maintenance strategies. The model optimizes decision making process and benefits decision makers by providing them with solutions for infrastructure asset management while meeting national goals towards sustainability and performance-based approach. In addition, provides a tool to run sensitivity analysis to evaluate annual budget effects and environmental impacts of different resource allocation scenarios. Application of the proposed approach is implemented on roadway asset items but it is not limited to roadways and is applicable to other infrastructure assets.
- Deploying Best Practices in Unfamiliar CountriesHorsey, Sara E. (Virginia Tech, 2013-09-06)This research developed a process to improve the systematic deployment of best practices in unfamiliar countries in response to rapid globalization in the engineering and construction industry. The engineering and construction industry needs processes, metrics and tools to improve the deployment of best practices in unfamiliar countries to help facilitate project success, as new challenges are encountered. The research identified issues that are commonly encountered when deploying best practices in unfamiliar countries. The issues were identified using content analysis and verified by experts using the Delphi Method. The Analytic Hierarchy Process was used to establish weightings for the importance of each issue. The weightings were then used to create a scoring metric for companies to measure their readiness for projects. In order to overcome the issues identified in the research, a series of processes and mitigation strategies to overcome the issues were developed, through a series of interviews and focus groups. The International Readiness Passport (IRP) is a tool created to support the use of the metric and the mitigation strategies. This tool utilizes a self-scoring section which is applied to the metric. The tool then generates a report with the relevant mitigation strategies related to each issue, based on the score. To ensure that the IRP provides a meaningful benefit to the systematic deployment of best practices in unfamiliar countries, it was validated through a series of retrospective tests. These tests have confirmed the accuracy and relevance of the process, metric, and tool, as well as the tool\'s capabilities.
- Design of Cellular Manufacturing Systems for Dynamic and Uncertain Production Requirements with Presence of Routing FlexibilityMungwattana, Anan (Virginia Tech, 2000-09-01)Shorter product life-cycles, unpredictable demand, and customized products have forced manufacturing firms to operate more efficiently and effectively in order to adapt to changing requirements. Traditional manufacturing systems, such as job shops and flow lines, cannot handle such environments. Cellular manufacturing, which incorporates the flexibility of job shops and the high production rate of flow lines, has been seen as a promising alternative for such cases. Although cellular manufacturing provides great benefits, the design of cellular manufacturing systems is complex for real-life problems. Existing design methods employ simplifying assumptions which often deteriorate the validity of the models used for obtaining solutions. Two simplifying assumptions used in existing design methods are as follows. First, product mix and demand do not change over the planning horizon. Second, each operation can be performed by only one machine type, i.e., routing flexibility of parts is not considered. This research aimed to develop a model and a solution approach for designing cellular manufacturing systems that addresses these shortcomings by assuming dynamic and stochastic production requirements and employing routing flexibility. A mathematical model and an optimal solution procedure were developed for the design of cellular manufacturing under dynamic and stochastic production environment employing routing flexibility. Optimization techniques for solving such problems usually require a substantial amount of time and memory space, therefore, a simulated annealing based heuristic was developed to obtain good solutions within reasonable amounts of time. The heuristic was evaluated in two ways. First, different cellular manufacturing design problems were generated and solved using the heuristic. Then, solutions obtained from the heuristic were compared with lower bounds of solutions obtained from the optimal solution procedure. The lower bounds were used instead of optimal solutions because of the computational time required to obtain optimal solutions. The results show that the heuristic performs well under various circumstances, but routing flexibility has a major impact on the performance of the heuristic. The heuristic appears to perform well regardless of problem size. Second, known solutions of two CM design problems from literature were used to compare with those from the heuristic. The heuristic slightly outperforms one design approach, but substantially outperforms the other design approach.
- Designing Operations of Geocomposite Membrane Installation in Flexible PavementsWanamakok, Phuwanai (Virginia Tech, 2000-11-27)Due to technological innovations new materials are introduced to the construction industry from time to time and need to be installed properly by contractors. Based on their past experience, the contractors have some ideas on how to carry out the operation. However, those ideas are just a good starting point. In order to attain an efficient and productive operation, many issues need to be considered and clarified. To design a new construction operation, the designer needs to completely understand the processes, consider all relevant issues, and review all governing criteria. Achieving practical and productive operations for new technologies requires careful and thorough planning. Simulation modeling can be a very effective technique to design construction operations for new technologies. Simulation modeling allows experimenting with many of the factors involved in the operations prior to initial construction. Early construction sequencing can allow testing of many alternatives without expensive installations. Geosynthetics are currently being incorporated in flexible pavement systems to improve their performance. However, geosynthetics must be used in the correct application and installed properly in order to produce good results. One of the newly developed geosynthetics is geocomposite membrane that thought to provide strain energy absorption and a moisture barrier. This research discusses the application of discrete-event simulation (DES) to design and analyze the installation of geocomposite membranes in flexible pavements. Data collected from two test sections at the Virginia Smart Road in Blacksburg, Virginia was used for modeling and analysis. STROBOSCOPE, a programming language designed for modeling complex operations, was used as the simulation engine. The process used in the development of simulation models is discussed. A number of installation alternatives were studied and simulated to examine their practicality and to investigate their productivity, resource utilization, and unit cost.
- Development of a Comprehensive Framework for the Efficiency Measurement of Road Maintenance Strategies using Data Envelopment AnalysisOzbek, Mehmet Egemen (Virginia Tech, 2007-09-19)For the last two decades, the road maintenance concept has been gaining tremendous attention. This has brought about new institutional changes, predominant of which is the challenge for maintenance managers to achieve maximum performance from the existing road system. Such challenge makes it imperative to implement comprehensive systems that measure road maintenance performance. However, the road maintenance performance measurement systems developed and implemented by researchers and state departments of transportation (DOTs) mainly focus on the effectiveness measures, e.g., the level-of-service. Such measurement systems do not sufficiently elaborate on the efficiency concept, e.g., the amount of resources utilized to achieve such level-of-service. Not knowing how "efficient" state DOTs are in being "effective" can lead to excessive and unrealistic maintenance budget expectations. This issue indicates the need for a performance measurement approach that can take the efficiency concept into account. Another important concept that is not investigated in the current road maintenance performance measurement systems is the effect of the environmental factors (e.g., climate, location, and etc.) and operational factors (e.g., traffic, load, design-construction adequacy, and etc.) on the performance of the road maintenance process. This issue, again, indicates the need for a performance measurement approach that can take such external and uncontrollable factors into account. The purpose of this research is to develop and implement a comprehensive framework that can measure the relative efficiency of different road maintenance strategies given the (i) multiple inputs and outputs that characterize the road maintenance process and (ii) uncontrollable factors (e.g., climate, traffic, etc.) that affect the performance of such process. It is challenging to measure the overall efficiency of a process when such process is a multiple input-multiple output process and when such process is affected by multiple factors. To address this challenge, an innovative approach to efficiency measurement, Data Envelopment Analysis, is used in this research. It is believed that this research, by taking the efficiency concept into account, will significantly improve the ways that are currently used to model and measure the performance of road maintenance. The findings of this research will contribute new knowledge to the asset management field in the road maintenance domain by providing a framework that is able to differentiate effective and efficient maintenance strategies from effective and inefficient ones.
- Development of a computer-understandable representation of design rationale to support value engineeringAlcantara, Primo T. (Virginia Tech, 1996-07-14)The life span of facilities produced by the Architecture-Engineering-Construction industry is typically 25 years or more Several distinct phases characterize the life span of a facility. Each of these phases involve numerous participants from different professional disciplines. These participants generate and use a lot of information about the facility. Current methods used by the industry to convey this information are drawings and specifications. However. these drawings and specifications reflect only a summary of the information generated and used by the project participants This summarized information only describes the product. Information about the process of generating these information becomes implicit in the drawings and specifications. Rationale is the collective term for this set of implicit process information. The main issue addressed by this dissertation is the need to communicate design rationale information. Design rationale is a subset of the entire rationale generated for a facility Design rationale refers to information about the design process. Explicitly stating design rationale information reduces the chance of misinterpreting design drawings and specifications. The primary objective of this dissertation is to determine a data structure capable of representing design rationale information. This data structure also allows a computer system to perform analytical tasks on the design rationale data. Examples of analytical tasks a computer system can perform on design rationale data include: generating a parameter dependency network and resolving data conflicts. This dissertation defines this data structure as two separate but complementary modules. The Knowledge Representation Module assists in gathering project-specific product information. The Rationale Storage Module assists in capturing project-specific process information. This dissertation discusses each of these two modules in detail. The secondary objectives of this dissertation include: (1) defining a computer program architecture, (2) creating a computer program interface, and (3) verifying the appropriateness of the data structure in representing design rationale. A proof-of-concept computer program, DRIVE, applied to an actual value engineering study project accomplishes these objectives.
- Development of a Novel Performance Index and a Performance Prediction Model for Metallic Drinking Water PipelinesSt. Clair, Alison Marie (Virginia Tech, 2013-04-23)Previous authors have developed many different types of water pipe condition and failure models using the various methodologies available. Contrary, current utilities are struggling to maintain their current water infrastructure system, due to the lack of effective prediction tools at hand. The gap between the methodologies available in academic research and the tools available to current water utilities needs to be addressed. This paper presents a fuzzy inference prediction model used to forecast the performance rating of individual drinking water pipeline sections (node to node) in which utilities can easily apply to their drinking water infrastructure system. Prior to the development of a prediction model, a through literature and current practice review is completed detailing and summarizing all the available mathematical models. Following, an infrastructure overview is presented detailing the various pipe materials, lifecycle and failure modes and mechanisms. A data structure is also detailed which lists all parameters that affect the condition and/or performance of a pipeline. All of these tools are successfully used to develop a fuzzy inference performance model. The fuzzy inference performance model is considered novel in that it considers close to 30 pipe parameters. Moreover, the performance model is applied using the Western Virginia Water Authority (WVWA) and the Washington Suburban Sanitary Commission (WSSC) databases to evaluate and verify the predicting results. Lab testing of several pipe samples is also used to evaluate the model. The testing consists of a ring bearing test which is used to calculate the rupture modulus of the pipe. Comparing the original vs. the current rupture modulus can determine the remaining strength of the pipe. The remaining strength can then be used to assess the performance results predicted by the fuzzy inference model. Further a framework is set forth which utilizes the model's predicted performance ratings to develop deterioration curves which can be used as a tool to forecast and plan future inspection, repair, rehabilitation and replacement of water pipelines. The deterioration model is made up of a Markov chain approach coupled with a non-optimization technique.
- The Development of Mathematical Models for Preliminary Prediction of Highway Construction DurationWilliams, Robert C. (Virginia Tech, 2008-11-04)Knowledge of construction duration is pertinent to a number of project planning functions prior to detailed design development. Funding, financing, and resource allocation decisions take place early in project design development and are significantly influenced by the construction duration. Currently, there is not an understanding of the project factors having a statistically significant relationship with highway construction duration. Other industry sectors have successfully used statistical regression analysis to identify and model the project parameters related to construction duration. While the need is seen for such work in highway construction, there are very few studies which attempt to identify duration-influential parameters and their relationship with the highway construction duration. This research identifies the project factors, known early in design development, which influence highway construction duration. The factors identified are specific to their respective project types and are those factors which demonstrate a statistically-significant relationship with construction duration. This work also quantifies the relationship between the duration-influential factors and highway construction duration. The quantity, magnitude, and sign of the factor coefficient yields evidence regarding the importance of the project factor to highway construction duration. Finally, the research incorporates the duration-influential project factors and their relationship with highway construction duration into mathematical models which assist in the prediction of construction duration. Full and condensed models are presented for Full-Depth Section and Highway Improvement project types. This research uses statistical regression analysis to identify, quantify, and model these early-known, duration-influential project factors. The results of this research contribute to the body of knowledge of the sponsoring organization (Virginia Department of Transportation), the highway construction industry, and the general construction industry at large.