An Examination of Psychological Meaningfulness, Safety, and Availability as the Underlying Mechanisms linking Job Features and Personal Characteristics to Work Engagement

The present study tested a nomological net of work engagement that was derived from its extant research. Two of the main work engagement models that have been presented and empirically tested in the literature, the JD-R model and Kahn’s model, were integrated to test the effects that job features and personal characteristics can have on work engagement through the psychological conditions of meaningfulness, safety, and availability. In this study, safety refers to psychological perceptions of safety and not workplace safety behaviors. The job features that were tested in this model included person-job fit, autonomy, co-worker relations, supervisor support, procedural justice, and interactional justice, while the personal characteristics consisted of self-consciousness, self-efficacy, extraversion, and neuroticism. Thirty-four hypotheses and a conceptual model were tested in order to establish the viability of this nomological net of work engagement in which it was expected that meaningfulness would mediate the relationships between job features and work engagement, safety would mediate the relationships that job features and personal characteristics have with work engagement, and availability (physical, emotional, and cognitive resources) would mediate the relationships that personal characteristics have with work engagement. Furthermore, analyses were run in order to determine the factor structure of work engagement, assess whether or not it exhibits differential validity from organizational commitment and job satisfaction, and confirm that it is positively related to the outcome variable of organizational citizenship behavior (OCB). The final sample consisted of 500 workers from an online labor market who responded to a questionnaire composed of measures of all constructs included in this study. Findings show that work engagement is best represented as a three-factor construct, composed of vigor, dedication and absorption. Furthermore, support was found for the distinction of work engagement from the related constructs of organizational commitment and job satisfaction. With regard to the proposed model, meaningfulness proved to be the strongest predictor of work engagement. Results show that it partially mediates the relationships that all job features have with work engagement. Safety proved to be a partial mediator of the relationships that autonomy, co-worker relations, supervisor support, procedural justice, interactional justice, and self-efficacy have with work engagement, and fully mediate the relationship between neuroticism and work engagement. Findings also show that availability partially mediates the positive relationships that extraversion and self-efficacy have with work engagement, and fully mediates the negative relationship that neuroticism has with work engagement. Finally, a positive relationship was found between work engagement and OCB. Research and organizational implications are discussed.

The relationship between job structure, burnout, and coping methods among public school county bus drivers, bus aides, mechanics, and clerical workers

The purpose of this study was to examine the relationship between the structure of jobs and burnout, and to assess to what extent, if any this relationship was moderated by individual coping methods. This study was supported by the Karasek's (1998) Job Demand-Control-Support theory of work stress as well as Maslach and Leiter's (1993) theory of burnout. Coping was examined as a moderator based on the conceptualization of Lazarus and Folkman (1984). ^ Two overall overarching questions framed this study: (a) what is the relationship between job structure, as operationalized by job title, and burnout across different occupations in support services in a large municipal school district? and (b) To what extent do individual differences in coping methods moderate this relationship? ^ This study was a cross-sectional study of county public school bus drivers, bus aides, mechanics, and clerical workers (N = 253) at three bus depot locations within the same district using validated survey instruments for data collection. Hypotheses were tested using simultaneous regression analyses. ^ Findings indicated that there were statistically significant and relevant relationships among the variables of interest; job demands, job control, burnout, and ways of coping. There was a relationship between job title and physical job demands. There was no evidence to support a relationship between job title and psychological demands. Furthermore, there was a relationship between physical demands, emotional exhaustion and personal accomplishment; key indicators of burnout. ^ Results showed significant correlations between individual ways of coping as a moderator between job structure, operationalized by job title, and individual employee burnout adding empirical evidence to the occupational stress literature. Based on the findings, there are implications for theory, research, and practice. For theory and research, the findings suggest the importance of incorporating transactional models in the study of occupational stress. In the area of practice, the findings highlight the importance of enriching jobs, increasing job control, and providing individual-level training related to stress reduction.^

The Relationship between Job Structure, Burnout, and Coping Methods among Public School county Bus Drivers, Bus Aides, Mechanics, and Clerical Workers

The purpose of this study was to examine the relationship between the structure of jobs and burnout, and to assess to what extent, if any this relationship was moderated by individual coping methods. This study was supported by the Karasek's (1998) Job Demand-Control-Support theory of work stress as well as Maslach and Leiter's (1993) theory of burnout. Coping was examined as a moderator based on the conceptualization of Lazarus and Folkman (1984). Two overall overarching questions framed this study: (a) what is the relationship between job structure, as operationalized by job title, and burnout across different occupations in support services in a large municipal school district? and (b) To what extent do individual differences in coping methods moderate this relationship? This study was a cross-sectional study of county public school bus drivers, bus aides, mechanics, and clerical workers (N = 253) at three bus depot locations within the same district using validated survey instruments for data collection. Hypotheses were tested using simultaneous regression analyses. Findings indicated that there were statistically significant and relevant relationships among the variables of interest; job demands, job control, burnout, and ways of coping. There was a relationship between job title and physical job demands. There was no evidence to support a relationship between job title and psychological demands. Furthermore, there was a relationship between physical demands, emotional exhaustion and personal accomplishment; key indicators of burnout. Results showed significant correlations between individual ways of coping as a moderator between job structure, operationalized by job title, and individual employee burnout adding empirical evidence to the occupational stress literature. Based on the findings, there are implications for theory, research, and practice. For theory and research, the findings suggest the importance of incorporating transactional models in the study of occupational stress. In the area of practice, the findings highlight the importance of enriching jobs, increasing job control, and providing individual-level training related to stress reduction.

Use of Fiber Reinforced Polymer Composite Cable for Post-tensioning Application

Corrosion of steel tendons is a major problem for post-tensioned concrete, especially because corrosion of the steel strands is often hard to detect inside grouted ducts. Non-metallic tendons can serve as an alternative material to steel for post-tensioning applications. Carbon fiber reinforced polymer (CFRP), given its higher strength and elastic modulus, as well as excellent durability and fatigue strength, is the most practical option for post-tensioning applications. The primary objective of this research project was to assess the feasibility of the use of innovative carbon fiber reinforced polymer (CFRP) tendons and to develop guidelines for CFRP in post-tensioned bridge applications, including segmental bridges and pier caps. An experimental investigation and a numerical simulation were conducted to compare the performance of a scaled segmental bridge model, post-tensioned with two types of carbon fiber strands and steel strands. The model was tested at different prestress levels and at different loading configurations. While the study confirms feasibility of both types of carbon fiber strands for segmental bridge applications, and their similar serviceability behavior, strands with higher elastic modulus could improve structural performance and minimize displacements beyond service loads. As the second component of the project, a side-by-side comparison of two types of carbon fiber strands against steel strands was conducted in a scaled pier cap model. Two different strand arrangements were used for post-tensioning, with eight and six strands, respectively representing an over-design and a slight under-design relative to the factored demand. The model was tested under service and factored loads. The investigation confirmed the feasibility of using carbon fiber strands in unbonded post-tensioning of pier caps. Considering both serviceability and overload conditions, the general performance of the pier cap model was deemed acceptable using either type of carbon fiber strands and quite comparable to that of steel strands. In another component of this research, creep stress tests were conducted with carbon fiber composite cable (CFCC). The anchorages for all the specimens were prepared using a commercially available expansive grout. Specimens withstood 95% of the guaranteed capacity provided by the manufacturer for a period of five months, without any sign of rupture.

Examining a proposed job retention model for adult workers with mental retardation in supported employment

This quantitative study investigated the predictive relationships and interaction between factors such as work-related social behaviors (WRSB), self-determination (SD), person-job congruency (PJC), job performance (JP), job satisfaction (JS), and job retention (JR). A convenience sample of 100 working adults with MR were selected from supported employment agencies. Data were collected using a survey test battery of standardized instruments. The hypotheses were analyzed using three multiple regression analyses to identify significant relationships. Beta weights and hierarchical regression analysis determined the percentage of the predictor variables contribution to the total variance of the criterion variables, JR, JP, and JS. ^ The findings highlight the importance of self-determination skills in predicting job retention, satisfaction, and performance for employees with MR. Consistent with the literature and hypothesized model, there was a predictive relationship between SD, JS and JR. Furthermore, SD and PJC were predictors of JP. SD and JR were predictors of JS. Interestingly, the results indicated no significant relationship between JR and JP, or between JP and JS, or between PJC and JS. This suggests that there is a limited fit between the hypothesized model and the study's findings. However, the theoretical contribution made by this study is that self-determination is a particularly relevant predictor of important work outcomes including JR, JP, and JS. This finding is consistent with Deci's (1992) Self-Determination Theory and Wehmeyer's (1996) argument that SD skills in individuals with disabilities have important consequences for the success in transitioning from school to adult and work life. This study provides job retention strategies that offer rehabilitation and HR professionals a useful structure for understanding and implementing job retention interventions for people with MR. ^ The study concluded that workers with mental retardation who had more self-determination skills were employed longer, more satisfied, and better performers on the job. Also, individuals whose jobs were matched to their interests and abilities (person-job congruency) were better at self-determination skills. ^

Employee perceptions of workplace empowerment in relation to self -reported intent to stay on the job

As the nursing profession faces a shortage of nurses, workplace initiatives focused on retaining employees are critical to the United States healthcare industry (Sochalski, 2002). The purpose of this research was to determine whether self-reported intent to stay on the job was related to perceptions of workplace empowerment using Kanter's (1977) theory of organizational empowerment as a framework. ^ The sample consisted of 206 Florida registered nurses. Four self-report scales and a demographic questionnaire were administered by mail. The Conditions for Work Effectiveness Questionnaire (CWEQ; Chandler, 1987), Job Activity Scale (JAS; Laschinger, Kutzscher, & Sabiston, 1993), Organizational Relationships Scale (ORS; Laschinger, Sabiston, & Kutzscher, 1993) and an intent to stay instrument (Kim, Price, Mueller & Watson, 1996) were used to measure perceived access to empowerment structures, perceived formal power, perceived informal power, and intent to stay, respectively. The data were analyzed using descriptive statistics, correlational analysis, and hierarchical regression. ^ Twenty-eight percent of the variance of intent to stay was explained by perceived access to empowerment structures, perceived formal power, and perceived informal power when holding age, gender, education, overall nursing experience, and number of years on current job constant. Perceived access to empowerment structures (CWEQ total score) was the best predictor of self-reported intent to stay for this sample. Of the four components of perceived access to work empowerment structures, perceived access to opportunity and resources were the best predictors of nurses' intent to stay on the job. ^ This study was the first step in establishing the relationship between Kanter's full model and intent to remain on the job, which is a stepping stone for the development of effective retention strategies based on a workplace empowerment model. This knowledge is particularly important in today's healthcare industry where healthcare administrators and human resource development practitioners are ideally positioned to implement organizational strategies to enhance access to work empowerment structures and potentially reduce turnover and mitigate the effects of nursing shortage. ^

Branch and price solution approach for order acceptance and capacity planning in make -to -order operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. ^ For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver.^ The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. ^ The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.^

Interoperable resource brokering with policy-based provisioning and job allocation

The increasing needs for computational power in areas such as weather simulation, genomics or Internet applications have led to sharing of geographically distributed and heterogeneous resources from commercial data centers and scientific institutions. Research in the areas of utility, grid and cloud computing, together with improvements in network and hardware virtualization has resulted in methods to locate and use resources to rapidly provision virtual environments in a flexible manner, while lowering costs for consumers and providers. ^ However, there is still a lack of methodologies to enable efficient and seamless sharing of resources among institutions. In this work, we concentrate in the problem of executing parallel scientific applications across distributed resources belonging to separate organizations. Our approach can be divided in three main points. First, we define and implement an interoperable grid protocol to distribute job workloads among partners with different middleware and execution resources. Second, we research and implement different policies for virtual resource provisioning and job-to-resource allocation, taking advantage of their cooperation to improve execution cost and performance. Third, we explore the consequences of on-demand provisioning and allocation in the problem of site-selection for the execution of parallel workloads, and propose new strategies to reduce job slowdown and overall cost.^

Developing an enhanced model for combined heat and air infiltration energy simulation

The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. ^ Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. ^ Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building's energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. ^ In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. ^ An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.^

An examination of psychological meaningfulness, safety, and availability as the underlying mechanisms linking job features and personal characteristics to work engagement

The present study tested a nomological net of work engagement that was derived from its extant research. Two of the main work engagement models that have been presented and empirically tested in the literature, the JD-R model and Kahn's model, were integrated to test the effects that job features and personal characteristics can have on work engagement through the psychological conditions of meaningfulness, safety, and availability. In this study, safety refers to psychological perceptions of safety and not workplace safety behaviors. The job features that were tested in this model included person-job fit, autonomy, co-worker relations, supervisor support, procedural justice, and interactional justice, while the personal characteristics consisted of self-consciousness, self-efficacy, extraversion, and neuroticism. Thirty-four hypotheses and a conceptual model were tested in order to establish the viability of this nomological net of work engagement in which it was expected that meaningfulness would mediate the relationships between job features and work engagement, safety would mediate the relationships that job features and personal characteristics have with work engagement, and availability (physical, emotional, and cognitive resources) would mediate the relationships that personal characteristics have with work engagement. Furthermore, analyses were run in order to determine the factor structure of work engagement, assess whether or not it exhibits differential validity from organizational commitment and job satisfaction, and confirm that it is positively related to the outcome variable of organizational citizenship behavior (OCB). The final sample consisted of 500 workers from an online labor market who responded to a questionnaire composed of measures of all constructs included in this study. Findings show that work engagement is best represented as a three-factor construct, composed of vigor, dedication and absorption. Furthermore, support was found for the distinction of work engagement from the related constructs of organizational commitment and job satisfaction. With regard to the proposed model, meaningfulness proved to be the strongest predictor of work engagement. Results show that it partially mediates the relationships that all job features have with work engagement. Safety proved to be a partial mediator of the relationships that autonomy, co-worker relations, supervisor support, procedural justice, interactional justice, and self-efficacy have with work engagement, and fully mediate the relationship between neuroticism and work engagement. Findings also show that availability partially mediates the positive relationships that extraversion and self-efficacy have with work engagement, and fully mediates the negative relationship that neuroticism has with work engagement. Finally, a positive relationship was found between work engagement and OCB. Research and organizational implications are discussed.

A generic model of execution for synthesizing domain-specific models

Software engineering researchers are challenged to provide increasingly more powerful levels of abstractions to address the rising complexity inherent in software solutions. One new development paradigm that places models as abstraction at the forefront of the development process is Model-Driven Software Development (MDSD). MDSD considers models as first class artifacts, extending the capability for engineers to use concepts from the problem domain of discourse to specify apropos solutions. A key component in MDSD is domain-specific modeling languages (DSMLs) which are languages with focused expressiveness, targeting a specific taxonomy of problems. The de facto approach used is to first transform DSML models to an intermediate artifact in a HLL e.g., Java or C++, then execute that resulting code.^ Our research group has developed a class of DSMLs, referred to as interpreted DSMLs (i-DSMLs), where models are directly interpreted by a specialized execution engine with semantics based on model changes at runtime. This execution engine uses a layered architecture and is referred to as a domain-specific virtual machine (DSVM). As the domain-specific model being executed descends the layers of the DSVM the semantic gap between the user-defined model and the services being provided by the underlying infrastructure is closed. The focus of this research is the synthesis engine, the layer in the DSVM which transforms i-DSML models into executable scripts for the next lower layer to process.^ The appeal of an i-DSML is constrained as it possesses unique semantics contained within the DSVM. Existing DSVMs for i-DSMLs exhibit tight coupling between the implicit model of execution and the semantics of the domain, making it difficult to develop DSVMs for new i-DSMLs without a significant investment in resources.^ At the onset of this research only one i-DSML had been created for the user- centric communication domain using the aforementioned approach. This i-DSML is the Communication Modeling Language (CML) and its DSVM is the Communication Virtual machine (CVM). A major problem with the CVM's synthesis engine is that the domain-specific knowledge (DSK) and the model of execution (MoE) are tightly interwoven consequently subsequent DSVMs would need to be developed from inception with no reuse of expertise.^ This dissertation investigates how to decouple the DSK from the MoE and subsequently producing a generic model of execution (GMoE) from the remaining application logic. This GMoE can be reused to instantiate synthesis engines for DSVMs in other domains. The generalized approach to developing the model synthesis component of i-DSML interpreters utilizes a reusable framework loosely coupled to DSK as swappable framework extensions.^ This approach involves first creating an i-DSML and its DSVM for a second do- main, demand-side smartgrid, or microgrid energy management, and designing the synthesis engine so that the DSK and MoE are easily decoupled. To validate the utility of the approach, the SEs are instantiated using the GMoE and DSKs of the two aforementioned domains and an empirical study to support our claim of reduced developmental effort is performed.^

Work Creativity as a Dimension of Job Performance

To stay competitive, many employers are looking for creative and innovative employees to add value to their organization. However, current models of job performance overlook creative performance as an important criterion to measure in the workplace. The purpose of this dissertation is to conduct two separate but related studies on creative performance that aim to provide support that creative performance should be included in models of job performance, and ultimately included in performance evaluations in organizations. Study 1 is a meta-analysis on the relationship between creative performance and task performance, and the relationship between creative performance and organizational citizenship behavior (OCB). Overall, I found support for a medium to large corrected correlation for both the creative performance-task performance (ρ = .51) and creative performance-OCB (ρ = .49) relationships. Further, I also found that both rating-source and study location were significant moderators. Study 2 is a process model that includes creative performance alongside task performance and OCB as the outcome variables. I test a model in which both individual differences (specifically: conscientiousness, extraversion, proactive personality, and self-efficacy) and job characteristics (autonomy, feedback, and supervisor support) predict creative performance, task performance, and OCB through engagement as a mediator. In a sample of 299 employed individuals, I found that all the individual differences and job characteristics were positively correlated with all three performance criteria. I also looked at these relationships in a multiple regression framework and most of the individual differences and job characteristics still predicted the performance criteria. In the mediation analyses, I found support for engagement as a significant mediator of the individual differences-performance and job characteristics-performance relationships. Taken together, Study 1 and Study 2 support the notion that creative performance should be included in models of job performance. Implications for both researchers and practitioners alike are discussed.

Branch and Price Solution Approach for Order Acceptance and Capacity Planning in Make-to-Order Operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.

A Generic Model of Execution for Synthesizing Domain-Specific Models

Software engineering researchers are challenged to provide increasingly more pow- erful levels of abstractions to address the rising complexity inherent in software solu- tions. One new development paradigm that places models as abstraction at the fore- front of the development process is Model-Driven Software Development (MDSD). MDSD considers models as first class artifacts, extending the capability for engineers to use concepts from the problem domain of discourse to specify apropos solutions. A key component in MDSD is domain-specific modeling languages (DSMLs) which are languages with focused expressiveness, targeting a specific taxonomy of problems. The de facto approach used is to first transform DSML models to an intermediate artifact in a HLL e.g., Java or C++, then execute that resulting code. Our research group has developed a class of DSMLs, referred to as interpreted DSMLs (i-DSMLs), where models are directly interpreted by a specialized execution engine with semantics based on model changes at runtime. This execution engine uses a layered architecture and is referred to as a domain-specific virtual machine (DSVM). As the domain-specific model being executed descends the layers of the DSVM the semantic gap between the user-defined model and the services being provided by the underlying infrastructure is closed. The focus of this research is the synthesis engine, the layer in the DSVM which transforms i-DSML models into executable scripts for the next lower layer to process. The appeal of an i-DSML is constrained as it possesses unique semantics contained within the DSVM. Existing DSVMs for i-DSMLs exhibit tight coupling between the implicit model of execution and the semantics of the domain, making it difficult to develop DSVMs for new i-DSMLs without a significant investment in resources. At the onset of this research only one i-DSML had been created for the user- centric communication domain using the aforementioned approach. This i-DSML is the Communication Modeling Language (CML) and its DSVM is the Communication Virtual machine (CVM). A major problem with the CVM’s synthesis engine is that the domain-specific knowledge (DSK) and the model of execution (MoE) are tightly interwoven consequently subsequent DSVMs would need to be developed from inception with no reuse of expertise. This dissertation investigates how to decouple the DSK from the MoE and sub- sequently producing a generic model of execution (GMoE) from the remaining appli- cation logic. This GMoE can be reused to instantiate synthesis engines for DSVMs in other domains. The generalized approach to developing the model synthesis com- ponent of i-DSML interpreters utilizes a reusable framework loosely coupled to DSK as swappable framework extensions. This approach involves first creating an i-DSML and its DSVM for a second do- main, demand-side smartgrid, or microgrid energy management, and designing the synthesis engine so that the DSK and MoE are easily decoupled. To validate the utility of the approach, the SEs are instantiated using the GMoE and DSKs of the two aforementioned domains and an empirical study to support our claim of reduced developmental effort is performed.

Developing an Enhanced Model for Combined Heat and Air Infiltration Energy Simulation

The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building’s energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.