This study aims to define workforce agility via a literature review and a conducted research survey of the Kennedy Space Center (KSC) Engineering workforce. The survey results will help us determine the workforce agility of the KSC engineering team and understand what has allowed them to transition from the Space Shuttle Program to the new Exploration Ground System (EGS) program. Structural Equation Modeling was used to develop a model of relationships to test the hypotheses. The results show that organizational practices and psychological empowerment significantly support workforce agility. The implications of this study for understanding the characteristics of workforce agility are also discussed.

As presidential candidates rhetorically articulate their beliefs during presidential debates, they reveal a lot about their underlying ideological beliefs. These beliefs were examined through the lens of an established methodology called the Operational Code, which uses a program to decipher a candidate's beliefs through what they say in debate transcripts. In this study, the belief trends of the Operational Codes of all presidential candidates from 1976-2012 were examined through a rhetorical lens, and it was found that rhetoric was indeed the driving force for the apparent changes in Operational Code beliefs. These changes were examined on a greater level of detail through four case studies, which illustrated the changes in Operational Code beliefs and rhetoric of Ronald Reagan, the incumbent presidential candidates, the 2004 election, and lastly, with the independent presidential candidates.

Early detection of faults in the vehicle operating systems is a research domain of high significance to sustain full control of the systems since anomalous behaviors usually result in performance loss for a long time before detecting them as critical failures. In other words, operating systems exhibit degradation when failure begins to occur. Indeed, multiple presences of the failures in the system performance are not only anomalous behavior signals but also show that taking maintenance actions to keep the system performance is vital. Maintaining the systems in the nominal performance for the lifetime with the lowest maintenance cost is extremely challenging and it is important to be aware of imminent failure before it arises and implement the best countermeasures to avoid extra losses. In this context, the timely anomaly detection of the performance of the operating system is worthy of investigation. Early detection of imminent anomalous behaviors of the operating system is difficult without appropriate modeling, prediction, and analysis of the time series records of the system. Data based technologies have prepared a great foundation to develop advanced methods for modeling and prediction of time series data streams. In this research, we propose novel methodologies to predict the patterns of multivariate time series operational data of the vehicle and recognize the second-wise unhealthy states. These approaches help with the early detection of abnormalities in the behavior of the vehicle based on multiple data channels whose second-wise records for different functional working groups in the operating systems of the vehicle. Furthermore, a real case study data set is used to validate the accuracy of the proposed prediction and anomaly detection methodologies.

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A fixed charge model has been developed for a case study of a total energy power plant involving energy demands for chilled water, high temperature hot water, and electrical power. Using a FORTRAN computer program, which employs the Land and Doig branch and bound algorithm, the system model is solved for different sets of system demands for multiple energy users, and the following set of information is obtained to guide the decisions of operations personnel: 1. Recommend on/off status for each piece of equipment in the system. 2. Recommended rate of operation for each piece of machinery. 3. Required amounts of different types of fuel to satisfy system demands. 4. A preferred path of flow through the system for each type of energy purchased or produced within the system.

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An interactive information system has been developed for the College of Engineering to promote faster and more accurate trial advisement interviews between professors and the students they advice. This system also provides departmental administrative personnel with information to guide course scheduling. The system has the capability of providing the following information concerning undergraduate students enrolled in the College of Engineering: 1. A student's academic progress toward graduation. 2. A projection for four quarters of enrollments in engineering core courses. 3. The current status of any course offered as a requirement for obtaining a Bachelor's Degree in one of the Engineering disciplines. 4. The current status of any program leading to a Bachelor's Degree in any of the Engineering disciplines. The system provides the user with the additional capabilities to: 1. Update the database containing information pertaining to students enrolled in the College of Engineering. 2. Update the database containing information concerning courses offered as a requirement for obtaining a Bachelor's Degree in one of the Engineering disciplines. 3. Update the database containing information concerning the degree programs offered by the College of Engineering. The system is user oriented and operation does not require any knowledge of computer programming. Complete documentation is available to facilitate trouble-free user operation and programming any desirable additional capabilities in the future.

A linear programming model has been developed for a Central Energy Plant which minimizes operational costs for a system involving the generation of chilled water and high temperature hot water plus the generation and/or purchase of electric power with equipment using natural gas or fuel oil energy. The fundamental concepts developed herein are sufficient for the analysis of any combination of energy supplies, demands, and energy conversion equipment. Utilization of this model is demonstrated with a case study and computer program results for high and low temperature environments. The linear programming model approach establishes a well-defined framework for the analysis of complex utility systems and provides valuable results for the economical operation of a Central Energy Plant.

This project, in collaboration with The Nordic Swan Ecolabel, deals with optimization of daylighting as well energy usage within a residential building for the purposes of Nordic ecolabelling/certification. One of the main purposes of this study is to understand the fundamentals of daylighting and to explore commonly used methods of daylight optimization and how these affect the energy consumption of the building. The other purpose of this study entails a comprehensive study of the evolution of daylight regulations within the Swedish building standard.In order to achieve the above intended aims of the project, a literature review was done on the fundamentals of daylighting as well as a review of the Swedish building standard. In order to evaluate the daylight optimization methods and how they affect energy usage, a mathematical model of a residential building was used within IDA ICE software. The simulated model was built based on certain requirements by the Nordic Swan Ecolabel.Due to time limitations, the study was focused on simulation of metric of daylight factor, and this limited the scope of the study. More realistic simulations with regards to control signals for internal shading were not possible within IDA ICE software. Therefore, simulations were done for only two extremes, that is, always drawn window blinds and never drawn.The window size, presence, and type of internal blinds as well as light transmittance affected both the average daylight factor as well energy consumption the most. The use of large windows with venetian blinds and light transmittance of 0.71 were the best alternatives for both average daylight factor and energy use. Increase in window size increased both the average daylight factor as well as the operational energy used within the building.