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No description available.

The concept of a Figure-of-Merit (FoM) is developed to assess specific mission designs. The variables for a mission plan are so numerous and interdependent that a single parameter cannot accurately represent the overall design performance. The introduction of in-situ resource utilization (ISRU) and the use of advanced modular engines further complicate the problem. For these reasons, the FoM approach has been proposed to provide a more comprehensive look at the overall picture. The analysis encompasses the important design parameters in addition to the less tangible aspects such as long-term effects, reliability and reparability of the hardware, and the risks that are inevitably associated with new technologies. FoM's have been examined in detail for historical missions and for a proposed Mars Sample Return (MSR) mission. Results are presented for a conventional MSR mission along with missions incorporating ISRU and modular engines for comparison. It is concluded that this quantitative FoM approach may well become a key tool in the analysis and design of future space missions.

<p> This dissertation studies two important problems in the field of biomass supply chain network. In the first part of the dissertation, we study the impact of different carbon regulatory policies such as carbon cap, carbon tax, carbon cap-and-trade and carbon offsetmechanism on the design and management of a biofuel supply chain network under both deterministic and stochastic settings. These mathematical models identify locations and production capacities for biocrude production plants by exploring the trade-offs that exist between transportations costs, facility investment costs and emissions. The model is solved using a modified L-shaped algorithm. We used the state of Mississippi as a testing ground for our model. A number of observations are made about the impact of each policy on the biofuel supply chain network. </p><p> In the second part of the dissertation, we study the impact of intermodal hub disruption on a biofuel supply chain network. We present mathematical model that designs multimodal transportation network for a biofuel supply chain system, where intermodal hubs are subject to site-dependent probabilistic disruptions. The disruption probabilities of intermodal hubs are estimated by using a probabilistic model which is developed using real world data. We further extend this model to develop a mixed integer nonlinear program that allocates intermodal hub dynamically to cope with biomass supply fluctuations and to hedge against natural disasters. We developed a rolling horizon based Benders decomposition algorithm to solve this challenging NP-hard problem. Numerical experiments show that this proposed algorithm can solve large scale problem instances to a near optimal solution in a reasonable time. We applied the models to a case study using data from the southeast region of U.S. Finally, a number of managerial insights are drawn into the impact of intermodal-related risk on the supply chain performance.</p>

This research investigation suggests a methodology for analyzing the spatial impacts of socio-economic changes in the urban environment. The study area is comprised of eighteen zones. Each zone reflects unique social and economic information resulting in a series of profiles of the study area. A linear programming algorithm is used to drive the interaction of elements of the system. Information is organized in the objective function of the linear program as an index of the relative socio-economic quality of each zone. This function is maximized subject to a series of constraints which reflect information about housing and economic requirements necessary for residency in each area. Changes in the environmental quality of each area are identified through the social accounting index and constraints in each location. The system is designed to link temporal models of housing production and cost changes, income and employment changes to optimal spatial allocation models. The results of this investigation suggest: (a) a procedure identifying key elements affecting locational decisions in the urban environment; (b) an impact analysis tool to assess impacts of changes in (a); (c) a mechanism offering the potential to assess impacts of public infrastructure investment on the attractiveness of social and economic areas, and (d) a forecasting procedure using linear programming to optimize within each time frame. Conceptual and design difficulties remain, and are identified. The structure developed herein provides an innovative foundation calculus for further understanding the critical variables that affect the location of economic classes in the urban environment / acase@tulane.edu

acase@tulane.edu

Application of a Hidden Bayes Naive Multiclass Classifier in Network Intrusion Detection