No description available.

No description available.

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

This dissertation investigates methods of real-time adaptive traffic signal control in the context of single isolated intersection and coordinated urban network applications. A primary goal in this dissertation is to identify and address scenarios where real-time optimized controllers do not maintain competitive performance with off-line calibrated, vehicle-actuated control techniques. An extensive literature review is supplemented by subsequent simulation experiments. Several strategies were implemented and evaluated, including OPAC, PRODYN, COP, ALLONS-D, Webster's optimized fixed-time control, and vehicle-actuated control. In particular, evaluation is based on simulation of a single, isolated intersection, where all algorithms are required to adopt the exact, deterministic traffic model used by the simulation. This approach eliminates confounding factors in comparison of algorithms, such as detector placement and disparate traffic models, focusing evaluation on the efficiency of the algorithms and their ultimate performance in terms of vehicle delay. A new algorithm is developed, employing neuro-dynamic programming techniques, also known as reinforcement learning techniques. Several very effective pruning strategies are also constructed. The final product is a very efficient algorithm capable of solving problems up to 2000 times faster than the most efficient previously published algorithm tested, with an 8% decrease in delay. This algorithm is then extended to a generalized, multi-ring control formulation. Simulation results with a standard dual-ring, eight-phase controller demonstrate that efficient, real-time solutions are achieved with a corresponding 12--22% reduction in delay relative to dual-ring, vehicle-actuated control. The real-time optimized, multi-ring controller is finally extended for urban network applications, expanding the objective function to consider downstream performance measures, and adopt standard, vehicle-actuated type coordination constraints. Control on an 8-intersection arterial is evaluated using a CORSIM simulation over a range of traffic conditions. Results are compared with TRANSYT optimized fixed-time control, coordinated vehicle-actuated control, and RHODES. Two regimes of control are revealed, where cyclic coordination constraints provide a significant benefit, and where they prevent more effective control. An adaptive coordination layer is prescribed as a unifying architecture with the potential of obtaining effective control under both regimes. The adaptive control layer specification is explicitly distinguished from existing algorithms, such as SCOOT, SCATS, and VFC-OPAC.

Automatically Switched Optical Network (ASON) is an optical/transport network that has dynamic optical channel connection and configuration capability. To achieve such functions, an ASON must be equipped with a control plane that is responsible for setting up, releasing, and restoring an "optical channel (connection)" between edge network nodes. However, the details of how to implement and deploy an automatically switched optical network have not been specified and addressed. The IETF has been working on Generalized Multiple Protocol Label Switching (GMPLS) as a control plane to manage optical networks. GMPLS presents itself as the ideal candidate for ASON's control plane. The purpose of this dissertation is to study how to apply GMPLS to build an automatically switched optical network, and the research is being conducted in three stages: (1) the implementation of GMPLS in ASON, building a GMPLS-based Automatically Switched Optical Network (GASON), (2) development of an OPNET-based simulation framework for evaluating ASON wavelength routing algorithms, (3) the management of optical physical impairments in GASON, both in the optical network structure and the GMPLS control plane. These research areas have not yet been addressed by the optical network community. First, the dissertation focuses on the application of GMPLS concepts to control and manage wavelength-routed optical networks. The dissertation discusses the design and modeling of a GMPLS-based Optical Switching Router (GOSR). The GOSR is modeled on OPNET Modeler(c). Based on the developed GOSR model, the GMPLS-based Automatically Switched Optical Network (GASON) is simulated and analyzed. Different wavelength routing algorithms have been studied within the context of GASON. To cope with optical physical impairments, this dissertation proposes the islands of transparency network architecture and develops a constraint-based dynamic wavelength routing algorithm (CDRWA). The comparisons between island of transparency optical network and other types of optical network are made. The developed CDRWA algorithm is the first Routing and Wavelength Assignment (RWA) algorithm that considers optical physical impairments caused by the optical layers. Currently CDRWA uses the hop-number as its constraint.