College of Engineering

The continuous growing demand for water, prolonged periods of drought, and climatic uncertainties attributed mainly to climate change mean surface water reservoirs more than ever need to be managed efficiently. Several optimization algorithms have been developed to optimize multi-reservoir systems operation, mostly during severe dry/wet seasons, to mitigate extreme-events consequences. Yet, convergence speed, presence of local optimums, and calculation-cost efficiency are challenging while looking for the global optimum. In this paper, the problem of finding an efficient optimal operation policy in multi-reservoir systems is discussed. The complexity of the long-term operating rules and the reservoirs’ upstream and downstream joint-demands projected in recursive constraints make this problem formidable. The original Coral Reefs Optimization (CRO) algorithm, which is a meta-heuristic evolutionary algorithm, and two modified versions have been used to solve this problem. Proposed modifications reduce the calculation cost by narrowing the search space called a constrained-CCRO and adjusting reproduction operators with a reinforcement learning approach, namely the Q-Learning method (i.e., the CCRO-QL algorithm). The modified versions search for the optimum solution in the feasible region instead of the entire problem domain. The models’ performance has been evaluated by solving five mathematical benchmark problems and a well-known continuous four-reservoir system (CFr) problem. Obtained results have been compared with those in the literature and the global optimum, which Linear Programming (LP) achieves. The CCRO-QL is shown to be very calculation-cost-effective in locating the global optimum or near-optimal solutions and efficient in terms of convergence, accuracy, and robustness.

Resilience is a relatively new concept in computer security that is continuing to evolve. The research community has not settled on an exact definition for resilience, but most agree that this security property should include resistence to attack, damage recovery, and the ability for a system to learn and better resist such an attack in the future. Much of the existing research has focused on resilience solely in terms of availability, or in defining metrics to describe and compare the resilience of systems. The goal of this dissertation is to not only explore the possibility of a more general framework for resilience, but to also analyze the effectiveness of methods and technologies that can be used to measure and provide resilience.

The dissertation begins by covering common elements of computer security, providing exam- ples, addressing vulnerabilities and exploits, and suggesting potential solutions. In later sections, we examine the feasibility of the proposed solutions. Alternative solutions are compared in the context of a network’s priorities, abilities, and dependencies. Our work is inspired by the need for better security metrics in order to quantitatively evaluate and compare different systems and networks. A robust set of metrics that describe the security and recovery features of systems can provide a foundation for at least two key concepts: a network resilience communication protocol and a resilience testing framework. The communication protocol could help network administrators maintain and improve the resilience of their networks. It would facilitate communication between systems on the network so that potential threats can be quickly identified and so that changes can be made autonomously to reduce the impact of a threat without the need for human intervention. The testing framework can be used to test a system’s resilience to specific attacks, packaged as portable modules. Network administrators can use data and visualization results of this framework to make informed decisions about how to improve their resilience. The communication protocol may be able to analyze results from the testing framework to improve a network’s resilience. The goal of these two projects would be to develop solutions that can improve the resilience of networks in general, taking into account their size, security requirements, and critical functions.

Tanglegrams are a tool to infer joint evolution of species. Tanglegrams are widely used in ecology to study joint evolution history of parasitic or symbiotically linked species.  Visually, a tanglegram is a pair of evolutionary trees drawn with the leaves facing at each other. One species at the leaf of one trees is related ecologically to a species at a leaf of another tree. Related species from the two trees are connected by an edge. The number of crossings between the edges joining the leaves indicate the relatedness of the trees.        Earlier work on tanglegrams considered the same number of leaves on both the trees and one edge between the leaves of the two trees. In this paper we consider multiple edges from a leaf in the trees. These edges correspond to ecological events like duplication, host switching etc. We generalize the definition of tanglegrams to admit multiple edges between the leaves. We show integer programs for optimizing the number of crossings. The integer program has an XOR formulation very similar to the formulation for the tanglegrams. We also show how the ideas for distance minimization on tanglegrams can be extended for the generalized tanglegrams.  We show that the tanglegram drawings used in ecology can be improved to have fewer crossings using our integer programs.

We propose a system for dynamic triangle mesh processing entirely on the GPU. Our system offers an efficient data structure that allows fast updates of the underlying mesh connectivity and attributes. Our data structure partitions the mesh into small patches which allows processing all dynamic updates for each patch within the GPU's fast shared memory. This allows us to rely on speculative processing for conflict handling, which has low rollback cost while maximizing parallelism and reducing the cost of locking. Our system also introduces a new programming model for dynamic mesh processing. The programming model offers concise semantics for dynamic updates, relieving the user from having to worry about conflicting updates in the context of parallel execution. Our programming model relies on the cavity operator, which is a general mesh update operator that formulates any dynamic operation as an element reinsertion by removing a set of mesh elements and inserting others in the created void. We used our system to implement Delaunay edge flips and isotropic remeshing applications on the GPU. Our system achieves a 3—18x speedup on large models compared to multithreaded CPU solutions. Despite our additional dynamic features, our data structure also outperforms state-of-the-art GPU static data structures in terms of speed and memory requirements.

The heterogeneous and homogeneous combustion-based homogeneous charge compression ignition of fuel-lean methane-air mixtures over alumina-supported platinum catalysts was investigated experimentally and numerically in free-piston micro-engines without ignition sources. Single-shot experiments were carried out in the purely homogeneous and coupled heterogeneous and homogeneous combustion modes, involved temperature measurements, capturing the visible combustion image sequences, exhaust gas analysis, and the physicochemical characterization of catalysts. Simulations were performed with a two-dimensional transient model that includes detailed heterogeneous and homogeneous chemistry and transport, leakage, and free-piston motion to gain physical insight and to explore the heterogeneous and homogeneous combustion characteristics. The micro-engine performance concerning combustion efficiency, mass loss, energy density, and free-piston dynamics was investigated. The results reveal that heterogeneous reactions cause earlier ignition, which is very favourable for the micro-device. Both purely homogeneous and coupled heterogeneous and homogeneous combustion of methane-air mixtures in a narrow cylinder with a diameter of 3 mm and a height of approximately 0.3 mm are possible. Heat losses result in higher mass losses. The coupled heterogeneous and homogeneous mode can not only significantly improve the combustion efficiency, in-cylinder temperature and pressure, output power and energy density, but also reduce the mass loss because of its lower compression ratio and less time spent around the top dead centre and during the expansion stroke, indicating that this coupled mode is a promising combustion scheme for micro-engines.

The most efficient and stable combustion occurs in a catalytic reactor when the burning mixture is in contact with the catalyst for a sufficiently long period. When the contract period is too short, insufficient energy is generated adjacent to the catalyst surface to sustain combustion in the main or free stream. This study is focused mainly upon the essential combustion characteristics of propane-air mixtures in flow tube reactors with a heat-recirculating structure. Computational fluid dynamics simulations are performed to gain a greater understanding of the mechanisms of flame stabilization. The essential factors affecting flame stability and combustion characteristics are determined in order to obtain design insights. The results indicate that in order to meet the emission level requirements, for industrial low emission gas turbine engines, staged combustion is required in order to minimise the quantity of the oxides of nitrogen produced. The combustion catalyst has several desirable characteristics: they are capable of minimizing nitrogen oxides emission and improving the pattern factor. Operating the combustion process in a very lean condition, namely high excess air, is one of the simplest ways of achieving lower temperatures and hence lower nitrogen oxides emissions. The use of a catalytic combustor offers the advantage that all of the fuel can be oxidized therein, resulting in ultra-low nitrogen oxides emissions and low carbon monoxide and unburned hydrocarbon levels. In mass transfer controlled catalytic reactions, one cannot distinguish between a more active catalyst and a less active catalyst because the intrinsic catalyst activity is not determinative of the rate of reaction. It is possible to achieve essentially adiabatic combustion in the presence of a catalyst at a reaction rate many times greater than the mass transfer limited rate. The maximum achievable velocity depends on flow conditions and catalyst parameters such as type, monolith cell size, and web thickness.

Direct oxidation of fuels such as methanol in proton-exchange membrane fuel cells at practical current densities with acceptable catalyst loadings is not as economically attractive as conversion of methanol fuel to a hydrogen-rich mixture of gases via steam reforming and subsequent electrochemical conversion of the hydrogen-rich fuel stream to direct current in the fuel cell. The potential of methanol reforming systems to greatly improve productivity in chemical reactors has been limited, due in part, to the effect of mass transfer limitations on the production of hydrogen. There is a need to determine whether or not a microchannel reforming reactor system is operated in a mass transfer-controlled regime, and provide the necessary criteria so that mass transfer limitations can be effectively eliminated in the reactor. Three-dimensional numerical simulations were carried out using computational fluid dynamics to investigate the essential characteristics of mass transport processes in a microchannel reforming reactor and to develop criteria for determining mass transfer limitations. The reactor was designed for thermochemically producing hydrogen from methanol by steam reforming. The mass transfer effects involved in the reforming process were evaluated, and the role of various design parameters was determined for the thermally integrated reactor. In order to simplify the mathematics of mass transport phenomena, use was made of dimensionless numbers or ratios of parameters that numerically describe the physical properties in the reactor without units. The results indicated that the rate of the reforming reaction is limited by mass transfer near the entrance of the reactor and by kinetics further downstream, when the heat transfer in the autothermal system is efficient. There is not an effective method to reduce channel dimensions if the flow rate remains constant, or to reduce fluid velocities if the residence time is kept constant. The performance of the reactor can be greatly improved by means of proper design of catalyst layer thickness and through adjusting feed composition to minimize or reduce mass transfer limitations in the reactor. Finally, the criteria that can be used to distinguish between different mass transport and kinetics regimes in the reactor with a first-order reforming reaction were presented.