Engineering Commons^™

Learning–Assisted Constraint Filtering To Enhance Power System Optimization Performance, Fouad Hasan

LSU Doctoral Dissertations

Machine learning (ML) is a powerful tool that provides meaningful insights for operators to make fast and efficient decisions by analyzing data from power systems. ML techniques have great potential to assist in solving optimization problems within a shorter time frame and with less computational burden. AC optimal power flow (ACOPF), dynamic economic dispatch (D-ED), and security-constrained unit commitment (SCUC) are the three energy management optimization functions studied in this dissertation. ACOPF is solved every 5~15 minutes. Because of the nonconvex and complex nature of ACOPF, solving this problem for large systems is computationally expensive and time-consuming. Classification and regression …

Studying Complex Aquifer Systems From Large-Scale Stratigraphy Development To Local Aquifer Storage And Recovery, Hamid Vahdat Aboueshagh

LSU Doctoral Dissertations

Hydrostratigraphy model is an essential component of building valid groundwater models. Many challenges are associated with constructing hydrostratigraphy models which include geological complexities such as faults, domes, and angular unconformities. Developing a method with an emphasis on capturing big data to thoroughly inform large-scale models is one of the challenges addressed in the first part of this study. The method is predicated upon discretization of the study domain into tiles based on the geological dip direction and faults. The application of the method in the state of Louisiana with the utilization of more than 114000 well logs demonstrates promising results …

Machine Learning Based Applications For Data Visualization, Modeling, Control, And Optimization For Chemical And Biological Systems, Yan Ma

LSU Doctoral Dissertations

This dissertation report covers Yan Ma’s Ph.D. research with applicational studies of machine learning in manufacturing and biological systems. The research work mainly focuses on reaction modeling, optimization, and control using a deep learning-based approaches, and the work mainly concentrates on deep reinforcement learning (DRL). Yan Ma’s research also involves with data mining with bioinformatics. Large-scale data obtained in RNA-seq is analyzed using non-linear dimensionality reduction with Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP), followed by clustering analysis using k-Means and Hierarchical Density-Based Spatial Clustering with Noise (HDBSCAN). This report focuses …

Optimizing The Performance Of Multi-Threaded Linear Algebra Libraries Based On Task Granularity, Shahrzad Shirzad

LSU Doctoral Dissertations

Linear algebra libraries play a very important role in many HPC applications. As larger datasets are created everyday, it also becomes crucial for the multi-threaded linear algebra libraries to utilize the compute resources properly. Moving toward exascale computing, the current programming models would not be able to fully take advantage of the advances in memory hierarchies, computer architectures, and networks. Asynchronous Many-Task(AMT) Runtime systems would be the solution to help the developers to manage the available parallelism. In this Dissertation we propose an adaptive solution to improve the performance of a linear algebra library based on a set of compile-time …

Applications Of Cfd Simulations On Chemical Processing Equipment Designs, Gongqiang He

LSU Doctoral Dissertations

The objective of this work is to achieve process intensification by seeking optimal equipment design with CFD investigations. In this work, two projects on chemical equipment design have been discussed.

The first project is on design and optimization of fractal distributor in a novel ion-exchanger. Flow distributors are adopted extensively by chemical industry to distribute an incoming process stream uniformly to the downstream equipment. Currently, the performance of chemical equipment installed with conventional distributor is severely undermined due to poor flow distribution. For conventional distributors such as spray nozzle distributors, their design concept is based on maintaining very high pressure …

Microcavity Enhanced Beaming And Magneto-Optical Switching Of Light, Ali Haddadpour

LSU Doctoral Dissertations

In this dissertation, we show numerically that a compact structure, consisting of multiple optical microcavities at both the entrance and exit sides of a subwavelength plasmonic slit, can lead to greatly enhanced directional transmission through the slit. The microcavities increase the resonant enhancement of the emission in the normal direction and/or the coupling between free space waves and the slit mode. An optimized structure with two microcavities on both the entrance and exit sides of the slit leads to ~ 16 times larger transmission cross section per unit angle in the normal direction compared to the optimized reference slit without …

Analytical Solutions And Multiscale Creep Analysis Of Functionally Graded Cylindrical Pressure Vessels, Jasem Amjad Ahmed

LSU Doctoral Dissertations

This study deals with the time-dependent creep analysis of functionally graded thick-cylinders under various thermal and mechanical boundary conditions. Firstly, exact thermoelastic stress, and iterative creep solutions for a heat generating and rotating cylindrical vessel made of functionally graded thermal and mechanical properties are proposed. Equations of equilibrium, compatibility, stress-strain, and strain-displacement relations are solved to obtain closed-form initial stress and strain solutions. It is found that material gradient indices have significant influences on thermoelastic stress profiles. For creep analysis, Norton’s model is incorporated into rate forms of the above-mentioned equations to obtain time-dependent stress and strain results using an …

Design And Optimization Of Nanoplasmonic Waveguide Devices, Pouya Dastmalchi

LSU Doctoral Dissertations

In this dissertation, we introduce compact absorption switches consisting of plasmonic metal-dielectric-metal (MDM) waveguides coupled to multisection cavities. The optimized multisection cavity switches lead to greatly enhanced modulation depth compared to optimized conventional Fabry-Perot cavity switches. We find that the modulation depth of the optimized multisection cavity switches is greatly enhanced compared to the optimized conventional Fabry-Perot cavity switches due to the great enhancement of the total electromagnetic field energy in the cavity region. We then investigate how to improve the computational efficiency of the design of nanoplasmonic devices. More specifically, we show that the space mapping algorithm, originally developed …

A Thermodynamic Framework For The Modeling And Optimization Of Crystallization Processes, David John Widenski

LSU Doctoral Dissertations

Crystallization is a widely used chemical engineering separation unit operation process. Since this technique can produce high purity products it is used for the industrial production of many chemical compounds, such as pharmaceuticals, agrochemicals, and fine chemicals. The production of these products is a multi-million dollar industry. Any methods to improve the production of these products would be highly valued. Thus, the main objective of this work is to target model-based optimal strategies for crystallization operations specifically targeting crystal size and crystal size distribution (CSD). In particular, take the knowledge gained and translate it into an economically and practically feasible …

Fault Detection Filter Design For Linear Systems, Xiaobo Li

LSU Doctoral Dissertations

This dissertation considers residual generation for robust fault detection of linear systems with control inputs, unknown disturbances and possible faults. First, multi-objective fault detection problems such as $\mathscr{H_-}/ \mathscr{H_\infty}$, $\mathscr{H}_2/\mathscr{H_\infty}$ and $\mathscr{H_\infty}/\mathscr{H_\infty}$ have been formulated for linear continuous time-varying systems (LCTVS) in time domain for finite horizon and infinite horizon case, respectively. It is shown that under mild assumptions, the optimal solution is an observer determined by solving a standard differential Riccati equation (DRE). The solution is also extended to the case when the initial state for the system is unknown. Second, the parallel problems are also solved for linear …

Eigenvalue Optimization And Its Applications In Buckling And Vibration, Srinivas Gopal Krishna

LSU Doctoral Dissertations

Eigenvalue problems are of immense interest and play a pivotal role not only in many fields of engineering but also in pure and applied mathematics. An in-depth understanding of this class of problems is a pre-requisite for vibration and buckling analyses of structures. Design optimization of structures to prevent failure due to instability (bucking) and vibration introduces the problem of determining optimal physical parameters such that load carrying capacity or the fundamental natural frequency is maximized. A classical example of such problems is the Lagrange problem of determining the shape of the strongest column against buckling. The primary objective of …

Optimal Control Of Production And Distribution In A Supply Chain System Operating Under A Jit Delivery Policy, Pablo Biswas

LSU Doctoral Dissertations

This research deals with a supply chain system where the production or manufacturing facility operates under a just-in-time (JIT) environment, and the facility consists of raw material suppliers, manufacturers, and retailers where inventory of raw materials, work-in-process, and finished goods are involved, respectively. This work considers that the production of finished goods in one cycle starts just after the production or uptime in preceding cycle to minimize the idle time of the facility. Considering this scenario, inventory models are developed for different delivery situations: (a) perfect matching condition where no finished good remains after the shipments and (b) imperfect matching …

Optimal Operating Strategy For Wells With Downhole Water Sink Completions To Control Water Production And Improve Performance, Ozan Arslan

LSU Doctoral Dissertations

Downhole water sink (DWS) technology is an alternative to conventional limited-entry completions to control water production in wells with bottom water drive. DWS wells comprise two completions: the bottom completion produces water and keeps the top completion open to oil inflow. The system performance depends on careful manipulation of the top and bottom rates to maximize oil productivity and produce oil-free water from the bottom completion. Conventional nodal analysis cannot provide a solution for DWS wells because the critical rates for water coning change with water drainage rate. A reservoir simulator is used to model two-phase flow to the dual …

Optimization Of A Skewed Logistic Distribution With Respect To The Kolmogorov-Smirnov Test, James Charles Finney

LSU Doctoral Dissertations

The four-parameter kappa distribution (Hosking 1994) was analyzed with respect to the various possible shapes of the probability density function. The general form for the cumulative distribution function when both h and k are non-zero is: F(x) = { 1 - h [ 1 - k ( x - ξ ) / α ]^1/k }^1/h. The parameters h and k work together to define the function's shape, ξ affects location, and α is the scale parameter. A method of selecting parameters to minimize the Kolmogorov-Smirnov test statistic, D, was developed. The technique was first described for the …