Engineering Commons^™

Multiscale Modeling Of Morphology And Proton/Ion Transport In Electrolytes, Zhenghao Zhu

Doctoral Dissertations

Understanding structure-function relationships in electrolytes is essential for advancing energy conversion and storage. This dissertation employs multiscale modeling and simulations to study the morphology and proton/ion transport in various electrolytes for electrochemical systems, including anion exchange membranes (AEMs), protic ionic liquids (PILs), pure phosphoric acid (PA) and aqueous acid solutions, ionic liquids (ILs), and polymerized ionic liquids (polyILs).

Mesoscale dissipative particle dynamics (DPD) simulations were employed to study the hydrated morphology of polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (SEBS)-based AEMs. The results indicate that the choice of the functional group moderately affects the water distribution and has little influence on the …

Prompt Vs Local Redeposition: Model Refinement And Experimental Design For Understanding High-Z Net Erosion In Magnetic Confinement Fusion, Davis C. Easley

Doctoral Dissertations

The economic and engineering success of magnetic confinement fusion reactors significantly depends upon the optimization of plasma facing component (PFC) design. For high-Z PFCs, the critical engineering condition is minimal net erosion (i.e. gross erosion – redeposition). Here, we present a high-Z net erosion model discriminating three primary redeposition mechanisms: prompt (geometric-driven), local (sheath-driven), and far (scrape-off-layer-driven). Using these distinctions, we show modeling for high-Z net erosion in magnetic-confinement fusion over a matrix of key plasma parameters. With Sobol’ methods we assess the sensitivity of each mechanism and show that prompt-vs-local trade-off critically explains underprediction in redeposition losses of up …

Multi-Objective Radiological Analysis In Real Environments, David Raji

Doctoral Dissertations

Designing systems to solve problems arising in real-world radiological scenarios is a highly challenging task due to the contextual complexities that arise. Among these are emergency response, environmental exploration, and radiological threat detection. An approach to handling problems for these applications with explicitly multi-objective formulations is advanced. This is brought into focus with investigation of a number of case studies in both natural and urban environments. These include node placement in and path planning through radioactivity-contaminated areas, radiation detection sensor network measurement update sensitivity, control schemes for multi-robot radioactive exploration in unknown environments, and adversarial analysis for an urban nuclear …

Stability Of Quantum Computers, Samudra Dasgupta

Doctoral Dissertations

Quantum computing's potential is immense, promising super-polynomial reductions in execution time, energy use, and memory requirements compared to classical computers. This technology has the power to revolutionize scientific applications such as simulating many-body quantum systems for molecular structure understanding, factorization of large integers, enhance machine learning, and in the process, disrupt industries like telecommunications, material science, pharmaceuticals and artificial intelligence. However, quantum computing's potential is curtailed by noise, further complicated by non-stationary noise parameter distributions across time and qubits. This dissertation focuses on the persistent issue of noise in quantum computing, particularly non-stationarity of noise parameters in transmon processors. It …

Understanding The Impact Of Divertor And Main Chamber Ion Fluxes On Divertor Closure In The Diii-D Tokamak, Kirtan M. Davda

Doctoral Dissertations

The diverted tokamak redirects extreme heat and particles to targets, a plasma-facing component designed for such loads. Here, the local fluxes produce strong particle recycling and sputtering. Recycled neutrals can “leak” into the region between the core and wall, the scrape-off-layer (SOL), impacting plasma performance. Increasing divertor closure can reduce leakage by containing neutrals within the divertor. However, there exists a need to quantify divertor baffle restrictions and understand closure directly from empirical data as opposed to indirectly through modeling.

Our study introduces the Geometric Restriction Parameter (GRP) based on simplifying neutral transport to ballistic pathways. Specifically, it considers the …

Multimodal Data Fusion And Machine Learning For Advancing Biomedical Applications, Md Inzamam Ul Haque

Doctoral Dissertations

This dissertation delves into the intricate landscape of biomedical imaging, examining the transformative potential of data fusion techniques to refine our understanding and diagnosis of health conditions. Daily influxes of diverse biomedical data prompt an exploration into the challenges arising from relying solely on individual imaging modalities. The central premise revolves around the imperative to combine information from varied sources to achieve a holistic comprehension of complex health issues.

The chapters included here contain articles and excerpts from published works. The study unfolds through an examination of four distinct applications of data fusion techniques. It commences with refining clinical task …

Experimental Quantum Key Distribution In Turbulent Channels, Kazi Mh Reaz

Doctoral Dissertations

Quantum Key Distribution (QKD) ensures security by relying on the laws of quantum physics rather than the mathematical intricacy of encryption algorithms. The transmission medium is a critical restricting factor for any quantum communication protocol. Fiber-based optical networks suffer great losses, making quantum communication impossible beyond metropolitan scales. Here free-space quantum communication can be a great alternative for long-distance communication. Even though modern Communications are mostly wireless the atmosphere poses a challenge for QKD. So QKD must be resistant to both atmospheric loss and variations in transmittance. In this thesis we conduct an experiment to strengthen the BB84 protocol's resistance …

Development Of An Integrated Workflow For Nucleosome Modeling And Simulations, Ran Sun

Doctoral Dissertations

Nucleosomes are the building blocks of eukaryotic genomes and thus fundamental to to all genetic processes. Any protein or drug that binds DNA must either cooperate or compete with nucleosomes. Given that a nucleosome contains 147 base pairs of DNA, there are approximately 4^147 or 10^88 possible sequences for a single nucleosome. Exhaustive studies are not possible. However, genome wide association studies can identify individual nucleosomes of interest to a specific mechanism, and today's supercomputers enable comparative simulation studies of 10s to 100s of nucleosomes. The goal of this thesis is to develop and present and end-to-end workflow that serves …

Adversarial Transferability And Generalization In Robust Deep Learning, Tao Wu

Doctoral Dissertations

Despite its remarkable achievements across a multitude of benchmark tasks, deep learning (DL) models exhibit significant fragility to adversarial examples, i.e., subtle modifications applied to inputs during testing yet effective in misleading DL models. These meticulously crafted perturbations possess the remarkable property of transferability: an adversarial example that effectively fools one model often retains its effectiveness against another model, even if the two models were trained independently. This research delves into the characteristics influencing the transferability of adversarial examples from three distinct and complementary perspectives: data, model, and optimization. Firstly, from the data perspective, we propose a new method of …