Evaluation and Validation of COLA in Complex Deep Neural Networks

Deep Neural Networks (DNNs) have achieved remarkable success in various applications; however, their performance can be significantly affected by hardware defects in specialized accelerators. The Error-Correcting Output Codes (ECOC) framework has been proposed to enhance fault tolerance by decomposing multi-class problems into multiple binary classification subproblems. Despite its potential, the ECOC framework faces limitations in maintaining clean accuracy and improving robust accuracy when subjected to hardware defects, primarily due to error correlation between networks. In this thesis, we evaluate the performance of a recently proposed error decorrelation framework, named COLA, which addresses the limitations of the ECOC framework. COLA primarily incorporates the Amplitude Adaptive Weight Orthogonalization technique to lower error correlation in shared layers and the Total Correlation based regularization technique to minimize output error correlation. We evaluate COLA on more complex networks, such as ResNet18 and ResNet34, using the Tiny-ImageNet dataset, demonstrating significant improvements in the performance of models employing the ECOC framework. Compared to the original ECOC model, the improved ECOC model with COLA achieves around 10% increase in clean accuracy and up to around 80% improvement in robust accuracy. However, due to the specific structure of ResNet networks, models with ECOC exhibit notably lower performance than the original networks, both with and without hardware defects. To investigate this issue, we explore the impact of shortcut connections on the ECOC model and found that the presence of these connections can increase the total correlation of the feature map, which may potentially have a detrimental effect on the performance of the model

Assessing the Efficacy of Process-Specific Topology Optimization for Direct-Ink Write 3D-Printed Hierarchical Composites and Structures

Polymers are ubiquitous in modern society. From food packaging to structural components inaerospace applications, plastics can be found. For applications like the latter, there is a requirement for exceptional performance characteristics - whether that be with respect to mechanical stiffness or strength, thermal or electrical conductivity, or other desirable engineering outcomes. As a result, much effort has been exerted in industry and academia toward optimizing the performance of structural components made out of polymers. Performance optimization of structural components, generally speaking, is a multi-layered problem. One layer of this problem is the material design problem – tailoring the properties of the material (by changing/adding to the manufacturing process, leveraging composites, etc.) in the desired component to have certain characteristics. Another layer is the structural design problem – the geometric features of the component (such as shape and topology) that govern its performance in service, such as under mechanical or thermal loading. For polymers, additive manufacturing (AM) is a tool which is very amenable to tailoring, both in terms of material behavior and structural geometry. Its use, in conjunction with structural optimization techniques (e.g. topology optimization, or TO) is the subject of this thesis. First, numerical and experimental benchmarking is presented on minimum mechanical compliance optimization and material extrusion AM techniques (fused filament fabrication, or FFF, and direct-ink writing, or DIW). A major focus of the benchmarking work is the analysis of the impact of mechanical anisotropy and material extrusion orientation on the outcomes of minimum compliance TO designs. Finite element calculations are performed using Matlab scripts and commercial software (ABAQUS) to complement flexural testing of AM specimens made of ABS polymer or epoxy-based polymer matrix composite inks. Next, analysis of multi-material topology optimization (MMTO) and multi-material additive manufacturing (MMAM) is presented. An analysis of choices regarding extrusion of material at the interfaces between materials is presented with corresponding experimental testing (e.g., printing and flexural testing) of specimens with disparate interface designs. Finally, numerical work towards the multi-material thermomechanical optimization of structures with orthotropic material behavior is presented. The main contributions of the thesis work lie in: (i) establishing baseline numerical and experimental evaluations of TO/AM structures using standard TO and AM methods (e.g. SIMP, material-extrusion AM with common infill patterns) (ii) quantifying the impact of process-specific design methodologies for the orientation design of orthotropic composites (iii) presenting a new application of optimization in multiphysics and multi-material TO for isotropic/orthotropic materials that considers elastic compliance and thermal conductance and (iv) initial experimental assessments of printing methodologies for their integrity at material interfaces in multi-material TO structures

Analysis of Nonlinear Control Systems: From Lifting Operators to Learning Interaction Laws in Networks

This dissertation explores a diverse set of problems in dynamical systems, control, estimation, and learning theory. Part I studies nonlinear systems using operator theory, specifically Carleman Linearization. Chapter one delves into the convergence of Carleman Linearization over a characterizable time horizon. The findings show that the Carleman Linearization converges to the original solution for general time-varying nonlinear systems with an analytic right-hand side over a finite time horizon. The third chapter introduces a new method to solve the Hamilton-Jacobi-Bellman Equation using the tools from Carleman Linearization. The analysis demonstrates the convergence of the method and proves that the control input obtained stabilizes the nonlinear dynamics after a certain truncation length. The second part of this dissertation is focused on examining the learning of dynamical systems under the presence of uncertainties. Chapter three explores techniques to enhance the robustness of recurrent neural networks by employing concepts from control and estimation theories. Initially, the chapter outlines how to measure the robustness of the recurrent neural networks and then introduces a novel algorithm to estimate the output covariance and biases for RNNs. We then utilized the gradient descent algorithm to minimize covariances along biases to obtain a robust RNN model. In Chapter four, we analyze the learning of nonlinear couplings in a network of interacting agents in a non-parametric set-up, where only a single sample trajectory is available. The study demonstrates that for geometrically ergodic networks, assuming the compactness of the hypothesis space, learning algorithms converge even when only a single sample trajectory is available. Additionally, we reveal that if the hypothesis space is convex and coercive, the empirical estimator converges uniquely. Part III of this dissertation is dedicated to developing and analyzing a systematic framework to study the risk of undesired events in the network of interconnected agents. In Chapter six, we explore the inherent risk associated with non-minimum phase systems. Using the systematic risk framework, we then investigate the trade-offs between collision risk, network topology, control cost, and non-minimum phase zeros of the system. In the last Chapter, we propose a framework to evaluate the risk of misperception resulting from noisy environmental observations. We employ the Expected Shortfall (Average Value-at-Risk) measure to evaluate the risk of collision between pairs of vehicles and the risk of violating traffic laws for each vehicle under possible misperceptions. Obtaining an explicit expression for the risk measure allows us to investigate potential trade-offs between overall misperception-induced risks and network architecture

Elucidation of local processes in Spontaneous and Turbulent Induced Emulsification

We performed a comprehensive study on understanding the mechanism of emulsification and developing effective methods to counteract it. In the first phase of this study, we discovered two distinct processes for the continuous extraction of organic-free water from detergent-stabilized oil-in-water emulsions. These findings provide promising solutions for mitigating the negative effects of emulsification.. The first process is based upon a modification of the so-called "electro-coagulation", which uses electro-chemically produced metal hydroxides that remove oil droplets via hetero-coagulation. In this method, metal particles are deposited over a graphite anode whereas an aluminum tube is used as a cathode in an electrolysis cell through which the emulsion flow. With an electrical potential applied between the graphite and aluminum, the metal particles are corroded to produce metal hydroxides that sweep the oil droplets from the emulsion. The study carried out with various metals show that the oil extraction efficiency increases with the basicity of the metal hydroxide. A second process, based on acid base interaction as well, uses surface functionalized nickel particles (~45 µm) that introduces amines onto the nickel surface. Here an additional advantage is that the metal particles bound to the oil droplets can be removed from aqueous phase with a magnetic field. While each of the above processes is effective in demulsifying water, their combination vastly improves the oil extraction efficiency. With the integrated process, the total organic content of the treated water could be as low as about 0.1 ppm with the surface tension of water (72 mN/m) being that of organic free water. As the second phase of this research, we introduce the studies we conducted in the emulsification of an oil in salinized water was under turbulent and agitation-free conditions in the presence of a mixture of an ionic and a non-ionic surfactant. The properties of the air-water and the oil-water interfaces were investigated using the methods of du-Nouy ring, drop resonance vibrometry and Langmuir film balance that allowed pinpointing the relevance of certain interfacial properties in emulsification. Estimation of the droplet size and its distribution from the nanometer to micrometer range was carried out with optical microscopy, acoustic attenuation spectroscopy and continuous hydrodynamic flow fractionation. These measurements provided the platform for the comparison of the emulsion droplet size with those predicted from the fluctuation of the dynamic stress in the turbulent water via a capillary-hydrodynamic model. While such a comparison was reasonably meaningful for micron size emulsion droplets, production of nanometer size droplets was beyond such a rudimentary expectation. We thus carried out systematic investigations into other factors that contribute to emulsification under both agitated and agitation free conditions. An important finding of these studies is that the infusion of air bubbles that profoundly enhance the hydrodynamic fluctuation produce mainly submicroscopic emulsion droplets, while a fluctuation inhibiting water-soluble polymer has the opposite effect. Furthermore, while a hydrophilic polymer dissolved in water enhances the ripening of the droplets with time, hydrophobic polymer in oil thwarts aging, plausibly by osmotic backpressure and interfacial stiffening, which, upon compression, acts against surface tension, thereby decreasing the chemical potential of the trapped oil molecules inside the droplet. These effects are similarly observed in spontaneous emulsifications, that is when a layer of oil containing the additives is deposited upon the surface of the aqueous phase in the absence of any external work input. Micro and/or Nano emulsions are formed when an organic liquid gently comes in contact with water in the presence of a surfactant, even with a positive interfacial tension. Many years of research made it clear that the driving force for spontaneous emulsification arises from the differences of the bulk chemical potentials of various components, which triggers various non-equilibrium coupled transport processes, such as diffusion and hydrodynamic fluctuation. While extraordinary theoretical developments have taken place that attempt to describe the emulsification processes within the formalisms of global equilibrium and non-equilibrium thermodynamics, the local processes underlying the spontaneous emulsification, however, still remain elusive. In this research, we attempt to shed light on some of the local processes that involve the transfer of surfactant as well as molecular water from one phase to another (i.e. water to oil), subsequent formation of inverted emulsion and its evolution to oil-in- water emulsion as they cross the phase boundary. These processes lead to either strong or weak fluctuation of component concentration just below the interface that announces fast (athermal) diffusion of the emulsion droplets farther into the bulk of water. These studies have been able to identify the relevant interfacial and hydrodynamic parameters, careful controls of which should be valuable in thwarting emulsification in various practical settings

A Preliminary Study on the Solidification Cracking and Stress Relief Cracking Susceptibility of Various Compositions of 10 Weight Percent Nickel Steel

Research involving the mechanical properties of 10 weight percent nickel steel has recently exemplified its great ballistic resistance and toughness at low temperatures. These superior mechanical properties support the candidacy of this steel to be used in naval combatant ships and other military components that are exposed to low sea temperatures. Despite its potential uses for such applications, limited research has been conducted on the mechanical stability during and after welding, which is essential for the fabrication of military parts. During the weld thermal cycle, the heat affected zone of the steel becomes exposed to very high temperature changes over a short amount of time. This thermal gradient across the span of the HAZ subjects it to high internal stresses after welding. To relieve these stresses, a post-weld heat treatment must be employed, which requires plastic deformation at elevated temperatures. During this process, localized deformation along the grain boundaries can result in low ductility failures, a process known as stress-relief cracking. Another common failure mechanism in steel welds is called solidification cracking, which is a result of non-equilibrium solidification and solute segregation. The solidification cracking and stress-relief cracking susceptibility of three 10 weight percent nickel alloy with varying compositions was investigated using Gleeble, Varestraint, and microscopy techniques. The cracking susceptibility of HY-100, a well-established steel currently being used in ship hull material was also investigated and compared to the 10 weight percent nickel alloys. It was found that the stress relief cracking response largely depend on the carbon content and the post-weld heat treatment temperature, while the trends in solidification cracking susceptibility also depend on the content of tramp elements such as P and S, however further investigation will be necessary to confirm these trends. This investigation provides a reasonable approach to identifying the most suitable composition to be used in hull structure material while avoiding failure via these two mechanisms, and identifies a good post-weld heat treatment temperature to be used after welding this alloy

Investigation Of The Effect Of Injection Pressure On Cavity Filling Of Hot Runner System

This research aims to examine the impact of injection pressure on the process of cavity filling in a hot runner injection molding system, under varying temperature conditions. The research utilizes a combination of analytical and experimental approaches to simulate and evaluate the performance of the hot runner system across various injection pressures and temperatures. The aim of this study is to investigate the impact of injection pressure on the process of cavity filling and to determine the most suitable range of injection pressure that can ensure complete cavity filling and optimal quality of the product. The results of the numerical investigation indicate that injection pressure is a critical parameter that affects the cavity filling process in hot runner injection molding systems. The experiments conducted at different temperatures show that injection pressure has a significant effect on cavity filling, with increasing injection pressure leading to better cavity filling. The optimal injection pressure range for complete cavity filling varies depending on the melting temperature. Incomplete filling occurs at lower injection pressures due to the increased material viscosity caused by the lower melting temperature. The findings of this study can be useful to manufacturers seeking to optimize their hot runner injection molding process for enhanced product quality. Future work includes investigating the effectiveness of Rheodrop technology in cavity filling under low injection pressure

Applications of Tunnel Oxides in Selective Contact and Schottky Barrier-Based Photovoltaics

Novel photovoltaic (PV) cell designs intended to replace p-n junctions are a subject of constant research in the push for more cost-effective solar power. Many of these new technologies benefit from the incorporation of tunnel insulators, which are deposited at the semiconductor interface but remain thin enough for quantum tunneling of charge carriers to occur. Atomic layer deposition (ALD) is a technique utilizing self-limiting chemical half reactions to deposit films with angstrom-level thickness control and is thus an ideal method for fabricating and studying tunnel oxides.PVs utilizing carrier-selective contacts (CSCs) add external layers to PV absorbers. These layers extract one type of charge carrier, either electrons or holes, from the absorber while blocking the other. Defect states may facilitate electron-hole recombination at the interface between the absorber and the CSC, hence tunnel oxides are often introduced at these interfaces to passivate the defects. Data presented in Chapter 3 of the present work have shown that ultrathin aluminum oxide can reduce recombination at the interface between p-type Si and hole-selective molybdenum oxide contacts, reducing surface recombination velocity (SRV) from >1,000 to ~200 cm·s-1 depending on substrate termination, interlayer thickness, and annealing parameters. The study in Chapter 4 examined electron-selective titanium oxide and showed that even without AlOx, interfacial chemical silicon oxide with proper thermal treatment reached SRV values as low as 40 cm·s-1 at the Si/TiOx interface. As-deposited samples incorporating AlOx at the interface exhibited SRV as low as 20 cm·s-1, however passivation degraded with annealing on these samples, and none of the AlOx samples achieved ohmic n-Si/TiOx contacts, suggesting a barrier to carrier collection. Metal-insulator-semiconductor (MIS) PVs instead utilize the Schottky barrier characteristic of metal-semiconductor contacts, relying on a large barrier height (?B) to separate charge carriers. Inserting tunnel oxides at the MS interface is known to affect ?B for several possible reasons, including the formation of dipoles at the interface between two dissimilar oxides. The study in Chapter 5 has investigated these different hypotheses by systematically studying the effects of inserting different high-? tunnel oxides into a n-Si/SiOx/Ni diode stack. ?B increases as large as 0.37 eV and decreases as large as 0.19 eV relative to a SiOx-only insulator were observed, depending on the high-? oxide added. The data correlated with the differences in the oxygen areal density (OAD) between the high-? oxides and SiOx. A relatively unexplored concept is the modulation of ?B using stacks of dissimilar high-? tunnel oxides. The experiments reported in Chapter 6 fabricated AlOx/LaOx tunnel stacks, hypothesizing that the large OAD difference between the two high-? oxides would induce a large dipole and ?B change. When LaOx was introduced, ?B changes relative to an AlOx-only insulator did occur but appeared to be the result of competing interactions between each high-? oxide with the substrate, rather than the high-?/high-? interface. Finally, Chapter 7 reports tunnel stacks of AlOx with a wider variety of other high-? oxides in both deposition orders (AlOx deposited before or after the other oxide). SiOx/high-? interfaces were considered in attempt to isolate the effects of the high-?/high-? interfaces. Apparent dipole strengths of up to 0.40 eV were attributed to the high-?/high-? interface, with the modulation of ?B loosely associated with the differences in both parent metal electronegativity and OAD between the stacked oxides. The larger the EN or OAD difference, the larger the change in ?B, with exceptions

Multidirectional Experimental Performance of a Seismically Resilient Self-Centering Cross-Laminated Timber Shear Wall System

Driven by demand for sustainable buildings, mass timber, specifically cross-laminated timber (CLT), is being widely considered for mid-rise buildings in the US. A post-tensioned self-centering (SC) controlled-rocking CLT shear wall (SC-CLT wall) has potential to be a low-damage lateral-load resisting system for seismically resilient buildings. However, to achieve seismically resilient buildings, improved knowledge of the lateral-load response and damage of the SC-CLT walls under multidirectional loading and the capability of various building structural components, i.e., the floor diaphragm, collector beams, and gravity load system components, to accommodate the multidirectional building seismic response including the controlled-rocking response of the SC-CLT walls, is needed. The overall goal of this research is to design, construct and test a low-damage, resilient three-dimensional CLT building sub-assembly, with an SC-CLT wall, a CLT floor diaphragm, glulam collector beams, and glulam gravity load system.A series of 0.625-scale lateral-load tests was conducted at the NHERI Lehigh Large-Scale Multi-Directional Hybrid Simulation Experimental Facility to investigate the lateral-load response of SC-CLT walls and their interaction with the adjacent building structural components, i.e., the floor diaphragm, collector beams, and gravity load system under multidirectional lateral loading. First, the conceptual design of the test sub-assembly main components and connection details to accommodate the kinematic conditions imposed by building lateral drift response and the controlled-rocking response of the SC-CLT wall under multidirectional loading is presented. The multidirectional displacement control scheme and the associated control algorithm for three-dimensional large-scale lateral-load testing is presented. A series of structural limit and damage states are introduced to characterize the lateral-load response of SC-CLT walls. Fragility functions are developed for assessing the potential damage to SC-CLT walls under unidirectional and multidirectional loading. The lateral-load response of a proposed steel-plate reinforced SC-CLT wall as a repair approach to restore the lateral-load response of a damaged SC-CLT wall and/or as an alternative low-damage lateral-load resisting system is investigated. Finally, the behavior of the CLT floor diaphragm, the SC-CLT wall connections, and the gravity load system connections under multidirectional cyclic lateral loading within a 0.625-scale timber test sub-assembly is investigated. The experimental results are valuable for calibrating numerical models for seismic performance prediction of SC-CLT wall buildings

Real-Time Hybrid Simulation of Complex Structural Systems Subjected to Multi-natural Hazards

The overall objective of this dissertation is to develop new computational algorithms for application to real-time hybrid simulation (RTHS) of complex structural systems subjected to multi-natural hazards. Resiliency of structural systems under natural hazards is of interest. Real-Time Hybrid Simulation (RTHS) is a testing tool that can be used to assess the resiliency of such systems. In a RTHS the complete system is considered, where selected components for which computational models exist are modeled numerical and the remaining components are modeled physically in the laboratory. The former is referred to as the analytical substructure while the latter the experimental substructure. It is necessary to expand RTHS to accommodate large complex structural systems that reflect real world problems. The current state-of-the-art includes modeling systems as two-dimensional planar problems with a limited number of degrees of freedom that excludes soil-foundation-structural system interaction effects. It is necessary to expand RTHS to three dimensional structural systems, to include soil-foundation-structural system interaction effects, to develop computationally efficient algorithms to enable the real-time numerical integration of the equations of motion of a system with a large number of degrees of freedom, and to deal with systems that possess many response modification devices (e.g., nonlinear viscous dampers) while only a limited number of experimental testbeds are available for a RTHS. Expanding RTHS to investigate the resiliency of large and complex renewable energy generation structures, such as offshore wind turbines, is also investigated and RTHS is proven to be a viable tool to understand the long- and short-term behavior of their piled foundation

Single-Cell Sensing Using Non-Specific Intracellular Targets: Leveraging Automation for Complex Diagnoses

Diagnosis of disease is traditionally dependent on identifying specific markers that can alert to the presence of physical abnormalities causing the symptoms within the patient. However, this model poses a problem for diagnosis of more complex states, limiting the ability to diagnose before significant symptoms present or to address some diseases where understanding is limited. Although specific markers help us ensure that an appropriate diagnosis is given, new techniques in data analysis like machine learning can help us solve more complex relationships to improve quantitative diagnosis. The main qualities emphasized in diagnostic techniques are reliability, speed, and cost effectiveness because these all impact the ability of the diagnostic to bring quality care to patients regardless of financial status or global location.While limitations in most diagnostic methods exist, electrical diagnostic methods are widely considered one of the most accessible options in terms of saving time and resources. With electronics, there are typically less required consumables and the need for skilled laboratory technicians supporting in the clinical setting. These low-cost and low-resource options make electrical diagnostic methods highly translatable for both rural and urban locations. In single-cell applications, lab-on-a-chip style diagnostics consolidate cell manipulation and measurement onto small footprint systems that give rapid electrical readings. Electrical impedance can also collect multiple frequencies quickly, leading to more features per cell to develop a more complete picture of distinct levels of cellular organization. Multi-frequency impedance can measure many single cells to represent an entire population and capture both unique properties of individuals and statistically relevant population changes.In the work described here, a microfluidic system integrated with broadband impedance measurement capabilities for single cell analysis is used to examine the way disease-related changes can be both measured and modelled electrically. As a cornerstone, device performance was improved through a systemic approach to integration between the physical and software components of the electronic and microfluidic system. Through these process improvements, optimization occurred in a data-driven manner to improve individual cell speed and location, the integration of control systems, and automated data processing. By taking an interdisciplinary approach and incorporating both hardware and software processes, the throughput was improved to enable study of larger populations than initially possible.As these system integrations improved the capability for measurement of single cells, two cell types were analyzed to look at potential impedance diagnostic markers to identify two different diseases. In one, a lymphoma cell line was treated to change the nucleus size to imitate changes associated with both cancer and apoptosis. In this project, feature selection and a classification learning model was used to identify the frequencies most relevant to alterations in nucleus size and show the ability to predict individual cell nucleus changed within a population based on an electrical signature. Alternatively, skeletal muscle cells were altered to induce a state of oxidative stress and calcium increase, ionic conditions associated with myalgic encephalomyelitis or chronic fatigue syndrome (ME/CFS). The characterization of these ionic changes was used to speculate on measurements of clinically sourced patient skeletal muscle cells from a patient with ME/CFS and an age and sex matched healthy person