PhD, University of Cincinnati, 2008, Engineering : Computer Science and Engineering

Wireless Mesh Networks (WMNs) have revolutionized provisioning of economical and broadband wireless internet service to the whole community of users. The self-configurable and self-healing ability of WMNs has encouraged their rapid proliferation, as adding a mesh router (MR) is as simple as plugging and turning on. The plug-and-play architecture of WMN, however paves way to malicious intruders. An attacker can raise several security concerns, like rogue routers, selfishness, and denial-of-service attacks. Unfortunately, current thrust of research in WMNs, is primarily focused on developing multi-path routing protocols; and security is very much in its infancy. Owing to the hierarchical architecture of WMNs, security issues are multi-dimensional. As mesh routers form the backbone of the network, it is critical to secure them from various attacks. In this dissertation we develop integrated security architecture to protect the mesh backbone. It is important to provide an end-to-end security for mesh clients and hence we design a novel authentication protocol for mutually authenticating mesh clients and mesh routers. The aim of this dissertation is to explore various issues that affect the performance and security of WMNs. We first examine the threat of an active attack like Denial of service attack on MRs and design a cache based throttle mechanism to control it. Next, we develop a MAC identifier based trace table to determine the precise source of a DoS attacker. We then evaluate the vulnerability of WMNs to passive attacks, like selfishness and propose an adaptive mechanism to penalize selfish MRs that discretely drop other's packets. In order to handle route disruption attacks like malicious route discovery, we design an intelligent Intrusion Detection System. Through extensive simulations, we evaluate effectiveness of our proposed solutions in mitigating these attacks. Finally, we design a light weight authentication protocol for mesh clients using inexpensive hash (open full item for complete abstract)

Committee: Dr. Dharma Agrawal (Advisor) Subjects:

Doctor of Philosophy, Case Western Reserve University, 2021, Biomedical Engineering

Post-surgical adhesions are internal scars that pathologically adhere together adjacent tissues/organs/biomaterials. They pose a tremendous but frequently underestimated burden across many surgical disciplines, being especially prevalent following abdominal surgery. Peritoneal adhesions can cause discomfort, intestinal obstructions, infertility, and increased morbidity/mortality of subsequent surgery. Once formed, treatments for adhesions tend to be risky and ineffective, so prophylactic strategies are desirable. Implantation of meshes, such as in hernia repair, often exacerbates peritoneal adhesions. Knitted polypropylene (PP) meshes are the most common hernioplasty devices, but are notoriously adhesiogenic owing to material and structural characteristics that promote incorporation, such as hydrophobicity and reticular construction. The ideal strategy to prevent mesh adhesions entails adhering a smooth, continuous, hydrophilic barrier material on the mesh visceral face to mitigate tissue attachment processes. Prior studies developed polymerized cyclodextrin (pCD) materials having unique capabilities for sustained, multi-window drug release, and suggested that these hydrophilic polymers passively resist cell attachment. In several animal species, pCD could deliver antibiotics for weeks to successfully resolve mesh infection, another hernioplasty complication for which only suboptimal solutions exist. In the present work, pCD materials were explored toward application as novel adhesion barriers for PP surgical meshes. First, nonthermal plasma activation was assessed as a strategy to improve PP-pCD bonding, as PP is generally unreceptive to coatings. Plasma introduced hydroxyls onto PP, enhancing PP-pCD adherence. Second, protein adsorption, bacterial attachment, and fibroblast viability/attachment upon pCD-coated and bare PP materials were evaluated. These events play roles in mesh adhesion, infection, and biocompatibility. pCD decreased protein adsorption and bacter (open full item for complete abstract)

Committee: Horst von Recum PhD (Advisor); Jeffrey Capadona PhD (Committee Chair); Kathleen Derwin PhD (Committee Member); Guang Zhou PhD (Committee Member); Michael Rosen MD (Committee Member) Subjects: Biomedical Engineering

Master of Science, The Ohio State University, 2017, Civil Engineering

The purpose of this research is to provide a two-dimensional quadrangular mesh-generating tool for modeling shallow water flow within a discontinuous Galerkin finite element framework – a setting where meshes of triangular or quadrilateral composition are easily accommodated and demonstrably advantageous. Prior research and development of ADMESH+ shows that automatic mesh generators can produce high-quality meshes with an appealing gradation of edge size given a minimal set of input, e.g., minimum element size, maximum element size, and domain shoreline and bathymetry. This research aims to expand upon the accomplishments of ADMESH+ by developing a novel method (QuADMESH+) for converting high-quality triangular meshes into quadrangular meshes that retain the geometric and aesthetic facets of the original mesh. Techniques employed in our approach include: triangular-mesh generation techniques used in ADMESH+; a heuristic decision-making algorithm for matching two triangular elements together to form quadrilaterals; a routine for removing any unmatched triangular elements; and common topological operations to improve the quality of quadrilateral elements in the resultant mesh, such as a finite element smoothing algorithm.

Committee: Ethan Kubatko (Advisor); Alan Zundel (Committee Member); Gil Bohrer (Committee Member); Abdollah Shafieezadeh (Committee Member) Subjects: Civil Engineering; Environmental Engineering; Water Resource Management

PhD, University of Cincinnati, 2010, Engineering and Applied Science: Computer Science and Engineering

Wireless mesh network (WMN) is a strong candidate for the next generation wireless network. A WMN is made up with three types of entities: Internet Gateways (IGWs), mesh routers (MRs), and mesh clients (MCs). IGWs provide interfaces to both the Internet and MRs. MRs together with IGWs form a mesh backbone by interconnecting each other via multi-hop wireless links. MCs access the Internet by setting up connections with MRs. The placement of three entities is one of the fundamental issues that could greatly affect the performance of a WMN. Positioning technique in WMNs aims at optimizing the positions of these nodes to improve network performance and could be further categorized into: IGW placement, MR placement and MC association. The first part of this dissertation introduces our work over MR placement. MR placement is a strategy that determines the minimal number and positions of MRs that satisfies various constraints such as network coverage, connectivity, Internet traffic demand, etc., for a given network area to be covered by a WMN. Some MR placement strategies may also indicate the appropriate number of interfaces each MR needs as well. A systematic MR placement is the first important step for establishing a WMN with desired network performance efficiently. Our study starts from modeling and formulating the MR placement problem. Then, we analyze the problem in an ideal homogeneous network model, which is characterized by single IGW, identical transmission rate, and MRs could be positioned anywhere in the network region. Hence, we extend the discussion into a more realistic constraint network model: MRs can only be placed in the pre-decided candidate positions; traffic demands is non-uniformly distributed. Furthermore, we deepen our study by taking into accounts the nature of multiple transmission ranges/rates of commercial MRs. We propose a heuristic placement algorithm called ILSearch, which considers both multiple transmission rates and co-channel interferenc (open full item for complete abstract)

Committee: Dharma Agrawal DSc (Committee Chair); Kenneth Berman PhD (Committee Member); Yizong Cheng PhD (Committee Member); Chia Han PhD (Committee Member); Wen Ben Jone PhD (Committee Member) Subjects: Computer Science

Doctor of Philosophy, The Ohio State University, 2024, Mechanical Engineering

Unstructured conforming meshes comprised of tetrahedral elements are widely used in finite element methods (FEM) for solving partial differential equations. To overcome the limitations of the iterative mesh generation techniques, the Conforming to Interface Structured Adaptive Mesh Refinement Algorithm (CISAMR) was developed that non-iteratively transforms a structured background mesh of tetrahedral elements into a fully conforming unstructured mesh with high-quality elements using 4 phases in 3D. In its original implementation, it was limited to only smooth geometries thereby limiting its capabilities for many problems encountered in engineering. This thesis introduces two new capabilities to the CISAMR algorithm. First, we present a framework to mesh non-smooth geometries with C0-continuities in 3D and create high-fidelity finite element (FE) models. A pre-processing stage is introduced to identify sharp features from a Stereolithography (STL) file. New algorithms are introduced to expedite the mesh geometry interaction process for a faster meshing time. A hierarchical r-adaptivity approach is used for relocating the background mesh nodes onto the sharp features of the geometry, an element deletion phase is introduced to eliminate degenerate tetrahedra and improve the mesh quality, and finally, a novel Kirigami-inspired sub-tetrahedralization algorithm is introduced to subdivide the remaining non-conforming tetrahedra and generate a conforming mesh that matches the material interface. These algorithms either upgrade or fully replace different phases of the original CISAMR technique, which was limited to modeling problems with smooth interfaces. Several example problems are then provided to demonstrate the upgraded CISAMR algorithm to handle domain geometries with complex, non-smooth interfaces. In the second part, a modified version of the CISAMR algorithm is presented for meshing closely packed microstructures as a part of an integrated computational framework fo (open full item for complete abstract)

Committee: Soheil Soghrati (Advisor); Alok Sutradhar (Committee Member); Carlos Castro (Committee Member) Subjects: Mechanical Engineering

Doctor of Philosophy, The Ohio State University, 2022, Mechanical Engineering

A modified version of the Conforming to Interface Structured Adaptive Mesh Refinement (CISAMR) algorithm is presented for the construction of higher order Lagrangian and NURBS-enhanced (NE) finite element meshes. CISAMR non-iteratively transforms a structured grid into a conforming mesh with an upper bound of three on aspect ratios of resulting elements. In this thesis, we introduce new algorithmic aspects for generating higher-order Lagrangian and NE meshes using CISAMR. For each type of element, a comprehensive study is then provided on the performance of first, second, and third-order meshes for solving linear elastic problems with smooth and oscillatory curvilinear edges. In these examples, local gradient recovery error, computational cost, and implementation complexity are used as performance metrics. Outcomes of this numerical study are used as a case study to elucidate some of the common sources of bias in interpreting or presenting results. In particular we show how bias, whether purposeful or not, could lead to misleading conclusions regarding the performance of a numerical technique that could even contradict the actual situation. In the next part, we expand the CISAMR algorithm for modeling complex two-dimensional (2D) crack growth problems involving contact/friction along the crack surface and interaction between multiple cracks. The CISAMR algorithm transforms a structured mesh into a high-quality conforming mesh non-iteratively, which is an attractive feature for modeling the evolution of the crack geometry with minimal changes to the underlying mesh structure. To model such problems, the mesh structure is first adaptively refined and updated near the crack tip to form a spider-web pattern of elements for the accurate approximation of the energy release rate and thereby predicting the new crack path. In each step of the crack advance simulation, a small subset of elements in the vicinity of the crack tip detected by employing a tree data structure a (open full item for complete abstract)

Committee: Soheil Soghrati Dr (Advisor); David Talbot Dr (Committee Member); Rebecca Dupaix Dr (Committee Member) Subjects: Mechanical Engineering

Master of Sciences (Engineering), Case Western Reserve University, 2022, Biomedical Engineering

This study investigated the effects of Ar/H2O plasma treatment on the surface and bulk properties of polytetrafluoroethylene (PTFE) and polyethylene terephthalate (PET) surgical mesh materials as a method to modify and mitigate biofouling events that reduce their performance. With regards to bulk properties, findings from uniaxial tensile testing of these substrates in mesh and suture form show that plasma treatment can weaken their tensile properties. Increasing treatment duration and surface area to volume ratio were found to be major factors that resulted in further reduction of these properties. With regards to surface properties, the direct application of plasma on these substrates was not found to reduce biofouling in the form of protein adsorption and S. aureus attachment compared to untreated control surfaces. These experiments suggest that the deposition of a subsequent coating after plasma treatment is needed to further control biofouling events and is a future direction worth investigating.

Committee: Horst von Recum PhD (Advisor); Julie Renner PhD (Committee Member); Sam Senyo PhD (Committee Member) Subjects: Biomedical Engineering

Doctor of Philosophy, The Ohio State University, 2019, Mechanical Engineering

Modeling of problems involving complex morphological features present significant challenges, particularly the creation of high quality conforming finite element meshes from realistic geometries. In addition to being computationally demanding, generating thousands of conforming meshes for problems such as design optimization and uncertainty quantification (UQ) is labor cost intensive. A new non-iterative mesh generation algorithm named Conforming to Interface Structured Adaptive Mesh Refinement (CISAMR) is introduced for the automated generation of high quality finite element meshes for complex geometries. The CISAMR transforms a structured background mesh into a conforming mesh with an upper bound on element aspect ratios. For two dimensional problems, the CISAMR algorithm transforms an initially structured quadrilateral grid into a conforming hybrid mesh composed of triangular and quadrilateral elements. Similarly, a structured tetrahedral grid is transformed into a conforming mesh composed solely of Tet elements for problems in three dimensions. This mesh transformation is initiated with the Structured Adaptive Mesh Refinement (SAMR) of elements in the vicinity of material interfaces. An r-adaptivity algorithm is subsequently employed to non-iteratively relocate select nodes of nonconforming elements. The final conforming mesh is constructed by sub-dividing the remaining nonconforming elements, including those containing hanging nodes generated during the local refinement phase. Regardless of problem complexity, the CISAMR ensures that aspect ratios are limited to an upper bound of three and five respectively, for conforming meshes generated in two and three dimensions, without requiring iterative smoothing or optimization techniques. However, a small fraction of heavily distorted tetrahedrons in 3-D are eliminated by performing a non-iterative face-swapping operation following the r-adaptivity phase. Furthermore, a modified version of this approach is intr (open full item for complete abstract)

Committee: Soheil Soghrati Dr. (Advisor); Carlos Castro Dr. (Committee Member); Stephen Niezgoda Dr. (Committee Member) Subjects: Mechanical Engineering

MS, University of Cincinnati, 2019, Engineering and Applied Science: Mechanical Engineering

Meshing is a crucial element of any FEA simulation. Accurate modeling & simulation requires close approximation of standard test conditions and definition of parameters influencing the phenomenon with the optimization. In current standards, the mesh size needs to be small to get an accurate estimation of the experimental result. However, this leads to long simulation time consuming vital time and resources. On the other hand, increasing the mesh size leads to inaccurate results. This problem is tackled in this study through mesh regularization by introducing mesh size-based scaling factor in the material damage model. The study for mesh regularization or mesh size optimization is studied in three examples. The mesh size-based scaling factor is found out through tensile tests, and the comparison of the numerical simulations results with the experimental tests. Then the scaling factor is implemented in the numerical simulations of a real structural experiment considered in this study. The study for mesh regularization or mesh size optimization goes through extensive research for the various experiments, i.e., Ballistic test, Milling test, and Engine casing penetration testing. Two different materials, namely, Titanium alloy (Ti-6Al-4V) and Aluminum alloy (Al7020-T651), are used. The material damage models used are Johnson Cook and GISSMO (Generalized Incremental Stress State-dependent Model). The study also tries to derive theoretical models to predict accurate scaling factors for mesh regularization. The theoretical scaling factors with the experimental scaling factor found through the numerical simulation of the experiments. Furthermore, this study also presents a summary of theoretical models published in the literature to predict certain scaling factors for mesh regularization. The theoretical scaling factors with the experimental scaling factor found through the numerical simulation of the experiments are compared and presented.

Committee: Ala Tabiei Ph.D. (Committee Chair); Michael Alexander-Ramos Ph.D. (Committee Member); Woo Kyun Kim Ph.D. (Committee Member) Subjects: Mechanical Engineering

Master of Science, Miami University, 2019, Computer Science and Software Engineering

Having high resolution Infra-Red (IR) imagery in cluttered environment of battlespace is crucial for capturing intelligence in search and target acquisition tasks such as whether or not a vehicle (or any heat source) has been moved or used and in which direction. While 3D graphic simulation of large scenes helps with retrieving information and training analysts, using traditional 3D rendering techniques are not enough, and an additional parameter needs to be solved due to different concept of visibility in IR scenes. In 3D rendering of IR scenes, the problem of what can currently be seen by a participant of the simulation does not just depend on emitted thermal energy from objects, and the visibility also depends on previous scenes as thermal energy is slowly retained and diffused over time. Therefore, time as an additional factor must be included since the aggregation of heat energy in the scene relates to its past. Our solution uses lightmaps for storing energy that reaches surfaces over time. We modify the lightmaps to solve the problem of lightmap parameterization between 3D surfaces and 2D mapping and add an extra ability to let us periodically update only necessary areas based on dynamic aspects of the scene.

Committee: John Femiani Dr. (Advisor); Eric Bachmann Dr. (Committee Member); Vijayalakshmi Ramasamy Dr. (Committee Member) Subjects: Computer Science

Master of Sciences, Case Western Reserve University, 2016, EMC - Mechanical Engineering

The present work is aimed at developing a dynamic adaptive mesh refinement (DAMR) method for the study of failure mechanisms in brittle materials within the eigenfracture framework. A mesh refinement method based on boundary representation technique (B-rep) and Delaunay triangulation is developed. In addition, a flip algorithm is employed to guarantee the quality of the refined mesh. The mesh refinement algorithm is verified in an example of static adaptive mesh generation of polycrystalline structures that are created by using Voronoi tessellation. Furthermore, the DAMR method is built upon the combination of the adaptive mesh refinement algorithm and the eigenfracture approach. In the DAMR, the energy release rate G is used as the adaption. Finally, the DAMR method is validated by comparing to mode-I and mixed mode fracture experiments on concrete materials. The simulation results show excellent agreement with experimental measurements and more accurate predictions than the original eigenfracture approach.

Committee: Bo Li (Committee Chair); Vikas Prakash (Committee Member); John Lewandowski (Committee Member) Subjects: Mechanical Engineering

MS, University of Cincinnati, 2013, Engineering and Applied Science: Mechanical Engineering

Hypoid and bevel gears are widely used in the rear axles of both on and off-highway vehicles, and are often subjected to harmful dynamic responses which cause gear whine noise and structural fatigue problems. The primary goal of this thesis is therefore to develop a more realistic mesh and dynamic model to predict the vibratory response of hypoid and bevel geared systems, and study the effect of different working conditions, e.g. operating speed, torque load, on the dynamic responses of those systems. First, a multi-point hypoid gear mesh model based on 3-dimensional loaded tooth contact analysis is incorporated into a coupled multi-body dynamic and vibration hypoid gear model to predict more detailed dynamic behavior of each tooth pair. To validate the accuracy of the proposed model, the time-averaged mesh parameters are applied to linear time-invariant (LTI) analysis to calculate the dynamic responses, such as dynamic mesh force and dynamic transmission error, which demonstrates good agreement with those predicted by using single-point mesh model. Furthermore, a nonlinear time-varying (NLTV) dynamic analysis is performed considering the effect of backlash nonlinearity and time-varying mesh parameters, such as time-varying mesh stiffness, transmission error, mesh point and line-of-action. One of the advantages of the multi-point mesh model is that it allows the calculation of dynamic responses for each engaging tooth pair, and simulation results for an example case are given to show the time history of the mesh parameters and dynamic mesh force for each pair of teeth within a full engagement cycle. This capability enables the analysis of durability of the gear tooth pair and more accurate prediction of the system response. Secondly, to have more insights on the load dependent mesh parameters and dynamic responses of the hypoid and spiral bevel geared systems, a load dependent mesh model is developed by using 3-dimensional loaded tooth contact analysis (LTCA). T (open full item for complete abstract)

Committee: Teik Lim Ph.D. (Committee Chair); J. Kim Ph.D. (Committee Member); David Thompson Ph.D. (Committee Member) Subjects: Mechanics

Doctor of Philosophy, The Ohio State University, 2011, Chemistry

Square nickel mesh perforated with micron scale holes exhibits extraordinary transmission due to propagating surface plasmon polaritions (PSPP) combined with cavity modes. Propagating surface plasmon resonances are known to disperse with the angle of incident light and such experiments yield rich information regarding the plasmonics of the material. More accurate polarized Gamma X dispersion is presented within, as well as the first polarized Gamma M dispersion of square nickel mesh. Calculation of resonance positions within these experiments predicts an effective index of refraction for the asymmetric coupled surface plasmon polaritons to have a value of n'eff, = 1.043. Gamma P and Gamma Q Dispersion of hexagonal mesh is presented and the coupling of asymmetric plasmonic surfaces examined. Calculations allowing interactions between PSPP states of square mesh are compared with experimental results and traditional predictions of mesh, PSPP transmission maxima; explaining variation from experimental results and traditional predictions and illustrating the polariton, or mixed state, nature of PSPPs. Lastly, scatter free infrared spectra of sixty-three individual micron scale dust particles are presented by placement of each particle in a hole of plasmonic square nickel mesh. The constituents of each particle and the process of quantification of materials is examined by use of Mie scattering, Lorentz dispersion, and Bruggeman effective medium theories. The propagation lengths for PSPP resonances on such mesh are poor (~1-2 hole-to-hole spacings), compared to smooth metal predictions or less absorbing metals, making this mesh ideal for studying individual particles. The PSPPs funnel light through the particles, but they are effectively isolated so long as the neighboring holes are empty. Saturation of absorption peaks at this scale are demonstrated.

Committee: James Coe V (Advisor); Singer Sherwin (Committee Member); Wyslouzil Barbara (Committee Member) Subjects: Physical Chemistry

Doctor of Philosophy, Case Western Reserve University, 2013, EMC - Mechanical Engineering

In the current environment of noise abatement, high frequency noises are especially objectionable. For gear drives, high frequency noises are symptoms of gear mesh-frequency vibrations which are ever-present due to the imperfect conjugate action between the gears. These vibrations are then transferred to the gear housing to be emitted as noise. The vibration energy flow can be disrupted, for example using a hydrostatic bearing as a low pass filter of vibrations while still preserving the positioning accuracy of the gear drive. Hydrostatic bearings are a class of fluid bearings consisting of externally pressurized fluid trapped in a recess to provide the necessary bearing support. Previous research has assumed the incompressibility of the working fluid in a hydrostatic bearing. In practice, the working fluid is not incompressible and the effect is not necessarily insignificant. Using the compressibility of the working fluid and the unique properties of a hydrostatic bearing, a low-pass filtering effect on the gear mesh-frequency vibrations can generated. This low-pass filter allows low frequency vibrations to be transmitted while high frequency vibrations are attenuated. The vibration attenuation disrupts its transmission to the gear housing and prevents its conversion into high frequency acoustic noise. Models to predict this low-pass filtering effect were developed using a control volume approach for constant flow and capillary flow compensation schemes while the compressibility of the working fluid is incorporated using the bulk modulus. A linear differential equation was then obtained. Using the solution to the differential equation and convolution, an expression for the frequency response of the transmitted dynamic pressure was developed. In addition, a proof of concept experiment was designed and implemented to validate the theoretical models. The experimental data shows similar attenuation of the transmitted dynamic pressure according to theoretical predicti (open full item for complete abstract)

Committee: Maurice Adams PhD (Committee Chair); Dario Gasparini PhD (Committee Member); Jaikrishnan Kadambi PhD (Committee Member); Joseph Mansour PhD (Committee Member); Robert White PhD (Committee Member) Subjects: Engineering; Mechanical Engineering

Doctor of Philosophy, The Ohio State University, 2024, Mechanical Engineering

The mechanical properties of materials are fundamentally governed by their microstructural characteristics, delineating a profound relationship between structure and behavior. Whether manifesting as polycrystalline arrangements composed of grains, particulate dispersion within composites, or the intricacies of Selective Laser Melting (SLM)-induced melt pools, microstructural heterogeneity profoundly influences material response to external loads. Moreover, the presence of defects such as voids, precipitates, and cracks introduces additional complexities, underscoring the critical role of microstructural analysis in elucidating material performance. As such, comprehending and manipulating these microstructural features hold paramount importance in the design and optimization of materials tailored to specific engineering requirements. This introductory exploration sets the stage for a comprehensive investigation into the interplay between microstructure and mechanical behavior in diverse material systems. The first component of this dissertation focuses on modeling Polycrystalline materials from imaging data. As mentioned earlier, polycrystalline microstructures are composed of grains and hence, it is important to accurately capture the grain boundaries when modeling them from microstructure images. Moreover, it is also possible for defects to be present in microstructures such as precipitates, voids, and cracks, which can impact mechanical behavior. Therefore, we also present an example modeling the presence of precipitates in a polycrystalline microstructure, which shows that the developed framework can handle them. To do this, we introduce a set of integrated image processing algorithms for processing low-resolution images of a polycrystalline microstructure and convert the grain boundaries into a Non-Uniform Rational B-Splines (NURBS) representation. Next, the NURBS representation of the material microstructures is used as an input to a non-iterative mesh (open full item for complete abstract)

Committee: Soheil Soghrati (Advisor); David Talbot (Committee Member); Rebecca Dupaix (Committee Member) Subjects: Artificial Intelligence; Computer Science; Materials Science; Mechanical Engineering

Doctor of Philosophy, Case Western Reserve University, 2024, Physics

CMB-S4 is a ground-based experiment aimed at studying the cosmic microwave background (CMB) with unprecedented sensitivity, which will deepen our fundamental understanding of the early universe. This thesis outlines three hardware development projects related to CMB-S4. A method is proposed to reduce sidelobe contamination by an order of magnitude by lining a large aperture telescope's cabin with a highly scattering material. The design and testing of a cold blackbody optical load which will be used to characterize CMB-S4 detectors is outlined. Finally, a new model is developed to characterize the transmission of metal-mesh flters as a function of the flters' geometry.

Committee: John Ruhl (Advisor); Johanna Nagy (Committee Member); Ben Monreal (Committee Member); Chris Zorman (Committee Member) Subjects: Physics

Doctor of Philosophy, The Ohio State University, 2024, Mechanical Engineering

Fiber-reinforced composites exhibit exceptional mechanical properties owing to their intricate microstructures, making them highly desirable materials for various engineering applications. However, accurately representing these complex microstructures in finite element (FE) models poses significant challenges. In this dissertation, we present a comprehensive computational framework aimed at synthesizing high-fidelity FE models of chopped fiber composite (CFC) and woven composite microstructures, integrating novel algorithms for microstructure reconstruction and mesh generation. The first component of our framework focuses on CFC microstructures. We introduce a new microstructure reconstruction algorithm integrated with a non-iterative meshing algorithm named CISAMR. This algorithm facilitates the synthesis of densely-packed CFC microstructures with desired statistical descriptors such as volume fraction, diameter distribution, and spatial arrangement of fibers. The reconstruction process involves a virtual packing algorithm based on Non-Uniform Rational B-Splines (NURBS) representation of fiber centerlines, followed by an explicit dynamic FE compression simulation to increase the fiber volume fraction. Subsequently, the shape and location of fibers are optimized to ensure the construction of high-quality conforming meshes using parallel CISAMR. We demonstrate the efficacy of this modeling framework in simulating both the linear elastic response and nonlinear failure behavior of polymer matrix CFCs with embedded glass fibers. An application of the modeling framework for CFC is conducted to study the anisotropy of the material. Two anisotropy indices are put forward, and their benefits and limitations are discussed. The second component of our framework focuses on woven composites. We present an integrated computational approach for generating realistic FE models of woven composites with high fiber volume fractions. This approach relies on a virtual microstructu (open full item for complete abstract)

Committee: Soheil Soghrati (Advisor); Jason Patrick (Committee Member); Carlos Castro (Committee Member); Marcelo Dapino (Committee Member) Subjects: Mechanical Engineering

Doctor of Philosophy, The Ohio State University, 2024, Computer Science and Engineering

Wireless meshes offer a resilient and cost-effective framework where multi-hop communication occurs among mesh clients, routers, and gateways. In this framework, computing and communication are essential to guarantee capacity and achieve high performance in terms of network planning, frequency scheduling, and packet routing. In order to optimize the achievable capacity to provide high throughput-latency communication with scalability, adaptivity, and reliability against various network configurations and dynamics, my thesis studies a cross-layer approach, from network infrastructure development to communication schedule and routing path selection, to show that the problem complexity can be managed by decomposition into subproblems via approximation, even learning based solutions. My study in this thesis consists of several approaches: first, we focus on the middle-mile network optimization problem to provide broadband connectivity in rural regions with a theoretical upper bound of infrastructure cost. Second, we investigate channel hopping to achieve high spectrum utilization, interference avoidance, and jamming tolerance. Third, we look into capacity-aware routing using bounded exploration regions to high throughput and reliability with low overhead. Finally, by developing machine learning algorithms using domain knowledge of bounded exploration on the network routing problem, we study the generalizability of the learned routing policies to all uniform random graphs. The middle-mile network optimization is to connect the last-mile networks to the core network service providers with minimal infrastructure cost and throughput constraints. It includes topology construction, tower height assignment, antenna and orientation selection, as well as transmit power assignment, which is known to be a computationally hard problem. We propose the first polynomial time approximation solution for a generalized version of the middle-mile network optimization problem, wherein (open full item for complete abstract)

Committee: Anish Arora (Advisor); Shaileshh Bojja Venkatakrishnan (Committee Member); Kannan Athreya (Committee Member); Ness Shroff (Committee Member) Subjects: Computer Science

Doctor of Philosophy, The Ohio State University, 2024, Civil Engineering

3D scene modeling techniques serve as the bedrocks in the geospatial engineering and computer science, which drives many applications ranging from automated driving, terrain mapping, navigation, virtual, augmented, mixed, and extended reality (for gaming and movie industry etc.). This dissertation presents a fraction of contributions that advances 3D scene modeling to its state of the art, in the aspects of both appearance and geometry modeling. In contrast to the prevailing deep learning methods, as a core contribution, this thesis aims to develop algorithms that follow first principles, where sophisticated physic-based models are introduced alongside with simpler learning and inference tasks. The outcomes of these algorithms yield processes that can consume much larger volume of data for highly accurate reconstructing 3D scenes at a scale without losing methodological generality, which are not possible by contemporary complex-model based deep learning methods. Specifically, the dissertation introduces three novel methodologies that address the challenges of inferring appearance and geometry through physics-based modeling. Firstly, we address the challenge of efficient mesh reconstruction from unstructured point clouds—especially common in large and complex scenes. The proposed solution employs a cutting-edge framework that synergizes a learned virtual view visibility with graph-cut based mesh generation. We introduce a unique three-step deep network that leverages depth completion for visibility prediction in virtual views, and an adaptive visibility weighting in the graph-cut based surface. This hybrid approach enables robust mesh reconstruction, overcoming the limitations of traditional methodologies and showing superior generalization capabilities across various scene types and sizes, including large indoor and outdoor environments. Secondly, we delve into the intricacies of combining multiple 3D mesh models, particularly those obtained through oblique ph (open full item for complete abstract)

Committee: Rongjun Qin (Advisor); Alper Yilmaz (Committee Member); Charles Toth (Committee Member) Subjects: Civil Engineering

Doctor of Philosophy, The Ohio State University, 2023, Civil Engineering

Multidimensional (coupled one-dimensional (1D) and two-dimensional (2D)) hydrodynamic models are developed to achieve computational efficiency for study areas with small-scale channel networks. Fine-scale computational domains are required to adequately resolve geometry of such study areas with typical 2D hydrodynamic models, which results in high computational cost. Coupled 1D/2D hydrodynamic models, which use 1D models for small-scale areas (typically small-scale channels), allow preserving geometric features of the study area with moderate computational cost and have been applied in various numerical studies. In this dissertation, we present computational techniques that further enhance coupled 1D/2D hydrodynamic models. The first one is an automatic mesh generation tool for coupled 1D/2D hydrodynamic models. Meshes are a required input for hydrodynamic models, and automatic mesh generation tools for 2D hydrodynamic models are well developed. However, development of such tools becomes challenging when they are designed for coupled 1D/2D hydrodynamic models. The difficulty of mesh generation in this case comes from the fact that the resolutions of the 1D/2D domains are closely intertwined with each other; however, the desired mesh resolutions for each domain may be quite different. The proposed mesh generator provides features to automatically identify 1D domains from given input data and to generates collocated meshes with efficient sizing along 1D domains. The developed techniques are demonstrated on three test cases, including two inland watersheds and a coastal basin. Second, a new smoothing method for digital elevation models (DEMs) is developed to enhance the application of an existing coupled 1D/2D kinematic wave model based on discontinuous Galerkin (DG) methods. The model has shown great success in rainfall-runoff simulations; however, it is highly sensitive to the topography represented by the mesh. The proposed method is compared to straightforwar (open full item for complete abstract)

Committee: Ethan J. Kubatko Dr. (Advisor); James H. Stagge Dr. (Committee Member); Yulong Xing Dr. (Committee Member); Ryan Winston Dr. (Committee Member) Subjects: Civil Engineering; Environmental Engineering; Fluid Dynamics