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Articles 1 - 13 of 13
Full-Text Articles in Engineering Science and Materials
Thermal Behavior Of Plain And Fiber-Reinforced Rigid Concrete Airfield Runways, Arash Karimi Pour
Thermal Behavior Of Plain And Fiber-Reinforced Rigid Concrete Airfield Runways, Arash Karimi Pour
Open Access Theses & Dissertations
The environmental condition and temperature gradient are important factors resulting in concrete airfield runways cracking during the time. Rigid concrete airfield runways experience different thermal gradients during the day and night due to changes in air temperature. Curling and thermal expansion stresses are the main consequences resulting in various types of cracking over the surface and thickness of concrete airfield runways and increasing maintenance costs. The curvature of concrete slabs increases with an increase in the temperature gradient which is amplified when runways open to traffic. Additionally, the combination of the curling and shrinkage stresses, in rare circumstances, can be …
Machine Learning-Based Data And Model Driven Bayesian Uncertanity Quantification Of Inverse Problems For Suspended Non-Structural System, Zhiyuan Qin
All Dissertations
Inverse problems involve extracting the internal structure of a physical system from noisy measurement data. In many fields, the Bayesian inference is used to address the ill-conditioned nature of the inverse problem by incorporating prior information through an initial distribution. In the nonparametric Bayesian framework, surrogate models such as Gaussian Processes or Deep Neural Networks are used as flexible and effective probabilistic modeling tools to overcome the high-dimensional curse and reduce computational costs. In practical systems and computer models, uncertainties can be addressed through parameter calibration, sensitivity analysis, and uncertainty quantification, leading to improved reliability and robustness of decision and …
Material Synthesis And Machine Learning For Additive Manufacturing, Jaime Eduardo Regis
Material Synthesis And Machine Learning For Additive Manufacturing, Jaime Eduardo Regis
Open Access Theses & Dissertations
The goal of this research was to address three key challenges in additive manufacturing (AM), the need for feedstock material, minimal end-use fabrication from lack of functionality in commercially available materials, and the need for qualification and property prediction in printed structures. The near ultraviolet-light assisted green reduction of graphene oxide through L-ascorbic acid was studied with to address the issue of low part strength in additively manufactured parts by providing a functional filler that can strengthen the polymer matrix. The synthesis of self-healing epoxy vitrimers was done to adapt high strength materials with recyclable properties for compatibility with AM …
Molecular Dynamics Simulations Of Self-Assemblies In Nature And Nanotechnology, Phu Khanh Tang
Molecular Dynamics Simulations Of Self-Assemblies In Nature And Nanotechnology, Phu Khanh Tang
Dissertations, Theses, and Capstone Projects
Nature usually divides complex systems into smaller building blocks specializing in a few tasks since one entity cannot achieve everything. Therefore, self-assembly is a robust tool exploited by Nature to build hierarchical systems that accomplish unique functions. The cell membrane distinguishes itself as an example of Nature’s self-assembly, defining and protecting the cell. By mimicking Nature’s designs using synthetically designed self-assemblies, researchers with advanced nanotechnological comprehension can manipulate these synthetic self-assemblies to improve many aspects of modern medicine and materials science. Understanding the competing underlying molecular interactions in self-assembly is always of interest to the academic scientific community and industry. …
A Hyperelastic Porous Media Framework For Ionic Polymer-Metal Composites And Characterization Of Transduction Phenomena Via Dimensional Analysis And Nonlinear Regression, Zakai J. Olsen
UNLV Theses, Dissertations, Professional Papers, and Capstones
Ionic polymer-metal composites (IPMC) are smart materials that exhibit large deformation in response to small applied voltages, and conversely generate detectable electrical signals in response to mechanical deformations. The study of IPMC materials is a rich field of research, and an interesting intersection of material science, electrochemistry, continuum mechanics, and thermodynamics. Due to their electromechanical and mechanoelectrical transduction capabilities, IPMCs find many applications in robotics, soft robotics, artificial muscles, and biomimetics. This study aims to investigate the dominating physical phenomena that underly the actuation and sensing behavior of IPMC materials. This analysis is made possible by developing a new, hyperelastic …
Development Of Reduced Order Models Using Reservoir Simulation And Physics Informed Machine Learning Techniques, Mark V. Behl Jr
Development Of Reduced Order Models Using Reservoir Simulation And Physics Informed Machine Learning Techniques, Mark V. Behl Jr
LSU Master's Theses
Reservoir simulation is the industry standard for prediction and characterization of processes in the subsurface. However, simulation is computationally expensive and time consuming. This study explores reduced order models (ROMs) as an appropriate alternative. ROMs that use neural networks effectively capture nonlinear dependencies, and only require available operational data as inputs. Neural networks are a black box and difficult to interpret, however. Physics informed neural networks (PINNs) provide a potential solution to these shortcomings, but have not yet been applied extensively in petroleum engineering.
A mature black-oil simulation model from Volve public data release was used to generate training data …
Consuming Digital Debris In The Plasticene, Stephen R. Parks
Consuming Digital Debris In The Plasticene, Stephen R. Parks
Theses and Dissertations
Claims of customization and control by socio-technical industries are altering the role of consumer and producer. These narratives are often misleading attempts to engage consumers with new forms of technology. By addressing capitalist intent, material, and the reproduction limits of 3-D printed objects’, I observe the aspirational promise of becoming a producer of my own belongings through new networks of production. I am interested in gaining a better understanding of the data consumed that perpetuates hyper-consumptive tendencies for new technological apparatuses. My role as a designer focuses on the resolution of not only the surface of the object through 3-D …
Microstructural Analysis Of Thermoelastic Response, Nonlinear Creep, And Pervasive Cracking In Heterogeneous Materials, Alden C. Cook
Microstructural Analysis Of Thermoelastic Response, Nonlinear Creep, And Pervasive Cracking In Heterogeneous Materials, Alden C. Cook
Electronic Theses and Dissertations
This dissertation is concerned with the development of robust numerical solution procedures for the generalized micromechanical analysis of linear and nonlinear constitutive behavior in heterogeneous materials. Although the methods developed are applicable in many engineering, geological, and materials science fields, three main areas are explored in this work. First, a numerical methodology is presented for the thermomechanical analysis of heterogeneous materials with a special focus on real polycrystalline microstructures obtained using electron backscatter diffraction techniques. Asymptotic expansion homogenization and finite element analysis are employed for micromechanical analysis of polycrystalline materials. Effective thermoelastic properties of polycrystalline materials are determined and compared …
Experimental Building Demonstration Model With Viscous Fluid Dampers, Blake Thomas Reeve, Brianna Jean Kufa, Aden Malek Stepanians, Sophie Carmion Ratkovich
Experimental Building Demonstration Model With Viscous Fluid Dampers, Blake Thomas Reeve, Brianna Jean Kufa, Aden Malek Stepanians, Sophie Carmion Ratkovich
Architectural Engineering
The Architectural Engineering major places a heavy emphasis on structural dynamics and the role of wind and seismic loading in building analysis and design. Buildings of high importance that are critical to community function, such as hospitals, often utilize supplemental damping devices like supplemental viscous fluid dampers or base isolators to reduce the overall demands on the structural system. The design and analysis of these dampers are typically not taught at the undergraduate level, and is frequently performed by mechanical engineers, in lieu of structural engineers.
To better understand and research building behavior with supplemental damping devices, our multi-disciplinary team …
Nanoscale Frictional Properties Of Nickel With One-Dimensional And Two-Dimensional Materials, Timothy K. Schlenger
Nanoscale Frictional Properties Of Nickel With One-Dimensional And Two-Dimensional Materials, Timothy K. Schlenger
Mechanical Engineering Undergraduate Honors Theses
When looking at the nanoscale, material interface interactions have been observed to exhibit particularly interesting properties. Our research looks into various combinations of carbyne and graphene atop a nickel block to look into the interface friction properties between them. Both the carbyne and graphene are tested using steered molecular dynamics (SMD) in sheering and peeling directions along the surface of the nickel block. These tests are then analyzed by comparing the magnitude of the acting force versus the displacement of the carbon allotrope sample across the nickel block. It is found that as the width of a carbon allotrope sample …
Towards The Scalability And Hybrid Parallelization Of A Spatially Variant Lattice Algorithm, Henry Roger Moncada Lopez
Towards The Scalability And Hybrid Parallelization Of A Spatially Variant Lattice Algorithm, Henry Roger Moncada Lopez
Open Access Theses & Dissertations
The purpose of this research is to design a faster implementation of the spatially variant algorithm that improves its performance when it is running on a parallel computer system.
The spatially variant algorithm is used to synthesize a spatially variant lattice for a periodic electromagnetic structure. The algorithm has the ability to spatially vary the unit cell orientation and exploit its directional dependencies. The algorithm produces a lattice that is smooth, continuous and free of defects. The lattice spacing remains strikingly uniform when the unit cell orientation, lattice spacing, fill fraction and more are spatially varied. This is important for …
Validation Of Weak Form Thermal Analysis Algorithms Supporting Thermal Signature Generation, Elton Lewis Freeman
Validation Of Weak Form Thermal Analysis Algorithms Supporting Thermal Signature Generation, Elton Lewis Freeman
Masters Theses
Extremization of a weak form for the continuum energy conservation principle differential equation naturally implements fluid convection and radiation as flux Robin boundary conditions associated with unsteady heat transfer. Combining a spatial semi-discretization via finite element trial space basis functions with time-accurate integration generates a totally node-based algebraic statement for computing. Closure for gray body radiation is a newly derived node-based radiosity formulation generating piecewise discontinuous solutions, while that for natural-forced-mixed convection heat transfer is extracted from the literature. Algorithm performance, mathematically predicted by asymptotic convergence theory, is subsequently validated with data obtained in 24 hour diurnal field experiments for …
Newton Parameter Update Algorithm For Recurrent Neural Networks Applied To Adaptive System Identification And Control, Donald Allen Gates
Newton Parameter Update Algorithm For Recurrent Neural Networks Applied To Adaptive System Identification And Control, Donald Allen Gates
Electrical & Computer Engineering Theses & Dissertations
This paper shows that the combination of a second-order neural network parameter update algorithm and internal network feedback can be effectively used for adaptive, nonlinear, dynamical system identification and control. Adaptive neural identification and control algorithms are typically utilized for real-time applications where the rate of adaptation is often critical. A fast, adaptive network parameter update algorithm is presented.
Simulation results show that this algorithm is capable of quickly identifying and adapting to changes in system parameters, making it feasible to use for real-time control and fault accommodation applications.