Computational Engineering Commons^™

Investigation Of The Effect Of Corundum Layer On The Heat Transfer Of Sic Slab, Sri Elsa Fatmi, Donanta Dhaneswara, Muhammad Anis, Ahmad Ashari

Journal of Materials Exploration and Findings

Aluminum is the most widely used metal in industry. Aluminum smelting is one of the important steps that needs to be carried out to produce products made of aluminum metal with good quality. In the process of smelting aluminum there are several problems that occur, one of which is the growth of corundum in Si C refractories which affects the quality of aluminum melt and the durability of Si C refractories. This research was conducted to see the heat transfer in Si C and the effect of the presence of Corundum on heat transfer. This research was carried out by …

Dynamic Rbi With Central Difference Method Approach In Calculation Of Uniform Corrosion Rate: A Casestudy On Gas Pipelines, M.Riefqi Dwi Alviansyah, Fernanda Hartoyo, Zahra Nadia Nurullia, Ari Kurniawan

Journal of Materials Exploration and Findings

The oil and gas industry generally uses a piping system to drain fluids. Even though the pipes used have been well designed, the use of pipes as a means of fluid transportation still provides the possibility of failure that can occur at any time, one of which is due to uniform corrosion. The use of standard Risk Based Inspection (RBI) according to the API RBI 581 document has been widely used to anticipate potential failures to pipe components. The use of standard RBI can reduce the risk of failure significantly. Because the standard RBI considers the component risk value to …

Scientists And Activists Work To Save The Planet, Myriam G. Vidal Valero

Capstones

Climate change and human intervention in nature are affecting people, ecosystems and ways of living all over the world. This portfolio of environmental pieces showcases the dire consequences of not addressing these issues, how solutions can be reached and the challenges facing those who try to change things.

Elucidation Of Active Site And Mechanism Of Metal Catalysts Supported In Nu-1000, Hafeera Shabbir

All Dissertations

Advances in extraction of shale oil and gas has increased the production of geographically stranded natural gas (primarily consisting of methane (C1) and ethane (C2)) that is burned on site. A potential utilization strategy for shale gas is to convert it into fuel range hydrocarbons by catalytic dehydrogenation followed by oligomerization by direct efficient catalysts. This work focuses on understanding metal cation catalysts supported on metal-organic framework (MOF) NU-1000 that will actively and selectively do this transformation under mild reaction conditions, while remaining stable to deactivation (via metal agglomeration or sintering). I built computational models validated by experimental methods to …

Wildfire Spread Prediction Using Attention Mechanisms In U-Net, Kamen Haresh Shah, Kamen Haresh Shah

Master's Theses

An investigation into using attention mechanisms for better feature extraction in wildfire spread prediction models. This research examines the U-net architecture to achieve image segmentation, a process that partitions images by classifying pixels into one of two classes. The deep learning models explored in this research integrate modern deep learning architectures, and techniques used to optimize them. The models are trained on 12 distinct observational variables derived from the Google Earth Engine catalog. Evaluation is conducted with accuracy, Dice coefficient score, ROC-AUC, and F1-score. This research concludes that when augmenting U-net with attention mechanisms, the attention component improves feature suppression …

Software Protection And Secure Authentication For Autonomous Vehicular Cloud Computing, Muhammad Hataba

Dissertations

Artificial Intelligence (AI) is changing every technology we deal with. Autonomy has been a sought-after goal in vehicles, and now more than ever we are very close to that goal. Vehicles before were dumb mechanical devices, now they are becoming smart, computerized, and connected coined as Autonomous Vehicles (AVs). Moreover, researchers found a way to make more use of these enormous capabilities and introduced Autonomous Vehicles Cloud Computing (AVCC). In these platforms, vehicles can lend their unused resources and sensory data to join AVCC.

In this dissertation, we investigate security and privacy issues in AVCC. As background, we built our …

Direct Calculation Of Configurational Entropy: Pair Correlation Functions And Disorder, Clifton C. Sluss

Doctoral Dissertations

Techniques such as classical molecular dynamics [MD] simulation provide ready access to the thermodynamic data of model material systems. However, the calculation of the Helmholtz and Gibbs free energies remains a difficult task due to the tedious nature of extracting accurate values of the excess entropy from MD simulation data. Thermodynamic integration, a common technique for the calculation of entropy requires numerous simulations across a range of temperatures. Alternative approaches to the direct calculation of entropy based on functionals of pair correlation functions [PCF] have been developed over the years. This work builds upon the functional approach tradition by extending …

Quantum-Mechanical Evaluation Of Defects In Uranium-Bearing Materials, Megan Hoover

All Dissertations

Quantum-mechanical calculations using density functional theory with the generalized gradient approximation were employed to investigate the effects dopants have on the uranium dioxide (UO₂) structure. Uraninite is a common U⁴⁺ mineral in the Earth's crust and an important material used to produce energy and medical isotopes. Though the incorporation mechanism remains unclear, divalent cations are known to incorporate into the uranium dioxide system. Three charge-balancing mechanisms were evaluated to achieve a net neutral system, including the substitution of (1) a divalent cation for a tetravalent uranium atom and oxygen atom; (2) two divalent cations for a tetravalent …

Single-Pass Inline Pipeline 3d Reconstruction Using Depth Camera Array, Zhexiong Shang, Zhigang Shen

Department of Construction Engineering and Management: Faculty Publications

A novel inline inspection (ILI) approach using depth cameras array (DCA) is introduced to create high-fidelity, dense 3D pipeline models. A new camera calibration method is introduced to register the color and the depth information of the cameras into a unified pipe model. By incorporating the calibration outcomes into a robust camera motion estimation approach, dense and complete 3D pipe surface reconstruction is achieved by using only the inline image data collected by a self-powered ILI rover in a single pass through a straight pipeline. The outcomes of the laboratory experiments demonstrate one-millimeter geometrical accuracy and 0.1-pixel photometric accuracy. …

Implementation Of A Least Squares Method To A Navier-Stokes Solver, Jada P. Lytch, Taylor Boatwright, Ja'nya Breeden

Rose-Hulman Undergraduate Mathematics Journal

The Navier-Stokes equations are used to model fluid flow. Examples include fluid structure interactions in the heart, climate and weather modeling, and flow simulations in computer gaming and entertainment. The equations date back to the 1800s, but research and development of numerical approximation algorithms continues to be an active area. To numerically solve the Navier-Stokes equations we implement a least squares finite element algorithm based on work by Roland Glowinski and colleagues. We use the deal.II academic library , the C++ language, and the Linux operating system to implement the solver. We investigate convergence rates and apply the least squares …

A Novel Method For Sensitivity Analysis Of Time-Averaged Chaotic System Solutions, Christian A. Spencer-Coker

Theses and Dissertations

The direct and adjoint methods are to linearize the time-averaged solution of bounded dynamical systems about one or more design parameters. Hence, such methods are one way to obtain the gradient necessary in locally optimizing a dynamical system’s time-averaged behavior over those design parameters. However, when analyzing nonlinear systems whose solutions exhibit chaos, standard direct and adjoint sensitivity methods yield meaningless results due to time-local instability of the system. The present work proposes a new method of solving the direct and adjoint linear systems in time, then tests that method’s ability to solve instances of the Lorenz system that exhibit …

Finite-Difference-Time-Domain Simulation Of Ultrafast Experiments, Alpha Ma

Macalester Journal of Physics and Astronomy

The Finite-Difference-Time-Domain (FDTD) method is a numerical method that calculates electric fields or magnetic fields by interleaving them in space and time. Using a python package called “MEEP”, I was able to write optical simulations of ultrafast experiments, especially the Terahertz Pump-Probe experiments. The goal of this project was to use FDTD simulation to measure the transmission of an electro-magnetic pulse passing through a thin film of conducting material on a dielectric substrate in order to study the characteristic conductivity of potential solar cell materials.

Development And Evaluation Of Modeling Approaches For Extrusion-Based Additive Manufacturing Of Thermoplastics, Christopher C. Bock

Electronic Theses and Dissertations

This work focuses on evaluating different modeling approaches and model parameters for thermoplastic AM, with the goal of informing more efficient and effective modeling approaches. First, different modeling approaches were tested and compared to experiments. From this it was found that all three of the modeling approaches provide comparable results and provide similar results to experiments. Then one of the modeling approaches was tested on large scale geometries, and it was found that the model results matched experiments closely. Then the effect of different material properties was evaluated, this was done by performing a fractional factorial design of experiments where …

Using Bluetooth Low Energy And E-Ink Displays For Inventory Tracking, David Whelan

Computer Science and Computer Engineering Undergraduate Honors Theses

The combination of Bluetooth Low energy and E-Ink displays allow for a low energy wire-less display. The application of this technology is far reaching especially given how the Bluetooth Low Energy specification can be extended. This paper proposes an extension to this specification specifically for inventory tracking. This extension combined with the low energy E-Ink display results in a smart label that can keep track of additional meta data and inventory counts for physical inventory. This label helps track the physical inventory and can help mitigate any errors in the logical organization of inventory.

Applications Of Parallel Discrete Event Simulation, Erik J. Jensen

Modeling, Simulation and Visualization Student Capstone Conference

This work presents three applications of parallel discrete event simulation (PDES), which describe the motivation for and the benefits of using PDES, the kinds of synchronization algorithms that are used, and scaling behavior with these different synchronization algorithms.

Intra-Hour Solar Forecasting Using Cloud Dynamics Features Extracted From Ground-Based Infrared Sky Images, Guillermo Terrén-Serrano

Electrical and Computer Engineering ETDs

Due to the increasing use of photovoltaic systems, power grids are vulnerable to the projection of shadows from moving clouds. An intra-hour solar forecast provides power grids with the capability of automatically controlling the dispatch of energy, reducing the additional cost for a guaranteed, reliable supply of energy (i.e., energy storage). This dissertation introduces a novel sky imager consisting of a long-wave radiometric infrared camera and a visible light camera with a fisheye lens. The imager is mounted on a solar tracker to maintain the Sun in the center of the images throughout the day, reducing the scattering effect produced …

Development Of Guidelines For Collecting Transit Ridership Data, Hong Yang, Kun Xie, Sherif Ishak, Qingyu Ma, Yang Liu

Computational Modeling & Simulation Engineering Faculty Publications

Transit ridership is a critical determinant for many transit applications such as operation optimizations and project prioritization under performance-based funding mechanisms. As a result, the quality of ridership data is of utmost importance to both transit administrative agencies and transit operators. Many transit operators in Virginia report their ridership data to the Department of Rail and Public Transportation (DRPT) and the National Transit Database (NTD). However, with no specific guidelines available to transit agencies in Virginia for collecting ridership data, the heterogeneous mixture of diverse data collection methods and technologies has often raised concerns about the consistency and quality of …

Representation Learning For Chemical Activity Predictions, Mohamed S. Ayed

Dissertations, Theses, and Capstone Projects

Computational prediction of a phenotypic response upon the chemical perturbation on a biological system plays an important role in drug discovery and many other applications. Chemical fingerprints derived from chemical structures are a widely used feature to build machine learning models. However, the fingerprints ignore the biological context, thus, they suffer from several problems such as the activity cliff and curse of dimensionality. Fundamentally, the chemical modulation of biological activities is a multi-scale process. It is the genome-wide chemical-target interactions that modulate chemical phenotypic responses. Thus, the genome-scale chemical-target interaction profile will more directly correlate with in vitro and in …

Sustainable Computing - Without The Hot Air, Noman Bashir, David Irwin, Prashant Shenoy, Abel Souza

Publications

The demand for computing is continuing to grow exponentially. This growth will translate to exponential growth in computing's energy consumption unless improvements in its energy-efficiency can outpace increases in its demand. Yet, after decades of research, further improving energy-efficiency is becoming increasingly challenging, as it is already highly optimized. As a result, at some point, increases in computing demand are likely to outpace increases in its energy-efficiency, potentially by a wide margin. Such exponential growth, if left unchecked, will position computing as a substantial contributor to global carbon emissions. While prominent technology companies have recognized the problem and sought to …

A Literature Review On Combining Heuristics And Exact Algorithms In Combinatorial Optimization, Hesamoddin Tahami, Hengameh Fakhravar

Engineering Management & Systems Engineering Faculty Publications

There are several approaches for solving hard optimization problems. Mathematical programming techniques such as (integer) linear programming-based methods and metaheuristic approaches are two extremely effective streams for combinatorial problems. Different research streams, more or less in isolation from one another, created these two. Only several years ago, many scholars noticed the advantages and enormous potential of building hybrids of combining mathematical programming methodologies and metaheuristics. In reality, many problems can be solved much better by exploiting synergies between these approaches than by “pure” classical algorithms. The key question is how to integrate mathematical programming methods and metaheuristics to achieve such …

Combining Green Metrics And Digital Twins For Sustainability Planning And Governance Of Smart Buildings And Cities, Casey R. Corrado, Suzanne M. Delong, Emily G. Holt, Edward Y. Hua, Andreas Tolk

VMASC Publications

Creating a more sustainable world will require a coordinated effort to address the rise of social, economic, and environmental concerns resulting from the continuous growth of cities. Supporting planners with tools to address them is pivotal, and sustainability is one of the main objectives. Modeling and simulation augmenting digital twins can play an important role to implement these tools. Although various green best practices have been utilized over time and there are related attempts at measuring green success, works in the published literature tend to focus on addressing a single problem (e.g., energy efficiency), and a comprehensive approach that takes …

Bounded-Degree Plane Geometric Spanners: Connecting The Dots Between Theory And Practice, Matthew Alexander Graham

UNF Graduate Theses and Dissertations

The construction of bounded-degree plane geometric spanners has been a focus of interest since 2002 when Bose, Gudmundsson, and Smid proposed the first algorithm to construct such spanners. To date, eleven algorithms have been designed with various trade-offs in degree and stretch factor. We have implemented these sophisticated algorithms in C++ using the CGAL library and experimented with them using large synthetic and real-world pointsets. Our experiments have revealed their practical behavior and real-world efficacy. We share the implementations via GitHub for broader uses and future research.

We present a simple practical algorithm, named AppxStretchFactor, that can estimate stretch factors …

New Development Of Neutrosophic Probability, Neutrosophic Statistics, Neutrosophic Algebraic Structures, And Neutrosophic Plithogenic Optimizations, Florentin Smarandache, Yanhui Guo

Branch Mathematics and Statistics Faculty and Staff Publications

This collective book presents state-of-the-art papers on new topics related to neutrosophic theories, such as neutrosophic algebraic structures, neutrosophic triplet algebraic structures, neutrosophic extended triplet algebraic structures, neutrosophic algebraic hyperstructures, neutrosophic triplet algebraic hyperstructures, neutrosophic n-ary algebraic structures, neutrosophic n-ary algebraic hyperstructures, refined neutrosophic algebraic structures, refined neutrosophic algebraic hyperstructures, quadruple neutrosophic algebraic structures, refined quadruple neutrosophic algebraic structures, neutrosophic image processing, neutrosophic image classification, neutrosophic computer vision, neutrosophic machine learning, neutrosophic artificial intelligence, neutrosophic data analytics, neutrosophic deep learning, and neutrosophic symmetry, as well as their applications in the real world.