Synthesizing Maritime Interaction Scenarios For Testing Autonomy,
2022
Old Dominion University
Synthesizing Maritime Interaction Scenarios For Testing Autonomy, Benjamin E. Hargis, Yiannis E. Papelis
Modeling, Simulation and Visualization Student Capstone Conference
This paper presents a method to deterministically synthesize maritime traffic interactions that can be presented to a system under test regardless of the state of the system under test. A background to the problem is given and the method is briefly outlined. Results indicate that the approach can enable more robust evaluation of maritime autonomous algorithms.
Real-Time External Labeling For Interactive Visualization In Virtual Environments,
2022
Old Dominion University
Real-Time External Labeling For Interactive Visualization In Virtual Environments, Shan Liu, Yuzhong Shen
Modeling, Simulation and Visualization Student Capstone Conference
A real-time external labeling algorithm has been developed to explore the potential for applying annotation and visualization to virtual reality environments, which manages label placement in the projections of virtual 3D models on the view plane. The approach intends to place labels with visual constraints, such as no overlapping, intersections, and occlusions, close proximity to the model parts, by adjusting external annotations' positions concerning available space in the view plane. This algorithm is based on the projected model's contour and adapts to camera viewpoint changes within interactive frame rates. It solves the visibility problem of annotations and operates in real-time …
Applications Of Parallel Discrete Event Simulation,
2022
Old Dominion University
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.
Method Of Embedded Imperfections For The Direct Simulation Of Deformation Instabilities In Film-Substrate Structures,
2022
University of New Mexico
Method Of Embedded Imperfections For The Direct Simulation Of Deformation Instabilities In Film-Substrate Structures, Siavash Nikravesh Kazeroni
Mechanical Engineering ETDs
In this dissertation, a novel finite-element methodology called “embedded imperfections” is proposed and employed for computationally simulating various types of deformation instabilities observed in film-substrate structures subjected to mechanical loading. The approach involves the incorporation of elements having distinctive material properties within the film-substrate interface. One can interpret this practice as a deliberate distribution of material defects within the numerical model. It has been shown that embedded imperfections not only can trigger the onset of instability, but also can lead to “direct” simulation of deformation instability problems in that primary and subsequent instability modes can all be captured in a …
Intra-Hour Solar Forecasting Using Cloud Dynamics Features Extracted From Ground-Based Infrared Sky Images,
2022
University of New Mexico
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 …
Three-Dimensional Numerical Modeling Of Flow Hydrodynamics And Cohesive Sediment Transport In Enid Lake, Mississippi,
2022
University of Mississippi
Three-Dimensional Numerical Modeling Of Flow Hydrodynamics And Cohesive Sediment Transport In Enid Lake, Mississippi, Xiaobo Chao, A. K. M. Azad Hossain, Mohammad Z. Al-Hamdan, Yafei Jia, James V. Cizdziel
Faculty and Student Publications
Enid Lake is one of the largest reservoirs located in Yazoo River Basin, the largest basin in the state of Mississippi. The lake was impounded by Enid Dam on the Yocona River in Yalobusha County and covers an area of 30 square kilometers. It provides significant natural and recreational resources. The soils in this region are highly erodible, resulting in a large amount of fine-grained cohesive sediment discharged into the lake. In this study, a 3D numerical model was developed to simulate the free surface hydrodynamics and transportation of cohesive sediment with a median diameter of 0.0025 to 0.003 mm …
Development Of Guidelines For Collecting Transit Ridership Data,
2022
Old Dominion University
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,
2022
CUNY Graduate Center
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 …
Numerical Simulation On The Fire Performance Of Reinforced Concrete Flat Slab,
2022
University of Alabama in Huntsville
Numerical Simulation On The Fire Performance Of Reinforced Concrete Flat Slab, Elias Ali
Summer Community of Scholars (RCEU and HCR) Project Proposals
No abstract provided.
Design And Development Of Active Flow Effectors,
2022
University of Alabama in Huntsville
Design And Development Of Active Flow Effectors, Konstantinos Kanistras
Summer Community of Scholars (RCEU and HCR) Project Proposals
No abstract provided.
Design And Development Of An Online Wind Tunnel,
2022
University of Alabama in Huntsville
Design And Development Of An Online Wind Tunnel, Konstantinos Kanistras
Summer Community of Scholars (RCEU and HCR) Project Proposals
No abstract provided.
A Literature Review On Combining Heuristics And Exact Algorithms In Combinatorial Optimization,
2022
Old Dominion University
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 …
Bounded-Degree Plane Geometric Spanners: Connecting The Dots Between Theory And Practice,
2022
University of North Florida
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,
2022
University of New Mexico
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.
Numerical And Scaling Study On Application Of Inkjet Technology To Automotive Coating,
2022
University of Kentucky
Numerical And Scaling Study On Application Of Inkjet Technology To Automotive Coating, Masoud Arabghahestani Dr.
Theses and Dissertations--Mechanical and Aerospace Engineering
A thorough literature review identified lack of precision control over quality of droplets generated by the currently available industrial sprayers and a growing need for higher quality droplets in the coating industry. Particularly, lack of knowledge and understanding in continuous inkjets (CIJ) and drop-on-demand (DOD) technologies is identified as significant. Motivated by these needs, this dissertation is dedicated to computational fluid dynamics (CFD) and scaling studies to improve existing inkjet technologies and develop new designs of efficient coating with single and/or multiple piezoelectric sensors to produce on-demand droplets. This dissertation study aims at developing a new DOD type coating technology, …
Coastal Housing Recovery In A Postdisaster Environment: A Supply Chain Perspective,
2022
Virginia Modeling, Analysis, and Simulation Center, Old Dominion University
Coastal Housing Recovery In A Postdisaster Environment: A Supply Chain Perspective, Rafael Diaz, Joshua Behr, Beatriz Acerp
VMASC Publications
In coastal cities, the damage stemming from hurricanes and severe tropical storms may reduce housing stock. Accelerating the reconstruction of housing stock becomes crucial in minimizing the time that residents are displaced. It is critical to understand how to better coordinate all available resources for an effective and balanced reconstruction where nongovernmental organizations (NGOs), government agencies, volunteers, and many other complex resources converge. This study combines Monte Carlo and beta models to assess supply, costs, and recovery times. The models capture the immediate and long-term costs of reconstruction activities under highly uncertain conditions using embedded stochastic components on projected materials, …
Image Geo-Localization With Cross-Attention,
2022
University of Kentucky
Image Geo-Localization With Cross-Attention, Connor Greenwell
Theses and Dissertations--Computer Science
The problem of estimating the location from which un-geotagged photographs were captured has been well studied by the computer vision community in recent years. The central proposal of this thesis is to define a common framework within which existing approaches can be constructed and evaluated, and to introduce a new method under this framework which uses cross-attention between the query image and a database of satellite imagery with known geotags. Our experiments fit within three broad categories: 1) evaluating the ability of image localization approaches to generalize to unseen regions; 2) examining performance changes under various reference database resolutions, scales, …
Simulation-Based Optimization: Implications Of Complex Adaptive Systems And Deep Uncertainty,
2022
The MITRE Corporation & Old Dominion University
Simulation-Based Optimization: Implications Of Complex Adaptive Systems And Deep Uncertainty, Andreas Tolk
VMASC Publications
Within the modeling and simulation community, simulation-based optimization has often been successfully used to improve productivity and business processes. However, the increased importance of using simulation to better understand complex adaptive systems and address operations research questions characterized by deep uncertainty, such as the need for policy support within socio-technical systems, leads to the necessity to revisit the way simulation can be applied in this new area. Similar observations can be made for complex adaptive systems that constantly change their behavior, which is reflected in a continually changing solution space. Deep uncertainty describes problems with inadequate or incomplete information about …
Combining Green Metrics And Digital Twins For Sustainability Planning And Governance Of Smart Buildings And Cities,
2022
The MITRE Corporation & Old Dominion University
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 …
A Simulation-Based Disaster Management Framework To Analyze Housing Recovery: The Case Of Hampton Roads, Usa,
2022
Virginia Modeling, Analysis, and Simulation Center, Old Dominion University
A Simulation-Based Disaster Management Framework To Analyze Housing Recovery: The Case Of Hampton Roads, Usa, Rafael Diaz, Joshua Behr, Beatriz Acero, Bridget D. Giles, Juita-Elena Wie Yusuf
VMASC Publications
In the aftermath of a catastrophic weather event, housing recovery and reconstruction activities are highly complex. Coordinating housing recovery activities is generally challenging because complex supply chains converge simultaneously in a highly uncertain environment. In this environment, anticipating and quantifying the extent of potential damage and determining the actions that must be taken to rebuild the housing stock may assist regions in allocating resources for reconstruction. This paper presents the development of a comprehensive disaster management framework to assist decision-makers in predicting the impact of projected natural disasters on housing. This framework uses a simulation-based approach to quantify likely regional …
