bluuebunny/crossref_metadata_2025_split huggingface dataset:
Curved Seawalls As an Erosion Management Tool for Saipan
Authors: Yagi Yoshihiro , An Yajun , Dillon Heather E. 
Published: February 2024

Abstract
The purpose of this research is to address the problem of coastal erosion on Beach Road, Saipan’s main highway, by analyzing what type of curved seawall would be most effective at reflecting wave energy. This project is motivated by the challenge of coastal erosion which has become a major issue for many Pacific Islands. If left unaddressed, coastal erosion and inundation will leave many islands in economic and societal ruin, as these islands build their communities and infrastructure along their coastlines. As these island-communities have a vested interest in preserving their way of life, our goal is to provide these islands with information related to seawall type, overtopping potential, and potential failure points of various seawall geometries.
Our analysis was conducted with the computational fluid dynamics (CFD) solver OpenFOAM where experimental work began with the adaptation of a baseline dam break simulation to simulate a single crashing wave onto various seawalls. These seawalls were traced, and their geometries developed into a triangular mesh using Salome. Once developed, our geometries were then taken to OpenFOAM and incorporated into the dam break simulation. We then compared the fluid behavior in Open-FOAM with a physical experiment using 3-D printed scaled models and a digital hydraulic bench. Through OpenFOAM simulations we confirmed that the FSS seawall performed the best for reducing wave overtopping and reflecting waves when compared to the VW and inclined wall. This analysis on seawall geometry can be used to jumpstart talks on coastal defense mechanisms for Saipan.
Numerical Study of Liquid Piston Compression Using Large-Eddy Simulation and Volume-of-Fluid Approach
Authors: Nguyen Thien D. , Rendall Joe , Kowalski Steve 
Published: February 2024

Abstract
Efforts to increase the efficiency of residential and commercial air conditioners and heat pumps have demonstrated that the compressor accounts for most of the system’s electrical energy usage. Therefore, the efficiency of this component should be improved to reduce its energy usage. The US Department of Energy’s Oak Ridge National Laboratory developed a near-isothermal liquid piston compressor (LPC) that uses propylene glycol (PG) to compress CO2. This report presents numerical studies of the LPC in which the compression chamber fills with injected PG from the bottom inlet. Numerical simulations were performed using the large-eddy simulation (LES) with the wall-adapting local eddy-viscosity (WALE) subgrid-scale model coupled with the multiphase volume-of-fluid (VOF) model to simulate the transient interface between gas and liquid and to capture the heat and mass transfer within the compression chamber. In this effort, effects of boundary conditions applied to the LES-VOF calculations (e.g., no wall, an adiabatic wall, and a wall with a heat flux subscribed) to the overall pressure and temperature of CO2 gas as well as the transient evolution of flow and heat transfer evolution within the compression chamber are investigated and discussed. It was found that the LES calculation with no wall have shown no dynamical flow patterns and the volume-averaged temperature of CO2 increased from 305 to 392.7 K, while LES calculations with a constant wall temperature or a wall heat flux had similar increases of CO2 temperatures. Results of LES simulation using a wall heat flux showed different stages in the compression process and revealed dynamical formation and interaction of CO2 gas layers and circulation flow patterns within the chamber that contribute to the overall heat transfer between the solid wall, gas, and liquid surface in the compressor.
An Inexpensive Multidisplinary Teaching Lab Kit for Remote Dual Enrollment Introductory Engineering Courses
Authors: Lacerna Alexander D. , Parker Joel L. , Traum Matthew J. 
Published: February 2024

Abstract
In University of Florida’s EGS1006 “Introduction to Engineering” course, students explore the 14 different undergraduate majors offered through the Herbert Wertheim College of Engineering. In addition to in-person attendees, UF registers dual enrollment (high school + college) remote learners from across Florida in EGS1006. These students are often ethnic minorities, first-generation college students, female, and/or from socioeconomically disadvantaged communities: precisely the groups underrepresented in engineering majors that colleges strive to attract and retain.
Due to geographic dispersion, dual enrollment students are not able to engage in-person with the EGS1006 pragmatic activities, which potentially puts them at a disadvantage relative to their in-person peers. Therefore, a shippable educational laboratory kit was developed and deployed in Spring 2023 to mitigate this disadvantage. The kit and supporting curriculum provide hands-on activities and exposure to all UF’s 14 UF engineering disciplines at reasonable per kit cost (when manufactured, shipped, and returned/refurbished at scale). Moreover, since the kits are designed to be returned and refurbished for reuse each semester, the cost-per-student-served over many semesters approaches ∼$36 with $16/kit for roundtrip shipping and $20/kit for refurbishment.
This paper introduces the EGS1006 kit, describes activities and experiments that showcase how each UF engineering major is represented, and explains how the kit is fabricated. Additionally, a series of indirect assessment questions have been developed and embedded within the dual enrollment EGS1006 assignments. These questions were designed to gauge students’ pre/post impressions on 1) using the kit, 2) self-efficiency, 3) attitude toward engineering overall, and 4) interest/disinterest in specific engineering majors. These questions are included to describe and frame an ongoing pedagogical study of the kits’ value and utility for the EGS1006 dual enrollment cohort.
Vortex Spoilers Do Not Work to Suppress Pulsations Generated by Turning Flows Into a Side Branch Against a Deadleg
Authors: Botros Kamal K. , Clavelle Eric , Chan Nic , Satish Hemanth 
Published: February 2024

Abstract
Turning flow into side branches against a deadleg along the main run can generate high levels of pulsations if the piping system acoustic resonance frequency matches closely the flow generated instabilities within the T-junction characterized by specific Strouhal number (St) that is function of the branch to main run diameters ratio (d/D). In order to suppress these pulsations, vortex spoilers (aka vortex breakers), akin to those employed and inserted inside the side branch to suppress pulsations generated due to flow past side branches, have been considered. The difference lies in the fact that these spoilers would have to be placed in the main-run close to the downstream trailing edge of the T-junction. Three spoilers of different geometries and characteristics were designed and tested experimentally on a high-pressure natural gas test setup at a pressure range of 4–5 MPa, mean gas velocities of 6–36 m/s in a DN100 piping arrangement and for d/D = 1.0. These spoilers are flat plate, perforated plate, and cross-plates all of length = 2.1D. Tests were carried out at different positions of the respective spoilers in relation of the T-junction intended to interfere and suppress the coherent vorticity generation and its interaction with the mean flow velocity and acoustic fields according to Howe acoustic source power theory. The paper presents details of the test setup, data collected, analysis of the normalized pulsation amplitude (P*) vs. St number and effectiveness of each of the three spoilers at three different positions inside the main run. It was found that the maximum amplitude of P* without spoilers was reached at St number approximately equals to 0.12 which is close to published data. However, none of the tested three spoilers was effective in suppressing the level of pulsations irrespective of their placement position inside the main run. It appears that due to the fact that the flow has to turn into the side branch, a high degree of shearing resulting in regions of high vorticity generation, combined with the predominant direction of the mean flow into to the side branch, all of which contribute to the acoustic power source, regardless of any interference or potential interference brought about by any spoiler. Complementary unsteady CFD simulations were also conducted on a similar experimental setup on air under well-defined flow and acoustic boundary conditions published in IMECE 2021. The combined experimental and CFD simulations concluded with that vortex spoilers appear to be of no use in suppressing pulsations generated by turning flows into a side branch against a deadleg at least in the range of spoiler placement positions studied.
Bison Verification and Validation Activities for TRISO
Authors: Toptan Aysenur , Hales Jason D. , Jiang Wen 
Published: February 2024

Abstract
Numerical modeling and simulation (M&S) tools play a key role in the research, development, and overall safety assessments of next-generation nuclear energy systems. One such tool, Bison, is a nuclear fuel performance code applicable to many different fuel forms (e.g., light-water reactor fuel, oxide and metallic fuel for fast reactors, tri-structural isotropic (TRISO) fuel, and plate fuel), and it uses the finite element method to model the thermo-mechanical response of nuclear fuels. One fuel form widely utilized in Generation-IV high-temperature gas-cooled and fluoride-salt-cooled nuclear reactor concepts is TRISO fuel. Recently, Bison’s capabilities were significantly expanded to enable it to model the performance of TRISO particles and compacts. It is important that Bison’s computational results be reliable and predictive, since this code is used to inform high-consequence decisions. The various processes developed to address this issue generally entail two fundamental steps: verification and validation (V&V). Verification ensures that the code functions correctly and is reliable. Code/solution verification, code benchmark, and software quality assurance (SQA) exercises are examples of verification activities, whereas validation is the process of assessing a code’s capability to accurately model physical problems. Comparisons between code results and experiments are used to quantify the validation level. Application of V&V procedures is crucial to the development of computational tools that are free of coding mistakes and can accurately represent reality. The current study presents an overview of Bison V&V activities relevant to the TRISO fuel concept, including code/solution verification exercises, International Atomic Energy Agency (IAEA)-coordinated Coordinated Research Program (CRP-6) benchmark exercises, and validation exercises utilizing the Advanced Gas Reactor (AGR) experiment series (e.g., AGR-1, AGR-2, and AGR-3/4).
Buckling Analysis of Filament-Wound Cylindrical Shells Considering Pattern Effect
Authors: Özaslan Emre , Yetgin Ali , Acar Bülent 
Published: February 2024

Abstract
A complexity of a filament-wound structure lies in the winding pattern that naturally occurs during the manufacturing process. The winding angle changes from +θ to −θ in the transition regions between the patterns. This type of geometrical change can potentially decrease the strength of the structure and lead to catastrophic failure, particularly under axial compression loading. It is well-known that compression loads can cause buckling failures, which are sudden and without prior warning. Therefore, considering the local deformation in the transition regions of the patterns as a source of imperfection in buckling analysis is crucial to prevent such failures. This study examines the effects of the pattern on the buckling behavior of a filament wound cylindrical composite shell numerically. After validating the finite element model with experimental results from the literature, a detailed investigation was performed to understand the influence of various parameters on the buckling load. These parameters include pattern number, winding angle and thickness. The importance of conducting geometrical nonlinear analysis to determine a realistic buckling load and mode was emphasized. It is observed that the effect of patterns on the buckling load is more pronounced in thin shells and at low winding angles. However, no direct relationship was detected between pattern number and the buckling load.
Best Fits, Dark Horses, and Cognitive Style: Investigating Differences in Design Solution Perceptions
Authors: Henderson Daniel , Patel Krina , Jablokow Kathryn , Kilicay-Ergin Nil , Sonalkar Neeraj 
Published: February 2024

Abstract
In industry, engineering design teams can be asked to produce design solutions that clearly follow given specifications and constraints of a problem (i.e., Best Fit solutions), or they may be encouraged to provide higher risk design solutions that challenge those constraints, but offer other potential rewards (i.e., Dark Horse solutions). This study utilized a self-assessment tool to investigate designers’ perceptions of their teams’ Best Fit and Dark Horse solutions. Kirton’s Adaption-Innovation theory of cognitive style provided the framework to explore the impacts of cognitive style on design solution perceptions. The study involved 17 design teams of 3–5 individuals (64 participants) from five different professional organizations, with each team generating one Best Fit solution and one Dark Horse solution in response to the same design prompt. Participants were then asked to place their team’s Best Fit and Dark Horse solutions onto a “FUN diagram,” which is a ternary-style triangular diagram where the vertices correspond to Feasibility, Usefulness, or Novelty, respectively.
The analysis of the responses showed that most adaptive and innovative individuals held distinct perceptions of their Best Fit and Dark Horse solutions, as reflected by their FUN diagram placements. While Best Fit solutions were more often perceived as being Feasible or Neutral, Dark Horse solutions were perceived as being Novel. More adaptive individuals perceived their Best Fit solutions as Feasible, whereas more innovative individuals perceived Best Fit solutions as Neutral. However, there was no apparent relationship between cognitive style and Dark Horse solution perceptions. Understanding more about how individuals perceived their Best Fit and Dark Horse solutions can enable engineering educators and industry practitioners to identify ways to support designers and teams more effectively.
A Comprehensive Review of Acoustic Induced Vibration Methodologies
Authors: Liu Yuqing , Diwakar Philip , Eljaouhari Ismat , Shen Lulin 
Published: February 2024

Abstract
High acoustic energy has the potential to cause severe Acoustic Induced Vibration (AIV) that lead to fatigue failure in a piping system. Over the past few decades, many technical papers have been published on AIV research, and several industry codes and guidelines have been developed. However, gaps and inconsistencies exist, due to limited data and unverified assumptions. With new technologies — in continuous development — in the oil and gas industry, process conditions (such as temperature and pressure) have seen significant changes in recent industrial projects. As a result, the acoustic energy in piping system has been growing exponentially, exceeding the limits of current industrial codes and guidelines.
In this paper, a comprehensive review of AIV methodologies is conducted. Failure data reported in 1980s and 90s, as well as AIV methodologies developed in the 2000s (Carucci-Mueller curve, Eisinger curve, Bruce curve, Energy Institute Guideline, MTD Guideline, etc.) are reviewed along with their limitations and unverified assumptions (based on available data at that time) and compared to the latest research. The latest failure data from recent projects is used to demonstrate the application range for each method. Methods developed based on data in 1980s/90s were limited to sound power level (PWL) of 180 dB, while many plants designed recently have PWL greater than 185 dB, with some as high as 200 dB. Applying traditional methods to new plants with excessive PWL leads to unrealistic and overly conservative design leading to thicker piping and higher costs.
This paper hopes to close these major gaps including noise induced by sonic flow, noise attenuation, effectiveness of asymmetric reinforcement, explore fatigue limits of contour fittings and risks of welded supports. Further goal is to evaluate inconsistencies between industry codes and standards. Most AIV methodologies developed in the past focused on branch fittings with nearly no testing data on welded supports. Many fittings such as sweepolet, sweeplus®, forged tee, 45-deg fitting, and short-contour were not evaluated due to lack of testing data.
Failure modes and lessons learned during the development phase are addressed to emphasize the importance of AIV evaluation during design and operation along with the latest trend in industry codes and guidelines on AIV. In the past, AIV evaluation was often conducted as a post-event assessment, resulting in costly physical changes after the plant had already been constructed. With the latest revision of ASME B31J Code, most engineers now perform AIV evaluation early in the design phase to mitigate risks. The comprehensive review of AIV methodologies presented in this paper helps to provide a more comprehensive guideline for safe design practices and structural integrity.
A Data-Driven Approach for Predicting the Onset of Entrainment in Two-Fluid Stratified Systems During Selective Withdrawal Process Using Machine Learning Techniques
Authors: Hassan Sabbir , James Darryl 
Published: February 2024

Abstract
Selective withdrawal is crucial in the US Strategic Petroleum Reserve and other applications, such as micro-particle coating, thin glass fiber fabrication, and local drug delivery. Physics-based mechanistic models are commonly used to predict the onset of entrainment but have challenges and uncertainties in its computational solutions. Machine learning (ML) models, like Gaussian Process Regression (GPR) and Artificial Neural Networks (ANN), can provide more efficient solutions to these problems.
This study uses experimental data from various sources to investigate GPR and ANN for predicting the onset of entrainment in two-fluid stratified systems. Non-dimensional parameters were used as model inputs to ensure generalizability, and dimensionality reduction techniques, like the Genetic Algorithm, were employed to optimize the models. The machine learning models’ predictions were compared with physics-based models across different flow regimes.
Preliminary findings show that GPR and ANN models have excellent predictive capabilities, surpassing physics-based models. GPR demonstrated slightly better performance than ANN. However, predictions are only accurate if the underlying physical regime remains unchanged. Machine learning models can unify physics-based models based on available training data at different flow regimes. This study emphasizes the potential of machine learning techniques in solving complex problems and offers a novel approach to predicting the onset of entrainment in select two-fluid stratified systems.
Fracture Mechanics of Tetragraphene Under Mixed Mode Loading
Authors: Haddadi Elnaz , Tabarraei Alireza 
Published: February 2024

Abstract
The need to overcome the limitations of graphene in electronic applications has prompted numerous investigations into the exploration of novel two-dimensional carbon-based materials that could potentially introduce an electronic bandgap. Graphene has many 2D carbon allotropes; a quasi-2D semiconductor carbon allotrope, called tetragraphene (TG), was recently proposed. TG is composed of hexagonal and tetragonal rings and shows metallic or semiconducting behaviors with no limitations in electronic applications. This study uses molecular dynamics (MD) simulations to understand fracture properties of triple-layered TG sheets under mixed mode I and II loading using the Tersoff-Erhart potential. We investigate the effect of loading phase angle and temperature on the crack propagation path and critical stress intensity factors. The findings reveal that the critical stress intensity factor and crack propagation path are influenced by both the loading phase angle and temperature. Nonetheless, temperature has an insignificant effect on the critical stress intensity factor, except for cases where the loading phase angle is either 0° or 90°.
Classification of Brain Malignant Tumors Using MRI Scans and CNN Architectures With Optimized Hyperparameters
Authors: Weiss Cohen Miri 
Published: February 2024

Abstract
Based on Magnetic Resonance Imaging (MRI) scans and Convolutional Neural Network (CNN) architectures with optimized hyperparameters, this study proposes a machine learning system for classification of brain malignant tumors. Using a two-level approach, the first level identifies the most suitable MRI modalities for classification by evaluating the performance of the modalities under different hyperparameters. The second level consists of the development and comparison of two CNN architectures, Inceptionv3 and DenseNet121, based on their respective training methods. As part of the optimization process, various hyperparameters are tested, such as epochs, batch sizes, learning rates, and dropout rates. Additionally, it was found that learning rate has an important impact on the training phase with a lower learning rate resulting in a smoother, more consistent process. As a result of optimizing the system, it has been demonstrated that it can accurately classify brain malignant tumors, particularly Glioblastomas.