bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information
Authors: Agogino Alice , Jang Hae Young , Rao Vivek , Batra Ritik , Liao Felicity , Sood Rohan , Fang Irving , Hu R. Lily , Shoichet-Bartus Emerson , Matranga John 
Published: January 2022

Abstract
Although the Industrial Internet of Things has increased the number of sensors permanently installed in industrial plants, there will be gaps in coverage due to broken sensors or sparse density in very large plants, such as in the petrochemical industry. Modern emergency response operations are beginning to use Small Unmanned Aerial Systems (sUAS) that have the ability to drop sensor robots to precise locations. sUAS can provide longer-term persistent monitoring that aerial drones are unable to provide. Despite the relatively low cost of these assets, the choice of which robotic sensing systems to deploy to which part of an industrial process in a complex plant environment during emergency response remains challenging.
This paper describes a framework for optimizing the deployment of emergency sensors as a preliminary step towards realizing the responsiveness of robots in disaster circumstances. AI techniques (Long short-term memory, 1-dimensional convolutional neural network, logistic regression, and random forest) identify regions where sensors would be most valued without requiring humans to enter the potentially dangerous area. In the case study described, the cost function for optimization considers costs of false-positive and false-negative errors. Decisions on mitigation include implementing repairs or shutting down the plant. The Expected Value of Information (EVI) is used to identify the most valuable type and location of physical sensors to be deployed to increase the decision-analytic value of a sensor network. This method is applied to a case study using the Tennessee Eastman process data set of a chemical plant, and we discuss implications of our findings for operation, distribution, and decision-making of sensors in plant emergency and resilience scenarios.
An Investigation of the Wake and Vortex Formation of a Helicopter Rotor Blade
Authors: Pulok Mohammad Khairul Habib , Chakravarty Uttam K. 
Published: January 2022

Abstract
Vortices are present in many engineering applications and are systematically generated by lifting surfaces. The vortex characteristics and the wake surrounding a helicopter rotor blade play an important role because they affect the flow physics surrounding the rotor blade. Therefore, an advanced mathematical and computational model of rotor wake and blade vortex gives a better understanding of the helicopter rotor dynamics. The strength of the vortex depends on the blade geometry, loading, and the aircraft’s operational state. A concentrated tip vortex line, an inboard trailing vortex sheet, and a shed vortex are accountable for aerodynamic airload generation. Among these, tip vortices have the maximum contribution and are formed by the rolling up of trailing vortices near the tip of the wing. In this study, tip vortex models are used to characterize the vortex core structure and prescribed wake models are utilized for analyzing the hovering flight. A Bo 105 composite, hingeless helicopter rotor blade is considered for the computational analysis. A fluid-structure interaction model is developed by coupling the finite element model of the rotor blade with a computational fluid dynamics model of the surrounding air to analyze the helicopter rotor blade dynamic response and to investigate vortex formation due to the fluid-structure interaction. The swirl velocity is minimum, and the axial velocity is maximum at the vortex center. The axial velocity decreases and swirl velocity increases with increasing the distance from the vortex center to the core radius.
Prognostic Health Monitoring Method for Thermal Fatigue Failure of Power Modules Based on Finite Element Method-Based Lagrangian Neural Networks
Authors: Kano Akira , Monda Tomoko , Suzuki Tomoyuki , Uehara Hideaki , Fumikura Tomoya , Hirohata Kenji 
Published: January 2022

Abstract
Prognostic health monitoring technologies for power electronic systems assess their performance degradation, load histories, and degrees of fatigue in order to increase maintenance effectiveness, reliability design methods, and equipment availability under conditions of actual use. To improve reliability and reduce downtime, prediction of reliability in terms of thermal fatigue life under field conditions is important, as is the use of load and health monitoring data from the field in cases of performance degradation during use, maintenance, and field failure. The fatigue life of solder joints is also affected by whether the load history waveform is symmetric or asymmetric. In this paper, we propose a novel health monitoring method for thermal fatigue failure corresponding to time-dependent inelastic strain response, such as in asymmetric cycles, by use of a surrogate model obtained by a finite element method-based thermal stress simulation. We applied this method to an insulated-gate bipolar transistor power module capable of monitoring module temperature, electrical performance, and number of revolutions of the cooling fan. With the proposed method, inelastic strain cycles and thermal fatigue life distribution of solder joints could be estimated from their temperature monitoring history. The method was judged to be useful for assessing thermal load histories and estimating thermal fatigue life in prognostic health monitoring.
Surface Defect Detection in Steel Plates Using Machine Vision
Authors: Mantoni Aaron , Chauhan Vedang 
Published: January 2022

Abstract
Surface defect detection and classification in small size steel plates using machine vision inspection has been researched and presented in this paper. The steel plates that are used in the automobile drive chains for power transmissions are used as the test parts. The components of chains undergo the manufacturing steps such as punching, heat treatment and polishing before the final assembly. Due to a high temperature and loading conditions, sometimes the plates get distorted. The research project was set out to detect, classify and sort non-defective and defective plates into separate bins using machine vision inspection. A database of non-defective and defective parts was generated using the vision acquisition program. The number of images in the database were increased using data augmentation techniques. Various vision inspection techniques such template matching based object classification implemented using NI Vision Builder Software and Convolutional Neural Networks (CNN) implemented in MATLAB have been trained and tested. The vision algorithms communicated pass or fail decision through the serial communication and controlled the sorting system using a microcontroller. Depending on the decision, the parts were sorted into accepted (non-defective parts) or rejected (defective parts) bins. The project was successful in achieving the milestones defined in the research objective. The results with the two inspection methods, Object classification and CNN based method, have been reported. A classification accuracy of 96 % was achieved using the object classification method, while the CNN based method resulted in the 100 % classification accuracy. The developed algorithms can be implemented on a high-speed smart camera and the system can be used for realtime online inspection.
Safety Technology Advancements for Autonomous Cars; Prospective of Manufacturing, Regulatory and Society
Authors: Pourgol Mohamad Mohammad , Pourgol Mohamad Amin 
Published: January 2022

Abstract
We have witnessed remarkable technology advancements and competitions in autonomous and connected vehicles. There has been a vigorous technological development effort in the past few years to introduce self-driving smart vehicles for a connected world. If applied correctly, these technologies can enable solutions to help city transportation systems improve the economics of transportation, environmental concerns, and quality of life for everyone. The problem requires a holistic approach. While technological development has been intriguing, competitive, and vigorous, the industry’s advances on the issues of safety, risk, and reliability have been dismal. Despite its limited uses and manufacturers’ stated goal of making autonomous cars demonstrably safer than an average human-controlled car, several accidents and near-misses have already occurred. The mean distance driven to an unsafe condition, near miss or accident has been far shorter than the conventional road vehicles. While the public at large is intrigued about these technologies, the safety concerns are profound. This article is aimed to review the safety of AV systems from design and manufacturing, society and ethics, advancement of the safety/reliability technologies assessing their readiness and a review from academic point of view to understand the area for further research.
A Novel Computational Framework for the Effective Transport Properties of Heterogeneous Materials Reconstructed From Digital Images
Authors: Ogbuanu Kelechi O. , Roy R. Valéry 
Published: January 2022

Abstract
In computational material science, Digital Image Processing and Big Data analysis play a crucial role in Microstructure Characterization and Reconstruction (MCR), especially in the estimation of structure-property relationships. In this work, we are interested in the calculation of the effective transport properties of composite materials from digital images. Because most MCR techniques are heavily statistical, they may suffer from significant microstructure information loss as they are incapable of reproducing exact images of microstructures. Here, we take advantage of pattern recognition algorithms to extract nearly exact morphological information pertaining to the interphase boundaries from digital microstructural images, thereby minimizing information loss. The data extracted then serves as the basis for our effective transport property module for calculating the effective properties of two-phase composite materials in a way that is automated, fast, stable, memory efficient, and accurate. Our current formulation is limited to circular or near-circular inclusions, with very large contrast properties. Preliminary numerical tests on four cases of 2D, two-phase microstructure images yielded relative errors ranging from 0.1% to 2.0%, for image pixel density around 1000 × 1000 pixels. These relative errors are perfectly acceptable without having to resort to unrealistic image sizes.
Senior Capstone Project: A Classroom Heat Exchanger Demonstration Kit
Authors: Quigley Matthew , Klebba Jason , Jawad Badih , Liu Liping 
Published: January 2022

Abstract
Funded by an Undergraduate Program Equipment Grant from ASHARE, five undergraduate students in Mechanical Engineering were tasked to design and build a heat-exchanger demonstration kit as a teaching aid for classroom usage. The students were allotted one semester for design and one semester for assembly. The team researched existing products, performed theoretical calculations, and further identified their constraints with student surveys. The team also consulted several faculty members who are teaching Heat Transfer and Thermal Science Lab to get their input in order to provide a design and construction that best serves the teaching purpose. The final product is a rolling display board (approximately 4 feet wide and 5 feet tall) featuring a concentric tube heat exchanger prominently. An LCD screen allows students to see real-time temperature readings at four predetermined locations. Flow meters output the individual fluid flow rate of the coolant contained in two discrete piping loops. The fluid in these loops can operate in either parallel or counter-flow modes with the flip of a switch. Provisions were made to ensure sustainability and environmental consciousness, such as serviceable components and non-toxic coolant. The project concluded on time and under budget. This teaching kit is expected to help implementing active collaborative learning (ACL) activities in the classroom.
A Methodology for Risk Assessment to Improve the Resilience and Sustainability of Critical Infrastructure With Case Studies From the United States Army
Authors: Blackwell Neil , Evans Aubrey , Lee Phoebe , Panlasigui Christine , Russell Duncan , Wells Ke'Shaun , McCarthy Stephen , McCoy Brad , Davidson F. Todd 
Published: January 2022

Abstract
Reliable performance of energy and water infrastructure is central to the mission readiness of the United States Army. These systems are vulnerable to coordinated attacks from an adversary as well as disruption from natural events. The objectives of this work were to investigate Army installations in North America, identify best practices for improving the resilience and sustainability of critical energy and water infrastructure, and develop a framework and methodology for analyzing the resilience of an installation under varying outage scenarios. This work was accomplished using a multi-layered decision process to identify unique case studies from the 117 active-duty domestic Army installations. A framework for analyzing and assessing the resilience of an installation was then developed to help inform stakeholders. Metered energy and water data from buildings across Fort Benning, GA were curated to inform the modeling framework, including a discrete-event simulation of the supply and demand for energy and water on the installation using ProModel. This simulation was used to study the scale of solutions required to address outage events of varying frequency, duration, and magnitude, the combination of which is described as the severity of outages at a given site. This project helps develop a framework to inform how installations might meet Army Directive 2020-03, which states that installations must be able to sustain mission requirements for a minimum of 14 days after a disruption has occurred.
Thermodynamic, Environmental and Cost Evaluation of Compression-Absorption Parallel and Cascade Refrigeration Chiller
Authors: Kadam Sambhaji , Khan Muhammad Saad , Kyriakides Alexios-Spyridon , Papadopoulos Athanasios I. , Hassan Ibrahim , Rahman Mohammad Azizur , Seferlis Panos 
Published: January 2022

Abstract
A district cooling system (DCS), that generally operates with vapor compression refrigeration (VCR) chillers, is superior to conventional air conditioning as it helps to reduce energy consumption and to protect the environment by reducing carbon dioxide emissions. The advantages of the district cooling plant can be further enhanced by integrating the VCR system with a vapor absorption refrigeration system (VAR). In this context, this paper presents the comparative assessment of a VCR chiller and two configurations of an integrated VCR and VAR chiller, consisting of the parallel and the cascade configuration. Two refrigerant-absorbent mixtures in the VAR system are considered, namely the conventional NH3/H2O and the novel acetaldehyde/N,N-dimethylformamide (Acet/DMF). The energy, exergy, environmental and economic analysis of the systems have been performed considering the coefficient of performance (COP), the exergy efficiency (ηexergy), the total equivalent warming impact (TEWI) and the cost rate (Ċtot) as performance indicators. It is observed that the connection of the evaporator of the VAR with the condenser of the VCR in the cascade configuration increases the COP of the VCR unit by 292% compared to the stand-alone VCR system. Overall, the COP of the parallel and the cascade refrigeration system with the novel Acet/DMF is better than that of NH3/H2O. This performance can further be improved by enhancing the exergy efficiency. Overall, the thermodynamic, environmental and cost benefits of the novel Acet/DMF with the cascade arrangement of the VCR and the VAR system are superior to those of NH3/H2O.
Nonlinear Dynamics of a Two-Cam System
Authors: Yousuf Louay S. , Marghitu Dan B. 
Published: January 2022

Abstract
In this paper, a multi-body dynamic system of two cams, flat-faced follower with a revolute joint, and guides are discussed and analyzed. The input moments as a function of angular velocity are applied for the rotation of the two cams. SolidWorks software is used to simulate the multi body system. The nonlinear dynamics is analyzed with phase plane, and Poincare’ diagrams. The cams with different angular velocity are considered. The influence of different angular velocities of the cam and different internal dimensions of the follower guide on nonlinear dynamics behavior are taken into consideration. The friction between the follower stem and the guide has been taken into account. The clearance between the follower’s stem and the guides leads to impacts.
Fatigue Assessment of Pipelines With Dent and Crack Subjected to Cyclic Pressure Loading
Authors: Al-Nutifat Shadid A. , Pu Yongchang , Al-Shammari Abdulrahman S. 
Published: January 2022

Abstract
Subsea pipelines are subjected to external damage by fishing trawlers or dragged anchors which may result in a pipe defect such as a puncture, dent, gouge, crack or a combination of such defects (Allouti et al., 2014). Therefore, evaluation of these defects is very important in terms of assessment and for continued safe operation. This study is to evaluate the effect of dent with crack defects on the fatigue life of natural gas transmission pipelines. In order to illustrate the effect of a crack on the dented pipe, this study is divided into two parts. The first part is to study on the effect of dents alone on the fatigue life of the material, while the second part is to study on the effect of dents and crack on the fatigue life. Therefore, a parametric study using finite element numerical models was conducted to study the effect of plain dent and dent with crack on the fatigue life of the pipeline.
A Computational Study of the Evolution of Fabri-Choke in a Two-Dimensional Supersonic Ejector
Authors: C. V. Sumesh Babu , Lijo V. 
Published: January 2022

Abstract
An ejector refrigeration system (ERS) can significantly reduce electricity consumption compared to traditional compressor-based systems. Fabri-choking is an indication of an ejector operating in the idealized condition with a maximum entrainment ratio. Backpressure has a significant influence on ejector performance. Severe degradation in performance is observed when the backpressure increases from the design value. Until now, many works have been performed to design and evaluate the ejector systems. In the majority of these works, it is assumed that the ejector is working with fixed designed backpressure, which gives maximum performance. In almost all of the practical applications of ERS, the backpressure varies, mainly as the cooling load requirement changes. In such practical applications, the flow in the ejector is very interesting, and this paper takes a new look at the transient operation of an ejector with varying backpressure. In the present study, numerical simulations have been used to provide detailed flow physics and, in particular, the occurrence of Fabri-choke in a supersonic ejector. The results obtained reveal compound choking, multiple evolutions of Fabri-choke, and its relation to wave reflections. Results showed that the first and second occurrences of Fabri-choke occurred when the backpressure is reduced by 6.0% and 8.0%, respectively. Methods to ascertain Fabri-choke in numerical simulations and experimental studies were also separately addressed.
Nanostructuring of Metallic Additively Manufactured Surfaces for Enhanced Jumping Droplet Condensation
Authors: Ho Jin Yao , Rabbi Kazi Fazle , Sett Soumyadip , Wong Teck Neng , Leong Kai Choong , Miljkovic Nenad 
Published: January 2022

Abstract
Vapor condensation on metallic surfaces is a phase-change phenomenon that has widespread applications in many processes. Jumping-droplet-enhanced condensation is an effective mode of dropwise condensation due to its higher droplet removal rate, enabling more efficient heat transfer. However, maintaining stable jumping-droplet condensation, requires surface structures to be suitably designed to prevent droplet pinning and surface flooding. In recent years, using metal additive manufacturing (AM) processes to create heat exchanger surfaces has received significant attention due to its design freedom and versatility in fabricating highly complex functional parts. Here, we present a highly scalable method of fabricating superhydrophobic (SHP) AM surfaces from aluminum alloy, AlSi10Mg, and an experimental investigation of their thermal performance during steam condensation. The test samples were fabricated by Selective Laser Melting (SLM), an AM technique for producing metallic parts. Through detailed material characterizations, we found that it is possible to achieve superior superhydrophobicity on AM surfaces, with unique cellular-like nanoscale surface features, by simple chemical etching and functionalization processes.
To understand the droplet dynamics and obtain insights on the effects of AM nanostructures on the condensate droplet morphology and jumping, we carried out condensation experiments with an environmental scanning electron microscope (ESEM) at low supersaturation of ∼1.06. The important relations between the fabricated AM nanostructure morphology and droplet dynamics are established by characterizing the droplet departure diameter and droplet jumping frequency. To determine the anti-flooding and condensation heat transfer performances of the AM SHP surfaces, pure vapor condensation experiments under higher supersaturation conditions were carried out in a well-controlled environmental chamber. Together with the aid of high-resolution imaging and heat transfer measurements, we demonstrate significant reduction in droplet pinning sites due to the implementation of the AM cellular-like structure. This reduces the thermal barrier between the condensing surface and surrounding vapor, and hence, increases the condensation heat transfer. Our results show that excellent droplet jumping performance and better droplet mobility can be achieved by using AM SHP surfaces as compared to conventional SHP aluminum extruded tubing. These results underscore the potential of advancing AM structured surfaces for jumping-droplet-enhanced condensation under high heat flux conditions.
Development of Bi-axial Tensile Testing for Porous Polymer Membranes and Its Deformation Characteristics
Authors: Kodaira Yasuhisa , Miura Tatsuma , Takano Yoshinori , Yonezu Akio 
Published: January 2022

Abstract
Porous polymer membranes are generally polymeric materials having numerous pores and complicate network structure. Due to their features, these materials sometimes exhibit anisotropic deformation in their elasto-plastic deformation. It is thus important to investigate the deformation behavior of materials, including anisotropic deformation under multi-axial loading. Here we developed a new testing machine for bi-axial tension for porous polymer membranes, in order to evaluate the deformation behavior under bi-axial tension and elucidate the deformation mechanism based on their microstructure. First, uni-axial tensile tests were conducted in each direction to investigate the change in Young’s modulus and yield strength depending on the tensile direction. It was found that there was deformation anisotropy. Next, we newly developed a bi-axial tensile testing for the present membranes. Since the present membrane has lower deformation rigidity and the thickness is very thin, gripping of specimen and applying uniform deformation are difficult. Thus, this study developed the gripping part to enable uniform tensile deformation during the test. Stress-strain curves of each loading axis were obtained by changing the applying strain ratio. Based on the results, a yield surface was created to investigate the deformation behavior under bi-axial tensile loading. We also investigated the deformation mechanism of the microstructure (porous structure) by using SEM observation.