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SSRN 2023年

作者： Sadaghian, Hamed Khalilzadehtabrizi, Sahand Khodadoost, Saeed Yeon, Jung Heum School of Architecture Building and Civil Engineering Loughborough University LoughboroughLE11 3TU United Kingdom Department of Civil and Environmental Engineering Centre for Infrastructure Systems Engineering University of Surrey Guilford United Kingdom Department of Civil Engineering University of Tabriz Tabriz Iran Civil Engineering Program Ingram School of Engineering Texas State University San MarcosTX78666 United States

Numerous materials, including soft sensors, microgrippers, metamaterials, bone substitutes, photopolymers, and functionally graded materials, undergo torsional loading throughout their service life. With the widespread adoption of additive manufacturing technology across various fields, many of the foregoing components are fabricated using additive manufacturing technology. Hence, it is essential to characterize the torsional behavior of additively-manufactured components before using them. More importantly, studies on additively-manufactured resin polymers are scarce, if any. To this end, the vat photopolymerization (VPP) technique was employed to fabricate 48 torsion specimens. These specimens were additively manufactured from the AnyCubic ultraviolet (UV) Tough Resin Material in a vertical build orientation. The study involved four different gage lengths: 20, 40, 60, and 80 mm. Additionally, five UV post-curing times (0, 15, 30, 60, 90, and 120 minutes) were considered as variables. Monotonic torsion was applied to the specimens at a rate of 0.1 revolutions per minute until failure. The results revealed that the failure patterns of all specimens were ductile. It was observed that longer post-curing times correlated with increased torsional capacities and shear moduli. However, no definitive conclusion could be drawn regarding the energy absorption per unit volume of the specimens. Furthermore, a normalized trilinear model was proposed to characterize the behavior of additively-manufactured resin polymers under monotonic torsion. This model is applicable for finite element software, enabling numerical simulation of the material’s response. © 2023, The Authors. All rights reserved.

关键词： Photopolymerization

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PBF-AMP-Onto: an ontology for powder bed fusion additive manufacturing processes 1

PBF-AMP-Onto: an ontology for powder bed fusion additive man...

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1st International Workshop on Semantic Materials Science: Harnessing the Power of Semantic Web Technologies in Materials Science, SeMatS 2024

作者： Pour, Mina Abd Nikooie Tarafder, Prithwish Wiberg, Anton Li, Huanyu Moverare, Johan Lambrix, Patrick Department of Computer and Information Science Linköping University Linköping Sweden Swedish e-Science Research Centre Linköping University Linköping Sweden Department of Management and Engineering Linköping University Linköping Sweden Wallenberg Initiative Materials Science for Sustainability Linköping University Linköping Sweden Wallenberg AI Autonomous Systems and Software Program Linköping University Linköping Sweden

Additive manufacturing is an innovative production approach aimed at creating products that traditional techniques cannot produce with the desired quality and requirements. Throughout the additive manufacturing process, data is either used (such as materials properties, printer characteristics and settings) or generated (such as monitoring data during printing, slicing strategies setting parameters). However, managing such data with complex relationships remains a significant challenge in both research and industry in the additive manufacturing field. To address this issue, we developed a modular ontology that can be used as the basis for a framework that supports decision-making systems, facilitate semanticsaware data management, and enhance the understanding and optimization of additive manufacturing processes. In this paper we focus on one of the state-of-the-art additive manufacturing approaches, i.e., powder bed fusion. To show the use and the feasibility of our approach, we created a knowledge graph for an actual additive manufacturing experiment based on our ontology, and show how queries relevant to domain experts can be answered using this knowledge graph. © 2024 CEUR-WS. All rights reserved.

关键词： Ontology

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Optimal Control Method for LLC Resonant Convertor of EV Battery Chargers

Optimal Control Method for LLC Resonant Convertor of EV Batt...

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International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Abdullah Memon Muhammad Majid Gulzar Noman Bashir Salman Habib Adnan Shakoor Farheen Ehsan Department of Control & Instrumentation Engineering Interdisciplinary Research Center for Sustainability Energy Systems (IRC-SES) Interdisciplinary Research Center for Smart Mobility and Logistics (IRC-SML) Interdisciplinary Research Center for Biosystems and Machines (IRC-BSM) King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia School of International and Public Affairs Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350375589

ISBN: (纸本)9798350375596

This research provides a thorough analysis of the LLC resonant converter's mathematical modeling, design, and control using MATLAB Simulink (R2024a). Distinct control strategies, Linear Active Disturbance Rejection Controller (LADRC), Proportional-Integral-Derivative (PID), PI and PI-PD controller, have been implemented and rigorously analyzed under varying operational conditions. The investigation encompassed dynamic response, stability, and disturbance rejection capabilities of each controller. The results consistently demonstrated the superiority of the LADRC in comparison to PID family controllers, highlighting enhanced transient response, reduced overshoot, and improved robustness across diverse scenarios. The conclusion drawn from this study supports the efficacy of LADRC in LLC resonant converters, providing valuable insights into the selection of control strategies for optimal performance in practical applications.

关键词： Dynamic response Transient response Renewable energy sources Software packages Optimal control Resonant converters Stability analysis Robustness PD control MATLAB

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Prediction and Identification of Vulnerable Areas Due to Heavy Snowfall Using Machine Learning and K-Means Clustering with Rcp Scenarios

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SSRN 2023年

作者： Song, Moon-Soo Yun, Hong-Sik Lee, Jae-Joon Yum, Sang-Guk Interdisciplinary Program in Crisis Disaster and Risk Management Sungkyunkwan University Suwon16419 Korea Republic of School of Civil Architectural Engineering & Landscape Architecture Sungkyunkwan University Suwon16419 Korea Republic of Department of Civil Engineering College of Engineering Gangneung-Wonju National University Gangneung25457 Korea Republic of

Heavy snowfall is a natural disaster that causes extensive damage in South Korea. Therefore, predicting heavy snowfall occurrence, identifying vulnerable areas, and establishing response plans to reduce risk are crucial. In this study, to predict heavy snowfall, meteorological, and geographic data from the past 30 years were collected, and four machine learning algorithms were trained and compared: multiple linear regression, support vector regression, random forest regressor (RFR), and extreme gradient boosting. We observed that the RFR model (R2 = 0.64) accurately predicted the occurrence of snowfall compared to other models. Representative concentration pathway (RCP) scenario data was input into the RFR model to generate prediction data up to 2100. Prediction results of more than 48.2 cm based on heavy snowfall events in the past 20 years were observed 17 times in RCP2.6, 19 times in RCP4.5, 16 times in RCP6.0, and 17 times in RCP8.5. Annual GIS-based snowfall images for the RCP8.5 scenario were classified using K-means clustering, grouped by vulnerable areas (Gangwon-do, Jeollabuk-do, northern Gyeonggi-do), and divided into five groups. Our study can aid decision-making on policies related to heavy snowfall disaster prevention standards, snow removal plans, budgeting, and the establishment of mid- to long-term climate change adaptation plans for government and public institutions. © 2023, The Authors. All rights reserved.

关键词： Machine learning

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US Army Aviation air movement operations assignment, utilization and routing

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Journal of Defense Analytics and Logistics 2023年第1期7卷 2-28页

作者： Nelson, Russell King, Russell McConnell, Brandon M. Thoney-Barletta, Kristin Operations Research Graduate Program North Carolina State University Raleigh NC United States Department of Industrial and Systems Engineering North Carolina State University Raleigh NC United States Center for Additive Manufacturing and Logistics North Carolina State University Raleigh NC United States Department of Textile and Apparel Technology and Management North Carolina State University at Raleigh Raleigh NC United States

Purpose: The purpose of this study was to create an air movement operations planning model to rapidly generate air mission request (AMR) assignment and routing courses of action (COA) in order to minimize unsupported AMRs, aircraft utilization and routing cost. Design/methodology/approach: In this paper, the US Army Aviation air movement operations planning problem is modeled as a mixed integer linear program (MILP) as an extension of the dial-a-ride problem (DARP). The paper also introduces a heuristic as an extension of a single-vehicle DARP demand insertion algorithm to generate feasible solutions in a tactically useful time period. Findings: The MILP model generates optimal solutions for small problems (low numbers of AMRs and small helicopter fleets). The heuristic generates near-optimal feasible solutions for problems of various sizes (up to 100 AMRs and 10 helicopter team fleet size) in near real time. Research limitations/implications: Due to the inability of the MILP to produce optimal solutions for mid- and large-sized problems, this research is limited in commenting on the heuristic solution quality beyond the numerical experimentation. Additionally, the authors make several simplifying assumptions to generalize the average performance and capabilities of aircraft throughout a flight. Originality/value: This research is the first to solve the US Army Aviation air movement operations planning problem via a single formulation that incorporates multiple refuel nodes, minimization of unsupported demand by priority level, demand time windows, aircraft team utilization penalties, aircraft team time windows and maximum duration and passenger ride time limits. © 2022, In accordance with section 105 of the US Copyright Act, this work has been produced by a US government employee and shall be considered a public domain work, as copyright protection is not available.

关键词： Aircraft Demand priority Dial-a-ride problem Helicopter routing Heuristic Military aviation Multiple refuel nodes Vehicle utilization

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Sweet–Bitter Taste Interactions in Binary Mixtures of Sweeteners: Relationship of Taste Receptor Activities with Sensory Perception

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SSRN 2024年

作者： Choi, Yoonha Wong, RunRou Cha, Yeon Kyung Park, Tai Hyun Kim, Yuri Chung, Seo-Jin Department of Nutritional Science and Food Management Ewha Womans University Seoul03760 Korea Republic of Interdisciplinary Program in Bioengineering Seoul National University Seoul08826 Korea Republic of Graduate Program in System Health Science and Engineering Ewha Womans University Seoul03760 Korea Republic of

Combining several low-calorie sweeteners in a food is a common strategy for reducing caloric sweeteners. The effects of binary sweetener mixtures on sweetness enhancement and sweet–bitter taste receptor interactions, specifically sensory perception and receptor activity, were investigated. Acesulfame K or saccharin was mixed with allulose, aspartame, erythritol, fructose, glucose, or sucrose to match a target sucrose sweetness. The effects of the mixtures on sweet and bitter taste receptors (expressed in HEK-293 cells) and sensory taste intensities were evaluated. Sweetness was enhanced in limited cases at the taste receptor level. Several monosaccharides reduced the bitter taste receptor activity triggered by acesulfame K or saccharin. The sweetness of acesulfame K and saccharin combined with any of the six sweeteners was perceptually enhanced, correlating with a reduction in their inherent bitterness. This finding suggested that sweetness perception likely increased because of the ability of monosaccharides to diminish bitter receptor activation by high-potency sweeteners. © 2024, The Authors. All rights reserved.

关键词： Binary mixtures

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Synthesis and Simulation Study of Titanium Dioxide-Based Nanomaterial for Electron Carrier Selective Contact Solar Cell

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SSRN 2024年

作者： Yi, Junsin Rahman, Rafi Ur Aslam, Junaid Jony, Jaljalalul Abedin Aida, Maha Nur Mengmeng, Chu Hussain, Shahzada Qamar Park, Sangheon Khan, Alamgeer Khokhar, Muhammad Quddamah Yousuf, Hasnain Department of Electrical and Computer Engineering Sungkyunkwan University Gyeonggi-do Suwon16419 Korea Republic of Department of Physics COMSATS University Islamabad Lahore Campus Lahore54000 Pakistan Interdisciplinary Program in Photovoltaic System Engineering Sungkyunkwan University Gyeonggi-do Suwon16419 Korea Republic of Department of Future Energy Engineering Sungkyunkwan University Gyeonggi-do Suwon16419 Korea Republic of Research Institute for Clean Energy College of Information and Communication Engineering Sungkyunkwan University Gyeonggi-do Suwon16419 Korea Republic of

This research focused on synthesizing titanium dioxide (TiO2) nanomaterials using the sol-gel method to improve Silicon Heterojunction (SHJ) solar cells. Iso-Propanol Alcohol and Titanium Tetra Isopropoxides were used in the synthesis process. TiO2's wide bandgap and low work function make it a suitable replacement for these cells' n-doped amorphous silicon layer. Atomic Force Microscopy (AFM) measured the roughness and 3D profile, while UV-V spectrophotometry assessed absorption. The nanomaterials' structure and surface morphology were analyzed using Scanning Electron Microscopy (SEM) and Transmission Electron Microscope (TEM). Simulations using the AFORS-HET simulator showed that the refractive index of TiO2 and a-Si:H(n), TiO2 with a work function of 4.6 eV enhanced the solar cells' performance by 22.57%, achieving an open-circuit voltage (Voc) of 716.8 mV, a short-circuit current density (Jsc) of 37.71 mA/cm2, a fill factor (FF) of 83.49. Future work will focus on refining TiO2's nanostructure to further advance its photovoltaic applications. © 2024, The Authors. All rights reserved.

关键词： Titanium dioxide

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Experimental investigation of effect of refrigerant gases,compressor lubricant and operating conditions on performance of a heat pump

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Journal of Central South University 2021年第11期28卷 3556-3568页

作者： AFSHARI Faraz SÖZEN Adnan KHANLARI Ataollah TUNCER Azim Doğuş ALI Hafiz Muhammad Department of Mechanical Engineering Erzurum Technical UniversityErzurumTurkey Department of Energy Systems Engineering Gazi UniversityAnkaraTurkey Department of Mechanical Engineering Faculty of EngineeringTarsus UniversityMersinTurkey Department of Energy Systems Engineering Burdur Mehmet Akif Ersoy UniversityBurdurTurkey Natural and Applied Science Institute Gazi UniversityAnkaraTurkey Mechanical Engineering Department King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia Interdisciplinary Research Center for Renewable Energy and Power Systems(IRC-REPS) King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia

In the field of heat pumps,there are a number of parameters that affect the performance and efficiency of the apparatus,which have been the subject of studies by individual researchers in the *** study describes an experimental method in order to investigate the effects of some significant parameters on heat pump *** this regard,a laboratory heat pump setup has been utilized to operate in different working conditions for achieving an appropriate estimation to find out effects of mentioned parameters such as refrigerant type and charge amount,compressor oil viscosity,compressor cooling fan,secondary fluids temperature and flow *** refrigerants have been selected and used as circulating fluid in the installed heat *** this work has been devoted to a detailed attempt to recognize the effects of various parameters on the coefficient of performance(COP) value,an appropriate method has been carried out to survey the obtained results by using economic *** was revealed that one of the main parameters is refrigerant charge amount which has a notable effect on *** temperature of the heat source was also tested and the performance of the system increased by more than 11% by employing mentioned modifications and various operating *** addition,by selecting a low viscosity compressor oil,the system performance increased by 18%.This improvement is more than 6% for the case that cooling fan is installed to cool the compressor element.

关键词： heat pump efficiency coefficient of performance(COP) performance compressor oil charge amount

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Measuring Consumer Willingness to Enroll in Battery Electric Vehicle Smart Charging programs

Measuring Consumer Willingness to Enroll in Battery Electric...

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Pingfan Hu Brian Tarroja Matthew Dean Kate Forrest Eric Hittinger Alan Jenn John Paul Helveston Department of Engineering Management and Systems Engineering George Washington University Washington DC USA Department of Civil and Environmental Engineering University of California Irvine Irvine CA USA Advanced Power and Energy Program University of California Irvine Irvine CA USA Department of Public Policy Rochester Institute of Technology Rochester NY USA Institute of Transportation Studies University of California Davis Davis CA USA

ISBN: (数字)9798331541606

ISBN: (纸本)9798331541613

As Battery Electric Vehicles (BEVs) gain popularity, managing their charging becomes crucial for grid stability. Smart charging programs can help utilities manage this demand and integrate more renewable energy by controlling when and how BEVs are charged. However, these programs require participation from BEV owners, who may be hesitant to freely provide such control. This study uses a discrete choice experiment (also called conjoint analysis) to measure BEV owners' willingness to participate in smart charging programs under various incentives and features. We examine two types of smart charging: Supplier-Managed Charging (SMC), which controls charging times, and Vehicle-to-Grid (V2G), allowing BEVs to return power to the grid. In an online survey conducted via Facebook and Instagram ads, we collected 858 valid responses, with 815 responses for SMC program choices and 414 for V2G program choices. We used mixed logit (MXL) models to quantify respondents' willingness to participate. The findings indicate a general reluctance to participate in both programs without some form of incentive, with respondents being most sensitive to recurring monetary incentives. For SMC, there is also concern about ensuring sufficient battery levels in the mornings. Simulations were conducted to predict enrollment rates based on different program features. Additional data will be collected to refine the models in the coming months.

关键词： Surveys Vehicle-to-grid Renewable energy sources Analytical models Power system stability Data models Stability analysis Batteries Web sites Smart charging

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IoT for Water Quality Categorization 5

IoT for Water Quality Categorization

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5th International Conference on Cybernetics and Intelligent systems, ICORIS 2023

作者： Sastrohartono, Hermantoro Krisdiarto, Andreas Wahyu Uktoro, Arief Ika Rahutomo, Reza Suparyanto, Teddy Pardamean, Bens Institute of Agriculture Stiper Faculty of Agricultural Technology Agricultural Engineering Department Yogyakarta Indonesia Bina Nusantara University School of Information Systems Information System Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics & Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350369489

In agricultural water research, the adoption of Internet of Things (IoT) technology has emerged as a pivotal approach for large-scale data collection. Water availability in the context of water quality is very important, both for domestic and industrial purposes. For domestic purposes, drinking water and bathing water are separated. Meanwhile, for the palm oil industry, boiler filler is differentiated from additional process water (dilution water). Water quality parameters can be assessed from turbidity and Total Dissolve Solid (TDS). Measurements using measuring instruments separately and repeatedly require significant energy, time, and costs. This research was conducted with the primary objective of presenting a novel method for categorizing water quality with the approach of IoT sensor technology. The research methodology entailed the utilization of an integrated IoT water sensors system in conjunction with manual water categorization. The methods consist of (1) system design, (2) design and installation of sensor and IoT-based microcontrollers, and (3) accuracy and precision testing compared with laboratory measurements. The precision of the integrated IoT water sensors was assessed through a dedicated sensor precision test, resulting in an accuracy rate of 94.4% for the turbidity sensor and 97.5% for the TDS sensor. Notably, this approach successfully discriminated drinking water with valid categorization, while other water types, including groundwater, water with tea, and water with coffee, yielded null categorization results. © 2023 IEEE.

关键词： Internet of things

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