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Simulation Winter Conference

作者： Yining Huang Hong Wan Xi Chen Operations Research Graduate Program North Carolina State University Raleigh NC USA Department of Industrial and Systems Engineering North Carolina State University Raleigh NC USA Grado Department of Industrial and Systems Engineering Virginia Tech Blacksburg VA USA

This study delves into the utilization of Generative Adversarial Networks (GANs) for generating subject-specific time series sensor data, offeringaninnovativealternativetotraditionalmetamodel-basedsimulations. We undertake an in-depth analysis of DoppelGANger, a prominent GAN variant for time series data and metadata generation, evaluating its efficiency and efficacy. The sensor data for this investigation was sourced from the National Health and Nutrition Examination Survey, which served as the foundational training set. We scrutinized the synthesized sensor data corresponding to various physical attributes, focusing on the temporal and multi-dimensional statistical properties. Our empirical findings underscore the potential of GANs to adeptly capture the time-dependent correlations and the intricate statistical characteristics inherent in multi-dimensional data. This insight into GANs’ capabilities is a crucial step towards more sophisticated synthetic data generation, with significant implications for future applications in wearable technology and personalized health monitoring systems.

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Thermodynamic and Environmental Assessment of Low-GWP Alternative Refrigerants for Domestic Cooling

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Journal of The Institution of Engineers (India): Series C 2023年第2期104卷 377-383页

作者： Islam, Md. Amirul Rupam, Tahmid Hasan Hosan, Shahadat Saha, Bidyut Baran Institute for Materials Chemistry and Engineering Kyushu University Kasuga-Koen 6-1 Kasuga-Shi Fukuoka816-8580 Japan Department of Electrical and Electronics Engineering Bangabandhu Sheikh Mujibur Rahman Science and Technology University Gopalganj8100 Bangladesh Kyushu University 744 Motooka Nishi-Ku Fukuoka819-0395 Japan Kyushu University Program for Leading Graduate School Green Asia Education Center Kyushu University Fukuoka Japan Department of Mechanical Engineering Kyushu University 744 Motooka Nishi-Ku Fukuoka819-0395 Japan

Nearly two billion air-conditioning (AC) units are currently being used for space cooling worldwide. The majority of these ACs use R134a as the working fluid, a greenhouse gas (GHG) with a global warming potential (GWP) of 1300 kg-CO2-eq. According to the rules set by the world environment safety organizations, the GWP of domestic air-conditioning systems must not exceed 750 kg-CO2-eq. Hence, the R134a must be phased out by 2025, and an alternative refrigerant with similar thermodynamic properties yet low GWP is required. Therefore, the authors have investigated several potential binary/ternary refrigerant blends in this study. Among the studied refrigerants, R445A, R30A, and NPB2 (newly proposed blend: 8% R152a + 92% R1234yf) can reduce 90–99% global warming impact (more than 200 million tonnes of CO2 emission equivalent) caused by the domestic air-conditioning systems every year. © 2023, The Institution of Engineers (India).

关键词： Refrigerants

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Preliminary Plan for Data Collection on Stakeholder Information Interdependence in Area-Business Continuity Management: A Case Study of Flood Management in Thai industrial Zones

Preliminary Plan for Data Collection on Stakeholder Informat...

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International Symposium on Communications and Information Technologies (ISCIT)

作者： Penpitcha Arayachookiat Kumpol Saengtabtim Akira Kodaka Natt Leelawat Jing Tang Kenji Watanabe Risk and Disaster Management Program Graduate School Chulalongkorn University Bangkok Thailand Department of Industrial Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Graduate School of System Design and Management Keio University Kanagawa Japan Disaster and Risk Management Information Systems Research Unit Chulalongkorn University Bangkok Thailand Faculty of Engineering International School of Engineering Chulalongkorn University Bangkok Thailand Graduate School of Social Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (数字)9798350353952

ISBN: (纸本)9798350353969

The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity Management (Area-BCM). This preliminary study focuses on identifying how stakeholders rely on information from each other to improve disaster preparedness and response. The research involves systematically identifying Area-BCM stakeholders and designing interview questions, which are evaluated by experts using the Index of Item-Objective Congruence (IOC) to ensure relevance and clarity. All interview questions surpassed the IOC threshold of 0.5, confirming their effectiveness in capturing information interdependencies. Expert feedback led to refinements in the questions, underscoring the importance of tailored data collection. This initial plan provides a critical foundation for understanding information interdependence and highlights the importance of well-designed data collection methods. The findings have significant implications for developing more resilient disaster management strategies in industrial areas, emphasizing the need for precise and relevant stakeholder communication to enhance Area-BCM effectiveness.

关键词： Disasters Disaster management Data collection Information and communication technology Stakeholders Floods Risk management Iterative methods Interviews Resilience

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All-Electric Ship On-Board Continuous Sustainable H2 Generation from Aluminum Scrap and Seawater

All-Electric Ship On-Board Continuous Sustainable H2 Generat...

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2023 IEEE Electric Ship Technologies Symposium, ESTS 2023

作者： Taher, Dhyogo M. Balmant, Wellington Och, Stephan H. Pitz, Diogo B. Venter, Giuliana S. Filho, Lucio C. Martins, Lauber S. Vargas, Jose V. C. Ordonez, Juan C. Federal University of Paraná Ufpr Graduate Program in Mechanical Engineering Sustainable Energy Research and Development Center PR Curitiba81531-980 Brazil Maringá State University Uem Department of Chemical Engineering PR Maringá87020-900 Brazil Advent Health University Ahu Department of Health and Biomedical Sciences OrlandoFL32803 United States Center for Advanced Power Systems and Energy Sustainability Center Florida State University Fsu Department of Mechanical Engineering TallahasseeFL32310 United States

ISBN: (纸本)9781665465151

A mathematical model of a sustainable H2 generation reactor that utilizes aluminum and seawater is introduced. Conservation of species and the kinetics of the H2 production reaction from aluminum and seawater allowed for obtaining the process transient response in a batch reactor. Continuous steady state production was assessed by adding a balance of energy, allowing for reactants inlet mass flow rates, and calculating the outlet H2 mass flow (generation) rate. The theoretical H2 production curve data showed good quantitative and qualitative agreement with experimental data. The validated mathematical model was then used to optimize the continuous reactor. The maximum was sharp, since an 85% variation between the maximum and the smallest H2 generation rate value as a function of the inlet NaOH solution volumetric flow rate tested range was verified. Such fundamental result stresses the importance of operating the system at the optimal condition, no matter how complex the actual reactor design may be. Since aluminum is inexpensive, abundant, and fully recyclable, in situ sustainable H2 production could allow for fuel cell stacks to become all electric ships (AES) power sources. © 2023 IEEE.

关键词： Aluminum

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Agent-Based Modeling for Forest Fire Simulation in Chiang Mai, Thailand

Agent-Based Modeling for Forest Fire Simulation in Chiang Ma...

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International Symposium on Communications and Information Technologies (ISCIT)

作者： Teerapat Tappanom Natt Leelawat Kumpol Saengtabtim Jing Tang Risk and Disaster Management Program Graduate School Chulalongkorn University Bangkok Thailand Department of Industrial Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Graduate School of System Design and Management Keio University Yokohama Japan Disaster and Risk Management Information Systems Research Unit Chulalongkorn University Bangkok Thailand

ISBN: (数字)9798350353952

ISBN: (纸本)9798350353969

Forest fires have a significant impact on ecosystems and human life, especially in northern Thailand, where Chiang Mai is severely affected. Traditional methods for detecting forest fires have limitations, so there is a need for advanced simulation models. This research uses Agent-Based Modeling (ABM) to develop a forest fire simulation for Chiang Mai. The methodology involves collecting historical data, performing Multiple Regression Analysis, designing the simulation, and testing it. Data from 1998 to 2021, including temperature, relative humidity, wind speed/direction, burn area, and slope, were collected from various sources. Multiple regression analysis identified wind speed as the most significant factor affecting burn area. The forest fire simulation, designed using ZF Wang's spread model and tested with AnyLogic, showed that wind direction and speed are crucial in fire spread. The simulation accurately predicted high-risk areas, helping in proactive planning and response. This study confirms that wind is a critical factor in forest fire spread, providing a valuable tool for fire districts to improve preparedness and management. Future research should focus on refining the model with localized data and integrating real-time detection to improve its accuracy and applicability.

关键词： Temperature distribution Biological system modeling Wind speed Refining Forestry Agent-based modeling Mathematical models Regression analysis Sensors Testing

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An Object Driven Fuzzy Decision Model for Sugarcane Yield Prediction in Indonesia's Sugar Industry 7

An Object Driven Fuzzy Decision Model for Sugarcane Yield Pr...

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7th International Seminar on Research of Information Technology and Intelligent systems, ISRITI 2024

作者： Utama, Ditdit Nugeraha Asrol, Muhammad Suharjito Harito, Christian Napthaleni Syafrudin, Muhammad Bina Nusantara University BINUS Graduate Program Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program Industrial Engineering Department Jakarta11480 Indonesia Sejong University Department of Artificial Intelligence and Data Science Seoul05006 Korea Republic of

ISBN: (纸本)9798331519643

A sugarcane yield of one plantation area depends on several independent variables. Practically it is challenging to predict accurately by using conventional methods. This study aims to develop a decision model based on a combination of fuzzy logic and object-oriented methods to predict sugarcane yield. The research is conducted in four main stages, employing object-oriented methods for model design and fuzzy logic for model construction. Object and activity diagrams are used for the object-oriented model design. The fuzzy membership functions employed are a combination of trapezoidal and triangular shapes. The resulting decision model can simulate 2,225 data from plantation areas in Indonesia. Based on the 10 examples of plantation area data in Indonesia, plantation number one obtained the largest sugarcane yield, which was 4.79%, with a similarity value of 0.90 (when compared to manual calculations as its ground truth). This similarity value is a higher value when compared to the average similarity value, which is 0.89. © 2024 IEEE.

关键词： Sugar industry

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Blockchain: A Review from the Perspective of Operations Researchers 22

Blockchain: A Review from the Perspective of Operations Rese...

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Proceedings of the Winter Simulation Conference

作者： Hong Wan Kejun Li Yining Huang Department of Industrial and Systems Engineering North Carolina State University Raleigh NC USA Operations Research Graduate Program North Carolina State University Raleigh NC USA

Blockchain is a distributed append-only digital ledger. The technology has caught much attention since the emergence of cryptocurrency, and there is an increasing number of blockchain applications in various businesses. The concept, however, is still novel to many members of the simulation and operations research community. In this tutorial, we introduce the blockchain technology and review its frontier related research. There are exciting opportunities for researchers in simulation, system analysis, and data science.

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Analysis of the Effect of Capacitors on the Voltage Generated by a 3-Phase Induction Generator

Analysis of the Effect of Capacitors on the Voltage Generate...

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2022 International Conference on Electrical engineering and Informatics, ICELTICs 2022

作者： Syukri, Mahdi Syuhada, Ahmad Tarmizi Suriadi Ramadhani, Satika Marwan Affan, Muzailin Yanis, Muhammad Universitas Syiah Kuala Doctoral Program School of Engineering Post Graduate Program Banda Aceh23111 Indonesia Universitas Syiah Kuala Dept. of Mechanical and Industrial Engineering Banda Aceh Indonesia Universitas Syiah Kuala Dept. of Electrical and Computer Engineering Banda Aceh Indonesia Universitas Syiah Kuala Dept. of Geophisic Engineering Banda Aceh Indonesia Universitas Syiah Kuala Dept. of Informatics Fmipa Banda Aceh Indonesia

ISBN: (数字)9781665487665

ISBN: (纸本)9781665487665

Induction motors can be operated as induction generators when additional capacitors are added to the stator terminals. Capacitors connected to induction generators can generate voltage and can provide reactive power. The advantage of induction generators can be used in small-scale plants such as micro-hydro power plants. However, the weakness of induction generators are weak voltage regulation and dependence on capacitors to generate voltage. This study conducted a test to see how the effect of capacitor capacity on the voltage generated by a induction generator when serving multiple incandescent lamp loads. The capacitor used is connected with a wye connection because the Wye connection can generate a higher voltage than the Delta connection circuit. This research has been successfully carried out with variations in capacitor values, namely 45 F, 60 F, and 75 F and variations in lamp load values, namely 5W, 15W, 25W, 40W and 60W. Based on the results of the study, the induction generators uses a 45 F capacitor with a load of 5 W, the terminal voltage for line to line is 374 V. However, when using a 75 F capacitor with a 60W load, the terminal voltage for line to line is 239 V. The terminals voltage of the induction generators can also be kept at a constant 380 V by providing varying capacitor values even though it serves varying loads. © 2022 IEEE.

关键词： Asynchronous generators

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Model Predictive Control of a Hybrid VA v for Parcel Delivery Applications 1

Model Predictive Control of a Hybrid VA v for Parcel Deliver...

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1st AIRPHARO Workshop on Aerial Robotic systems Physically Interacting with the Environment, AIRPHARO 2021

作者： Konyalioglu, Turan Alnipak, Sinan Altug, Erdinc İstanbul Technical University System Dynamics and Control Graduate Program İstanbul Technical University Autonomous Systems Research Laboratory Department of Mechanical Engineering İstanbul Turkey

ISBN: (纸本)9781665433891

Within the last decade, e-commerce has increased at an extraordinary level. The widespread use of Unmanned Aerial Vehicles (VAVs) in the logistics sector can reduce traffic density, improve delivery time, and can provide contactless delivery. This work proposes a new hybrid VAV, that combines the benefits of vertical take-off and land vehicle and a fixed-wing aircraft. It can carry multiple packages, which can decent automatically towards the recipients. This approach eliminates time-consuming landing maneuvers of the VA V for delivery. This work focuses on the design of the vehicle, and the challenges of the transitions from VTOL to aircraft modes and vice versa with a Model Predictive Controller. © 2021 IEEE.

关键词： Fixed wings

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A Machine Learning-Based Digital Twin Model for Pressure Prediction in the Fuel Injection System 48

A Machine Learning-Based Digital Twin Model for Pressure Pre...

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48th Annual Conference of the IEEE industrial Electronics Society, IECON 2022

作者： Duarte, Edwin P. Viegas, Eduardo K. Santin, Altair O. Graduate Program in Computer Science PPGIa Pontificia Universidade Catolica Do Parana-Pucpr Brazil Robert Bosch GmbH Engineering Systems Curitiba Brazil Secure Systems Research Center Abu Dhabi United Arab Emirates

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

Over the last years, the engine calibration task has mostly been conducted based on the engineers' knowledge. As a result, considering the complexity of modern engines, finding the most suitable configuration for each situation has become an impractical and expensive task. Apart from causing engines to be produced with inadequate calibration configuration, it can also decrease the lifespan of their components, degrading their efficiency. This paper proposes a machine learning-based digital twin model for pressure prediction in a fuel injection system, split into two steps. First, we extract statistical engine features based on a predefined time window to represent the engine behavior over time. Second, a digital twin implemented through a machine learning model is used to predict pressure levels in the fuel injection system. As a result, the predicted values can be used to assist the engine common rail system module in avoiding undesired engine states. Experiments performed on a new dataset, built over a real diesel-based engine, consisting of 208 features and over 1.3 million instances, have shown the feasibility of our proposal. The proposed scheme can predict in an advance time of 0.1 seconds the pressure levels for a fuel injection system with only 0.057 RMSE. Moreover, it increases its error rate by only 10.6% if a 0.5-second time advance is required. © 2022 IEEE.

关键词： Machine learning

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