• Title/Summary/Keyword: optimization flow

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Techno-economic Analysis of Power to Gas (P2G) Process for the Development of Optimum Business Model: Part 1 Methane Production

  • Roy, Partho Sarothi;Yoo, Young Don;Kim, Suhyun;Park, Chan Seung
    • Clean Technology
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    • v.28 no.2
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    • pp.182-192
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    • 2022
  • This study provides an overview of the production costs of methane and hydrogen via water electrolysis-based hydrogen production followed by a methanation based methane production technology utilizing CO2 from external sources. The study shows a comparative way for economic optimization of green methane generation using excess free electricity from renewable sources. The study initially developed the overall process on the Aspen Plus simulation tool. Aspen Plus estimated the capital expenditure for most of the equipment except for the methanation reactor and electrolyzer. The capital expenditure, the operating expenditure and the feed cost were used in a discounted cash flow based economic model for the methane production cost estimation. The study compared different reactor configurations as well. The same model was also used for a hydrogen production cost estimation. The optimized economic model estimated a methane production cost of $11.22/mcf when the plant is operating for 4000 hr/year and electricity is available for zero cost. Furthermore, a hydrogen production cost of $2.45/GJ was obtained. A sensitivity analysis was performed for the methane production cost as the electrolyzer cost varies across different electrolyzer types. A sensitivity study was also performed for the changing electricity cost, the number of operation hours per year and the plant capacity. The estimated levelized cost of methane (LCOM) in this study was less than or comparable with the existing studies available in the literature.

Optimization of VIGA Process Parameters for Power Characteristics of Fe-Si-Al-P Soft Magnetic Alloy using Machine Learning

  • Sung-Min, Kim;Eun-Ji, Cha;Do-Hun, Kwon;Sung-Uk, Hong;Yeon-Joo, Lee;Seok-Jae, Lee;Kee-Ahn, Lee;Hwi-Jun, Kim
    • Journal of Powder Materials
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    • v.29 no.6
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    • pp.459-467
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    • 2022
  • Soft magnetic powder materials are used throughout industries such as motors and power converters. When manufacturing Fe-based soft magnetic composites, the size and shape of the soft magnetic powder and the microstructure in the powder are closely related to the magnetic properties. In this study, Fe-Si-Al-P alloy powders were manufactured using various manufacturing process parameter sets, and the process parameters of the vacuum induction melt gas atomization process were set as melt temperature, atomization gas pressure, and gas flow rate. Process variable data that records are converted into 6 types of data for each powder recovery section. Process variable data that recorded minute changes were converted into 6 types of data and used as input variables. As output variables, a total of 6 types were designated by measuring the particle size, flowability, apparent density, and sphericity of the manufactured powders according to the process variable conditions. The sensitivity of the input and output variables was analyzed through the Pearson correlation coefficient, and a total of 6 powder characteristics were analyzed by artificial neural network model. The prediction results were compared with the results through linear regression analysis and response surface methodology, respectively.

Pathogenesis and Prevention of Intraventricular Hemorrhage in Preterm Infants

  • Pei-Chen Tsao
    • Journal of Korean Neurosurgical Society
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    • v.66 no.3
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    • pp.228-238
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    • 2023
  • Intraventricular hemorrhage (IVH) is a serious concern for preterm infants and can predispose such infants to brain injury and poor neurodevelopmental outcomes. IVH is particularly common in preterm infants. Although advances in obstetric management and neonatal care have led to a lower mortality rate for preterm infants with IVH, the IVH-related morbidity rate in this population remains high. Therefore, the present review investigated the pathophysiology of IVH and the evidence related to interventions for prevention. The analysis of the pathophysiology of IVH was conducted with a focus on the factors associated with cerebral hemodynamics, vulnerabilities in the structure of cerebral vessels, and host or genetic predisposing factors. The findings presented in the literature indicate that fluctuations in cerebral blood flow, the presence of hemodynamic significant patent ductus arteriosus, arterial carbon dioxide tension, and impaired cerebral venous drainage; a vulnerable or fragile capillary network; and a genetic variant associated with a mechanism underlying IVH development may lead to preterm infants developing IVH. Therefore, strategies focused on antenatal management, such as routine corticosteroid administration and magnesium sulfate use; perinatal management, such as maternal transfer to a specialized center; and postnatal management, including pharmacological agent administration and circulatory management involving prevention of extreme blood pressure, hemodynamic significant patent ductus arteriosus management, and optimization of cardiac function, can lower the likelihood of IVH development in preterm infants. Incorporating neuroprotective care bundles into routine care for such infants may also reduce the likelihood of IVH development. The findings regarding the pathogenesis of IVH further indicate that cerebrovascular status and systemic hemodynamic changes must be analyzed and monitored in preterm infants and that individualized management strategies must be developed with consideration of the risk factors for and physiological status of each preterm infant.

Design of Optimal Thermal Structure for DUT Shell using Fluid Analysis (유동해석을 활용한 DUT Shell의 최적 방열구조 설계)

  • Jeong-Gu Lee;Byung-jin Jin;Yong-Hyeon Kim;Young-Chul Bae
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.4
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    • pp.641-648
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    • 2023
  • Recently, the rapid growth of artificial intelligence among the 4th industrial revolution has progressed based on the performance improvement of semiconductor, and circuit integration. According to transistors, which help operation of internal electronic devices and equipment that have been progressed to be more complicated and miniaturized, the control of heat generation and improvement of heat dissipation efficiency have emerged as new performance indicators. The DUT(Device Under Test) Shell is equipment which detects malfunction transistor by evaluating the durability of transistor through heat dissipation in a state where the power is cut off at an arbitrary heating point applying the rating current to inspect the transistor. Since the DUT shell can test more transistor at the same time according to the heat dissipation structure inside the equipment, the heat dissipation efficiency has a direct relationship with the malfunction transistor detection efficiency. Thus, in this paper, we propose various method for PCB configuration structure to optimize heat dissipation of DUT shell and we also propose various transformation and thermal analysis of optimal DUT shell using computational fluid dynamics.

AI based complex sensor application study for energy management in WTP (정수장에서의 에너지 관리를 위한 AI 기반 복합센서 적용 연구)

  • Hong, Sung-Taek;An, Sang-Byung;Kim, Kuk-Il;Sung, Min-Seok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.322-323
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    • 2022
  • The most necessary thing for the optimal operation of a water purification plant is to accurately predict the pattern and amount of tap water used by consumers. The required amount of tap water should be delivered to the drain using a pump and stored, and the required flow rate should be supplied in a timely manner using the minimum amount of electrical energy. The short-term demand forecasting required from the point of view of energy optimization operation among water purification plant volume predictions has been made in consideration of seasons, major periods, and regional characteristics using time series analysis, regression analysis, and neural network algorithms. In this paper, we analyzed energy management methods through AI-based complex sensor applicability analysis such as LSTM (Long Short-Term Memory) and GRU (Gated Recurrent Units), which are types of cyclic neural networks.

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Thermodynamic simulation and structural optimization of the collimator in the drift duct of EAST-NBI

  • Ning Tang;Chun-dong Hu;Yuan-lai Xie;Jiang-long Wei;Zhi-Wei Cui;Jun-Wei Xie;Zhuo Pan;Yao Jiang
    • Nuclear Engineering and Technology
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    • v.54 no.11
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    • pp.4134-4145
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    • 2022
  • The collimator is one of the high-heat-flux components used to avoid a series of vacuum and thermal problems. In this paper, the heat load distribution throughout the collimator is first calculated through experimental data, and a transient thermodynamic simulation analysis of the original model is carried out. The error of the pipe outlet temperature between the simulated and experimental values is 1.632%, indicating that the simulation result is reliable. Second, the model is optimized to improve the heat transfer performance of the collimator, including the contact mode between the pipe and the flange, the pipe material and the addition of a twisted tape in the pipe. It is concluded that the convective heat transfer coefficient of the optimized model is increased by 15.381% and the maximum wall temperature is reduced by 16.415%; thus, the heat transfer capacity of the optimized model is effectively improved. Third, to adapt the long-pulse steady-state operation of the experimental advanced superconducting Tokamak (EAST) in the future, steady-state simulations of the original and optimized collimators are carried out. The results show that the maximum temperature of the optimized model is reduced by 37.864% compared with that of the original model. The optimized model was changed as little as possible to obtain a better heat exchange structure on the premise of ensuring the consumption of the same mass flow rate of water so that the collimator can adapt to operational environments with higher heat fluxes and long pulses in the future. These research methods also provide a reference for the future design of components under high-energy and long-pulse operational conditions.

Fabrication of Ceramic Filters via Binder Jetting Type 3D Printing Technology (바인더 젯팅 적층제조기술을 활용한 다공성 세라믹필터 제작)

  • Mose Kwon;Jong-Han Choi;Kwang-Taek Hwang;Jung-Hoon Choi;Kyu-Sung Han;Ung-Soo Kim;Jin-Ho Kim
    • Korean Journal of Materials Research
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    • v.33 no.7
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    • pp.285-294
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    • 2023
  • Porous ceramics are used in various industrial applications based on their physical properties, including isolation, storage, and thermal barrier properties. However, traditional manufacturing environments require additional steps to control artificial pores and limit deformities, because they rely on limited molding methods. To overcome this drawback, many studies have recently focused on fabricating porous structures using additive manufacturing techniques. In particular, the binder jet technology enables high porosity and various types of designs, and avoids the limitations of existing manufacturing processes. In this study, we investigated process optimization for manufacturing porous ceramic filters using the binder jet technology. In binder jet technology, the flowability of the powder used as the base material is an important factor, as well as compatibility with the binder in the process and for the final print. Flow agents and secondary binders were used to optimize the flowability and compatibility of the powders. In addition, the effects of the amount of added glass frit, and changes in sintering temperature on the microstructure, porosity and mechanical properties of the final printed product were investigated.

Modeling and experimental verification of phase-control active tuned mass dampers applied to MDOF structures

  • Yong-An Lai;Pei-Tzu Chang;Yan-Liang Kuo
    • Smart Structures and Systems
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    • v.32 no.5
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    • pp.281-295
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    • 2023
  • The purpose of this study is to demonstrate and verify the application of phase-control absolute-acceleration-feedback active tuned mass dampers (PCA-ATMD) to multiple-degree-of-freedom (MDOF) building structures. In addition, servo speed control technique has been developed as a replacement for force control in order to mitigate the negative effects caused by friction and inertia. The essence of the proposed PCA-ATMD is to achieve a 90° phase lag for a structure by implementing the desired control force so that the PCA-ATMD can receive the maximum power flow with which to effectively mitigate the structural vibration. An MDOF building structure with a PCA-ATMD and a real-time filter forming a complete system is modeled using a state-space representation and is presented in detail. The feedback measurement for the phase control algorithm of the MDOF structure is compact, with only the absolute acceleration of one structural floor and ATMD's velocity relative to the structure required. A discrete-time direct output-feedback optimization method is introduced to the PCA-ATMD to ensure that the control system is optimized and stable. Numerical simulation and shaking table experiments are conducted on a three-story steel shear building structure to verify the performance of the PCA-ATMD. The results indicate that the absolute acceleration of the structure is well suppressed whether considering peak or root-mean-square responses. The experiment also demonstrates that the control of the PCA-ATMD can be decentralized, so that it is convenient to apply and maintain to real high-rise building structures.

Numerical and statistical analysis of Newtonian/non-Newtonian traits of MoS2-C2H6O2 nanofluids with variable fluid properties

  • Manoj C Kumar;Jasmine A Benazir
    • Advances in nano research
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    • v.16 no.4
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    • pp.341-352
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    • 2024
  • This study investigates the heat and mass transfer characteristics of a MoS2 nanoparticle suspension in ethylene glycol over a porous stretching sheet. MoS2 nanoparticles are known for their exceptional thermal and chemical stability which makes it convenient for enhancing the energy and mass transport properties of base fluids. Ethylene glycol, a common coolant in various industrial applications is utilized as the suspending medium due to its superior heat transfer properties. The effects of variable thermal conductivity, variable mass diffusivity, thermal radiation and thermophoresis which are crucial parameters in affecting the transport phenomena of nanofluids are taken into consideration. The governing partial differential equations representing the conservation of momentum, energy, and concentration are reduced to a set of nonlinear ordinary differential equations using appropriate similarity transformations. R software and MATLAB-bvp5c are used to compute the solutions. The impact of key parameters, including the nanoparticle volume fraction, magnetic field, Prandtl number, and thermophoresis parameter on the flow, heat and mass transfer rates is systematically examined. The study reveals that the presence of MoS2 nanoparticles curbs the friction between the fluid and the solid boundary. Moreover, the variable thermal conductivity controls the rate of heat transfer and variable mass diffusivity regulates the rate of mass transfer. The numerical and statistical results computed are mutually justified via tables. The results obtained from this investigation provide valuable insights into the design and optimization of systems involving nanofluid-based heat and mass transfer processes, such as solar collectors, chemical reactors, and heat exchangers. Furthermore, the findings contribute to a deeper understanding of stretching sheet systems, such as in manufacturing processes involving continuous casting or polymer film production. The incorporation of MoS2-C2H6O2 nanofluids can potentially optimize temperature distribution and fluid dynamics.

Evaluation of Evacuation Safety in University Libraries Based on Pathfinder

  • Zechen Zhang;Jaewook Lee;Hasung Kong
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.2
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    • pp.237-246
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    • 2024
  • In recent years, the frequent occurrence of fire accidents in university libraries has posed significant threats to the safety of students' lives and property, alongside negative social impacts. Accurately analyzing the factors affecting evacuation during library fires and proposing optimized measures for safe evacuation is thus crucial. This paper utilizes a specific university library as a case study, simulating fire evacuation scenarios using the Pathfinder software, to assess and validate evacuation strategies and propose relevant optimizations. Pathfinder, developed by Thunderhead Engineering in the United States, is an intuitive and straightforward personnel emergency evacuation assessment system, offering advanced visualization interfaces and 3D animation effects. This study aims to construct evacuation models and perform simulation analysis for the selected university library using Pathfinder. The library's structural layout, people flow characteristics, and the nature of fire and smoke spread are considered in the analysis. Additionally, evacuation scenarios involving different fire outbreak locations and the status of emergency exits are examined. The findings underscore the importance of effective evacuation in fire situations, highlighting how environmental conditions, individual characteristics, and behavioral patterns significantly influence evacuation efficiency. Through these investigations, the study enhances understanding and optimization of evacuation strategies in fire scenarios, thereby improving safety and efficiency. The research not only provides concrete and practical guidelines for building design, management, and emergency response planning in libraries but also offers valuable insights for the design and management of effective evacuation systems in buildings, crucial for ensuring occupant safety and minimizing loss of life in potential hazard situations