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Records with Subject: Optimization
Showing records 25 to 49 of 1511. [First] Page: 1 2 3 4 5 6 Last
Optimization of Supercritical Carbon Dioxide Fluid Extraction of Medicinal Cannabis from Quebec
Hinane Boumghar, Mathieu Sarrazin, Xavier Banquy, Daria C. Boffito, Gregory S. Patience, Yacine Boumghar
August 3, 2023 (v1)
Subject: Optimization
Keywords: Box–Behnken, cannabinoids, Optimization, supercritical carbon dioxide
Research on cannabis oil has evolved to encompass the pharmaceutical industry for the therapeutic potential of the active compounds for pathologies such as Alzheimer, auto-immune disorders, and cancer. These debilitating diseases are best treated with cannabinoids such as tetrahydrocannabinol (∆9-THC), cannabigerol (CBG), and cannabinol (CBN), which relieve neuropathic pain and stimulate the immune system. We extracted cannabinoids from plants with supercritical CO2 and produced an extract with a total yield close to 26%. The three-level Box−Behnken experimental design considered four factors: Temperature, pressure, CO2 flow rate, and processing time, with predetermined parameters at low, medium, and high levels. The mathematical model was evaluated by regression analysis. The yield of ∆9-THC and CBG reached a maximum after 2 h and 15 g/min of CO2, 235 bar, 55 °C (64.3 g THC/100 g of raw material and 4.6 g CBG/100 g of raw material). After another 2 h of extraction time, the yield of C... [more]
Removal of Organic Contaminants in Gas-to-Liquid (GTL) Process Water Using Adsorption on Activated Carbon Fibers (ACFs)
Roghayeh Yousef, Hazim Qiblawey, Muftah H. El-Naas
August 2, 2023 (v1)
Subject: Optimization
Keywords: activated carbon fibers, adsorption regeneration, GTL process, industrial water treatment, isotherm models, kinetics models, Optimization
Gas-To-Liquid (GTL) processing involves the conversion of natural gas to liquid hydrocarbons that are widely used in the chemical industry. In this process, the Fischer−Tropsch (F-T) approach is utilized and, as a result, wastewater is produced as a by-product. This wastewater commonly contains alcohols and acids as contaminants. Prior to discharge, the treatment of this wastewater is essential, and biological treatment is the common approach. However, this approach is not cost effective and poses various waste-related issues. Due to this, there is a need for a cost-effective treatment method. This study evaluated the adsorption performance of activated carbon fibers (ACFs) for the treatment of GTL wastewater. The ACF in this study exhibited a surface area of 1232.2 m2/g, which provided a significant area for the adsorption to take place. Response surface methodology (RSM) under central composite design was used to assess the effect of GTL wastewater’s pH, initial concentration and dos... [more]
A Software Toolbox for Realistic Dataset Generation for Testing Online and Offline 3D Bin Packing Algorithms
Luis Ribeiro, Anan Ashrabi Ananno
August 2, 2023 (v1)
Subject: Optimization
Keywords: 3DBPP, dataset, offline 3DBPP, online 3DBPP, problem instance, toolbox
Packing products into a pallet or other medium is an unavoidable activity for producing companies. In many cases, packing is based on operator experience and training using packing patterns that have worked before. Automated packing, on the other hand, requires a systematic procedure for devising packing solutions. In the scientific literature, this problem is known as 3D bin packing (3DBP) and many authors have proposed exact and heuristic solutions for many variations of the problem. There is, however, a lack of datasets that can be used to test and validate such solutions. Many of the available datasets use randomly generated products with extremely limited connection to real practice. Furthermore, they contain a reduced number of product configurations and ignore that packing relates to customers’ orders, which have specific relative mixes of products. This paper proposes a software toolbox for generating arbitrarily large datasets for 3DBPP based on real industry data. The toolbox... [more]
Optimization Design of an Intermediate Fluid Thermoelectric Generator for Exhaust Waste Heat Recovery
Wei Zhang, Wenjie Li, Shuqian Li, Liyao Xie, Minghui Ge, Yulong Zhao
July 13, 2023 (v1)
Subject: Optimization
Keywords: intermediate fluid, Optimization, power deviation, thermoelectric generator
The intermediate fluid thermoelectric generator (IFTEG) represents a novel approach to power generation, predicated upon the principles of gravity heat pipe technology. Its key advantages include high-power output and a compact module area. The generator’s performance, however, is influenced by the variable exhaust parameters typical of automobile operation, which presents a significant challenge in the design process. The present study establishes a mathematical model to optimize the design of the IFTEG. Our findings suggest that the optimal module area sees substantial growth with an increase in both the exhaust heat exchanger area and the exhaust flow rate. Interestingly, the optimal module area appears to demonstrate a low sensitivity to changes in exhaust temperature. To address the challenge of determining the optimal module area, this study introduces the concept of peak power deviation. This method posits that any deviation from the optimal module area results in an equivalent... [more]
Matrix Non-Structural Model and Its Application in Heat Exchanger Network without Stream Split
Dinghao Li, Jingde Wang, Wei Sun, Nan Zhang
July 13, 2023 (v1)
Subject: Optimization
Keywords: Genetic Algorithm, heat exchanger network synthesis, matrix real-coded, non-structural model, Optimization
Heat integration by a heat exchanger network (HEN) is an important topic in chemical process system synthesis. From the perspective of optimization, the simultaneous synthesis of HEN belongs to a mixed-integer and nonlinear programming problem. Both the stage-wise superstructure (SWS) model and the chessboard model are the most widely adopted and belong to structural models, in which a framework is assumed for stream matching, and the global optimal solution outside its feasible domain may be defined by the framework. A node-wise non-structural model (NW-NSM) is proposed to find more universal stream matching options, but it requires a mass of structural variables and extra multiple correction strategies. The aim of this paper is to develop a novel matrix non-structural model (M-NSM) for HEN without stream splits from the perspectives of global optimization methods and superstructure models. In the proposed M-NSM, the heat exchanger position order is quantized by matrix elements at eac... [more]
A Method for Predicting Surface Finish of Polylactic Acid Parts Printed Using Fused Deposition Modeling
Meifa Huang, Shangkun Jin, Zhemin Tang, Yuanqing Chen, Yuchu Qin
July 13, 2023 (v1)
Subject: Optimization
Keywords: adaptive particle swarm optimization algorithm, fused deposition modeling, K-nearest neighbor algorithm, multi-category prediction, surface finish
Accurately predicting the surface finish of fused deposition modeling (FDM) parts is an important task for the engineering application of FDM technology. So far, many prediction models have been proposed by establishing a mapping relationship between printing parameters and surface roughness. Each model can work well in its specific context; however, existing prediction models cannot meet the requirements of multi-factor and multi-category prediction of surface finish and cope with imbalanced data. Aiming at these issues, a prediction method based on a combination of the adaptive particle swarm optimization and K-nearest neighbor (APSO-KNN) algorithms is proposed in this paper. Seven input variables, including nozzle diameter, layer thickness, number of perimeters, flow rate, print speed, nozzle temperature, and build orientation, are considered. The printing values of each specimen are determined using an L27 Taguchi experimental design. A total of 27 specimens are printed and experim... [more]
Design and Optimization of the Insulation Performance of a 4000 m3 Liquid Hydrogen Spherical Tank
Yang Yu, Fushou Xie, Ming Zhu, Shuai Yu, Yanzhong Li
July 7, 2023 (v1)
Subject: Optimization
Keywords: 4000 m3 LH2 spherical tank, efficient storage, liquid-nitrogen-cooled shield, multilayer insulation, vapor-cooled shield
Efficient insulation technology is one of the key technologies for the development of large LH2 storage tanks. This paper aimed at a 4000 m3 LH2 spherical tank, many insulation schemes were designed, including multilayer insulation systems integrated with a vapor-cooled shield (VCS) and liquid-nitrogen-cooled shield (LN2CS). The heat transfer model was developed to predict the insulation performance of a LH2 spherical tank. The effect of the VCS position on insulation performance was studied, and the different configurations of double VCSs were compared and discussed. The results showed that the daily evaporation rate of MLI, hollow glass microspheres (HGMs) and vacuum was only 2.05 × 10−3%, 3.62 × 10−3% and 7.94 × 10−2% at 1.34 Pa, respectively. MLI was still the optimal insulation scheme for a 4000 m3 LH2 spherical tank. Meanwhile, it was found that when the single VCS was placed at the 10th layer, the heat leakage was reduced by approximately 40.5% compared with MLI. The heat leakag... [more]
An Investigation on Optimized Performance of Voluteless Centrifugal Fans by a Class and Shape Transformation Function
Meijun Zhu, Zhehong Li, Guohui Li, Xinxue Ye, Yang Liu, Ziyun Chen, Ning Li
July 7, 2023 (v1)
Subject: Optimization
Keywords: centrifugal fan, class-shape-transformation function, dissipation function, Kriging model, Optimization
Class and shape transformation functions are proposed to carry out the parametric design of the blade profiles because fan efficiency is closely related to the shape of blade profiles. An optimization with the objectives of fan efficiency and static pressure based on the Kriging models was established, and numerical simulation data were applied to construct the Kriging models. The dissipation function was used to analyze the fan energy loss. The prediction results show that the maximum accuracy error between the Kriging model and the experimental data is approximately 0.81%. Compared with the prototype fan, the optimized fan was able to ameliorate the distribution of the flow field pressure and velocity; the outlet static pressure increased by 9.03%, and the efficiency increased by 2.35%. The dissipation function is advantageous because it can intuitively indicate the location and amount of energy loss in the fan, while effectively obtaining the total energy loss as well. The situation... [more]
Natural Deep Eutectic Solvent Optimization to Obtain an Extract Rich in Polyphenols from Capsicum chinense Leaves Using an Ultrasonic Probe
Kevin Alejandro Avilés-Betanzos, Juan Valerio Cauich-Rodríguez, Marisela González-Ávila, Matteo Scampicchio, Ksenia Morozova, Manuel Octavio Ramírez-Sucre, Ingrid Mayanin Rodríguez-Buenfil
July 7, 2023 (v1)
Subject: Optimization
Keywords: Capsicum chinense, green extraction, natural deep eutectic solvent, Optimization, polyphenols, ultrasonic probe
Jacq., from the Yucatan peninsula, is recognized worldwide for its pungency, flavor, and secondary metabolites content. This has resulted in an increase in its production, which has led to an increase in the number of byproducts considered waste, mainly its leaves. Capsicum chinense leaves have been demonstrated to contain polyphenols with bioactive properties (antioxidant, anti-inflammatory, antiobesogenic capacity, etc.); hence, the extraction of polyphenols through the use of natural deep eutectic solvents (NADES) with a green technology, such as an ultrasonic probe, could help to revalue these leaves by maximizing the extraction efficiency and preserving their bioactive properties. The objective of this study was to optimize the composition of a eutectic solvent for obtaining an extract rich in polyphenols from the Capsicum chinense leaf using a sonic probe. The optimum conditions of the composition of NADES for obtaining the highest Antioxidant capacity (Ax, 79.71% inhibition) wer... [more]
Application of an Improved Link Prediction Algorithm Based on Complex Network in Industrial Structure Adjustment
Yixuan Ma, Rui Zhao, Nan Yin
July 7, 2023 (v1)
Subject: Optimization
Keywords: complex networks, industrial structure (IS), link prediction algorithm, mixed similarity
For a healthy industrial structure (IS) and stable economic development in China, this study proposes an improved link prediction algorithm (LP) based on complex networks. The algorithm calculates the similarity by constructing a mixed similarity index. A regional IS network model is built in the study, and the direction of IS adjustment is calculated with the mixed similarity indicators. In this study, the prediction accuracy of the proposed improved LP algorithm in the real network dataset is up to 0.944, which is significantly higher than that of the other algorithms. In the reality of IS optimization, industries of high similarity could be obtained through similarity algorithms, and reasonable coordinated development strategies are proposed. In addition, the simulated IS adjustment strategy in this study shows that it is highly sustainable in development, which is reflected in its lower carbon emissions. The optimization of IS adjustment could be achieved through IS network model a... [more]
Mach Number Prediction for 0.6 m and 2.4 m Continuous Transonic Wind Tunnels
Luping Zhao, Wei Jia, Yawen Shao
July 7, 2023 (v1)
Subject: Optimization
Keywords: continuous transonic wind tunnel, FNN algorithm, IOSBC-PSO algorithm, model migration, NARX-BP algorithm, prediction model
With the development of the design technology, more and more advanced and diverse wind tunnels have been constructed to match complex requirements. However, it is hard to design a precise physical model of a wind tunnel that can be controlled. In addition, if a new wind tunnel is designed, the experimental data may be insufficient to build a controlling model. This article reports research on the following two models: (1) for a 0.6 m continuous transonic wind tunnel supported by a large amount of historical data, the false nearest neighbor (FNN) algorithm was adopted to calculate the order of the input variables, and the nonlinear auto-regressive model with the exogenous inputs−backpropagation network (NARX-BP) was proposed to build its Mach number prediction model; (2) for a new 2.4 m continuous transonic wind tunnel with only a small amount of experimental data, the method of model migration, the input and output slope/bias correction−particle swarm optimization (IOSBC-PSO) algorithm... [more]
Decision Models for Selection of Industrial Robots—A Comprehensive Comparison of Multi-Criteria Decision Making
G. Shanmugasundar, Kanak Kalita, Robert Čep, Jasgurpreet Singh Chohan
July 7, 2023 (v1)
Subject: Optimization
Keywords: decision making, MCDM, optimal selection, Optimization, robots
Due to increased demands of production capacity and higher quality requirements, industries are automating at a fast pace. Industrial robots are an important component of the industrial automation ecosystem. However, the selection of appropriate robots is a challenging task due to the sheer number of alternatives present and their varied specifications. The various characteristics or attributes of industrial robots that need due consideration before selection of an optimal robot for a given application are found to be conflicting in nature. Thus, in this paper, several multi-criteria decision-making (MCDM) methods are deployed to select an optimal robot depending on the application. Three different industrial robot selection problems are solved in this paper by using Simple Additive Weighing (SAW), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the Linear Programming Technique (LINMAP), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Elimi... [more]
Design Optimization of Counter-Flow Double-Pipe Heat Exchanger Using Hybrid Optimization Algorithm
B. Venkatesh, Mudassir Khan, Bayan Alabduallah, Ajmeera Kiran, J. Chinna Babu, B. Bhargavi, Fatimah Alhayan
July 4, 2023 (v1)
Subject: Optimization
Keywords: double-pipe heat exchanger, Genetic Algorithm, gray
Double-pipe counter-flow heat exchangers are considered more suitable for heat recovery in the heat transfer industry. Numerous studies have been conducted to develop static tools for optimizing operating parameters of heat exchangers. Using this study, an improved heat exchanger system will be developed. This is frequently used to solve optimization problems and find optimal solutions. The Taguchi method determines the critical factor affecting a specific performance parameter of the heat exchanger by identifying the significant level of the factor affecting that parameter. Gray relational analysis was adopted to determine the gray relational grade to represent the multi-factor optimization model, and the heat exchanger gray relation coefficient target values that were predicted have been achieved using ANN with a back propagation model with the Levenberg−Marquardt drive algorithm. The genetic algorithm improved the accuracy of the gray relational grade by assigning gray relational co... [more]
Water-Assisted Catalytic VACNT Growth Optimization for Speed and Height
Karlheinz Strobl, Fahd Rajab
July 4, 2023 (v1)
Subject: Optimization
Keywords: Al2O3 buffer layer, CVD, super-growth, VACNT, water vapor
The super-growth approach for carbon nanotubes synthesis is frequently used to boost the growth rate, catalyst lifespan, and height of vertically aligned carbon nanotubes. The elimination of amorphous carbon from catalyst particles, commonly made of iron, by injecting water vapor into a chemical vapor deposition process can enhance the purity, alignment, and height of carbon nanotubes and prevent the partial oxidation of the metallic catalyst. We present the development of a modified growth-optimized water-assisted super-growth vertically aligned carbon nanotube process by optimizing the catalyst layer structure and water vapor concentration for a carbon nanotube growth process for 4” diameter Si wafers. A significant finding is that under optimized water-assisted growth conditions over 4 mm, highly uniform tall, vertically aligned carbon nanotube structures can be grown with a minimum top crust layer of about ~5−10 μm thickness. This was achieved with a catalyst film comprising a >400... [more]
Air and O2-Assisted Catalytic VACNT Growth Optimization for Uniformity and Throughput
Karlheinz Strobl, Fahd Rajab
July 4, 2023 (v1)
Subject: Optimization
Keywords: air-assisted, CVD processing, FAB, O2-assisted, super-growth, VACNT
The development of an optimized air or O2-assisted multi-wall vertically aligned carbon nanotubes (VACNT) process that adjusts the vertical height profile of a standard H2O vapor-assisted VACNT process is reported. The effect of the air or O2 chemical vapor deposition (CVD) precursor flow rate, the catalytic Fe layer thickness, the process growth temperature, and the H2/C2H4 ratio on VACNT length was first investigated to find the optimum growth conditions. Spatial distribution height mapping of VACNT structures on six patterned 4′′ catalyst Si wafers prepared with a 70−90 min long O2-assisted growth step shows an average growth height of 1.8−2.2 mm, with a standard deviation of less than 10%. Characterization techniques included Raman spectroscopy, scanning electron microscopy (SEM), and spatial height mapping analysis for a range of Fluid channel Array Brick (FAB) components with a length of 30 mm, a width range of 2.5−15 mm, a fluid channel diameter range of d = 5−100 mm, and a flui... [more]
Modification of Meso-Micromixing Interaction Reaction Model in Continuous Reactors
Junan Jiang, Ning Yang, Hanyang Liu, Jianxin Tang, Chenfeng Wang, Rijie Wang, Xiaoxia Yang
June 9, 2023 (v1)
Subject: Optimization
Keywords: continuous reactors, mesomixing, micromixing, Optimization
The yields of chemical reactions are highly dependent on the mixing pattern between reactants. Herein, we report the modification of a meso-micromixing interaction reaction model which is applied in batch reactors by leveraging the flow characteristics in the continuous reactors. Both experimental and model-predicted yields were compared using the classical Villermaux−Dushman method in a self-designed split and recombination reactor. This modified model significantly reduced the error in predicted product yields from approximately 15% to within 3%, compared to a model containing the micromixing term only. The effects of flow rates and reactor structure parameters on mixing performance were analyzed. We found that increasing flow rates and the degree of twist in the mixing element’s grooves, as well as decreasing the cross-sectional area of grooves, improved mixing performance. The optimization of reactor flow rates and structural parameters was achieved by combining Gaussian process re... [more]
Task Containerization and Container Placement Optimization for MEC: A Joint Communication and Computing Perspective
Ao Liu, Shaoshi Yang, Jingsheng Tan, Zongze Liang, Jiasen Sun, Tao Wen, Hongyan Yan
June 9, 2023 (v1)
Subject: Optimization
Keywords: cloud computing, computing force network, computing power network, container, edge computing, joint communication and computing, workflow
Containers are used by an increasing number of Internet service providers to deploy their applications in multi-access edge computing (MEC) systems. Although container-based virtualization technologies significantly increase application availability, they may suffer expensive communication overhead and resource use imbalances. However, so far there has been a scarcity of studies to conquer these difficulties. In this paper, we design a workflow-based mathematical model for applications built upon interdependent multitasking composition, formulate a multi-objective combinatorial optimization problem composed of two subproblems—graph partitioning and multi-choice vector bin packing, and propose several joint task-containerization-and -container-placement methods to reduce communication overhead and balance multi-type computing resource utilization. The performance superiority of the proposed algorithms is demonstrated by comparison with the state-of-the-art task and container scheduling... [more]
Bionic Optimization Design and Discrete Element Experimental Design of Carrot Combine Harvester Ripping Shovel
Wenqi Zhou, Xue Ni, Kai Song, Nuan Wen, Jinwu Wang, Qiang Fu, Mingjun Na, Han Tang, Qi Wang
June 7, 2023 (v1)
Subject: Optimization
Keywords: bionic technology, carrot, discrete element method, efficient drag reduction, soil-loosening shovel
Aiming at the common problems of the high working resistance, low soil disturbance, and high rates of missed extraction in the operation of carrot combine harvesters, a high-efficiency drag-reducing bionic soil-loosening shovel was designed in this study. The physical parameters of the soil and carrots were measured, and the bionic drag-reducing shovel was designed using the badger claw toe as a bionic prototype. The shovel wing structures were designed. Based on the EDEM discrete element simulation technology, a multi-element simulation model of the shovel−soil−carrot contact was established to determine the effects of the operating speed and sliding angle of the shovel handle on the resistance. The effects of the blade inclination angle and blade opening angle on the resistance, carrot extraction force, and soil disturbance rate were also studied. The results show that the resistance increases with an increase in operating speed. With a blade angle (α) and blade inclination angle (β)... [more]
Online Monitoring of Flowmeter Anomaly in Tobacco Production Process Using Sliding Window Recursive Lasso
Ziyi Guan, Suijun Liu, Ying Liu, Ting Cui, Linchao Yang, Jinhui Cai, Bin Liu, Yuhao Liu, Jinming Li
June 7, 2023 (v1)
Subject: Optimization
Keywords: anomaly detection, flowmeter measurement, recursive Lasso, sliding-window
Ensuring the accuracy of flow measurement is crucial to promoting high-quality cigarette production. In order to monitor the working status of flowmeters, this paper proposes an anomaly detection method based on the sliding-window recursive Lasso (Least absolute shrinkage and selection operator), which is able to track the changes in flowmeter operating conditions by self-adapting model parameters based on observed measurements. Due to the frequent mode switch and high sampling frequency of flow data, this paper introduces the sliding-window strategy to remove the effect of outdated data and accelerate the optimization. The tracking errors are used as a measure of anomaly and different thresholds are introduced based on the operating manual of cigarette production, which are used to distinguish between mode switch and flowmeter anomalies. The method’s effectiveness is verified by detecting flowmeter anomalies in a real cigarette production line. The mean absolute error (MAE) is 8.1479... [more]
Application of the MPPT Control Algorithm Based on Hybrid Quantum Particle Swarm Optimization in a Photovoltaic Power Generation System
Xiaowei Xu, Wei Zhou, Wenhua Xu, Yongjie Nie, Shan Chen, Yangjian Ou, Kaihong Zhou, Mingxian Liu
June 7, 2023 (v1)
Subject: Optimization
Keywords: HQPSO, LF strategy, local shadow occlusion, MPPT, photovoltaic array, PPG
The Maximum Power Point Tracking method is a mainstream method for improving the operational efficiency of photovoltaic power generation, but it is difficult to adapt to the rapidly changing environment and lacks good steady-state and dynamic performance. To achieve fast and accurate tracking of the Maximum Power Point Tracking, the optimization of the contraction expansion coefficient of the Quantum Particle Swarm Optimization algorithm is studied, and then the Levy flight strategy is introduced to optimize the algorithm’s global convergence ability, thereby constructing the Hybrid Quantum Particle Swarm Optimization algorithm. Finally, the Hybrid Quantum Particle Swarm Optimization combined with the Maximum Power Point Tracking algorithm is obtained. The research results showed that the Hybrid Quantum Particle Swarm Optimization combined with the Maximum Power Point Tracking algorithm can always converge to the theoretical minimum value with a probability of more than 94% in the Rose... [more]
Prediction in Catalytic Cracking Process Based on Swarm Intelligence Algorithm Optimization of LSTM
Juan Hong, Wende Tian
June 7, 2023 (v1)
Subject: Optimization
Keywords: catalytic cracking process, cuckoo search, long short-term memory network, Particle Swarm Optimization, prediction
Deep learning can realize the approximation of complex functions by learning deep nonlinear network structures, characterizing the distributed representation of input data, and demonstrating the powerful ability to learn the essential features of data sets from a small number of sample sets. A long short-term memory network (LSTM) is a deep learning neural network often used in research, which can effectively extract the dependency relationship between time series data. The LSTM model has many problems such as excessive reliance on empirical settings for network parameters, as well as low model accuracy and weak generalization ability caused by human parameter settings. Optimizing LSTM through swarm intelligence algorithms (SIA-LSTM) can effectively solve these problems. Group behavior has complex behavioral patterns, which makes swarm intelligence algorithms exhibit strong information exchange capabilities. The particle swarm optimization algorithm (PSO) and cuckoo search (CS) algorit... [more]
Multi-Objective Optimization of Variable Density Multi-Layer Insulation for Liquid Hydrogen Containers Based on Reduced-Order Surrogate Model
Hao Wu, Hongbo Tan, Zhangliang Xu, Yanzhong Li
June 7, 2023 (v1)
Subject: Optimization
Keywords: liquid hydrogen container, reduced-order surrogate model optimization, variable density multi-layer insulation
For liquid hydrogen transportation, thermal insulation materials that are lightweight, compact and exhibit high-performance have been pursued for several decades, and variable density multi-layer insulation (VD-MLI) has been regarded as a promising choice. The thermal insulation performance of the insulation materials is important, but is not at the top of the list; many constraints, such as the space and weight of the insulation structures, are imposed on the design of a VD-MLI. Consequently, this makes the optimization of VD-MLIs more complicated. The present authors conducted a multi-objective optimization of a VD-MLI stacked with specific insulation units. The number of repetitions of the basic insulation unit was regarded as the dimensionless design parameter of the VD-MLI. Based on the experimentally validated layer-by-layer (LBL) model for MLI design, the multi-objective optimization of VD-MLI for liquid hydrogen storage was conducted by the combination of proper orthogonal deco... [more]
An Optimization-Based Model for A Hybrid Photovoltaic-Hydrogen Storage System for Agricultural Operations in Saudi Arabia
Awsan Mohammed
June 7, 2023 (v1)
Subject: Optimization
Keywords: hydrogen storage, mixed-integer linear programming, Optimization, photovoltaic system
Renewable energy technologies and resources, particularly solar photovoltaic systems, provide cost-effective and environmentally friendly solutions for meeting the demand for electricity. The design of such systems is a critical task, as it has a significant impact on the overall cost of the system. In this paper, a mixed-integer linear programming-based model is proposed for designing an integrated photovoltaic-hydrogen renewable energy system to minimize total life costs for one of Saudi Arabia’s most important fields, a greenhouse farm. The aim of the proposed system is to determine the number of photovoltaic (PV) modules, the amount of hydrogen accumulated over time, and the number of hydrogen tanks. In addition, binary decision variables are used to describe either-or decisions on hydrogen tank charging and discharging. To solve the developed model, an exact approach embedded in the general algebraic modeling System (GAMS) software was utilized. The model was validated using a far... [more]
Economic Dispatch Optimization of a Microgrid with Wind−Photovoltaic-Load-Storage in Multiple Scenarios
Haipeng Wang, Xuewei Wu, Kai Sun, Xiaodong Du, Yuling He, Kaiwen Li
May 24, 2023 (v1)
Subject: Optimization
Keywords: economic power dispatching, microgrid, multi-scenario, wind–photovoltaic-load storage
The optimal economic power dispatching of a microgrid is an important part of the new power system optimization, which is of great significance to reduce energy consumption and environmental pollution. The microgrid should not only meet the basic demand of power supply but also improve the economic benefit. Considering the generation cost, the discharge cost, the power purchase cost, the electricity sales revenue, the battery charging and discharging power constraints, and the charging and discharging time constraints, a joint optimization model for a multi-scenario microgrid with wind−photovoltaic-load storage is proposed in our study. Additionally, the corresponding model solving algorithm based on particle swarm optimization is also given. In addition, taking the Wangjiazhai project in Baiyangdian region as a case study, the effectiveness of the proposed model and algorithm is verified. The joint optimization model for a microgrid with wind−photovoltaic-load storage in multiple scen... [more]
Model-Based Performance Optimization of Thermal Management System of Proton Exchange Membrane Fuel Cell
Jiaming Zhang, Fuwu Yan, Changqing Du, Wenhao Li, Hongzhang Fang, Jun Shen
May 24, 2023 (v1)
Subject: Optimization
Keywords: nanofluid, PEMFC, radiator parameters, thermal management system
As a promising new power source, the proton exchange membrane fuel cell (PEMFC) has attracted extensive attention. The PEMFC engine produces a large amount of waste heat during operation. The excessive temperature will reduce the efficiency and lifespan of PEMFC engine and even cause irreversible damage if not taken away in time. The thermal management system of the PEMFC plays a critical role in efficiency optimization, longevity and operational safety. To solve the problem of high heat production in the operation of the PEMFC, two approaches are proposed to improve the heat dissipation performance of the radiators in thermal management systems. Three kinds of nanofluids with excellent electrical and thermal conductivity−Al2O3, SiO2 and ZnO− are employed as the cooling medium. The radiator parameters are optimized to improve the heat transfer capability. A typical 1D thermal management system and an isotropic 3D porous medium model replacing the wavy fin are constructed to reveal the... [more]
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