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Journal articles on the topic 'Computer Storage Optimization'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 September 2023

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1

Allen, Frances E., and Janet Fabri. "Automatic storage optimization." ACM SIGPLAN Notices 39, no. 4 (2004): 28–37. http://dx.doi.org/10.1145/989393.989398.

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Yolchuyev, Agil, and Janos Levendovszky. "Data Chunks Placement Optimization for Hybrid Storage Systems." Future Internet 13, no. 7 (2021): 181. http://dx.doi.org/10.3390/fi13070181.

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“Hybrid Cloud Storage” (HCS) is a widely adopted framework that combines the functionality of public and private cloud storage models to provide storage services. This kind of storage is especially ideal for organizations that seek to reduce the cost of their storage infrastructure with the use of “Public Cloud Storage” as a backend to on-premises primary storage. Despite the higher performance, the hybrid cloud has latency issues, related to the distance and bandwidth of the public storage, which may cause a significant drop in the performance of the storage systems during data transfer. This

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Hofmann, René, Sabrina Dusek, Stephan Gruber, and Gerwin Drexler-Schmid. "Design Optimization of a Hybrid Steam-PCM Thermal Energy Storage for Industrial Applications." Energies 12, no. 5 (2019): 898. http://dx.doi.org/10.3390/en12050898.

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The efficiency of industrial processes can be increased by balancing steam production and consumption with a Ruths steam storage system. The capacity of this storage type depends strongly on the volume; therefore, a hybrid storage concept was developed, which combines a Ruths steam storage with phase change material. The high storage capacity of phase change material can be very advantageous, but the low thermal conductivity of this material is a limiting factor. On the contrary, Ruths steam storages have fast reaction times, meaning that the hybrid storage concept should make use of the advan

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Gagliardi, Marco, and Cosimo Spera. "Optimization models for computer data storage design: An application." Computers & Industrial Engineering 26, no. 4 (1994): 743–56. http://dx.doi.org/10.1016/0360-8352(94)90009-4.

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5

Joisha, Pramod G., and Prithviraj Banerjee. "Static array storage optimization in MATLAB." ACM SIGPLAN Notices 38, no. 5 (2003): 258–68. http://dx.doi.org/10.1145/780822.781160.

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6

Melikov, A. Z., and A. A. Molchanov. "Stock optimization in transportation/storage systems." Cybernetics and Systems Analysis 28, no. 3 (1992): 484–87. http://dx.doi.org/10.1007/bf01125431.

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Kim, Younghyun. "Computer-Aided Design and Optimization of Hybrid Energy Storage Systems." Foundations and Trends® in Electronic Design Automation 7, no. 4 (2013): 247–338. http://dx.doi.org/10.1561/1000000035.

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8

Engelfriet, Joost, and Willem de Jong. "Attribute storage optimization by stacks." Acta Informatica 27, no. 6 (1990): 567–81. http://dx.doi.org/10.1007/bf00277390.

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Jiang, L., and C. W. Wu. "Topology optimization of energy storage flywheel." Structural and Multidisciplinary Optimization 55, no. 5 (2016): 1917–25. http://dx.doi.org/10.1007/s00158-016-1576-1.

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Wang, Xun, and Jie Rong. "The Computer Network Optimization Model Based on Neural Network Algorithm Research." Advanced Materials Research 798-799 (September 2013): 545–48. http://dx.doi.org/10.4028/www.scientific.net/amr.798-799.545.

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The speed of development of the computer network is an urgent need to comprehensively improve and optimize the overall performance of the network. Neural network algorithm has a massively parallel processing and distributed information storage, Hopfield neural network showed a unique advantage in the associative memory and optimization based on the neural network algorithm for computer network optimization model of Hopfield neural network theory and reality computer network, modern optimization methods, it is combined.

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Jia, Heping, Rui Peng, Yi Ding, and Changzheng Shao. "Reliability analysis of distributed storage systems considering data loss and theft." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 234, no. 2 (2019): 303–21. http://dx.doi.org/10.1177/1748006x19885508.

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With the advancement of cloud computing and internet of things, data are usually stored on distributed computers and these data may risk being lost or stolen. In this article, we consider a common case where the entirety of the data is partitioned into several parts and each data part can be allocated to one or more computers. In the case where a computer fails, all the data parts on it are lost. Before the failure of any computer, the data parts may also be stolen by hackers. The basic model of computer failure and computer intrusion resulting in the theft of all the data parts on the compute

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Wunarso, Novita Belinda, Andrias Rusli, Michelle Angelica, and Arabella Margaret Salim. "Implementasi Distributed File Server pada Apache Web Server." Jurnal ULTIMA InfoSys 4, no. 2 (2013): 84–88. http://dx.doi.org/10.31937/si.v4i2.245.

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In this research, a Distributed File Server (DFS) is developed to manage the need of a large storage space in the server, especially when the multimedia files are saved permanently in the web server. In the development, Apache Web Server is used with 1 computer as the main server, 2 computers as file servers, and 1 computer as the client who sends request. The result from the implementation of the DFS is the usage of main server’s storage space can be reduced by 99,77% from the full usage condition, causing an optimization in the web server. Another parameter is also being tested by the implem

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Shang-Cai Chi, Shang-Cai Chi, and Ya-Ping Li Shang-Cai Chi. "Research on Optimization Strategy of Stacker Scheduling in Intelligent Storage System Based on Intelligent Improved Algorithm." 電腦學刊 33, no. 6 (2022): 143–54. http://dx.doi.org/10.53106/199115992022123306012.

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<p>With the vigorous development of e-commerce, higher requirements are put forward for the storage capacity and operation efficiency of the warehousing system to ensure the performance of the entire supply chain in the business process. The factors that affect the operation efficiency and storage capacity of the warehousing system mainly include: storage space planning, shelf design, goods access strategy, stacker scheduling strategy, goods picking efficiency, etc. The main research object of this paper is the optimization of the scheduling strategy of the stacker in the storage system,

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Jiang, L., W. Zhang, G. J. Ma, and C. W. Wu. "Shape optimization of energy storage flywheel rotor." Structural and Multidisciplinary Optimization 55, no. 2 (2016): 739–50. http://dx.doi.org/10.1007/s00158-016-1516-0.

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15

Thies, William, Frédéric Vivien, Jeffrey Sheldon, and Saman Amarasinghe. "A unified framework for schedule and storage optimization." ACM SIGPLAN Notices 36, no. 5 (2001): 232–42. http://dx.doi.org/10.1145/381694.378852.

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Tabatabaei, Seyed-Kourosh, Omid Fatahi Valilai, Ali Abedian, and Mohammad Khalilzadeh. "A novel framework for storage assignment optimization inspired by finite element method." PeerJ Computer Science 7 (February 16, 2021): e378. http://dx.doi.org/10.7717/peerj-cs.378.

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Considering necessary fundamental and structural changes in the production and manufacturing industries to fulfill the industry 4.0 paradigm, the proposal of new ideas and frameworks for operations management of production and manufacturing system is inevitable. This research focuses on traditional methods proposed for storage assignment problem and struggles for new methods and definitions for industry 4.0 based storage assignment concepts. At the first step, the paper proposes a new definition of storage assignment and layout problem for fulfilling storage mechanism agility in terms of autom

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Ren XunYi, and Ma XiaoDong. "A* Algorithm Based Optimization for Cloud Storage." International Journal of Digital Content Technology and its Applications 4, no. 8 (2010): 203–8. http://dx.doi.org/10.4156/jdcta.vol4.issue8.23.

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Liu, Jicheng, Fangqiu Xu, Shuaishuai Lin, Hua Cai, and Suli Yan. "A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization." Energies 11, no. 12 (2018): 3286. http://dx.doi.org/10.3390/en11123286.

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The optimal operation of microgrids is a comprehensive and complex energy utilization and management problem. In order to guarantee the efficient and economic operation of microgrids, a three-layer multi-agent system including distributed management system agent, microgrid central control agent and microgrid control element agent is proposed considering energy storage units and demand response. Then, based on this multi-agent system and with the objective of cost minimization, an operation optimization model for microgrids is constructed from three aspects: operation cost, environmental impact

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Jane, Parker, Vaucher, and Berman. "Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and Design." Energies 13, no. 3 (2020): 577. http://dx.doi.org/10.3390/en13030577.

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A microgrid consists of electrical generation sources, energy storage assets, loads, and the ability to function independently, or connect and share power with other electrical grids. Thefocus of this work is on the behavior of a microgrid, with both diesel generator and photovoltaic resources, whose heating or cooling loads are influenced by local meteorological conditions. Themicrogrid's fuel consumption and energy storage requirement were then examined as a function of the atmospheric conditions used by its energy management strategy (EMS). A fuel-optimal EMS, able to exploit meteorological

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Chen, Si, and Gang Zhao. "High-Performance Server-Based Live Streaming Transmission Optimization for Sports Events in Smart Cities." Mobile Information Systems 2021 (April 9, 2021): 1–7. http://dx.doi.org/10.1155/2021/9958703.

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Smart cities allow cities to run more efficiently and have been approved by a lot of cities. During the process of building smart cities, a large amount of data is generated. Particularly, live sports events have been regarded as the inalienable part of smart cities. However, with the improvement in the quality of life, people tend to obtain better watching experience in terms of sports events. For such purpose, this paper proposes the live streaming transmission optimization method based on high-performance server, called HPTO, including two main modules, that is, high-performance server opti

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Li, Qi, and Xiao Hong Cheng. "Warehouse Information Intelligent Optimization System." Advanced Materials Research 791-793 (September 2013): 1597–600. http://dx.doi.org/10.4028/www.scientific.net/amr.791-793.1597.

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Scientific and rational management of warehouses and warehouse information to build flexible and effective business development is an important factor. The use of modern computer technology advanced and mature, network communication technology, software development, technical and scientific analysis and design methods, modern scientific management ideas and methods of storage of organic integration into the system, to achieve in all types of enterprise management system procedures, system security electronics.

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Yun, Pingping, Yongfeng Ren, and Yu Xue. "Energy-Storage Optimization Strategy for Reducing Wind Power Fluctuation via Markov Prediction and PSO Method." Energies 11, no. 12 (2018): 3393. http://dx.doi.org/10.3390/en11123393.

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Wind power penetration ratios of power grids have increased in recent years; thus, deteriorating power grid stability caused by wind power fluctuation has caused widespread concern. At present, configuring an energy storage system with corresponding capacity at the grid connection point of a large-scale wind farm is an effective solution that improves wind power dispatchability, suppresses potential fluctuations, and reduces power grid operation risks. Based on the traditional energy-storage battery dispatching scheme, in this study, a multi-objective hybrid optimization model for joint wind-f

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23

ZHU, Xiao-qian, Chao SUN, Xiang-fei MENG, Bao ZHANG, and Jing-hua FENG. "Storage performance analysis and optimization of NENO system on TH-1A computer." Journal of Computer Applications 32, no. 5 (2013): 1411–14. http://dx.doi.org/10.3724/sp.j.1087.2012.01411.

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24

Yuan, Ruiping, Juntao Li, Wei Wang, Jiangtao Dou, and Luke Pan. "Storage Assignment Optimization in Robotic Mobile Fulfillment Systems." Complexity 2021 (November 25, 2021): 1–11. http://dx.doi.org/10.1155/2021/4679739.

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Robotic mobile fulfillment system (RMFS) is a new type of parts-to-picker order picking system, where robots carry inventory pods to stationary pickers. Because of the difference in working mode, traditional storage assignment methods are not suitable for this new kind of picking system. This paper studies the storage assignment optimization of RMFS, which is divided into products assignment stage and pods assignment stage. In the products assignment stage, a mathematical model maximizing the total correlation of products in the same pods is established to reduce the times of pod visits, and a

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25

Zhang, Jingyu, Siqi Zhong, Jin Wang, Xiaofeng Yu, and Osama Alfarraj. "A Storage Optimization Scheme for Blockchain Transaction Databases." Computer Systems Science and Engineering 36, no. 3 (2021): 521–35. http://dx.doi.org/10.32604/csse.2021.014530.

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26

Baron, Carlo, Ameena S. Al-Sumaiti, and Sergio Rivera. "Impact of Energy Storage Useful Life on Intelligent Microgrid Scheduling." Energies 13, no. 4 (2020): 957. http://dx.doi.org/10.3390/en13040957.

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Planning the operation scheduling with optimization heuristic algorithms allows microgrids to have a convenient tool. The developments done in this study attain this scheduling taking into account the impact of energy storage useful life in the microgrid operation. The scheduling solutions, proposed for the answer of an optimization problem, are obtained by using a metaheuristic algorithm called Differential Evolutionary Particle Swarm Optimization (DEEPSO). Thanks to the optimization that is conducted in this study, it is possible to formulate dispatches of the existent microgrid (MG) by alwa

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Chen, Biaosong, Gang Liu, Jian Kang, and Yunpeng Li. "Design optimization of stiffened storage tank for spacecraft." Structural and Multidisciplinary Optimization 36, no. 1 (2007): 83–92. http://dx.doi.org/10.1007/s00158-007-0174-7.

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28

He, Hai, Feixiang Peng, Zhengnan Gao, et al. "A Multi-Objective Risk Scheduling Model of an Electrical Power System-Containing Wind Power Station with Wind and Energy Storage Integration." Energies 12, no. 11 (2019): 2153. http://dx.doi.org/10.3390/en12112153.

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The integrated operation of wind storage is a developmental trend for future wind power stations. Compared with energy storage and wind power system scheduling, the utilization ratio of wind power is improved. This paper analyzes the power system scheduling risks that are brought about by wind power stations with wind and energy storage integration and puts forward the corresponding risks indexes, which are based on the physical structure and the long-operation features of the battery energy storage system. This paper also proposes the multi-objective optimization scheduling model, considering

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Sivan-Zimet, Miriam, and Tara M. Madhyastha. "Workload based optimization of probe-based storage." ACM SIGMETRICS Performance Evaluation Review 30, no. 1 (2002): 256–57. http://dx.doi.org/10.1145/511399.511368.

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Yahya Soltani, Nasim, and Adel Nasiri. "Chance-Constrained Optimization of Energy Storage Capacity for Microgrids." IEEE Transactions on Smart Grid 11, no. 4 (2020): 2760–70. http://dx.doi.org/10.1109/tsg.2020.2966620.

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31

Zhu, Hong. "The Optimization Function of Computer Image Technology in Processing Oil Painting Creation." Wireless Communications and Mobile Computing 2022 (March 10, 2022): 1–6. http://dx.doi.org/10.1155/2022/3188527.

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In terms of processing methods, machine learning mainly takes the network as the core and uses the network as a medium to provide services such as computing and delivery. The “cloud” is mainly composed of computers and servers, and the Internet is used to provide network services. With the continuous progress and development of computer technology, digital image processing technology based on machine learning is widely used in production and life. Machine learning uses its own storage and computing capabilities to make the development space of image processing technology broader and effectivel

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Liu, Xiyang, Lei Fan, Liming Wang, and Sha Meng. "Multiobjective Reliable Cloud Storage with Its Particle Swarm Optimization Algorithm." Mathematical Problems in Engineering 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/9529526.

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Information abounds in all fields of the real life, which is often recorded as digital data in computer systems and treated as a kind of increasingly important resource. Its increasing volume growth causes great difficulties in both storage and analysis. The massive data storage in cloud environments has significant impacts on the quality of service (QoS) of the systems, which is becoming an increasingly challenging problem. In this paper, we propose a multiobjective optimization model for the reliable data storage in clouds through considering both cost and reliability of the storage service

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Chowdhury, Nayeem, Fabrizio Pilo, and Giuditta Pisano. "Optimal Energy Storage System Positioning and Sizing with Robust Optimization." Energies 13, no. 3 (2020): 512. http://dx.doi.org/10.3390/en13030512.

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Energy storage systems can improve the uncertainty and variability related to renewable energy sources such as wind and solar create in power systems. Aside from applications such as frequency regulation, time-based arbitrage, or the provision of the reserve, where the placement of storage devices is not particularly significant, distributed storage could also be used to improve congestions in the distribution networks. In such cases, the optimal placement of this distributed storage is vital for making a cost-effective investment. Furthermore, the now reached massive spread of distributed ren

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Yang, Yang, Chong Lian, Chao Ma, and Yusheng Zhang. "Research on Energy Storage Optimization for Large-Scale PV Power Stations under Given Long-Distance Delivery Mode." Energies 13, no. 1 (2019): 27. http://dx.doi.org/10.3390/en13010027.

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Western China has good conditions for constructing large-scale photovoltaic (PV) power stations; however, such power plants with large fluctuations and strong randomness suffer from the long-distance power transmission problem, which needs to be solved. For large-scale PV power stations that do not have the conditions for simultaneous hydropower and PV power, this study examined long-distance delivery mode and energy storage optimization. The objective was to realize the long-distance transmission of electrical energy and maximize the economic value of the energy storage and PV power storage.

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Pajot, Camille, Nils Artiges, Benoit Delinchant, Simon Rouchier, Frédéric Wurtz, and Yves Maréchal. "An Approach to Study District Thermal Flexibility Using Generative Modeling from Existing Data." Energies 12, no. 19 (2019): 3632. http://dx.doi.org/10.3390/en12193632.

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Energy planning at the neighborhood level is a major development axis for the energy transition. This scale allows the pooling of production and storage equipment, as well as new possibilities for demand-side management such as flexibility. To manage this growing complexity, one needs two tools. The first concerns modeling, allowing exhaustive simulation analyses of buildings and their energy systems. The second concerns optimization, making it possible to decide on the sizing or control of energy systems. In this article, we analyze, in the case of an existing residential neighborhood, the ab

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Sun, Bo, Simin Li, Jingdong Xie, and Xin Sun. "IGDT-Based Wind–Storage–EVs Hybrid System Robust Optimization Scheduling Model." Energies 12, no. 20 (2019): 3848. http://dx.doi.org/10.3390/en12203848.

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Wind power has features of uncertainty. When wind power producers (WPPs) bid in the day-ahead electricity market, how to deal with the deviation between forecasting output and actual output is one of the important topics in the design of electricity market with WPPs. This paper makes use of a non-probabilistic approach—Information gap decision theory (IGDT)—to model the uncertainty of wind power, and builds a robust optimization scheduling model for wind–storage–electric vehicles(EVs) hybrid system with EV participations, which can make the scheduling plan meet the requirements within the rang

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Li, Li. "Intelligent Data Processing and Optimization of University Logistics Combined with Block Chain Storage Algorithm." Advances in Multimedia 2022 (July 18, 2022): 1–10. http://dx.doi.org/10.1155/2022/4141552.

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The traditional Hadoop-based logistic data processing platform of universities cannot fully collect and control remote data in the process of data processing and has defects such as poor efficiency, high error, and difficult query. In existing designs, devices often need to store complete block data. When retrieving or verifying specific data on the chain, a large number of blocks need to be traversed to find the corresponding data, which reduces the response speed on the user side. In addition, the traditional consensus algorithm is not suitable for resource-constrained terminal devices. Ther

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38

Chen, Haitian, Yan Zhao, Yanwei Ji, Shunjiang Wang, Weichun Ge, and Anlong Su. "Optimization Location Selection Analysis of Energy Storage Unit in Energy Internet System Based on Tabu Search." International Journal of Software Engineering and Knowledge Engineering 29, no. 07 (2019): 941–54. http://dx.doi.org/10.1142/s0218194019400072.

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Energy Internet has become the theme of the new round of industrial revolution. Energy storage, as a key technical support for the development of energy Internet, has always been of concern to numerous people, since the energy Internet consists of various energy networks that can provide energy support for different energy subnetworks. Therefore, the energy storage unit is in a crucial position in the entire energy network. This paper points out the importance of various energy storage technologies in the energy Internet. An energy storage unit location analysis method based on Tabu search alg

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39

Kluba, Anna, and Robert Field. "Optimization and Exergy Analysis of Nuclear Heat Storage and Recovery." Energies 12, no. 21 (2019): 4205. http://dx.doi.org/10.3390/en12214205.

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The APR1400 Nuclear Heat Storage and Recovery (NHS&R) System described here represents the conceptual design and interface of a tertiary cycle with the secondary system of the Korean nuclear reactor plant APR1400. The system is intended to reliably and efficiently store and recover thermal energy from a Nuclear Power Plant (NPP) steam system in order to allow flexible power generation using an economical and scalable design. The research incorporates a comprehensive performance analysis of three interface configurations with comparisons based on the 1st and 2nd Laws of Thermodynamics. The

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Gallo, Daniele, Carmine Landi, Mario Luiso, and Rosario Morello. "Optimization of Experimental Model Parameter Identification for Energy Storage Systems." Energies 6, no. 9 (2013): 4572–90. http://dx.doi.org/10.3390/en6094572.

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Abdulgalil, Mohammed Atta, Muhammad Khalid, and Fahad Alismail. "Optimal Sizing of Battery Energy Storage for a Grid-Connected Microgrid Subjected to Wind Uncertainties." Energies 12, no. 12 (2019): 2412. http://dx.doi.org/10.3390/en12122412.

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In this paper, based on stochastic optimization methods, a technique for optimal sizing of battery energy storage systems (BESSs) under wind uncertainties is provided. Due to considerably greater penetration of renewable energy sources, BESSs are becoming vital elements in microgrids. Integrating renewable energy sources in a power system together with a BESS enhances the efficiency of the power system by enhancing its accessibility and decreasing its operating and maintenance costs. Furthermore, the microgrid-connected BESS should be optimally sized to provide the required energy and minimize

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42

Pons, Michel. "Exergy Analysis and Process Optimization with Variable Environment Temperature." Energies 12, no. 24 (2019): 4655. http://dx.doi.org/10.3390/en12244655.

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In its usual definition, exergy cancels out at the ambient temperature which is thus taken both as a constant and as a reference. When the fluctuations of the ambient temperature, obviously real, are considered, the temperature where exergy cancels out can be equated, either to the current ambient temperature (thus variable), or to a constant reference temperature. Thermodynamic consequences of both approaches are mathematically derived. Only the second approach insures that minimizing the exergy loss maximizes performance in terms of energy. Moreover, it extends the notion of reversibility to

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Jingyan Zeng, Zhenji Zhang, Xiaolan Guan, and Ruize Gao. "An Optimization of Storage Yard Planning in Whampoa Terminal." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 5, no. 4 (2013): 580–86. http://dx.doi.org/10.4156/aiss.vol5.issue4.71.

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Liu, Jing, Yu Chi Zhao, Xiao Hua Shi, and Su Juan Liu. "The Application of Neural Network in Computer Control." Applied Mechanics and Materials 380-384 (August 2013): 421–24. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.421.

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In recent years, it is a very active direction of research to use neural network to control computer. Neural network is a burgeoning crossing subject, and the way it processes information is different from the past symbolic logic system, which has some unique properties: such as the distributed storage and parallel processing of information, the unity of the information storage and information processing, and have the ability of self-organizing and self-learning. And it has been applied widespread in pattern recognition, signal processing, knowledge process, expert system, optimization, intell

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Indana Zulfa, Mulki, Rudy Hartanto, Adhistya Erna Permanasari, and Waleed Ali. "GenACO a multi-objective cached data offloading optimization based on genetic algorithm and ant colony optimization." PeerJ Computer Science 7 (September 28, 2021): e729. http://dx.doi.org/10.7717/peerj-cs.729.

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Background Data exchange and management have been observed to be improving with the rapid growth of 5G technology, edge computing, and the Internet of Things (IoT). Moreover, edge computing is expected to quickly serve extensive and massive data requests despite its limited storage capacity. Such a situation needs data caching and offloading capabilities for proper distribution to users. These capabilities also need to be optimized due to the experience constraints, such as data priority determination, limited storage, and execution time. Methods We proposed a novel framework called Genetic an

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46

Wu, Shasha, Cheng Chi, Wei Wang, and Yaohua Wu. "Research of the layout optimization in robotic mobile fulfillment systems." International Journal of Advanced Robotic Systems 17, no. 6 (2020): 172988142097854. http://dx.doi.org/10.1177/1729881420978543.

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To improve the order fulfillment throughput and space utilization in the robotic mobile fulfillment system (RMFS), the research developed two design aspects: the layout design and the warehouse structural parameter configuration. Based on the semiopen queue network theory, we built the queue network model to estimate the performance of RMFS. A scheme was proposed to move the picking stations inside the storage area, and seven layout scenes were designed according to the location arrangement of stations and storage area. The performance estimation and parameter configuration platform were devel

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Liu, Jiajun, Huachao Dong, Tianxu Jin, Li Liu, Babak Manouchehrinia, and Zuomin Dong. "Optimization of Hybrid Energy Storage Systems for Vehicles with Dynamic On-Off Power Loads Using a Nested Formulation." Energies 11, no. 10 (2018): 2699. http://dx.doi.org/10.3390/en11102699.

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In this paper, identification of an appropriate hybrid energy storage system (HESS) architecture, introduction of a comprehensive and accurate HESS model, as well as HESS design optimization using a nested, dual-level optimization formulation and suitable optimization algorithms for both levels of searches have been presented. At the bottom level, design optimization focuses on the minimization of power loss in batteries, converter, and ultracapacitors (UCs), as well as the impact of battery depth of discharge (DOD) to its operation life, using a dynamic programming (DP)-based optimal energy m

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Urbanucci, Luca, Francesco D’Ettorre, and Daniele Testi. "A Comprehensive Methodology for the Integrated Optimal Sizing and Operation of Cogeneration Systems with Thermal Energy Storage." Energies 12, no. 5 (2019): 875. http://dx.doi.org/10.3390/en12050875.

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Cogeneration systems are widely acknowledged as a viable solution to reduce energy consumption and costs, and CO2 emissions. Nonetheless, their performance is highly dependent on their capacity and operational strategy, and optimization methods are required to fully exploit their potential. Among the available technical possibilities to maximize their performance, the integration of thermal energy storage is recognized as one of the most effective solutions. The introduction of a storage device further complicates the identification of the optimal equipment capacity and operation. This work pr

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Liu, Jun. "Storage-Optimization Method for Massive Small Files of Agricultural Resources Based on Hadoop." Journal of Advanced Computational Intelligence and Intelligent Informatics 23, no. 4 (2019): 634–40. http://dx.doi.org/10.20965/jaciii.2019.p0634.

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The main function of Hadoop is the storage and processing of big data, especially the processing of large datasets. However, in practice, there are numerous small files, and Hadoop has many flaws when dealing with these small files. A storage-optimization method for numerous agricultural resource small files based on Hadoop is proposed, using the precursor and subsequent relationship between different small files of agricultural resources to merge small files. By accessing small files and performing metadata caching through an index mechanism, as well as the prefetching mechanism of associated

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50

Wu, Yiwei, Hongyu Zhang, Shuaian Wang, and Lu Zhen. "Mathematical Optimization of Carbon Storage and Transport Problem for Carbon Capture, Use, and Storage Chain." Mathematics 11, no. 12 (2023): 2765. http://dx.doi.org/10.3390/math11122765.

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The greenhouse effect caused by carbon dioxide (CO2) emissions has forced the shipping industry to actively reduce the amount of CO2 emissions emitted directly into the atmosphere over the past few years. Carbon capture, utilization, and storage (CCUS) is one of the main technological methods for reducing the amount of CO2 emissions emitted directly into the atmosphere. CO2 transport, i.e., shipping CO2 to permanent or temporary storage sites, is a critical intermediate step in the CCUS chain. This study formulates a mixed-integer programming model for a carbon storage and transport problem in

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