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Oilfield sustainability and management:An optimization model for the reconstruction of oil and gas gathering systems based on potential location mining

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Petroleum Science 2025年第2期22卷 935-955页

作者： Jie Chen Wei Wang Wen-Yuan Sun Dong Li Yu-Bo Jiao National Engineering Laboratory for Pipeline Safety/MOE Key Laboratory of Petroleum Engineering China University of Petroleum (Beijing)

The carbon emissions and cost during the construction phase are significant contributors to the oilfield *** oilfields enter the late stage,the adaptability of facilities *** achieve sustainable development,oilfield reconstruction was usually conducted in discrete rather than continuous *** by economic and sustainability goals,a 3-phase heuristic model for oilfield reconstruction was developed to mine potential locations in continuous *** phase 1,considering the process characteristics of the oil and gas gathering system,potential locations were mined in continuous *** phase 2,incorporating comprehensive reconstruction measures,a reconstruction model was established in discrete *** phase 3,the topology was further adjusted in continuous ***,the model was transformed into a single-objective mixed integer linear programming model using the augmented ε-constraint *** experiments revealed that the small number of potential locations could effectively reduce the reconstruction cost,and the quality of potential locations mined in phase 1 surpassed those generated in random or grid *** studies showed that cost and carbon emissions for a new block were reduced by up to 10.45% and 7.21 %,*** reductions were because the potential locations mined in 1P reduced the number of metering stations,and 3P adjusted the locations of metering stations in continuous space to shorten the pipeline *** an old oilfield,the load and connection ratios of the old metering station increased to 89.7% and 94.9%,respectively,enhancing operation ***,recycling facilitated the diversification of reconstruction measures and yielded a profit of 582,573 ￥,constituting 5.56% of the total *** study adopted comprehensive reconstruction measures and tapped into potential reductions in cost and carbon emissions for oilfield reconstruction,offering valuable insights for future oilfield de

关键词： Oilfield reconstruction Sustainable development optimization model Potential location 3-phase heuristic model

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A stomatal optimization model integrating leaf stomata-photosynthetic capacity regulation in response to soil water stress

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AGRICULTURAL WATER MANAGEMENT 2025年 308卷

作者： Liu, Yong Hu, Tiesong Zhu, Rui Chen, Qiuwen Zeng, Xiang Jing, Peiran Huang, Yifan Wuhan Univ State Key Lab Water Resources Engn & Management Wuhan 430072 Peoples R China Nanjing Hydraul Res Inst Natl Key Lab Water Disaster Prevent Nanjing 210098 Peoples R China Minist Water Resources Pearl River Water Resources Commiss Pearl River Water Resources Res Inst Guangzhou 510611 Peoples R China Wuhan Univ Sch Resource & Environm Sci Wuhan 430079 Peoples R China Sun Yat Sen Univ Sch Civil Engn Guangzhou 510275 Peoples R China

Leaf stomatal regulation of water-carbon exchange processes plays a crucial role in the water-carbon cycle. Uncovering the response mechanism of leaf gas exchange to soil water stress is challenging due to the complex effects of both the stomatal regulation ( i.e. , stomatal conductance, g s ) and non-stomatal regulation ( i.e. , photosynthetic carboxylation capacity, V-cmax25). Different from previous studies that achieved stomatal and nonstomatal regulation in stomatal optimization models by linearly simplifying or independently optimizing V-cmax25 , this study hypothesizes that V-cmax25 and g(s) are co-regulated by balancing intercellular CO2 concentration (C-i). By adjusting stomatal opening to minimize water-carbon cost, a stomatal optimization model (SRSC model) that integrates the synergistic regulation of gs and V-cmax25 was developed. Experimental and numerical results show that the SRSC model accurately reproduces the stomatal response to environmental changes, especially for the low soil water potential conditions ( Psi(soil) <-2 MPa) compared to the previous models, which increased the R-2 of g(s) , photosynthetic rate (A(n)), and Ci reaching 2.56 %, 1.97 %, and 9.04 %, respectively. Additionally, the SRSC model reasonably predicted a coordinated decline in g(s) and V-cmax25 and concurrently mitigated the classical models that simulate gs and leaf water potential responses deviating from the actual values under drought conditions. More importantly, the SRSC model revealed that experiencing drought and flooding stresses in rice improved intrinsic water use efficiency by increasing photosynthetic capacity. This study refines the application of the stomatal optimization model and enhances the mechanistic understanding of the stomatal optimization model to a certain extent.

关键词： optimization model Stomatal conductance Photosynthetic carboxylation capacity Drought Water use efficiency

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Improving the healthcare user experience: an optimization model grounded in patient-centredness

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BMC HEALTH SERVICES RESEARCH 2025年第1期25卷 1-11页

作者： Peruzzo, Elisa Seghieri, Chiara Vainieri, Milena De Rosis, Sabina St Anna Sch Adv Studies Inst Management Management & Healthcare Lab Pisa Italy

BackgroundPatient satisfaction and experience are key outcomes of healthcare and can be computed as powerful measures of service quality. Understand what affects them is essential for service quality improvement. Investigating whether the care setting (i.e., medical or surgical) can impact the patients' perception of the quality can be also important for the actionability of this data. The aim is to explore which experiential factors should be prioritized to improve patient satisfaction with hospitalization service, using experience items as intermediate results and considering different ***-reported experience measures are used in an Italian region. This study uses the optimization approach to identify factors of healthcare user experience affecting and enhancing *** results confirm that, among the significant determinants of satisfaction, some specific experiential aspects emerged as the potential primary focus to be prioritized in improvement actions. These aspects vary according to the specific departmental *** study presents an optimization model directly informed by healthcare service users, utilizing their insights to drive healthcare delivery improvements. It emphasizes the necessity of not only collect patient perspectives but also applying different methodologies to understand what matters to patients and what interventions could be prioritized, and to strategically use diverse insights to enhance the delivery of healthcare services and patient experience and satisfaction.

关键词： Patient satisfaction Patient experience Hospitalization optimization model Healthcare service User-centricity Quality improvement

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Thermal management of electric vehicle power cabin based on fast zero-dimensional integrating accurate three-dimensional optimization model

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APPLIED ENERGY 2025年 378卷

作者： Li, Peimiao Wang, Shibo Wang, Hui Feng, Yun Li, Hongliang Xiao, Heye Xi An Jiao Tong Univ Sch Energy & Power Engn MOE Key Lab Thermofluid Sci & Engn Xian 710049 Shaanxi Peoples R China Northwestern Polytech Univ Sch Aeronaut Xian 710072 Shaanxi Peoples R China COMAC Beijing Aircraft Technol Res Inst Beijing 102211 Peoples R China Northwestern Polytech Univ Unmanned Syst Res Inst Xian 710072 Shaanxi Peoples R China

The heat dissipation scheme design of power cabin is limited by complex configuration and slow iteration speed. Given the considerable time and computing resources required by numerical experiment, this work proposes a fast zero dimensional integrating accurate three-dimensional optimization model to calculate the heat dissipation and optimize the thermal management in electric vehicle power cabin. Based on the existing thermal equivalent circuit model, the heat capacity and thermal resistance network among each equipment is established in fast zero-dimensional model, and the output of fast zero-dimensional model is corrected by referring to the accurate initial three-dimensional simulation results. Then, the optimal heat dissipation configuration is searched by zero- dimensional model and validated by experimental data. Results show that the optimization result of fast zero dimensional integrating accurate three-dimensional optimization model is well verified by three-dimensional model. The chip temperature of the power cabin motor controller can be reduced from 551.73 K to 352.31 K after optimizing the number and size of the pin-fins of the motor controller using the proposed model. The time consumption of fast zero dimensional integrating accurate three-dimensional optimization model is 72.0872 h, while the time consumption of three-dimensional model is about 576 h with 224 cores of computer. The proposed model can be used to achieve the purpose of rapidly predicting the temperature change of the complex vehicle design, and provide theoretical reference for the reasonable formulation of the heat dissipation scheme.

关键词： Thermal management Electric vehicle Power cabin Zero and three dimensional integrating optimization model

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Cost and energy synergy optimization model for ironmaking processes: Hybrid knowledge and data driven

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JOURNAL OF CLEANER PRODUCTION 2025年 486卷

作者： Wang, Jiabao Zhang, Jianliang Wang, Yaozu Liu, Zhengjian Sun, Qingke Song, Xiaoran Li, Zhen Univ Sci & Technol Beijing Sch Met & Ecol Engn Dept Phys Chem 30th Xueyuan Rd Beijing 100083 Peoples R China Univ Sci & Technol Beijing Sch Intelligence Sci & Technol 30th Xueyuan Rd Beijing 100083 Peoples R China Univ Sci & Technol Beijing Inst Artificial Intelligence 30th Xueyuan Rd Beijing 100083 Peoples R China

Traditional ironmaking process optimization models mostly focus on the compositional properties of the product as constraints in order to optimize the material structure of the ironmaking process, and have not yet considered the influence of nonlinear quality factors on the dosage optimization scheme. In this paper, an integrated model coupling sinter ore quality performance to cost and energy co-optimization of the ironmaking process is proposed. A mathematical model for the whole-process batching of sinter and blast furnace was established by considering the material and energy flows, and a sinter ore quality prediction model was developed based on a data-based approach. With the lowest cost and energy consumption as the optimization objective, an improved genetic algorithm was used to solve the model and find the group of batching schemes that meet the conventional performance and quality indexes. At the same time to meet the conditions of the optimization scheme of a number of indicators for a comprehensive evaluation, to give to meet the requirements of the optimal program *** the optimization of the test, the cost and energy consumption per ton of iron of the optimal solution are reduced by 5.373 & YEN;/t and 2.129 kgce/t, respectively. Future optimization of the proportion of raw materials for ironmaking, taking into account quality factors, is an important step in the development of lowcarbon and low-cost, especially in the optimization of blast furnace production in the "black box" state.

关键词： Ironmaking optimization model Smart metallurgy Energy consumption and carbon reduction Integration of knowledge and data

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Comprehensive performance optimization of aero-engine accessory system: A multi-objective analysis based on a thermal management optimization model

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APPLIED THERMAL ENGINEERING 2025年 267卷

作者： Lin, Dengke Lian, Wenlei Wan, Hao Wu, Zhiwei Nanjing Univ Aeronaut & Astronaut Coll Energy & Power Engn Nanjing Peoples R China Minist Ind & Informat Technol Key Lab Thermal management & Energy Utilizat Aviat Beijing Peoples R China

Gradual overheating of the engine accessories occurs as the speed of the aircraft increases. In order to establish an efficient accessory thermal management system (TMS), this paper carries out a comprehensive integrated study of the cabin's thermal environment, accessory thermal protection and accessory system thermal management based on five typical accessories in the cabin of a specific high-speed turbine engine. This study is based on an experimentally validated numerical method for simulating the cabin thermal environment. Firstly, the study investigates the thermal characteristics of the cabin, heat load distribution among the accessories, and the underlying causes of accessory over-temperature. The findings reveal that the thermal protection requirements for the five accessories vary according to their heat source sizes. Specifically, accessories with larger heat sources require cooling via lubricating oil, while smaller heat source accessories can benefit from the addition of aerogel to further lower surface temperatures. For accessories with high thermal loads, the integration of RAF-89 wing fins in the flow path can save up to 69.2% of the minimum lubricating oil flow required for cooling. Additionally, various flow path layouts for the accessories were designed and evaluated through a thermal protection evaluation model to determine the optimal combinations of protection strategies, the corresponding temperatures of accessories 1 to 5 are 335.0 K, 340.7 K, 361.1 K, 393.3 K, and 399.8 K, respectively, which meet the requirement that the accessory temperatures do not exceed 400 K. Lastly, a thermal management optimization model is developed, incorporating multiple performance indexes, including liquid nitrogen demand, cooling capacity utilization, cost of TMS, fuel compensation losses, and energy utilization efficiency. The model is applied to optimize the initial TMS, resulting in a 10 % improvement in overall system performance.

关键词： Comprehensive integrated study Cabin's thermal environment Accessory thermal protection Accessory system thermal management optimization model

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Development and application of an optimization model to evaluate future charging demand for long-haul electric vehicles in Ontario, Canada

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JOURNAL OF TRANSPORT GEOGRAPHY 2025年 122卷

作者： Dimatulac, Terence Maoh, Hanna Carriveau, Rupp Univ Windsor Cross Border Inst Civil & Environm Engn Dept 401 Sunset Ave Windsor ON N9B 3P4 Canada

Establishing a charging network is critical to support vehicle electrification. Determining the ideal locations of charging stations can be challenging due to conflicting stakeholder constraints. This study aims to identify the optimal number of on-route charging locations that can support the projected maximum charging demand of long-haul electric vehicles (LHEVs) in the Canadian province of Ontario in the year 2040. A flow-based path- segment coverage model is proposed, which considers the time when each charging event at each candidate location is likely to occur. The impact of charging LHEVs on the grid is also evaluated. Based on projected 2040 LHEV adoption, results suggest that almost 90 % of the trips will be completed without the need to recharge. However, at least 82 fast charging station locations must be established throughout Ontario to support the remaining LHEV trips within the province. Moreover, almost 75 % of these trips are dependent primarily on 18 of these locations. In general, more than 46 GW of electricity per day is expected to be used when LHEVs have been adopted on a much larger scale in Ontario. Specifically, the Greater Toronto Area (GTA) is likely to experience approximately 4.86 GW of additional energy from LHEV charging activities during peak hours.

关键词： optimization model Charging station location problem Long-haul electric vehicle Heavy-duty charging locations Electricity demand Ontario, Canada

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Self-Trained Robust Adaptive Network Communication (STRANC) optimization model Based on Deep Learning Algorithm

Self-Trained Robust Adaptive Network Communication (STRANC) ...

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2025 International Conference on Multi-Agent Systems for Collaborative Intelligence, ICMSCI 2025

作者： Lang, Weiwei Beijing Information Technology College Department of Electronic Information Beijing100070 China

ISBN: (纸本)9798331509828

With the advent of the information age and the continuous development and application of network communications, some nodes or links may be overloaded in high-frequency and high-concurrency network communications, resulting in increased latency, increased packet loss, and other problems. To face with this challenge, this study proposes the novel self-trained robust adaptive network communication optimization model based on the deep learning algorithm. The proposed model is a 3-step approach, and the first step is link communication quality detection model. In order to effectively detect the communication quality of network links, a deep learning algorithm is introduced to establish the network link communication model. Then, network communication error data repair optimization is studied. This model improves the output stability and environmental adaptability of the network communication by adaptively repairing and estimating communication error data. Finally, dynamic network communication resource allocation optimization is proposed. Communication Resource Allocation (CRA) optimization is studied from the perspective of the communication load adaptive balancing. Experiments show that compared with traditional neural network and FCM models, the proposed model has an improved repair accuracy of about 15%. At the same time, the proposed model can effectively reduce communication delay in a test environment with 500 nodes and 200 communication links. © 2025 IEEE.

关键词： Adaptive Network Communication Deep Learning Algorithm optimization model Self-trained model

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Towards an efficient electric bus system: Multi-phase optimization model for incremental electrification of bus network with uncertain energy consumption

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2025年 173卷

作者： Davazdah, Behnam Zhang, Yiling Khani, Alireza Song, Ying Univ Minnesota Dept Civil Environm & Geoengn Minneapolis MN 55455 USA Univ Minnesota Dept Ind & Syst Engn Minneapolis MN USA Univ Minnesota Dept Geog Environm & Soc Minneapolis MN USA

Electrifying bus transit systems emerges as a practical solution to environmental degradation resulting from the unprecedented level of mobility nowadays. In the U.S., with the intensified efforts to expand EV infrastructure, a special emphasis is now placed on providing emission-free transit services. This initiative is central to America's push towards a net-zero-emissions future. In response, a growing number of cities have started replacing diesel buses with battery electric buses (BEBs). However, technological, operational, and economic barriers related to charging infrastructure and power supplies make the electrification of bus systems a gradual process, where only a part of the system is electrified at each stage. Moreover, due to the limited battery capacities of BEBs and their stochastic discharge rates influenced by factors like weather, traffic, and road conditions, BEBs often require daytime charging to be able to continue operating throughout the day. Therefore, transit agencies need to develop an integrated strategy that can address various costs of electrification and minimize the planning and operational costs. This study proposes a framework to facilitate the incremental electrification of bus systems. We formulate the problem as a two-stage stochastic mixed-integer linear programming model. The first stage optimizes long-term strategical decisions related to fleet sizing, charging station siting, and charging-station-route assignments under random BEB charging demand and time- of-use electricity tariffs. The second-stage optimizes the charging operations of the BEB fleet for a realized charging demand scenario while maintaining the service schedule for passenger convenience. We also develop a Benders decomposition method to solve the problem with better computational efficiency than existing solvers. To validate the proposed model, we test it on a real-world bus network to design an incremental electrification plan. We show the efficacy of the sol

关键词： Electric buses optimization model Charging infrastructure Charging station Stochastic model Electric transit system Transportation and sustainability Public transportation

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A Flight Slot optimization model for Beijing-Tianjin-Hebei Airport Cluster Considering Capacity Fluctuation Factor

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AEROSPACE 2025年第4期12卷 336-336页

作者： Ren, Jie Qu, Shiru Wang, Lili Liu, Changjie Ma, Lijing Sun, Zhiyuan Northwestern Polytech Univ Sch Automat Xian 710072 Peoples R China Civil Aviat Univ China Sch Air Traff Management Tianjin 300300 Peoples R China

The rapid expansion of China's civil aviation sector, particularly within the Beijing-Tianjin-Hebei airport cluster, has led to significant airspace congestion and operational inefficiencies. This study develops a dynamic flight slot allocation model that integrates both airport and airspace capacity constraints, accounting for real-time fluctuations in resource availability. The model aims to optimize slot distribution, minimize delays, and enhance operational efficiency by adapting to variations in airport and waypoint capacities, offering a more flexible solution compared with traditional static approaches. A case study based on real-world data from the Beijing-Tianjin-Hebei region demonstrates the model's effectiveness. Computational experiments show that incorporating capacity fluctuations significantly reduces the need for slot adjustments, particularly at secondary airports with volatile demand. The results indicate a marked improvement in operational efficiency, including reduced adjustment times and fewer affected flights. This research underscores the value of adaptive data-driven strategies in managing complex air traffic systems and provides valuable insights for policymakers and aviation authorities. Future research could extend this work by incorporating additional dynamic factors, such as weather conditions and emerging technologies, to further enhance the sustainability and efficiency of air traffic management.

关键词： flight slot allocation airport cluster capacity fluctuations air traffic management Beijing-Tianjin-Hebei optimization model

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