检索结果-内蒙古大学图书馆

Coupled THMC model‑based prediction of hydraulic fracture geometry and size under self‑propping phase‑transition fracturing

引用

International Journal of Coal Science & Technology 2024年第6期11卷 29-53页

作者： Nanlin Zhang Fushen Liu Liangliang Jiang Pinqiang Mo Jingwen Xiao Qi Song Yuhao Luo Computing Center for Geotechnical Engineering College of Civil Engineering and ArchitectureZhejiang UniversityHangzhou 310058ZijingangChina Research Center of Coastal and Urban Geotechnical Engineering College of Civil Engineering and ArchitectureZhejiang UniversityHangzhou 310058ZijingangChina Engineering Research Center of Urban Underground Development of Zhejiang Province Hangzhou 310058China Department of Chemical and Petroleum Engineering University of CalgaryCalgaryAB T2N1N4Canada State Key Laboratory of Intelligence Construction and Healthy Operation and Maintenance of Deep Underground Engineering School of Mechanics and Civil EngineeringChina University of Mining and TechnologyXuzhou 221116JiangsuChina Safety Environment and Technology Supervision Research InstitutePetro China Southwest Oil and Gas Field CompanyChengdu 610041China

The Self-Propping Phase-transition Fracturing Technology(SPFT)represents a novel and environmentally friendly approach for a cost-effective and efficient development of the world’s abundant unconventional resources,especially in the context of a carbon-constrained sustainable *** involves the coupling of Thermal,Hydraulic,Mechanical,and Chemical(THMC)fields,which makes it challenging to understand the mechanism and path of hydraulic fracture *** study addresses these challenges by developing a set of THMC multifield coupling models based on SPFT parameters and the physical/chemical characteristics of the Phase-transition Fracturing Fluid System(PFFS).An algorithm,integrating the Finite Element Method,Discretized Virtual Internal Bonds,and Element Partition Method(FEM-DVIB-EPM),is proposed and validated through a case *** results demonstrate that the FEM-DVIB-EPM coupling algorithm reduces complexity and enhances solving *** length of the hydraulic fracture increases with the quantity and displacement of PFFS,and excessive displacement may result in uncontrolled fracture *** the parameters considered,a minimal difference in fracture length is observed when the PFFS amount exceeds 130 m^(3),that means the fracture length tends to *** study contributes to understanding the hydraulic fracture propagation mechanism induced by SPFT,offering insights for optimizing hydraulic fracturing technology and treatment parameters.

关键词： Sustainable development,Self Propping phase Transition fracturing technology,Thermal Hydraulic Mechanical Chemical coupling,FEM DVIB EPM,Hydraulic fracture propagation

来源：评论

学校读者我要写书评

暂无评论

Improving Energy Harvesting System from Ambient RF Sources in Social Systems with Overcrowding

引用

International Journal of Crowd Science 2025年第1期9卷 13-28页

作者： Agieb, Ramy Amer, Ayman Mansour, Ibrahim Solyman, Ahmed Yahya, Khalid Samir, Ahmed Department of Electrical Engineering Faculty of Engineering MTI University Cairo11511 Egypt Faculty of Engineering Zarqa University Zarqa13110 Jordan School of Computing Engineering and Built Environment Glasgow Caledonian University GlasgowG4 0BA United Kingdom College of Engineering University of Business and Technology Jeddah22233 Saudi Arabia Department of Electrical and Electronics Engineering Faculty of Engineering and Architecture Istanbul Gelisim University Istanbul34310 Turkey

This paper presents a novel approach to enhance energy harvesting systems from ambient Radio Frequency (RF) sources in overcrowded environments. In environments like shopping malls, coffee shops, and airports, where wireless devices are prevalent, the electromagnetic energy emitted by these devices can be harvested and converted into electrical energy to power small devices, specifically those associated with the Social Internet of Things (SIoT). However, due to the high density of devices in such environments, the RF signals can be weak, resulting in low energy harvesting efficiency. This study focuses on developing technologies for wireless power transfer through a radio frequency ambient energy harvesting scheme, specifically designing to improve energy harvesting systems in crowded social environments. Recognizing the growing importance of energy harvesting for low-power devices in intelligent environments, our proposed method utilizes the ambient environment to capture energy in the downlink radio frequency range of the GSM-900 band. The system architecture comprises four main stages: a supercapacitor, a Villard voltage doubler circuit with seven stages, a lumped element matching network, and a microstrip patch antenna. The voltage doubler circuit is designed and simulated using the Agilent Advanced Design System (ADS) 2014 environment, and simulations and tests are conducted across different input power levels. Throughout the study, several key factors are identified as crucial to the system’s efficiency, including the frequency band, input power level, voltage doubler circuit design, impedance matching, diode selection, number of rectification stages, and load resistance. The proposed method demonstrates significant potential in enhancing the energy harvesting efficiency from ambient RF sources in crowded social environments. By providing a sustainable power source for SIoT devices in such settings, our approach contributes to the advancement of energy harves

关键词： Slot antennas

来源：评论

学校读者我要写书评

暂无评论

Enhanced satellite imagery analysis for post-disaster building damage assessment using integrated ResNet-U-Net model

引用

Multimedia Tools and Applications 2025年第5期84卷 2689-2714页

作者： Bhardwaj, Diwakar Nagabhooshanam, N. Singh, Ajeet Selvalakshmi, B. Angadi, Sanjeevkumar Shargunam, S. Guha, Tapas Singh, Gurkirpal Rajaram, A. Computer Engineering and Applications GLA University Chaumuhan India Department of Research Analytics Saveetha Dental College and Hospitals Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India Aditya University Surampalem Andhra Pradesh India VIT Bhopal University Madhya Pradesh Bhopal466114 India Department of Computing Science and Engineering Tagore Engineering College Rathinamangalam Tamil Nadu Chennai600127 India Department of Computing Science and Engineering Nutan College of Engineering and Research Talegaon Dabhade Maharashtra 410507 India Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Tamil Nadu Srivilliputhur626126 India Department of CSE Techno International New Town West Bengal Kolkata700156 India Department of Architecture PTU Punjab Mohali140307 India Department of Electronics and Communication Engineering E.G.S. Pillay Engineering College Tamil Nadu Nagapattinam611002 India

In the aftermath of natural disasters, timely and accurate building damage assessment is crucial for effective disaster response. This research introduces an innovative integrated ResNet-U-Net ensemble model that significantly enhances the accuracy and efficiency of damage detection from satellite imagery. The model combines the deep feature extraction capabilities of ResNet with the precise localization advantages of U-Net, supplemented by attention mechanisms to focus on critical damage indicators. Methodologically, the research employs a dataset of high-resolution satellite images from post-Hurricane Iota, processed through normalization and augmentation techniques. The model demonstrates exceptional accuracy, achieving 96.91% on an unbalanced dataset representative of real-world conditions, and 89.35% on a balanced dataset. This performance indicates a substantial improvement over existing approaches, offering a rapid and reliable tool for aiding disaster relief efforts. The proposed model's computational efficiency and generalizability underscore its potential to transform disaster management practices. Future work will explore the model's application to various disaster types and integration with real-time data processing systems. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Satellite imagery

来源：评论

学校读者我要写书评

暂无评论

Tropical Cyclone Analysis and Accumulated Precipitation Predictive Model Using Regression Machine Learning Algorithm 3rd

Tropical Cyclone Analysis and Accumulated Precipitation Pred...

引用

3rd International Conference on Computer and Communication engineering, CCCE 2023

作者： Abalos, Maribel S. Fajardo, Arnel C. College of Engineering Architecture and Technology Isabela State University Isabela Ilagan Philippines College of Computing Studies Information and Communication Technology Isabela State University Isabela Cauyan City Philippines

ISBN: (纸本)9783031352980

The Philippines is susceptible to tropical cyclones due to its geographical location which generally produces heavy rains and flooding of a large area that result in heavy casualties to human life and destruction of crops and properties. In the past 4 years, the Cagayan Valley region is hit by almost 20 Tropical Cyclones with different strengths and attributes. It is of utmost importance to have sufficient knowledge of such maritime phenomena for beneficial purposes. This study analyzed the Tropical Cyclones that hit Cagayan Valley using Philippine Atmospheric Geophysical and Astronomical Services Administration (PAGASA) dataset from 2017–2021. Different attributes were considered to create a framework, statistical analysis, and comparison matrix. Also, the dataset is analyzed using four Regression Machine Learning Algorithms namely MultilayerPerceptron, Linear Regression, SMOReg, and Gaussian Processes, and compared their performances where the best-performed algorithm is used to develop a predictive model for rainfall accumulation. Results of the study found that Cagayan Valley accumulated 219.857 mm of rainfall and an average Tropical Cyclone Maximum Sustained winds of 123.438 kph. Tropical Cyclone Ulysses reached almost the highest value in all the attributes as evidence of its devastating nature last November 2020. Also, the Linear Regression algorithm revealed a better performance which displayed a higher correlation coefficient and lower error estimates and took less time in developing the model. Lastly, the results can be considered to be a basis of the impact of a Tropical Cyclone based on their attributes and can be implemented into technological platforms for predictive application which helps foresee the prediction rate of rain accumulation to develop techniques and preventive measures to target reduction of damage on properties and the number of casualties. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Tropical cyclone

来源：评论

学校读者我要写书评

暂无评论

Mechanistic investigation of highly bendable magnesium alloy sheet fabricated by short-process manufacturing

引用

Journal of Magnesium and Alloys 2024年第10期12卷 4289-4310页

作者： Shiwei Xu Peijie Xiao Xiaofan Wu John Holmes Frédéric Mompiou Zhenyu Xiao Chen Jin Tianjiao Li Kuaishe Wang Zhuoran Zeng College of Mechanical and Vehicle Engineering Hunan UniversityChangsha 410082China State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan UniversityChangsha 410082China Suzhou Research Institute of Hunan University Suzhou 215131China College of Engineering Computing and CyberneticAustralian National UniversityACT 2601Australia CEMES-CNRS Universitéde Toulouse29 rue J.MarvigToulouse 31055France Qinghai Salt Lake Teli Magnesium Co. Ltd.Xining 810000China International Joint Laboratory for Light Alloys(Ministry of Education) College of Materials Science and EngineeringChongqing UniversityChongqing 400044China School of Metallurgical Engineering Xi’an University of Architecture&TechnologyXi’an 710055China College of Materials Science and Engineering Hunan UniversityChangsha 410082China

In this study,a commercial magnesium alloy AZ31(Mg-3Al-1Zn-0.3Mn)sheet through a short manufacturing process was found to be ductile and highly formable in *** possessing a strong basal texture,the short-processed sheet without any annealing can be bent at a small radius,only 0.2 times its thickness in the 90°bending ***,it could withstand direct deformation by repeated *** in-situ microstructural characterization reveals that extension twin bands with strain localization appear in the bending *** subsequent flattening,these twin bands underwent detwinning,reducing local strain concentrations and enabling further bending *** outstanding bend formability originated from the significant-type dislocation loops slipping on the prismatic crystal planes within dynamic-recrystallized *** grains underwent a uniform refinement to several microns in the short manufacturing process and exhibited low residual *** active prismatic dislocation slip within refined grains was due to its much lower relative activation stress to basal slip(CRSSprism/CRSSbasal of only∼1.6)owing to the effective grain boundary ***,the prismatic dislocation activity was further enhanced when bypassing Al-Mn nano-particles during motion,leaving debris and loops that facilitated easy multiplication.

关键词： Magnesium Deformation Texture In-situ characterization Dislocation slip.

来源：评论

学校读者我要写书评

暂无评论

Classifying Fake News in Filipino Language using Improved DistilBERT Model

Classifying Fake News in Filipino Language using Improved Di...

引用

International Conference on Information Technology, Computer and Electrical engineering (ICITACEE)

作者： Jan Mar Ruel Espiritu Ralph John E. Policarpio Aliah Chavy B. Sabado Vince Marc B. Sabado Hajah T. Sueno College of Engineering Architecture and Computing Notre Dame of Marbel University Koronadal City Philippines

ISBN: (数字)9798350389302

ISBN: (纸本)9798350389319

Detecting misinformation in the Filipino language poses unique challenges, especially when working with limited data resources. This study explored the use of transformer models, specifically pre-trained models like BERT, to construct a fake news classification model for Filipino. However, BERT's large size and computation hinder its deployment in resource-constrained environments. To address this, the study focuses on developing a lightweight fake news classifier using the DistilBERT architecture, fine-tuned for Filipinos. The model's performance was evaluated against BERT based on accuracy, precision, recall, F1 score, inference time, memory requirement, and parameter size. Results indicate that while BERT exhibits slightly better classification performance, DistilBERT offers significant advantages in efficiency with faster inference time and smaller resource requirements.

关键词： Electrical engineering Accuracy Computational modeling Memory management Transformers Fake news Information technology

来源：评论

学校读者我要写书评

暂无评论

Rough Rice Grading in the Philippines Using Infrared Thermography 3rd

Rough Rice Grading in the Philippines Using Infrared Thermog...

引用

3rd International Conference on Computer and Communication engineering, CCCE 2023

作者： Bejarin, Orfel L. Fajardo, Arnel C. College of Engineering Architecture and Technology Isabela State University Isabela Ilagan3300 Philippines College of Computing Studies Information and Communication Technology Isabela State University Isabela Cauayan City3305 Philippines

ISBN: (纸本)9783031352980

The Rough rice grading is a set of standard methods and processes for evaluating quality that are important to marketing and process controls. IR thermography uses the electromagnetic spectrum’s infrared region to detect heat that has been emitted. FLIR ONE thermal camera was used to acquire images of the sample. In order to represent each sample, a thermal index was generated using the average value of the pixels in the thermal image. In this study, the grading of rough rice was evaluated using infrared thermography and image processing techniques. Using infrared thermography, the results of the study indicated that detecting moisture content was 87.30% accurate and detecting foreign matter was 95.04% accurate. The results showed that infrared thermography evaluation using spectral analysis could accurately determine the moisture content of rough rice. Farmers, rice millers, and other related government agencies can greatly benefit from the application of non-contact, non-destructive methods for determining the purity and moisture content of rough rice. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Moisture

来源：评论

学校读者我要写书评

暂无评论

Automated Solar-Powered Corn Planting Robot

Automated Solar-Powered Corn Planting Robot

引用

IEEE Symposium on Wireless Technology and Applications (ISWTA)

作者： Michael Adrian P. Agustin Ferdinand H. Lopez Adrean Rey L. Tiu Huan Jenith F. Guaro Joriel S. Tiba College of Engineering Architecture and Computing Notre Dame of Marbel University Koronadal City Philippines

ISBN: (数字)9798350351354

ISBN: (纸本)9798350351361

The Philippine economy is based primarily on agriculture. Nowadays, there's a bigger need than ever for efficient and automated farming methods. Slow and poor production has been one of the major problems of agriculture. The best approach to deal with these problems is for the agricultural industry to become more automated. This leads to more systematic farming, which raises productivity rates. The purpose of this study is to design and create an automated robot that plants corn seeds automatically. To make the most of the tropical climate in the area, this automated robot is also integrated with a solar power. The Automated Solar-Powered Corn Planting Robot (ASP-CPR) was designed by the researchers with the following functions: it can drill farmed soil with a regular depth and distance and release a standard amount of corn seeds on the drilled soil automatically that follows the standard set-up of the Department of Agriculture. Upon multiple testing, results revealed the accuracy on releasing the standard number of seeds is 94%, 98 % for the depth of drilled soil, and 92% accuracy for the distance taken by ASP-CPR between planted seeds. Additionally, the researchers integrated a notification system that notifies the user if the robot experiences low power or immovability, or if the seed container is empty. Moreover, the researchers conducted a product quality evaluation ISO/IEC 25010 for 20 respondents where the gathered data and results revealed an overall weighted mean of 4.13 which indicates a strong agreement amongst respondents that ASP-CPR adhere to the quality model.

关键词： Productivity Accuracy Service robots Soil Message services Agriculture Seeds (agriculture)

来源：评论

学校读者我要写书评

暂无评论

Reliable Multihop Routing and Congestion Aware Chicken Swarm Optimization in Vehicular Ad-Hoc Network 3

Reliable Multihop Routing and Congestion Aware Chicken Swarm...

引用

3rd International Conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Anitha, Cuddapah Al-Tarazi, Dalia Vignesh, G.D. Vasuki, A. Vinotha Giri, Jayant Dinesh, M. School of Computing Mohan Babu University Erstwhile Sree Vidyanikethan Engineering College Department of Computer Science and Engineering Tirupati India Zarqa University Faculty of Engineering Department of Architecture Engineering Zarqa Jordan College of Engineering University of Business and Technology Jeddah Saudi Arabia St. Joseph's College of Engineering Department of Electronics and Communication Engineering Chennai India J.P. College of Engineering Department of Computer Science and Engineering Tenkasi India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Lovely Professional University Division of Research and Development Phagwara India Department of Vlsi Microelectronics Chennai India

ISBN: (纸本)9798331508456

Background: Vehicular Ad Hoc Networks (VANETs) play a crucial role in intelligent transportation by facilitating communication between vehicles and vehicles with infrastructure-based models. They encounter problems such as significant movement, overcrowding, and loss of data. This research presents a novel deep reinforcement learning-based resource allocation and congestion optimization (DRLRCO) framework aimed at improving communication efficiency and high reliability using an effective learning process. Method Used: The DRLRCO framework employs agent-based learning to ensure precise data transmission, AdMAC Protocol for dynamic packet delivery, and Congestion-Aware Chicken Swarm Optimization (CSO) to enhance network performance. Result: The DRLRCO framework surpasses reinforcement learning models for comprehensive testing. Significant enhancements involve improved accuracy, reduced data loss, minimized overhead, increased throughput, and shorter average delays for real-time communication. Conclusion: The DRLRCO framework successfully tackles congestion and data loss in vehicular communication. Future studies might involve Artificial Intelligence (AI) for traffic forecasting, experimentation among high-speed vehicles and investigating blockchain for enhanced security. © 2025 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Cognitive computing Applications in Real-Time Financial Risk Management

Cognitive Computing Applications in Real-Time Financial Risk...

引用

2024 Asian Conference on Intelligent Technologies, ACOIT 2024

作者： Josyula, Hari Prasad Landge, Sunil Rajaram Ranjan, Piyush Gajjar, Kishan D. Kumar, P. Anand Bdair, Mohammad Jamal 203 Quail Crk PrincetonNJ08540 United States PSG College of Arts & Science Civil Aerodrome Post Sitra Coimbatore641014 India School of Architecture Computing and Engineering University of East London United Kingdom

ISBN: (纸本)9798350374933

The incorporation of cognitive computing into real-time financial threat operations, to highlight the revolutionary potential of this technology for the financial sector. Cognitive computing, which is a combination of artificial intelligence, machine literacy, and natural language processing, improves the capability to reuse enormous quantities of financial data quickly and directly. The purpose of this study is to investigate how cognitive systems can recognise, evaluate, and mitigate financial risks in real-time. These systems offer greater prophetic analytics and decision-making support in comparison to traditional methods. Cognitive computing makes it possible to conduct more accurate threat assessments, detect implicit dangers earlier, and improve nonsupervisory compliance. This is accomplished through the use of sophisticated algorithms and data analytics. Case studies illustrate the practical applications of these technologies through the use of colourful financial scripts, demonstrating how beneficial they are in improving threat operating methods. In the final section of the study, the author discusses the counterarguments that cognitive computing poses for the future of fiscal threat operation, as well as the implicit issues that are associated with its widespread abandonment. © 2024 IEEE.

关键词： Decentralized finance

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：