Engineering Commons^™

Accumulation Mechanisms And Resource Potential Of Helium In Coal Measures: A Case Study Of The Eastern Margin Of The Ordos Basin, Liu Xiangbai, Tao Shizhen, Yang Xiuchun, Zhao Qun, Chen Yanyan, Liu Ziyang, Pei Xiangbing, Wang Longfei, Yi Wei, Feng Jianqiu, Zhang Tan, Gao Jianrong, Tao Xiaowan, Liu Zhuangxiaoxue, Li Chaozheng, Yang Yiqing, Chen Yue

Coal Geology & Exploration

Background Helium, with advantages such as stable chemical properties and high thermal conductivity, has been extensively applied in high-tech sectors like national defense, military, aviation, and aerospace, playing an irreplaceable role. Presently, helium in China is primarily imported from other countries, manifesting a high degree of dependence on foreign trade, suggesting a prominent issue concerning helium resource security. Previous studies on helium principally focus on conventional natural gas, rendering helium in coal measures relatively under-studied. Objective and Methods To determine the distribution and potential of helium resources in coal measures, this study analyzed the coal-measure gas sampled from the eastern …

Coal Permeability Enhancement Via Cyclic Percussion Using Low-Temperature Liquid Co2 And High-Temperature Water Vapor And Simulations Of Resultant Gas Drainage Performance, Qin Lei, Wang Ping, School Of Civil And Resource Engineering, University Of Science And Technology Beijing, Beijing 100083, China Shugang, Wang Hui, Liu Pengfei, Li Jiawei, Lin Haifei

Coal Geology & Exploration

Objective In the application of the coal seam permeability enhancement technique based on liquid CO₂, pore water in coal seams freezes due to low temperatures, blocking pathways for gas migration. Hence, this study developed a technique for coal permeability enhancement through cyclic percussion using low-temperature liquid CO₂ and high-temperature water vapor (also referred to as the cyclic cold and hot percussion). Methods This study delved into the permeability evolutionary patterns of coals under cyclic cold and hot percussion using a low-field nuclear magnetic resonance (NMR) spectrometer, an automatic coal permeability tester, a contact angle tester, and 3D …

Deep Beam Theory-Based Mechanical Analysis Of Water-Resisting Key Strata Of Coal Seam Floors In A Deep Mining Environment, Wang Bingwen, Zha Wenhua, Lu Haifeng

Coal Geology & Exploration

Objective An increase in the mining depth of mines poses a more serious threat from highly confined karst water, resulting in water hazards like water inflow and inrushes on the mining faces of coal seams. The key content used to address this issue is to analyze the water pressure resistance of the water-resisting key stratum of the coal seam floor in a deep mining environment. Methods This study simplified a water-resisting key stratum into a rock beam model and then dealt with this model using the deep beam theory in the prediction of water inrushes in deep mining. Specifically, by …

Fracture Mechanical Criteria And Simulation Of Floors With Y-Shaped Branches Of Major Faults In Coal Mines, Li Ang, Sun Jingxin, Zhang Wenzhong, Zhang Zhuang, Yang Yuxuan, Wang Weidong, Lyu Wei, Fan Liuyi

Coal Geology & Exploration

Objective Despite wide distribution, the branches of major faults (also referred to as the fault branches) tend to be overlooked. However, they represent one of the primary causes of water inrush. Methods Under the engineering geological background of the Liuzhuang coal mine in Anhui Province, this study established a fracture mechanical disaster model for fault branches under the impacts of both seepage and stress based on the criteria for compression-shear fracture of rock masses considering the Mohr-Coulomb criterion. Using this model, this study obtained the critical water pressure and the minimum safe distance between the fault branch and the floor's …

Elastoplastic Stress Analysis Of Multi-Refrigerant Combined Heterogeneous Artificial Frozen Wall, Wang Bin, Liang Xiuling, Zhang Zihao, Cai Haibing, Rong Chuanxin

Coal Geology & Exploration

Objective Affected by the temperature difference of the refrigerant and the distance difference between the frozen formation and the freezing pipes, the heterogeneity of the multi-refrigerant combined double-row-pipe frozen wall is more significant. In order to evaluate the safety of such frozen wall reasonably, the elastic plastic stress analysis should be carried out for the artificial frozen wall with multi-refrigerant considering the heterogeneity. Methods The frozen wall at 1/4 pipe distance was selected as the characteristic section. Then, the temperature distribution curve on this section was equivalently converted to three linear functions, and the frozen wall was regarded as a …

Analytical Model For Reactive Solute Transport In A Channel-Matrix System, Wei Nana, Li Xu, Xu Guangquan, Zhang Haitao, Shao Zefan

Coal Geology & Exploration

Objective The accurate quantitative characterization of fractured media and the theoretical research on solute transport in fractured media have become the key to the prevention and control of groundwater contamination in fractured aquifers. Currently, fractured aquifers are generalized to horizontal fractures, ignoring the geometric characteristics of the open parts of fractures, called channels, and the impacts of matrix diffusion on solute transport. Methods A model for solute transport in a single channel-matrix system was established, obtaining the semi-analytical solutions using Laplace and numerical inverse transforms. The COMSOL Multiphysics software was employed to construct a numerical model for verification. Furthermore, the …

Landslide Sensitivity Assessment Of Coal Mining Subsidence Areas Based On Information Value - Machine Learning Coupling Models, Niu Chenhao, Jiao Runcheng, Han Jianfeng, Wang Shengyu, Guo Xuefei, Liu Chang, Han Yucheng, Song Guofeng

Coal Geology & Exploration

Objective Due to their special geological conditions and coal mining background, coal mining subsidence areas are prone to suffer from ground cracks and subsidence, which tend to further induce geological disasters such as landslides. This makes it extremely necessary to conduct landslide sensitivity assessment of these areas using appropriate influencing factors and training models. Methods This study investigated the Xishan coal mine area in Beijing as an example to conduct landslide sensitivity assessment of coal mining subsidence areas by coupling slope units with mathematical statistical and machine learning models. With 10 influencing factors, including topographic and geomorphic factors such as …

Research And Application Of The Seismic Exploration Technique Using Reflected In-Seam Waves In Identifying Folds And Faults In Coal Seams, Wu Guoqing

Coal Geology & Exploration

Background Accurately identifying subsurface anomalies is crucial to building a geological transparency system in the transformation to intelligent coal mines. The precise exploration of fold anomalies is a challenge of underground geophysical exploration technology, holding great significance for reducing excavation costs, mining difficulties, and safety risks. Objective and Methods Previous in-seam seismic explorations reveal that folds pose significant impacts on the propagation characteristics of in-seam waves. However, conventional inversion techniques of in-seam waves are difficult to distinguish folds from faults. This study constructed numerical models for faults and folds with similar geometric shapes and equal exploration distances. Specifically, the differences …

A Method For Reconstructing Consecutively Missing Seismic Data Based On Recurrent Feature Reasoning, Li Zijuan, Chang Guangyao, Jia Yongna

Coal Geology & Exploration

Objective Due to the constraints of natural environments like rapids, rifts, and high mountains, the acquired seismic data are often challenged by consecutive missing, affecting subsequent seismic data processing and geologic analysis. Hence, it is necessary to reconstruct the missing data through interpolation. Methods This study proposed a method for reconstructing consecutively missing seismic data based on recurrent feature reasoning. First, the missing seismic data undergo partial convolution operations, in which the weight of the convolution results is adaptively adjusted based on the proportion of valid feature map data in the receptive field, avoiding invalid convolution operations on consecutively missing …

A Neural Network-Based Method For Analyzing Diffracted Wave Velocity, Tao Junhong, Zhao Jingtao, Sheng Tongjie

Coal Geology & Exploration

Background In seismic imaging, accurate velocity models are crucial for characterizing subsurface structures in a fine-scale manner. Notably, in coal mining, small-scale geological structures like faults and collapse columns are closely associated with mining accidents. These structures typically occur as diffracted waves in seismograms.Objective and Methods To effectively image these small-scale geological bodies, fine-scale velocity modeling using diffracted wave information is particularly important. Hence, this study proposed a neural network-based method for analyzing diffracted-wave velocity. First, diffracted-wave velocity spectra were generated using the gathers of diffracted waves that were separated in the common virtual source domain. Second, a gamma-ray …

Key Technology And Practice Of Deep Borehole Pneumatic Directional Drilling In Broken-Soft Coal Seam In Yangquan Mining Area, Liu Fei, Li Quanxin, Fang Jun, Liu Jianlin, Yang Weifeng, Chu Zhiwei, Zhao Jianguo, Wang Siyi

Coal Geology & Exploration

Objective In response to the need for precise, proactive, and regional management of gas in the broken-soft coal seam of the Yangquan Mining Area, a technical scheme utilizing pneumatic directional drilling for pre-drainage boreholes was proposed. Methods Based on the analysis of the technical challenges in pneumatic directional drilling, a series of technologies suitable for the broken-soft coal seam in the Yangquan Mining Area were developed. These include stable operation technology for pneumatic downhole motors, precise control technology for drilling boreholes, efficient deep-hole slag discharge technology, and pneumatic milling and salvage technology. The pneumatic directional drilling equipment was optimized, and …

Emergency Response And Critical Technologies For Large-Diameter Boreholes In Mine Rescue Through Surface Drilling, Ma Tan, Zhuge Lei, Zhao Weidong

Coal Geology & Exploration

Objective Large-diameter lifesaving holes have been successfully applied multiple times in mine rescue through surface drilling. However, they show limitations in emergency response like quick dispatch and cross-regional rescue, and their technological adaptability is insufficient to cope with complex strata. Methods From the perspective of overall emergency rescue, with rescue timeliness as an indicator, this study summarized the critical technologies like response capability enhancement and borehole-forming technology for complex strata. It constructed an emergency handling process for mine rescue through surface drilling, specified the improvements in contingency plan activation, response actions, and response speeds, and established the hierarchical cross-regional rescue …

Accumulation Patterns And Exploitation And Utilization Targets Of Geothermal Resources In The Coal-Bearing Area In North China, Pang Zhonghe, Duan Zhongfeng

Coal Geology & Exploration

Objective China is a major producer and consumer of coal resources in the world. The urgent need for the transition of the coal industry necessitates the investigation of both the origin and distribution patterns of geothermal resources in the coal-bearing areas of the country. The coal-bearing area in North China, with geothermal reserves accounting for 74.7% of the whole country, stands out as one of the areas with the most abundant geothermal resources nationally. This area encompasses four major coal-bearing basins: the Bohai Bay, Ordos, Qinshui, and Southern North China, with the lithospheric thermal state gradually weakening from east to …

Convection - Heat Transfer Coupling Mechanism For Closed-Loop Heat Extraction From Hydrothermal Resources Using Horizontal Wells, Gu Feng, Li Youwu, Zhang Yue, Gao Ying, Yang Peng, Wang Anran, Cui Jingyun

Coal Geology & Exploration

Objective Closed-loop heat extraction technology, which extracts geothermal energy without draining geothermal water, has emerged as a research focus in geothermal energy exploitation. However, there is a lack of studies on the impacts of convection in reservoirs on heat transfer. Methods To improve single-well heat extraction, this study proposed a technology of closed-loop heat extraction from hydrothermal reservoirs using horizontal wells. This technology aims to increase the contact area between wellbores and reservoirs while fully leveraging the convection in reservoirs. A flow and heat transfer model characterized by the coupling of horizontal wells, circulating water and reservoirs was established to …

Power Quality Enhancement In Hybrid Pv-Bes System Based On Ann-Mppt, Heli̇n Bozkurt, Özgür Çeli̇k, Ahmet Teke

Turkish Journal of Electrical Engineering and Computer Sciences

Battery energy systems (BESs) assisted photovoltaic (PV) plants are among the popular hybrid power systems in terms of energy efficiency, energy management, uninterrupted power supply, grid-connected and off-grid availability. The primary objective of this study is to enhance the power quality of a grid-tied PV-BES hybrid system by developing an operation strategy based on Artificial Neural Network (ANN) based maximum power point tracking (MPPT) method. A test system comprising a 10-kWh BES and a 12.4 kW PV plant is structured and simulated on the MATLAB/Simulink platform. The hybrid system is validated with three different cases: constant radiation, rapid changing radiation, …

Mention Detection In Turkish Coreference Resolution, Şeni̇z Demi̇r, Hani̇fi̇ İbrahi̇m Akdağ

Turkish Journal of Electrical Engineering and Computer Sciences

A crucial step in understanding natural language is detecting mentions that refer to real-world entities in a text and correctly identifying their boundaries. Mention detection is commonly considered a preprocessing step in coreference resolution which is shown to be helpful in several language processing applications such as machine translation and text summarization. Despite recent efforts on Turkish coreference resolution, no standalone neural solution to mention detection has been proposed yet. In this article, we present two models designed for detecting Turkish mentions by using feed-forward neural networks. Both models extract all spans up to a fixed length from input text …

A Single Operational Amplifier-Based Grounded Meminductor Mutators And Their Applications, Shalini Gupta, Kunwar Singh, Shireesh Kumar Rai

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, three simple configurations of meminductor mutator are presented. The first two configurations of meminductor mutator have been implemented utilizing one CMOS-based operational amplifier, one memristor, one capacitor, and five resistors, while the third configuration of meminductor mutator is implemented utilizing one CMOS based operational amplifier, two memristors, one capacitor, and four resistors. The implementation and simulation of the proposed configurations are done by using LTspice tool. The viability of the proposed circuits is demonstrated by utilizing TSMC 180 nm CMOS technology parameters. The proposed circuits of the meminductor have a simple structure in contrast to many of …

Finger Movement Recognition Using Machine Learning Algorithms With Tree-Seed Algorithm, Muhammed Sami̇ Karakul, Ahmet Gökçen

Turkish Journal of Electrical Engineering and Computer Sciences

Electromyography (EMG) signals have been used to recognize various actions of hand movements, finger movements, and hand gestures. This paper aims to improve the classification accuracy of EMG signals while decreasing the number of features using the Tree-Seed Algorithm. The dataset containing EMG signals utilized in this investigation is derived from a publicly accessible source. The rationale for selecting the Tree-Seed Algorithm centers on its ability to enhance classification accuracy while minimizing the dimensionality of feature sets. The object function and Tree-Seed Algorithm's nature avoids the results to have low accuracy with fewer features. The aim is not just to …

Enhancing Dtc Control Of Im Using Fuzzy Logic And Three-Level Inverter: A Comparative Study, Siham Mencou, Majid Benyakhlef, Elbachir Tazi

Turkish Journal of Electrical Engineering and Computer Sciences

Direct torque control is the most appropriate strategy for induction motor drive systems, due to its considerable ability to reduce the impact of of machine parameter variations, while offering fast dynamic response and simplified control implementation. However, persistent problems associated with high torque ripple and variable switching frequencies prevent its widespread adoption. To overcome these limitations, several techniques have been developed, in particular the use of multi-level inverters and fuzzy logic algorithms. This article proposes an in-depth evaluation of these techniques in a MATALB/Simulink environment, under various operational conditions. The main objective is to provide a detailed performance analysis of …

Prediction Of Mooring System Characteristics Of The Floating Barge Using Deep Neural Networks, Janghoon Seo, Dong-Woo Park

Journal of Marine Science and Technology–Taiwan

The present study establishes deep learning models to predict the tensions and inclinations of mooring lines of a floating barge and verifies applicability of these models. Hydrodynamic and mooring analyses are conducted on the dataset used for the deep learning models. Three types of neural network models include a deep neural network (DNN) with input data representing the six degrees of freedom motions of a floating barge, convolutional neural network (CNN) with input images of the floating barge and mooring lines on a horizontal plane, and hybrid neural network (HNN) that consolidates the characteristics of DNN and CNN models. The …

Research On Development Status And Strategy Of Advanced Materials In Guangdong-Hong Kong-Macao Greater Bay Area, Ziwei Zhao, Can Wang, Weihua Wang, Qingli Huang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Advanced materials are an important source of new quality productivity. Guangdong-Hong Kong-Macao Greater Bay Area is now facing the internal and external pressure of manufacturing upgrading, and there is an urgent need to play the leading and supporting role of advanced materials in the construction of modernized industrial system. This study combs through the basic situation of the development of materials science and industry in Guangdong-Hong Kong-Macao Greater Bay Area, analyzes its advantages, characteristics and problems in depth, and puts forward a number of suggestions around how to develop materials science, technology, and industry in the Greater Bay Area.

A Limited-Preemption Scheduling Model Inspired By Security Considerations, Benjamin Standaert, Fatima Raadia, Marion Sudvarg, Sanjoy Baruah, Thidapat Chantem, Nathan Fisher, Christopher Gill

Computer Science and Engineering Faculty Research

Safety-critical embedded systems such as autonomous vehicles typically have only very limited computational capabilities on board that must be carefully managed to provide required enhanced functionalities. As these systems become more complex and inter-connected, some parts may need to be secured to prevent unauthorized access, or isolated to ensure correctness.

We propose the multi-phase secure (MPS) task model as a natural extension of the widely used sporadic task model for modeling both the timing and the security (and isolation) requirements for such systems. Under MPS, task phases reflect execution using different security mechanisms which each have associated execution time costs …

The Evaluation Of Machine Learning Techniques For Isotope Identification Contextualized By Training And Testing Spectral Similarity, Aaron P. Fjelsted, Tyler J. Morrow, Clayton D. Scott, Yilun Zhu, Darren E. Holland, Azaree T. Lintereur, Douglas E. Wolfe

Faculty Publications

Precise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset …

09.16.2024 Orsp Connect, Liz Williamson

ORED Newsletter

Human Research with AI workshop

External Funding Opportunities for Students

Research On Simulation Resource Management Based On Graph Association Organization, Zewei Liu, Yishan Ding, Tingyu Lin, Mingxing Ke, Liqing Guo, Yingying Xiao, Zhilong Zhao, Yan Li, Xuan Lü

Journal of System Simulation

Abstract: The simulation test and evaluation of intelligent system of systems, systems and single equipment is a complex system engineering, which requires effective management of multi-source, heterogeneous and distributed massive simulation resources scattered in cloud test centers and test sites of various units; and good control of dynamically generated tasks, assumptions, configurations, results, evaluations and other data and files. The traditional way of managing and querying simulation resources by category is inefficient and difficult to meet the requirements of large-scale intelligent simulation test and evaluation activities. An overall framework for simulation resource management based on graph association organization, defines a …

Path Planning Based On Improved A* And Dynamic Window Approach, Peng Ji, Xinyuan Zhang, Shuaixuan Gao, Shuorang Wei

Journal of System Simulation

Abstract: In response to the low efficiency, redundant turning points, and collision issues of the traditional A* algorithm, a smart vehicle path planning algorithm that integrates an improved A* algorithm with a dynamic window approach has been proposed. The algorithm has enhanced the search point selection method, optimized the evaluation function, selected key turning points based on the slope values between turning points, and removed redundant turning points. Between every two optimized key turning points, a dynamic window approach that balances speed and safety is used for local obstacle avoidance. Experiments show that compared to the traditional A* algorithm, this …

Research On Digital Twin System Of Rockshaft Hoist, Baiting Zhao, Jianguo Shi, Xiaofen Jia

Journal of System Simulation

Abstract: In order to solve the problem of low intelligence and digitization of the current mine hoisting system, a method based on DT for digital modeling, 3D visualization, and virtual real interaction of shaft hoisting machines is proposed. Aiming at the rockshaft hoist system, based on the digital twin five dimensional model framework, we analyze the operating mechanism of the equipment, and model the fully physical digital system of the rockshaft hoist. By constructing multidimensional multi-scale models and multidimensional heterogeneous data models, twin digital scenes are constructed, and virtual real mapping technology is combined to achieve dynamic mapping and virtual …

A Multimodal Residual Spatial-Temporal Fusion Model Based On Automatic Sleep Classification, Yecai Guo, Shuang Tong

Journal of System Simulation

Abstract: Highly accurate sleep staging plays a crucial role in correctly assessing sleep conditions. Aiming at the problem that the existing convolutional network cannot obtain the topological characteristics of physiological signals, a sleep staging algorithm based on multi-modal residual spatio-temporal fusion is proposed. Time-frequency images and spatio-temporal images are obtained using short-time Fourier transform and adaptive map convolution, which are converted into high-dimensional feature vectors; lightweight interaction of feature information flow is realized through time-frequency feature and spatiotemporal feature extraction modules; the feature enhancement fusion module fuses feature information to outputs sleep staging results. The results show that the model …

Research On Autonomous Decision-Making In Air-Combat Based On Improved Proximal Policy Optimization, Dianwei Qian, Hongmin Qi, Zhen Liu, Zhiming Zho, Jianqiang Yi

Journal of System Simulation

Abstract: To address the problems of high information redundancy and slow convergence speed of traditional reinforcement learning in air-combat autonomous decision-making applications, a proximal policy optimization air-combat autonomous decision-making method, based on dual observation and composite reward is proposed. A dual observation space, which contains interaction information as the main information and individual feature information as a supplement, was designed to reduce the influence of redundant battlefield information on the training efficiency of the decision model. A composite reward function combining result reward and process reward was designed to improve convergence speed. The generalized advantage estimator was applied in the …

An Intelligent Adversaries Behavior Simulation Technology Based On Improved Behavior Trees, Fang Zhou, Bo Fan, Xiaoyi Liu, Yishan Ding, Ningxin Zhang, Yachao Shao, Xiaoyu Zhai

Journal of System Simulation

Abstract: Intelligent algorithm/intelligent platform/intelligent system intelligence capability testing and evaluation need to solve high-level intelligent opponent simulation problems, an intelligent opponent behavior simulation technology based on improved behavior tree is proposed. Four types of behavior tress nodes are designed, including behavior control, combat tasks, behavior actions, and execution condition node. Five atomic behavior actions and parameters are established, including maneuver, reconnaissance and early warning, command and decision-making, firepower strike, and electronic interference node. Five atomic condition nodes are provided, including target selection, weapon launch, and incoming weapon judgment node. The intelligent adversarial behavior simulation system is designed, including a behavior …