Engineering Commons^™

Log-Based Identification Of Sedimentary Facies In Coal Measures In The Southern Wuxiang Block, Shanxi Province, China, Jin Yi, Tian Yunqing, Song Huibo, Hu Bin, Yu Zhenfeng

Coal Geology & Exploration

Objective The Carboniferous and Permian coal-bearing strata in the southern Wuxiang block, Qinshui Basin, Shanxi Province, China contain abundant coalbed methane (CBM) resources. To develop intelligent discrimination technology for CBM exploration in this block, it is necessary to establish lithology discrimination criteria based on log data, reveal the response relationships between logging and sedimentary facies, and determine sedimentary patterns. Methods Using a comprehensive analysis of lithologies, sedimentary facies, and logging facies, this study systematically investigated the distributions of logging and sedimentary facies in the Shanxi and Taiyuan formations—the primary coal-bearing strata in the southern Wuxiang block. By comprehensively analyzing the …

Fractures And Their Macro-Mesoscopic Mechanical Evolution Pattern In Coals In The Benxi Formation, Ordos Basin, Zhu Boxu, Yang Xu, Li Gaoren, Li Gao, Feng Jiaxin

Coal Geology & Exploration

Objective This study aims to determine the relationship between multi-scale fracture characteristics and the mechanical behavior of deep coals, thereby helping gain further insights into the mechanisms behind the macro-mesoscopic damage and failure of the coals and providing a scientific basis for the stability assessment and mechanical modeling of deep coalbed methane (CBM) reservoirs. To this end, it is necessary to examine the differences in the coals’ mechanical properties under varying scales. Methods This study conducted uniaxial and triaxial mechanical tests, nanoindentation experiments, and CT scanning of the No. 8 coal seam in the Benxi Formation within the Ordos Basin. …

Spatial Distribution Of Coalbed Methane Migration Pathways And Selection Of Optimal Target Areas For Coalbed Methane Extraction For Abandoned Mines, Liu Qinjie, Yang Youxing, Wu Benniu, Duan Minke, Deng Zhuoyue, Guo Chenye, Sun Qiang

Coal Geology & Exploration

Objective and Methods The spatial distribution and long-term evolution of effective migration pathways determine the migration pathways of residual coalbed methane (CBM) in abandoned mines. Furthermore, they provide an important basis for selecting the optimal target areas for CBM extraction drilling in abandoned mines and maximizing extraction efficiency. This study investigated the first mining area at the first horizontal elevation of the Songzao Coal Mine in Chongqing. Using a comprehensive approach that integrated theoretical analysis, numerical simulations, and physical simulation experiments using similar materials, this study systematically examined the distribution patterns of effective CBM migration pathways in abandoned mines under …

Mechanisms Underlying Responses Of Pore Structures In Continental Oil Shale To Microwave Pyrolysis, Lyu Pengrui, Yuan Shihao, Geng Jishi, Li Delu, Zhang Huiyuan, Ge Zhenlong

Coal Geology & Exploration

Objective and Methods Microwave pyrolysis technology holds great potential to achieve clean energy conversion and efficient energy utilization of oil shale resources. This study investigated oil shale in the Triassic Yanchang Formation, Ordos Basin. Through microwave pyrolysis experiments under different power values (600 W, 800 W, and 1000 W) conducted using a microwave equipment monitoring system, this study tested the gas products generated during pyrolysis. Using the nitrogen adsorption method, this study compared and analyzed the pore structure characteristics between the original oil shale and samples after microwave heating under different power values. Additionally, the mechanisms behind damage to oil …

Spatiotemporal Evolution Pattern Of The Inertial Horizontal Displacement Of Mining Overburden And A Surface Prediction Model Considering Inertial Horizontal Displacement, Chen Yuanfei, Wang Lei

Coal Geology & Exploration

Objective Substantial measured data indicate that the along-strike horizontal displacement of the surface tends to be nonzero in the central part of the mining-affected zone. This phenomenon deviates from traditional understanding, leading to systematic deviations in the predicted results of the traditional prediction model for horizontal displacement. Methods This study investigated mining face 1414 of the Guqiao Coal Mine in the Huainan mining area, Anhui Province. Using measured data and numerical simulation methods, this study explored the spatiotemporal evolution of the horizontal displacement within the mining overburden and of the surface. Then, it analyzed the sources, patterns, and distribution characteristics …

Deterioration And Instability Mechanisms Of Water-Rich And Weakly Cemented Open-Pit Slopes, Wang Ming, Wu Zhang, Xu Changyou, Zhao Fu, Meng Xiangchun, Shi Bin, Liu Jingyu, Xu Yongchao, Wang Jingwei, Zhao Lichun

Coal Geology & Exploration

Background During the mining of an open-pit mine, denudated layers contain loose Neogene and Quaternary aeolian, alluvial, and diluvial deposits, facilitating water storage and conduction. This is prone to cause slope degradation and instability, severely threatening mining safety. Methods Based on results from field surveys and laboratory experiments, this study systematically analyzed the impacts of groundwater on the weak layer along a slope of an open-pit mine in the Huolinhe Coalfield, Inner Mongolia, focusing on its softening effect on mudstones. By establishing a mechanical model for unconsolidated strata, this study derived an equation for calculating the seepage force in the …

3d Advanced Geological Prediction Based On Reflected Seismic Waves And Its Application Effects, Cai Sheng

Coal Geology & Exploration

Objective For the advance geological prediction of tunnels based on reflected seismic waves, the traditional 2D observation method tends to cause spatial positioning deviations of anomalies. To overcome this limitation, this study developed a 3D seismic wave-based advance geological prediction method according to the actual geometries of tunnels. Methods Using the technical path consisting of theoretical analysis, numerical simulation, and engineering verification, this study solved key technical challenges including 3D wavefield reconstruction, spatial modeling, and migration imaging in the 3D detection system. Based on the principle of geometric seismology, this study demonstrated the enhancement effects of 3D observation on the …

A Time Series Forecasting Model Integrating Spatial Features For Inter-Borehole Resistivity And Its Application, Wang Jianghong, Liu Shuo, Wang Gang, Xue Wuqiang, Li Bofan

Coal Geology & Exploration

Background Mine resistivity prediction serves as a core technique for water hazards monitoring in coal mines. However, due to sparse monitoring points and insufficient spatial resolution, conventional prediction approaches fail to capture dynamic resistivity variations under complex geological conditions.Objective and Methods To address this challenge, this study developed a deep learning-based time series forecasting model integrating spatial features for inter-borehole resistivity. Using a prediction framework constructed based on long short-term memory (LSTM) and critical spatial monitoring points selected through Pearson correlation analysis, this model (also referred to as the LSTM model) enabled high-precision prediction of resistivity in unknown areas. …

Parameter Characteristics And Rock-Breaking Mechanisms Of Horizontal Drilling Of Underground Collapsed Bodies In Coal Mines, Yao Ningping, Dou Xuqian, Han Zhaoyang, Zhang Guohua, Sun Yuchen, Li Hao, Wang Li

Coal Geology & Exploration

Objective With continuously increasing coal mining depth, the risks of hazards such as roof collapse and personnel entrapment caused by high in situ stress and mining-induced pressure have significantly intensified. Drilling emerges as a key means of rapidly establishing rescue passageways. However, the drilling process tends to face multiple challenges, including complex geological structures, unstable collapsed bodies, and low drilling efficiency. Methods This study aims to reveal the rock-breaking mechanisms during the drilling of collapsed bodies, optimize drilling parameters to ensure reliable borehole formation, and achieve efficient drilling of collapsed bodies. To this end, this study developed a large-scale experimental …

A Design Method For Timeliness Optimization Of The Round-Trip Actuating Mechanisms Of Rescue Vehicle-Mounted Drilling Rigs, Cao Chao, Mao Bingquan, Zhang Zhonghai, Chang Renqi, Zhao Jiyun, Han Jing, Huang Di

Coal Geology & Exploration

Objective In the field of mine accident rescue, creating vertical rescue channels through surface drilling operations using a rescue vehicle-mounted drilling rig (RVMDR) proves the most effective. However, the limitation of the vehicle’s load capacity necessitates balancing the driving speeds and stability of the round-trip actuating mechanisms. Furthermore, establishing an optimization design and configuration system of parameters to maximize the operational capacities of these actuating mechanisms plays a key role in ensuring rescue efficiency. Methods By establishing a multiple spatiotemporal planning model for the round-trip actuating mechanisms of the RVMDR, this study determined the value ranges and design processes of …

Probing The Effect Of Peg-Dna Interactions And Buffer Viscosity On Tethered Dna In Shear Flow, Fatema Tuz Zohra, Huda Al-Zuhairi, Jefferson Reinoza, Hyeongjun Kim, Andreas Hanke

Mechanical Engineering Faculty Publications

DNA flow-stretching is a widely employed, powerful technique for investigating the mechanisms of DNA-binding proteins involved in compacting and organizing chromosomal DNA. We combine single-molecule DNA flow-stretching experiments with Brownian dynamics simulations to study the effect of the crowding agent polyethylene glycol (PEG) in these experiments. PEG interacts with DNA by an excluded volume effect, resulting in compaction of single, free DNA molecules in PEG solutions. In addition, PEG increases the viscosity of the buffer solution. By stretching surface-tethered bacteriophage lambda DNA in a flow cell and tracking the positions of a quantum dot labeled at the free DNA end …

3d-Printable Hydrogel With Rapid Ambient Self-Healing, Anna M. Petre

Research from the Berry Summer Thesis Institute, 2025

Inspired by nature, soft robots composed of compliant (“soft”) materials are well-suited for uncertain, dynamic tasks requiring safe interaction between a robot and its environment. Soft robots with the ability mend minor damage (e.g. perforations, tears) have been enabled by the rapid development of self-healing soft materials. Recently, one of these hydrogel materials (internally dubbed “BeckOHflex”) – made entirely from commercially available precursors – was developed with several appealing characteristics including rapid ambient self-healing, 3D printability on commercial machines, and competitive mechanical properties. However, the self-healing performance of BeckOHflex falls short of competitors that leverage custom-synthesized precursors. This project aims …

Transfer Learning-Based Multi-Sensor Approach For Predicting Keyhole Depth In Laser Welding Of 780dp Steel, Byeong-Jin Kim, Young-Min Kim, Cheolhee Kim

Mechanical and Materials Engineering Faculty Publications and Presentations

Penetration depth is a critical factor determining joint strength in butt welding; however, it is difficult to monitor in keyhole-mode laser welding due to the dynamic nature of the keyhole. Recently, optical coherence tomography (OCT) has been introduced for real-time keyhole depth measurement, though accurate results require meticulous calibration. In this study, deep learning-based models were developed to estimate penetration depth in laser welding of 780 dual-phase (DP) steel. The models utilized coaxial weld pool images and spectrometer signals as inputs, with OCT signals serving as the output reference. Both uni-sensor models (based on coaxial pool images) and multi-sensor models …

Novel Nano-Composite Materials (Nncms) With The Designations J1, J2, And J3 For Removal Several Harmful Ions, Mohammed K. Al-Doseri, Safaa. R. Fouda, Mohamed Mossad, Mahmoud H. Mahmoud

Mansoura Engineering Journal

The most toxic material to the environment is heavy metals. remove heavy metals from wastewater is done by adsorption. Many papers have been done using different materials to take off toxic dangerous ions from wastewater. Noval Nano-composites material (NNCM)as designated as J1, J2, and J3 the most used adsorbents in this study. To conduct the experiments, synthetic wastewater was generated in the lab. Batch experiments were conducted to create the best conditions for removing these ions from the wastewater. The optimum conditions obtained were 90 min optimum contact time, and pH equal seven, optimal NNCM dose was 0.5 g/L achieving …

Intelligent Motion Tracking: A Low-Cost Surveillance Framework Using Soc Devices And Sensor Fusion, Aung Myat Khaung, Nicholas Michael Stiffler

Research from the Berry Summer Thesis Institute, 2025

This thesis presents the design and implementation of a lightweight surveillance system capable of realtime motion detection, object tracking, and behavioral history reconstruction in controlled environments. The system uses System-on-Chip devices such as Raspberry Pi boards equipped with NOIR cameras, monocular cameras, and break-beam sensors that work together to detect and track single or multiple moving objects like colored balls. The prototype is validated in structured settings with the goal of eventual deployment in more dynamic environments, addressing the challenge of reliably tracking visually similar objects with minimal distinguishing features. The architecture integrates computer vision with sensor fusion by combining …

An Investigation Of Hydro-Morphological Changes At The Estuarine Outlet Of Kitchener Drain, Northern Coast Of Egypt, Nada Mansour, Karim Nassar, Mahmoud El-Gamal, Tharwat Sarhan

Mansoura Engineering Journal

In recent years, sedimentation and coastline erosion have occurred in the Kitchener Drain, where its outflow meets the Mediterranean Sea. Several measures have been taken to mitigate the impact of these problems. Excavation continues toward the drain's outlet, and there have been multiple stages of hard protection work, such as groins along the drain's eastern and western banks. What would happen if the working near the drain was kept, where accretion and erosion are most severe. The Coastal Modelling System (CMS) was used to find it out. The two-dimensional hydrodynamic circulation model known as the CMS is outfitted with modules …

Learning Neural Point Processes For Long Event Sequences, Zhuoqun Li

LSU Doctoral Dissertations

This research presents a comprehensive series of studies aimed at advancing learning neural point processes for long event sequences, with applications spanning disaster resilience, crime forecasting, and healthcare. Structured around three interconnected studies, this work addresses core challenges in temporal point process (TPP) modeling, efficient handling of long event sequences, and improving accuracy over extended forecasting horizons by reinforcement learning.

The first study proposes the Sparse Transformer Hawkes Process (STHP) to model long asynchronous event sequences. Traditional neural network-based TPPs struggle with long event sequences due to computational inefficiencies. To address this, the STHP model combines two components: a temporal …

Exploring Arabic Large Language Models: A Comprehensive Review, Lamar Aljahdali, Joud Kaki

Effat Undergraduate Research Journal

This paper presents a comprehensive review of Arabic large language models (LLMs), exploring their capabilities, limitations, and potential impact on the Arabic NLP landscape. We analyze the performance of prominent LLMs, including JAIS, AraBERT, and BLOOM, highlighting their strengths and weaknesses on various NLP tasks. The review delves into critical challenges faced by Arabic LLMs, such as domain adaptation, cross-lingual capabilities, and ethical considerations. Additionally, the paper emphasizes the importance of responsible development and deployment practices for LLMs, ensuring fairness, transparency, and cultural sensitivity.

Analog To Digital Converters Topologies For Radar System Application: A Comparison, Kulsoom Mateen, Wafa Alharbi, Aziza I. Hussein

Effat Undergraduate Research Journal

Analog-to-digital converters (ADCs) that convert analog signals into digital ones play a significant role in radar systems. The accuracy and resolution of radar readings are significantly influenced by the quality and performance of ADCs. This paper discusses and compares the application of five different types of ADCs in radar systems. It also elaborates on each ADC's working principle, advantages, and limitations. The parameters compared are resolution and dynamic range, signal-to-noise ratio (SNR), latency and sampling rate, power consumption, size, and cost. After thorough research, we concluded that each ADC differs depending on the designer’s desired application. For example, flash ADCs …

Satellite Internet Technology: Connect The Unconnected, Nora Turki Alamoudi Ms., Aziza I.Hussien Proffessor

Effat Undergraduate Research Journal

Satellite Internet is the internet provided through a network of communication satellite constellations in space. This type of internet can cover an area of a wider range than the commonly used cable internet. The development of small-sized satellite technology in the commercial space sector has entered a vigorous phase of development. However, approximately four billion individuals worldwide lack internet access. Most of these citizens live in developing countries. It is in this context that the industry of satellite internet is expanding its social and economic development through connectivity. The implementation of the idea requires examining the advantages provided by satellite …

Sar Analog-To-Digital Converters For Point-Of-Care Biosensors: A Comparison, Eithar Alammari, Joud Alamro, Sara Alashwali, Ghadah S. Alyami, Aziza I. Hussein

Effat Undergraduate Research Journal

The SAR ADC, recognized for its low power consumption, moderate resolution, and satisfactory processing speed, stands as an ideal choice for ultra-low power biomedical applications. Recent efforts have been concentrated on enhancing the power efficiency of the SAR ADC sub-components through intricate refinements and innovative techniques. These efforts aim to minimize energy consumption without compromising the ADC's performance. Therefore, this paper aims to thoroughly examine various implementation approaches for the main components of the SAR ADC, highlighting their individual strengths, weaknesses, and limitations within wireless biomedical applications.

Electrical Energy Consumption Forecasting Based On Conventional And Artificial Intelligence Methods: A Comparison, Haya H. Binsalim, Jana Kamal, Salma Badaam, Danah Milyani, Ghadah S. Alyami, Aziza I. Hussein

Effat Undergraduate Research Journal

Artificial Intelligence (AI)-based models have been widely applied for energy consumption forecasting over the past decades. The purpose of this paper is to review and compare the classical techniques and the emerging new AI-based techniques used for forecasting electrical energy consumption in buildings. The findings revealed that the Artificial Neural Network (ANN) model achieved the lowest Mean Absolute Percentage Error (MAPE) of 0.928%. AI-based techniques have many advantages over classical techniques, such as their ability to handle a large amount of data and provide accurate and fast results.

Intelligent System Designs For Hvac Energy Reduction In Buildings: Ai-Based Forecasting And Hybrid Active/Passive Approaches, Leena N. Alam, Rim M. Obaid, Thoraya Musa, Wegdan O. Alshateri, Passent M. Elkafrawy Prof

Effat Undergraduate Research Journal

The majority of building energy utilization worldwide is related to HVAC (Heating, Ventilation, and Air-Conditioning) systems. Eighty percent of the energy produced in Saudi Arabia is used by buildings, and since 70\% of that energy is used for ventilation, air conditioning accounts for roughly 50\% of the nation’s electrical use. This study reviewed and compared much research that used various AI-based forecasting algorithms. Specifically, the study explored the potential of passive and active cooling methods and intelligent system designs and used this analysis to develop a hybrid model that combined AI-based forecasting with active/passive approaches for optimal energy savings. The …

Continuous Versus Discrete-Time Sigma-Delta Analog To Digital Converters For Biomedical Applications: A Comparison, Haya H. Binsalim, Batool Alaidroos, Basma Shigdar, Salma Badaam, Aziza I. Hussein

Effat Undergraduate Research Journal

Continuous-time (CT) and discrete-time (DT) sigma-delta (ΔΣ) converters are two commonly used techniques for analog-to-digital conversion. While both methods operate based on the principles of oversampling and noise shaping, they differ in their implementation and performance characteristics. CT ΔΣ converters use analog circuits to sample and process signals continuously, while DT ΔΣ utilizes digital circuits to sample and process signals at discrete intervals. This paper presents a comprehensive comparison between CT and DT ΔΣ converters, highlighting their advantages and limitations. The comparison is made in terms of design complexity, power consumption, signal-to-noise ratio (SNR), and other essential parameters in medical …

Wideband Spectrum Sensing For Cognitive Radio Using Under-Sampled Successive Approximation Adc, Aziza I. Hussein

Effat Undergraduate Research Journal

The radio spectrum, an inherently limited resource, has been increasingly utilized owing to the recent exponential growth of wireless services. This has led to a new approach, termed cognitive radio, predicated upon exploitation of spectrum holes for omnipresent spectrum utilization. This is made possible via cognitive radio networks’ employment of spectrum sensing. Wideband spectrum sensing has been the focal challenge point in cognitive radio technology, since existing techniques are reliant on analog to digital converters (ADC) with sampling at the Nyquist rate. Unfortunately, in order to perform digitization of wideband RF signals at the Nyquist rate, a very high sampling …

Fault Detection In Analog Vlsi Circuits Based On Artificial Intelligence

Effat Undergraduate Research Journal

In thepastdecade,artificialintelligence(AI)hasbeenonthe rise asatooltobeutilizedacrossallthefieldsavailableintheindustry. Specificallyinthemicroelectronicsfield,exploringthecurrentoptionsof VLSI faultdetectionandtheirtypesiscrucialforadvancementandis importantinidentifyingwhetherthereisroomforimprovementorthe optimumisalreadybeingdone.Therefore,thepurposeofthisresearch is tocompareandcontrastbetweenVLSIfaultdetectionindigitaland analog circuitsusingAI.Techniquestoimproveefficiencysuchastrou- bleshootinginsmallsegmentsratherthanthewholesystemandsome resolutions todrawbacksthataren’tdetectibletohumansliketimingare discussed andresolvedinthispaper.Moreover,somenon-idealitiesand risks likemarginalstabilitywereconsidered.Finally,presentelements that areusedintoday’sfaultdetectioncircuitslikeneuralcontrollers and theANNswerediscussedaswell.Currently,theANNsarethemost utilized toolforfaultdiagnosesanddetection;however,forthecontinu- ation ofthistechnology’sgrowth,developersneedtofindmoreefficient methodstomovepastit.

Intelligent Energy Management Mechanisms For Electric Vehicles: A Review, Aziza I. Hussein

Effat Undergraduate Research Journal

This paper investigates intelligent methods used for energy management (EM) in Electric Vehicles (EV). The key role of EM in EVs to increase the performance of the vehicle and reduce Fuel Consumption (FC) thus producing less greenhouse effect. However, the used tactics had limitations. An introduced model of Intelligent Energy Management System (IEMS) for Plug-in hybrid electric vehicles (PHEVs) was efficient for FC reduction. Whereas for IEMS Based on Kalman Filtering showed a low percentage of error. While EM using Tags Threshold Admission And Greedy Scheduling improves EV’s performance, but it can only manage energy per one EV. Another model …

Electrical Energy Consumption Forecasting Analysis Based On Conventional And Artificial Intelligence Methods: A Comparison, Aziza I. Hussein

Effat Undergraduate Research Journal

Artificial intelligence (AI)-based models have been widely applied for energy consumption forecasting over the past decades. The purpose of this paper is to review the classical techniques and the emerging new techniques based on AI of the building electrical energy consumption forecasting. The advantages of AI-based techniques over the classical are that AI methods can handle a large amount of data yet gives accurate results, the results can be found very quickly, in addition to AI having the ability to solve complex nonlinear patterns of raw data. This paper will discuss several studies using different models of forecasting based on …

Posture - A Framework With Measures And Mediating Effects In Support Of A Structural Model For Attitude In Identity Formation, Christopher Kyle Prather

Doctoral Dissertations

This dissertation develops a framework and new, valid, abbreviated instruments for researching engineering identity formation as an evolving relational and attitudinal development process rather than a fixed outcome. The framework centers on “posture”, a mediating effect analogous to physical posture in human factors engineering. The investigation was unique, and developed evidence for a structural model using an interdisciplinary, systems-oriented approach. Methodologically, a clinical measure of internal emotional states from the Marriage and Family Therapy literature was administered alongside existing scales for perseverance, perceived workload, and psychological ownership. This study used the broad coverage of the clinical instrument to search for …

Evaluation Of The Performance Of The Traveling Wave Differential Element In Protective Relays, Niranjan Kc

Master's Theses

This thesis evaluates the dependability, security, and limitations of the traveling wave differential protection function (TW87) in modern time-domain-based protective relays, using a combination of simulations and hardware testing in a laboratory environment. Fault transients are first generated using the electromagnetic transients program model of a real, 230 kV, 65.7 km long overhead transmission line, which are then played back on real time-domain-based protective relays. Various fault scenarios are chosen to evaluate the impacts of factors such as fault inception angle, distance to fault from line terminals, fault type, fault impedance, and external faults on the relay functions’ performance. Results …