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A dual attention-based deep learning model for lithology identificationwhile drilling 认领 引用 被引量：3
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作者 Jie Chen Zhen Gui +6 位作者 Yichao Rui Xusheng Zhao Xiaokang Pan Qingfeng Wang Yuanyuan Pu Zheng Li Maoyi Liu 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第2期1177-1192,共16页
Lithology identificationwhile drilling technology can obtain rock information in real-time.However,traditional lithology identificationmodels often face limitations in feature extraction and adaptability to complex ge... Lithology identificationwhile drilling technology can obtain rock information in real-time.However,traditional lithology identificationmodels often face limitations in feature extraction and adaptability to complex geological conditions,limiting their accuracy in challenging environments.To address these challenges,a deep learning model for lithology identificationwhile drilling is proposed.The proposed model introduces a dual attention mechanism in the long short-term memory(LSTM)network,effectively enhancing the ability to capture spatial and channel dimension information.Subsequently,the crayfishoptimization algorithm(COA)is applied to optimize the model network structure,thereby enhancing its lithology identificationcapability.Laboratory test results demonstrate that the proposed model achieves 97.15%accuracy on the testing set,significantlyoutperforming the traditional support vector machine(SVM)method(81.77%).Field tests under actual drilling conditions demonstrate an average accuracy of 91.96%for the proposed model,representing a 14.31%improvement over the LSTM model alone.The proposed model demonstrates robust adaptability and generalization ability across diverse operational scenarios.This research offers reliable technical support for lithology identification while drilling. 展开更多
关键词 Lithology identificationwhile drilling Deep learning Dual attention mechanism Metaheuristic algorithm Field applications
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Real-Time Image and Video Artistic Style Rendering System Based on GPU 认领 引用 被引量：1
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作者 Yang Zhao Guowu Yuan +2 位作者 Hao Wu Yuanyuan Pu Dan Xu 《国际计算机前沿大会会议论文集》 EI 2021年第1期314-338,共25页
Aiming at the practical engineering application of video stylization,in this paper, a GPU-based video art stylization algorithm is proposed, and areal-time video art stylization rendering system is implemented. The fo... Aiming at the practical engineering application of video stylization,in this paper, a GPU-based video art stylization algorithm is proposed, and areal-time video art stylization rendering system is implemented. The four mostcommon artistic styles including cartoon, oil painting, pencil painting and watercolorpainting are realized in this system rapidly. Moreover, the system makesgood use of the GPU’s parallel computing characteristics, transforms the videostylized rendering algorithm into the texture image rendering process, acceleratesthe time-consuming pixel traversal processing in parallel and avoids the loop processingof the traditional CPU. Experiments show that the four art styles achievedgood results, and the system has a good interactive experience. 展开更多
关键词 Non-photorealistic rendering GPU Structure tensor Line integral convolution Kuwahara filter
Locating acoustic emission sources in pseudo-triaxial experiments with the shortest path and orthogonal constraint 认领 引用
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作者 Yichao Rui Yuanyuan Pu +5 位作者 Jie Chen Cunjin Zhu Sheng Zhang Jiongkun Chen Zelin Zhou Wenzhong Wang 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2025年第9期5453-5464,共12页
Acoustic waves in the pseudo-triaxial experiment system experience refraction phenomena.The conventional assumption that acoustic waves propagate along a straight line in traditional methods can lead to significant er... Acoustic waves in the pseudo-triaxial experiment system experience refraction phenomena.The conventional assumption that acoustic waves propagate along a straight line in traditional methods can lead to significant errors in localization results.To the end,this paper presents a method for locating acoustic emission(AE)sources in pseudo-triaxial experiments using shortest paths and orthogonal constraints.The approach consists of three main steps:(1)establishing control equations for refraction paths from AE sources to sensor locations;(2)calculating refraction point locations using the shortest travel principle and orthogonal constraints;(3)determining source coordinates using Taylor's first-order expansion.The results from laboratory AE experiments demonstrate that the average localization accuracy of the new method is only 6.5 mm,which is 66%more precise than the accuracy(19.4 mm)of the traditional method.Furthermore,simulation results indicate that the new method is not affected by the refraction ratio of the media and maintains the highest positioning accuracy across various arrival and velocity errors. 展开更多
关键词 Acoustic emission(AE) Source localization Pseudo-triaxial experiment Shortest path Orthogonal constraint
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Machine learning methods for rockburst prediction-state-of-the-art review 认领 引用 被引量：48
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作者 Yuanyuan Pu Derek B.Apel +1 位作者 Victor Liu Hani Mitri 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2019年第4期565-570,共6页
One of the most serious mining disasters in underground mines is rockburst phenomena.They can lead to injuries and even fatalities as well as damage to underground openings and mining equipment.This has forced many re... One of the most serious mining disasters in underground mines is rockburst phenomena.They can lead to injuries and even fatalities as well as damage to underground openings and mining equipment.This has forced many researchers to investigate alternative methods to predict the potential for rockburst occurrence.However,due to the highly complex relation between geological,mechanical and geometric parameters of the mining environment,the traditional mechanics-based prediction methods do not always yield precise results.With the emergence of machine learning methods,a breakthrough in the prediction of rockburst occurrence has become possible in recent years.This paper presents a state-ofthe-art review of various applications of machine learning methods for the prediction of rockburst potential.First,existing rockburst prediction methods are introduced,and the limitations of such methods are highlighted.A brief overview of typical machine learning methods and their main features as predictive tools is then presented.The current applications of machine learning models in rockburst prediction are surveyed,with related mechanisms,technical details and performance analysis. 展开更多
关键词 Rockburst prediction Burst liability Artificial neural network Support vector machine Deep learning
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Numerical modeling for rockbursts:A state-of-the-art review 认领 引用 被引量：21
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作者 Jun Wang Derek B.Apel +3 位作者 Yuanyuan Pu Robert Hall Chong Wei Mohammadali Sepehri 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2021年第2期457-478,共22页
As the depth of excavation increases,rockburst becomes one of the most serious geological hazards damaging equipment and facilities and even causing fatalities in mining and civil engineering.This has forced researche... As the depth of excavation increases,rockburst becomes one of the most serious geological hazards damaging equipment and facilities and even causing fatalities in mining and civil engineering.This has forced researchers worldwide to identify different methods to investigate rockburst-related problems.However,some problems,such as the mechanisms and the prediction of rockbursts,continue to be studied because rockburst is a very complicated phenomenon influenced by the uncertainty and complexity in geological conditions,in situ stresses,induced stresses,etc.Numerical modeling is a widely used method for investigating rockbursts.To date,great achievements have been made owing to the rapid development of information technology(IT)and computer equipment.Hence,it is necessary and meaningful to conduct a review of the current state of the studies for rockburst numerical modeling.In this paper,the categories and the origin of different numerical approaches employed in modeling rockbursts are reviewed and the current usage of various numerical modeling approaches is investigated by a literature research.Later,a state-of-the-art review is implemented to investigate the application of numerical modeling in the mechanism study,and prediction and prevention of rockbursts.The main achievements and problems are highlighted.Finally,this paper discusses the limitations and the future research of numerical modeling for rockbursts.An approach is proposed to provide researchers with a systematic and reasonable numerical modeling framework. 展开更多
关键词 Rockburst Numerical modeling Rockburst mechanism Dynamic modeling
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Assessment of digital image correlation method in determining large scale cemented rockfill strains 认领 引用 被引量：11
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作者 Bob A.Lingga Derek B.Apel +1 位作者 Mohammadali Sepehri Yuanyuan Pu 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2019年第5期771-776,共6页
A conventional contact method(using linear transducers)and a non-contact method are deployed to measure the axial and lateral deformations of large scale cylindrical cemented rockfill specimens.Experimental works inco... A conventional contact method(using linear transducers)and a non-contact method are deployed to measure the axial and lateral deformations of large scale cylindrical cemented rockfill specimens.Experimental works incorporating two pinhole cameras to create one stereovision by digital image correlation shows that the non-contact method is as reliable for testing large cylindrical specimens as measurements done by using linear variable displacement transformer and string potentiometer.Considering this particular large specimen,the experiment resulted in the acceptable mean difference between lateral strain using both methods is 5.1 percent,and 14.5 percent for the axial strain.This occurrence is inevitable due to the heterogeneity of the concrete system and the placement of the monitoring point in digital image correlation method,although the comparison of stress-strain relationship in both methods still indicates a conformity.Based on the results of the present experiments,the authors recommend the noncontact method for a detailed investigation of the material behavior during the uniaxial compressive strength tests.Full field strain measurement enables this digital method to examine local strains near cracks at any point,a very useful tool for studying material deformation behavior. 展开更多
关键词 Experimental testing Cemented rockfill Digital image correlation Strain measurement Mine backfill
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Enhancing microseismic/acoustic emission source localization accuracy with an outlier-robust kernel density estimation approach 认领 引用 被引量：8
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作者 Jie Chen Huiqiong Huang +4 位作者 Yichao Rui Yuanyuan Pu Sheng Zhang Zheng Li Wenzhong Wang 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2024年第7期943-956,共14页
Monitoring sensors in complex engineering environments often record abnormal data,leading to significant positioning errors.To reduce the influence of abnormal arrival times,we introduce an innovative,outlier-robust l... Monitoring sensors in complex engineering environments often record abnormal data,leading to significant positioning errors.To reduce the influence of abnormal arrival times,we introduce an innovative,outlier-robust localization method that integrates kernel density estimation(KDE)with damping linear correction to enhance the precision of microseismic/acoustic emission(MS/AE)source positioning.Our approach systematically addresses abnormal arrival times through a three-step process:initial location by 4-arrival combinations,elimination of outliers based on three-dimensional KDE,and refinement using a linear correction with an adaptive damping factor.We validate our method through lead-breaking experiments,demonstrating over a 23%improvement in positioning accuracy with a maximum error of 9.12 mm(relative error of 15.80%)—outperforming 4 existing methods.Simulations under various system errors,outlier scales,and ratios substantiate our method’s superior performance.Field blasting experiments also confirm the practical applicability,with an average positioning error of 11.71 m(relative error of 7.59%),compared to 23.56,66.09,16.95,and 28.52 m for other methods.This research is significant as it enhances the robustness of MS/AE source localization when confronted with data anomalies.It also provides a practical solution for real-world engineering and safety monitoring applications. 展开更多
关键词 Microseismic source/acoustic emission(MS/AE) Kernel density estimation(KDE) Damping linear correction Source location Abnormal arrivals
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A genomic variation map provides insights into potato evolution and key agronomic traits 认领 引用 被引量：4
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作者 Qun Lian Yingying Zhang +25 位作者 Jinzhe Zhang Zhen Peng Weilun Wang Miru Du Hongbo Li Xinyan Zhang Lin Cheng Ran Du Zijian Zhou Zhenqiang Yang Guohui Xin Yuanyuan Pu Zhiwen Feng Qian Wu Guochao Xuanyuan Shunbuer Bai Rong Hu Sónia Negrao Glenn J.Bryan Christian W.B.Bachem Yongfeng Zhou Ruofang Zhang Yi Shang Sanwen Huang Tao Lin Jianjian Qi 《Molecular Plant》 SCIE CAS CSCD 2025年第4期570-589,共20页
Hybrid potato breeding based on diploid inbred lines is transforming the way of genetic improvement of this staple food crop,which requires a deep understanding of potato domestication and differentiation.In the prese... Hybrid potato breeding based on diploid inbred lines is transforming the way of genetic improvement of this staple food crop,which requires a deep understanding of potato domestication and differentiation.In the present study,we resequenced 314 diploid wild and landrace accessions to generate a variome map of 47,203,407 variants.Using the variome map,we discovered the reshaping of tuber transcriptome during potato domestication,characterized genome-wide differentiation between landrace groups Stenotomum and Phureja.We identified a jasmonic acid biosynthetic gene possibly affecting the tuber dormancy period.Genome-wide association studies revealed a UDP-glycosyltransferase gene for the biosynthesis of anti-nutritional steroidal glycoalkaloids(SGAs),and a Dehydration Responsive Element Binding(DREB)transcription factor conferring increased average tuber weight.In addition,genome similarity and group-specific SNP analyses indicated that tetraploid potatoes originated from the diploid Solanum tuberosum group Stenotomum.These findings shed light on the evolutionary trajectory of potato domestication and improvement,providing a solid foundation for advancing hybrid potato-breeding practices. 展开更多
关键词 potato domestication differentiation tuber dormancy steroidal glycoalkaloids average tuber weight
Exploring machine learning techniques for open stope stability prediction:A comparative study and feature importance analysis 认领 引用
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作者 Alicja Szmigiel Derek B.Apel +2 位作者 Yashar Pourrahimian Hassan Dehghanpour Yuanyuan Pu 《Rock Mechanics Bulletin》 CSCD 2025年第3期39-52,共14页
The stability of underground excavations is essential for ensuring the safety of mining operations.Classical stability assessment methods,established in empirical formulas and rock mass classification systems,have lon... The stability of underground excavations is essential for ensuring the safety of mining operations.Classical stability assessment methods,established in empirical formulas and rock mass classification systems,have long been employed for evaluating stope stability in underground mining.Stability graphs,a popular empirical approach,utilize factors like rock stress,joint orientation,and surface orientation to calculate stability numbers critical for stope design.However,modern advancements in machine learning present new opportunities for enhancing predictive capabilities and understanding complex relationships influencing stope stability.Building upon research demonstrating the feasibility of using machine learning for stability prediction,our study investigates and compares several machine learning algorithms.By analyzing a dataset comprising stope dimensions and geomechanical properties,we explore the potential of machine learning models such as Random Forest,Support Vector Machine,AdaBoost,XGBoost,LightGBM,and Artificial Neural Network in predicting stope stability.Evaluation metrics including accuracy,precision,recall,and F1 score are employed to assess model performance,with the Artificial Neural Network emerging as the most effective.Furthermore,SHapley Additive exPlanations(SHAP)analysis enhances interpretability by explaining the contribution of individual features to model predictions. 展开更多
关键词 Machine learning Stope stability Feature importance Artificial neural network
A systematic review of Coda Wave Interferometry technique for evaluating rock behavior properties:From single to multiple perturbations 认领 引用
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作者 Jie Chen Chao Zhu +3 位作者 Yuanyuan Pu Yichao Rui Bo Liu Derek B.Apel 《Earth Energy Science》 2025年第2期180-192,共13页
Understanding rock behavior is crucial in mine geotechnical engineering to ensure construction efficiency,mitigate rock-related hazards,and promote environmental sustainability.Coda Wave Interferometry(CWI),a non-dest... Understanding rock behavior is crucial in mine geotechnical engineering to ensure construction efficiency,mitigate rock-related hazards,and promote environmental sustainability.Coda Wave Interferometry(CWI),a non-destructive ultrasonic testing method,has been widely employed to assess micro-damage evolution in rocks induced by perturbations in scatterer position,velocity,or source location due to its exceptional sensitivity.However,challenges persist in evaluating cross-scale rock behavior influenced by nonlinear deformation and multi-field interactions under multiple coupled perturbations.A comprehensive review of the perturbation factors affecting rock damage evolution and potential failure mechanisms is essential for presenting available knowledge in a more systematic and structured manner.This review provides an in-depth analysis of the CWI technique,encompassing its origins,theoretical framework,and classical data processing methodologies.Additionally,it explores the diverse applications of CWI in assessing rock behavior under various perturbation factors,including temperature variations,fluid infiltration,and stress conditions,with a particular emphasis on nonlinear deformation and multi-field coupling effects.Furthermore,a novel method for calculating relative velocity changes in coda waves is introduced,enabling a more precise characterization of the entire rock failure process.The study also proposes a cutting-edge concept of ultra-early and refined monitoring and warning technology for mine rock disasters,leveraging the advancements in CWI.Finally,the review highlights the potential future developments of CWI in high-level intelligent mining scenarios,particularly its integration with ambient noise interferometry and microseismic coda wave analysis.This work serves as a valuable reference,contributing to the refinement of CWI applications for assessing complex rock behavior and enhancing the accuracy of rock disaster prediction and early warning systems. 展开更多
关键词 Non-destructive monitoring Coda wave interferometry technique Nonlinear deformation Multi-field coupling Rock disasters warning
Study on instability fracture and simulation of surrounding rock induced by fault activation under mining influence 认领 引用 被引量：12
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作者 Jie Chen Kaiwen Shi +7 位作者 Yuanyuan Pu Derek B.Apel Chuanjiu Zhang Yujun Zuo Jiongkun Chen Le Xu Zhen Gui Longfei Song 《Rock Mechanics Bulletin》 2023年第2期32-40,共9页
The fault is potentially vulnerability's geological structure in the working face and its vicinity,and it is also a crucial geological factor affecting coal mine safety exploitation.To investigate the unstable fai... The fault is potentially vulnerability's geological structure in the working face and its vicinity,and it is also a crucial geological factor affecting coal mine safety exploitation.To investigate the unstable failure of surrounding rock induced by fault activation under the influence of adoption,which was studied utilizing field case and numerical analysis for the deformation and failure process of surrounding rock near the fault-affected zone.Combined with field cases,this paper analyzes disturbance stress and roof abscission layer monitoring in effecting zones of fault activation.Using the discrete element 3DEC numerical analysis method,the model of surrounding rock unstable fracture induced by fault activation under adoption is established.The unstable fracture and stress variation characteristics of surrounding rock induced by fault activation during the excavation of the upper side wall and lower side wall of the faults are simulated and analyzed.Field analysis shows that as the coal working face continues to advance,the mining stress gradually increases.There is a zigzag wave on the relationship curve between coal mining and roof displacement near the fault,which reveals that the surrounding rock of the fault activation affected zone is in the superposition state of static load and dynamic load.Furthermore,the simulation results show that the stress and displacement of surrounding rock near the fault increase with the advance of coal mining face.The closer to the fault plane,the displacement gradually returns to zero,and the stress is also in a lower state. 展开更多
关键词 Surrounding rock mining Fault activation Instability fracture Simulation analysis
Developing a new model system for potato genetics by androgenesis 认领 引用 被引量：2
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作者 Miru Du Ting Wang +5 位作者 Qun Lian Xiaojie Zhang Guohui Xin Yuanyuan Pu Glenn JBryan Jianjian Qi 《Journal of Integrative Plant Biology》 SCIE CAS CSCD 2021年第4期628-633,共6页
High heterozygosity and tetrasomic inheritance complicate studies of asexually propagated polyploids,such as potato.Reverse genetics approaches,especially mutant library construction,can be an ideal choice if a proper... High heterozygosity and tetrasomic inheritance complicate studies of asexually propagated polyploids,such as potato.Reverse genetics approaches,especially mutant library construction,can be an ideal choice if a proper mutagenesis genotype is available.Here,we aimed to generate a model system for potato research using anther cultures of Solanum verrucosum,a self-compatible diploid potato with strong late blight resistance.Six of the 23 regenerants obtained(SVA4,SVA7,SVA22,SVA23,SVA32,and SVA33)were diploids,and their homozygosity was estimated to be>99.99%with 22 polymorphic In Del makers.Two lines-SVA4 and SVA32-had reduced stature(plant height≤80 cm),high seed yield(>1,000 seeds/plant),and good tuber set(>30 tubers/plant).We further confirmed the full homozygosity of SVA4 and SVA32 using wholegenome resequencing.These two regenerants possess all the characteristics of a model plant:diploidy,100%homozygosity,self-compatibility,and amenability to transgenesis.Thus,we have successfully generated two lines,SVA4 and SVA32,which can potentially be used for mutagenesis and as model plants to rejuvenate current methods of conducting potato research. 展开更多
关键词 diploid potato homozygous model system self-compatible Solanum verrucosum
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