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Prediction of bearing capacity of pile foundation using deep learning approaches

Frontiers of Structural and Civil Engineering 2024年第6期18卷 870-886页

作者： Manish KUMAR Divesh Ranjan KUMAR Jitendra KHATTI Pijush SAMUI Kamaldeep Singh GROVER Department of Civil Engineering SRM Institute of Science and Technology Tiruchirappalli CampusTrichy 621105India Department of Civil Engineering National Institute of Technology PatnaBihar 800005India Department of Civil Engineering Faculty of EngineeringThammasat School of EngineeringThammasat UniversityBangkok10200Thailand Department of Civil Engineering Rajasthan Technical UniversityKota 324010India

The accurate prediction of bearing capacity is crucial in ensuring the structural integrity and safety of pile *** research compares the Deep Neural Networks(DNN),Convolutional Neural Networks(CNN),Recurrent Neural Networks(RNN),Long Short-Term Memory(LSTM),and Bidirectional LSTM(BiLSTM)algorithms utilizing a data set of 257 dynamic pile load tests for the first ***,this research illustrates the multicollinearity effect on DNN,CNN,RNN,LSTM,and BiLSTM models’performance and accuracy for the first time.A comprehensive comparative analysis is conducted,employing various statistical performance parameters,rank analysis,and error matrix to evaluate the performance of these *** performance is further validated using external validation,and visual interpretation is provided using the regression error characteristics(REC)curve and Taylor *** from the comparative analysis reveal that the DNN(Coefficient of determination(R^(2))_(training(TR))=0.97,root mean squared error(RMSE)_(TR)=0.0413;R^(2)_(testing(TS))=0.9,RMSE_(TS)=0.08)followed by BiLSTM(R^(2)_(TR)=0.91,RMSE_(TR)=0.782;R^(2)_(TS)=0.89,RMSE_(TS)=0.0862)model demonstrates the highest performance *** is noted that the BiLSTM model is better than LSTM because the BiLSTM model,which increases the amount of information for the network,is a sequence processing model made up of two LSTMs,one of which takes the input in a forward manner,and the other in a backward *** prediction of pile-bearing capacity is strongly influenced by ram weight(having a considerable multicollinearity level),and the effect of the considerable multicollinearity level has been determined for the model based on the recurrent neural network *** this study,the recurrent neural network model has the least performance and accuracy in predicting the pile-bearing capacity.

关键词： deep learning algorithms high-strain dynamic pile test bearing capacity of the pile

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Multi-Axis Attention With Convolution Parallel Block for Organoid Segmentation

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1295-1297页

作者： Pengwei Hu Xun Deng Feng Tan Lun Hu Xinjiang technical institute of Physics and Chemistry Chinese Academy of SciencesUrumqi 830011 University of Chinese Academy of Sciences Beijing 100049 Xinjiang Laboratory of Minority Speech and Language Information Processing Urumqi 830011China Merck KGaA Darmstadt 64293Germany

Dear Editor,This letter presents an organoid segmentation model based on multi-axis attention with convolution parallel *** adeptly captures dynamic dependencies within bright-field microscopy images,improving global ... 详细信息

关键词： letter convolution organo

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Synergistic extraction of rare earth elements and alumina from coal fly ash by potassium pyrosulfate

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Journal of Rare Earths 2024年第4期42卷 749-758页

作者： Jingjing Zou Yiping Sun Chunbin Guo Daye Chen Yonghong Song Yongfeng Wu Zhaotianhui Li Department of Environment Science and Engineering Liaoning Technical UniversityFuxin23000China Department of Materials Science and Engineering Liaoning Technical UniversityFuxin123000 China Technology Research and Development Department Chinese Institute of Coal ScienceBeijing100013China Shenhua Zhungeer Energy and Resource Comprehensive Development Co. Ltd.Erdos10300China Liaoning Yingguan High-tech Ceramic Co. Ltd.Jinzhou121213China

Although coal fly ash(CFA)contains a high content of rare earth elements(REEs),the related extraction methods have limitations because of their low efficiencies,high levels of energy consumption,and other *** address these problems,in this study,we examined the coextraction of REEs and Al_(2)O_(3)from two types of Al_(2)O_(3)-rich CFA,pulverized CFA(PCFA)and circulating fluidized bed fly ash(CFBFA)using low-temperature calcination in the presence of K_(2)S_(2)O_(7).The total REEs,heavy REEs(HREEs),and light REEs(LREEs)extraction efficiencies were determined using different K_(2)S_(2)O_(7)/Al_(2)O_(3) molar ratios and calcination temperatures and correlated with the Al_(2)O_(3) extraction efficiency using Pearson correlation coefficient *** REEs are concentrated within CFA particles encapsulated in an aluminosilicate glass phase,and the REEs extraction efficiency is related to the form of Al in *** extraction efficiencies of Al_(2)O_(3) and REEs increase as the K_(2)S_(2)O_(7)/Al_(2)O_(3) molar ratio and calcination temperature increase,and the extraction selectivity of the more industrially valuable HREEs from CFBFA is *** high K_(2)S_(2)O_(7)/Al_(2)O_(3) molar ratios,the extraction of REEs from PCFA is more efficient than that from CFBFA with the regeneration of the highly active Al-O-Si bonds in *** Al_(2)O_(3) extraction efficiencies of PCFA as well as CFBFA correlate strongly with the total REEs,HREEs,and LREEs extraction *** developed extraction technology has the potential to promote CFA valorization and expand REEs resources,thus mitigating the bottlenecks of REEs procurement.

关键词： Rare earths Alumina Coal fly ash Potassium pyrosulfate Calcination Extraction

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Understanding host-graft crosstalk for predicting the outcome of stem cell transplantation

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World Journal of Stem Cells 2024年第3期16卷 232-236页

作者： Luminita Labusca Florin Zugun-Eloae Magnetic Materials and Sensors National Institute of Research and Development for Technical PhysicsIasi 700050Romania Orthopedics and Trauma Emergency County Hospital Saint SpiridonIasi 700000Romania Transcend Regional Oncology InstituteIasi 7000000Romania

Mesenchymal stromal cells(MSCs)hold great promise for tissue regeneration in debilitating *** reported improvements,the short-term outcomes of MSC transplantation,which is possibly linked to poor cell survival,demand extensive ***-associated stress microenvironments further complicate *** debate underscores the need for a deeper understanding of the phenotypes of transplanted MSCs and their environment-induced ***,questions arise about how to predict,track,and comprehend cell fate *** vivo cellular imaging has emerged as a critical requirement for both short-and long-term safety and efficacy ***,translating preclinical imaging methods to clinical settings remains *** fate and function of transplanted cells within the host environment present intricate challenges,including MSC engraftment,variability,and inconsistencies between preclinical and clinical *** study explored the impact of high glucose concentrations on MSC survival in diabetic environments,emphasizing mitochondrial *** these factors may enhance MSC survival,suggesting potential strategies involving genetic modification,biomaterials,and *** stressors in diabetic patients is crucial for predicting the effects of MSC-based *** multifaceted challenges call for a holistic approach involving the incorporation of large-scale data,computational disease modeling,and possibly artificial intelligence to enable deterministic insights.

关键词： Mesenchymal stem cells Phenotype Transplantation Host Microenvironment Cellular imaging Diabetes mellitus

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Early Detection of Colletotrichum Kahawae Disease in Coffee Cherry Based on Computer Vision Techniques

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 759-782页

作者： Raveena Selvanarayanan Surendran Rajendran Youseef Alotaibi Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical ScienceChennai602105India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia

Colletotrichum kahawae(Coffee Berry Disease)spreads through spores that can be carried by wind,rain,and insects affecting coffee plantations,and causes 80%yield losses and poor-quality coffee *** deadly disease is hard to control because wind,rain,and insects carry *** researchers utilized a deep learning system to identify CBD in coffee cherries at three growth stages and classify photographs of infected and uninfected cherries with 93%accuracy using a random forest *** the dataset is too small and noisy,the algorithm may not learn data patterns and generate accurate *** overcome the existing challenge,early detection of Colletotrichum Kahawae disease in coffee cherries requires automated processes,prompt recognition,and accurate *** proposed methodology selects CBD image datasets through four different stages for training and *** to train a model on datasets of coffee berries,with each image labeled as healthy or *** themodel is trained,SHAP algorithmto figure out which features were essential formaking predictions with the proposed *** of these characteristics were the cherry’s colour,whether it had spots or other damage,and how big the Lesions *** inception is important for classification to virtualize the relationship between the colour of the berry is correlated with the presence of *** evaluate themodel’s performance andmitigate excess fitting,a 10-fold cross-validation approach is *** involves partitioning the dataset into ten subsets,training the model on each subset,and evaluating its *** comparison to other contemporary methodologies,the model put forth achieved an accuracy of 98.56%.

关键词： Computer vision coffee berry disease colletotrichum kahawae XG boost shapley additive explanations

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Comparative chemical sensor for detection of chromium(VI) in aqueous solution

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Optoelectronics Letters 2024年

作者： Sura H. AL-Rekabi A.A.Alwahib Electrical Technique Department， Al Suwayrah technical institute， Middle technical University Laser and Optoelectronics Department， University of Technology-Iraq

A process for purifying aqueous solutions containing heavy and toxic metals such as chromium has been investigated. One of the extremely harmful pollutants in rivers and seawater are the heavy metal ions due to their direct impact on human， animals and plants are hexavalent chromium Cr （VI）. Consequently， highly sensitive sensor to detect Chromium is essential. Surface Plasmon resonance （SPR） technique has attracted huge research interest in detecting heavy metals specifically. In this study， three types of prism-based SPR sensor; gold （Au）/silver （Ag）， Au/polyaniline （PANI） and Au/ titanium dioxide (TiO2) nanostructured films are investigated as potential sensing material to detect the presence of Cr （VI） ions in water. The base Au layer with thickness of 48.3 nm is deposited on a glass slide for all sensors. For Au/Ag， Au/PANI nanofibers and Au/ (TiO2) sensor films， the Cr （VI） concentration is varied from 1 to 15 ppm with sensitivity of 0.270 o ppm-1， 0.082o ppm-1and 0.039 o ppm-1 respectively. Based on these results， the Au/ PANI nanofibers are the most sensitive to chromium Cr （VI） among tested sensing materials.

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Mechanism of cross-level settlements and void accumulation of wide and conventional sleepers in railway ballast

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Railway Engineering Science 2024年第3期32卷 361-383页

作者： Olga Nabochenko Mykola Sysyn Norman Krumnow Szabolcs Fischer institute of Railway Systems and Public Transport Technical University of DresdenDresdenGermany Rhomberg Sersa Deutschland GmbH BerlinGermany Central Campus Győr Széchenyi István UniversityGyorHungary

The cross-level and twist irregularities are the most dangerous irregularity types that could cause wheel unloading with the risk of derailments and additional maintenance ***,the mechanism of the irregularities initiation and development is *** motivation of the present study was the previous experimental studies on the application of wide sleepers in the ballasted *** long-term track geometry measurements with wide sleepers show an enormous reduction of the vertical longitudinal irregularities compared to the conventional ***,wide sleepers had higher twist and cross-section level *** present paper aims to explain the phenomenon by discrete element method(DEM)modeling the development process of sleeper inhomogeneous support at cross-level depending on the sleeper *** DEM simulations show that the maximal settlement intensity is up to 3.5 times lower for a wide sleeper in comparison with the conventional ***,the cross-level differential settlements are almost the same for both *** particle loading distribution after all loading cycles is concentrated on the smaller area,up to the half sleeper length,with fully unloaded zones under sleeper *** flow limitation under the central part of the sleeper could improve the resilience of wide sleepers to the development of cross-level *** mechanism of initiation of the cross-level irregularity is proposed,which assumes the loss of sleeper support under sleeper *** further growth of inhomogeneous settlements along the sleeper is assumed as a result of the interaction of two processes:ballast flow due to dynamic impact during void closing and on the other side high pressure due to the concentration of the pressure under the middle part of the *** DEM simulation results support the assumption of the mechanism and agree with the experimental studies.

关键词： Wide sleeper Ballasted track Sleeper support inhomogeneity Sleeper foot form Discrete element modeling Void accumulation

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Advancing oxygen separation:insights from experimental and computational analysis of La_(0.7)Ca_(0.3)Co_(0.3)Fe_(0.6)M_(0.1)O_(3-δ)(M=Cu,Zn)oxygen transport membranes

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Frontiers of Chemical Science and Engineering 2024年第6期18卷 17-29页

作者： Guoxing Chen Wenmei Liu Marc Widenmeyer Xiao Yu Zhijun Zhao Songhak Yoon Ruijuan Yan Wenjie Xie Armin Feldhoff Gert Homm Emanuel Ionescu Maria Fyta Anke Weidenkaff Fraunhofer Research Institution for Materials Recycling and Resource Strategies IWKS Alzenau 63755Germany Electrochemistry Laboratory Paul Scherrer InstituteVilligen PSI 5232Switzerland Department of Materials and Earth Sciences Materials and ResourcesTechnical University of DarmstadtDarmstadt 64287Germany institute of Physical Chemistry and Electrochemistry Leibniz University HannoverHannover 30167Germany institute for Computational Physics University of StuttgartStuttgart 70569Germany Computational Biotechnology RWTH AachenAachen 52074Germany

In this study,perovskite-type La_(0.7)Ca_(0.3)Co_(0.3)Fe_(0.6)M_(0.1)O_(3-δ)(M=Cu,Zn)powders were synthesized using a scalable reverse co-precipitation method,presenting them as novel materials for oxygen transport *** comprehensive study covered various aspects including oxygen permeability,crystal structure,conductivity,morphology,CO_(2) tolerance,and long-term regenerative durability with a focus on phase structure and *** membrane La_(0.7)Ca_(0.3)Co_(0.3)Fe_(0.6)M_(0.1)O_(3-δ)exhibited high oxygen permeation fluxes,reaching up to 0.88 and 0.64 mL·min^(−1)·cm^(−2) under air/He and air/CO_(2) gradients at 1173 K,*** 1600 h of CO_(2) exposure,the perovskite structure remained intact,showcasing superior CO_(2) resistance.A combination of first principles simulations and experimental measurements was employed to deepen the understanding of Cu/Zn substitution effects on the structure,oxygen vacancy formation,and transport behavior of the *** findings underscore the potential of this highly CO_(2)-tolerant membrane for applications in high-temperature oxygen *** enhanced insights into the oxygen transport mechanism contribute to the advancement of next-generation membrane materials.

关键词： perovskite oxygen permeation membrane oxygennionsdiffusiono xygen vacancy formation energy energy barrier

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Multi-Branch Fault Line Location Method Based on Time Difference Matrix Fitting

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Energy Engineering 2024年第1期121卷 77-94页

作者： Hua Leng Silin He Jian Qiu Feng Liu Xinfei Huang Jiran Zhu School of Electrical and Information Engineering Hunan UniversityChangsha410082China Distribution Network technical Center State Grid Hunan Electric Power Research InstituteChangsha410007China technical Center China Energy Construction Group Hunan Thermal Power ConstructionZhuzhou412011China School of Electrical and Information Engineering Changsha University of Science and TechnologyChangsha410076China

The distribution network exhibits complex structural characteristics,which makes fault localization a challenging *** when a branch of the multi-branch distribution network fails,the traditional multi-branch fault location algorithm makes it difficult to meet the demands of high-precision fault localization in the multi-branch distribution network *** this paper,the multi-branch mainline is decomposed into single branch lines,transforming the complex multi-branch fault location problem into a double-ended fault location *** on the different transmission characteristics of the fault-traveling wave in fault lines and non-fault lines,the endpoint reference time difference matrix S and the fault time difference matrix G were *** time variation rule of the fault-traveling wave arriving at each endpoint before and after a fault was comprehensively *** realize the fault segment location,the least square method was *** was used to find the first-order fitting relation that satisfies the matching relationship between the corresponding row vector and the first-order function in the two matrices,to realize the fault segment ***,the time difference matrix is used to determine the traveling wave velocity,which,combined with the double-ended traveling wave location,enables accurate fault location.

关键词： Multi-branch lines distribution network fault location double-ended traveling wave positioning least square method

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Improving Heat Transfer Performance of Flat Plate Water Solar Collectors Using Nanofluids

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Journal of Harbin institute of Technology(New series) 2024年

作者： Barhm Mohamad Department of Petroleum Technology， Koya technical institute， Erbil Polytechnic University

This study delves into both experimental and analytical examinations of heat exchange in a straight channel， where Al2O3-water nanofluids are utilized， spanning the Reynolds number spectrum from 100 to 1800. Diverse volume fractions （1%， 2%， and 3%） of Al2O3-water nanofluids are meticulously prepared and analyzed. The essential physical properties of these nanofluids， critical for evaluating their thermal and flow characteristics， have been comprehensively assessed. From a quantitative perspective， numerical simulations are employed to predict the Nusselt number （Nu） and friction factor （f）. The empirical findings reveal intriguing trends: the friction factor experiences an upward trend with diminishing velocity， attributed to heightened molecular cohesion. Conversely， the friction factor demonstrates a decline with diminishing volume fractions， a consequence of reduced particle size. Both the nanofluid’s viscosity and heat transfer coefficient exhibit a rise in tandem with augmented volume flow rate and concentration gradient. Notably， the simulation results harmonize remarkably well with experimental data. Rigorous validation against prior studies underscores the robust consistency of these outcomes. In the pursuit of augmenting heat transfer， a volume fraction of 3% emerges as particularly influential， yielding an impressive 53.8% enhancement. Minor increments in the friction factor， while present， prove negligible and can be safely overlooked.

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