The progressive failure characteristics of geomaterial are a remarkable and challenging topic in geotechnical engineering.To study the effect of salt content and temperature on the progressive failure characteristics ...The progressive failure characteristics of geomaterial are a remarkable and challenging topic in geotechnical engineering.To study the effect of salt content and temperature on the progressive failure characteristics of frozen sodium sulfate saline sandy soil,a series of uniaxial compression tests were performed by integrating digital image correlation(DIC)technology into the testing apparatus.The evolution law of the uniaxial compression strength(UCS),the failure strain,and the formation of the shear band of the frozen sodium sulfate saline sandy soil were analyzed.The test results show that within the scope of this study,with the increase of salt content,both the UCS and the shear band angle initially decrease with increasing salt content before showing an increase.In contrast,the failure strain and the width of the shear band exhibit an initial increase followed by a decrease in the samples.In addition,to investigate the brittle failure characteristics of frozen sodium sulfate saline sandy soil,two classic brittleness evaluation methods were employed to quantitatively assess the brittleness level for the soil samples.The findings suggest that the failure characteristics under all test conditions in this study belong to the transition stage between brittle and ductile,indicating that frozen sodium sulfate saline sandy soil exhibits certain brittle behavior under uniaxial compression conditions,and the brittleness index basically decreases and then increases with the rise in salt content.展开更多
The effect of deformation resistance of AlCr_(1.3)TiNi_(2) eutectic high-entropy alloys under various current densities and strain rates was investigated during electrically-assisted compression.Results show that at c...The effect of deformation resistance of AlCr_(1.3)TiNi_(2) eutectic high-entropy alloys under various current densities and strain rates was investigated during electrically-assisted compression.Results show that at current density of 60 A/mm^(2) and strain rate of 0.1 s^(−1),the ultimate tensile stress shows a significant decrease from approximately 3000 MPa to 1900 MPa with reduction ratio of about 36.7%.However,as current density increases,elongation decreases due to intermediate temperature embrittlement.This is because the current induces Joule effect,which then leads to stress concentration and more defect formation.Moreover,the flow stress is decreased with the increase in strain rate at constant current density.展开更多
The mechanical behavior of cemented gangue backfill materials(CGBMs)is closely related to particle size distribution(PSD)of aggregates and properties of cementitious materials.Consequently,the true triaxial compressio...The mechanical behavior of cemented gangue backfill materials(CGBMs)is closely related to particle size distribution(PSD)of aggregates and properties of cementitious materials.Consequently,the true triaxial compression tests,CT scanning,SEM,and EDS tests were conducted on cemented gangue backfill samples(CGBSs)with various carbon nanotube concentrations(P_(CNT))that satisfied fractal theory for the PSD of aggregates.The mechanical properties,energy dissipations,and failure mechanisms of the CGBSs under true triaxial compression were systematically analyzed.The results indicate that appropriate carbon nanotubes(CNTs)effectively enhance the mechanical properties and energy dissipations of CGBSs through micropore filling and microcrack bridging,and the optimal effect appears at P_(CNT)of 0.08wt%.Taking PSD fractal dimension(D)of 2.500 as an example,compared to that of CGBS without CNT,the peak strength(σ_(p)),axial peak strain(ε_(1,p)),elastic strain energy(Ue),and dissipated energy(U_(d))increased by 12.76%,29.60%,19.05%,and90.39%,respectively.However,excessive CNTs can reduce the mechanical properties of CGBSs due to CNT agglomeration,manifesting a decrease inρ_(p),ε_(1,p),and the volumetric strain increment(Δε_(v))when P_(CNT)increases from 0.08wt%to 0.12wt%.Moreover,the addition of CNTs improved the integrity of CGBS after macroscopic failure,and crack extension in CGBSs appeared in two modes:detour and pass through the aggregates.Theσ_(p)and U_(d)firstly increase and then decrease with increasing D,and porosity shows the opposite trend.Theε_(1,p)andΔε_(v)are negatively correlated with D,and CGBS with D=2.150 has the maximum deformation parameters(ε_(1,p)=0.05079,Δε_(v)=0.01990)due to the frictional slip effect caused by coarse aggregates.With increasing D,the failure modes of CGBSs are sequentially manifested as oblique shear failure,"Y-shaped"shear failure,and conjugate shear failure.展开更多
AZ31/Al/Ta composites were prepared using the vacuum hot compression bonding(VHCB)method.The effect of hot compressing temperature on the interface microstructure evolution,phase constitution,and shear strength at the...AZ31/Al/Ta composites were prepared using the vacuum hot compression bonding(VHCB)method.The effect of hot compressing temperature on the interface microstructure evolution,phase constitution,and shear strength at the interface was investigated.Moreover,the interface bonding mechanisms of the AZ31/Al/Ta composites during the VHCB process were explored.The results demonstrate that as the VHCB temperature increases,the phase composition of the interface between Mg and Al changes from the Mg-Al brittle intermetallic compounds(Al_(12)Mg_(17)and Al_(3)Mg_(2))to the Al-Mg solid solution.Meanwhile,the width of the Al/Ta interface diffusion layer at 450℃increases compared to that at 400℃.The shear strengths are 24 and 46 MPa at 400 and 450℃,respectively.The interfacial bonding mechanism of AZ31/Al/Ta composites involves the coexistence of diffusion and mechanical meshing.Avoiding the formation of brittle phases at the interface can significantly improve interfacial bonding strength.展开更多
Data compression plays a vital role in datamanagement and information theory by reducing redundancy.However,it lacks built-in security features such as secret keys or password-based access control,leaving sensitive da...Data compression plays a vital role in datamanagement and information theory by reducing redundancy.However,it lacks built-in security features such as secret keys or password-based access control,leaving sensitive data vulnerable to unauthorized access and misuse.With the exponential growth of digital data,robust security measures are essential.Data encryption,a widely used approach,ensures data confidentiality by making it unreadable and unalterable through secret key control.Despite their individual benefits,both require significant computational resources.Additionally,performing them separately for the same data increases complexity and processing time.Recognizing the need for integrated approaches that balance compression ratios and security levels,this research proposes an integrated data compression and encryption algorithm,named IDCE,for enhanced security and efficiency.Thealgorithmoperates on 128-bit block sizes and a 256-bit secret key length.It combines Huffman coding for compression and a Tent map for encryption.Additionally,an iterative Arnold cat map further enhances cryptographic confusion properties.Experimental analysis validates the effectiveness of the proposed algorithm,showcasing competitive performance in terms of compression ratio,security,and overall efficiency when compared to prior algorithms in the field.展开更多
With the increase in the quantity and scale of Static Random-Access Memory Field Programmable Gate Arrays (SRAM-based FPGAs) for aerospace application, the volume of FPGA configuration bit files that must be stored ha...With the increase in the quantity and scale of Static Random-Access Memory Field Programmable Gate Arrays (SRAM-based FPGAs) for aerospace application, the volume of FPGA configuration bit files that must be stored has increased dramatically. The use of compression techniques for these bitstream files is emerging as a key strategy to alleviate the burden on storage resources. Due to the severe resource constraints of space-based electronics and the unique application environment, the simplicity, efficiency and robustness of the decompression circuitry is also a key design consideration. Through comparative analysis current bitstream file compression technologies, this research suggests that the Lempel Ziv Oberhumer (LZO) compression algorithm is more suitable for satellite applications. This paper also delves into the compression process and format of the LZO compression algorithm, as well as the inherent characteristics of configuration bitstream files. We propose an improved algorithm based on LZO for bitstream file compression, which optimises the compression process by refining the format and reducing the offset. Furthermore, a low-cost, robust decompression hardware architecture is proposed based on this method. Experimental results show that the compression speed of the improved LZO algorithm is increased by 3%, the decompression hardware cost is reduced by approximately 60%, and the compression ratio is slightly reduced by 0.47%.展开更多
Robotics plays an increasingly important role in all areas of human activity.Teleoperation robots can effectively ensure the safety of operators when operating in difficult and high‐risk industrial scenarios,which ob...Robotics plays an increasingly important role in all areas of human activity.Teleoperation robots can effectively ensure the safety of operators when operating in difficult and high‐risk industrial scenarios,which obviously requires instant and efficient signal compression and transmission in the system.However,most of the existing algorithms cannot fully explore the correlation within the signal,which mostly limits the compression efficiency.In this paper,a novel prediction‐aided kinaestheticsignal compression framework is proposed,which uses semantic communication methods to explore the temporal and spatial correlations of signals and employs neural network predictions to uncover their internal correlations.Specifically,the signal is first divided into two groups:the base part and the predictable part,and then a series of transformation matrices are introduced to establish the correlation between the two groups of the signal,which can be automatically optimised by a well‐designed neural network.This strategy of using learnable transformation matrices for prediction can not only accurately construct the correlation within the signal through massive data mining but also efficiently execute inference in a simple matrix multiplication computing form.Experimental results demonstrate that the proposed method outperforms the existing traditional tactile codecs and the latest tactile semantic communication methods.展开更多
An additional hot compression process was applied to a dilute Mg−Mn−Zn alloy post-extrusion.The alloy was extruded at 150℃ with an extrusion ratio of 15:1 and subsequently hot-compressed at 180℃ with a true strain o...An additional hot compression process was applied to a dilute Mg−Mn−Zn alloy post-extrusion.The alloy was extruded at 150℃ with an extrusion ratio of 15:1 and subsequently hot-compressed at 180℃ with a true strain of 0.9 along the extrusion direction.The microstructure,mechanical properties and thermal conductivity of as-extruded and as-hot compressed Mg−Mn−Zn alloys were investigated using optical microscopy,scanning electron microscopy,electron backscattering diffraction,and transmission electron microscopy.The aim was to concurrently enhance both strength and thermal conductivity by fostering uniform and refined microstructures while mitigating basal texture intensity.Substantial improvements were observed in yield strength(YS),ultimate tensile strength(UTS),and elongation(EL),with increase of 77%,53% and 10%,respectively.Additionally,thermal conductivity demonstrated a notable enhancement,rising from 111 to 125 W/(m·K).The underlying mechanism driving these improvements through the supplementary hot compression step was thoroughly elucidated.This study presents a promising pathway for the advancement of Mg alloys characterized by superior thermal and mechanical properties.展开更多
In recent years,video coding has been widely applied in the field of video image processing to remove redundant information and improve data transmission efficiency.However,during the video coding process,irrelevant o...In recent years,video coding has been widely applied in the field of video image processing to remove redundant information and improve data transmission efficiency.However,during the video coding process,irrelevant objects such as background elements are often encoded due to environmental disturbances,resulting in the wastage of computational resources.Existing research on video coding efficiency optimization primarily focuses on optimizing encoding units during intra-frame or inter frame prediction after the generation of coding units,neglecting the optimization of video images before coding unit generation.To address this challenge,This work proposes an image semantic segmentation compression algorithm based on macroblock encoding,called image semantic segmentation compression algorithm based on macroblock encoding(ISSC-ME),which consists of three modules.(1)The semantic label generation module generates interesting object labels using a grid-based approach to reduce redundant coding of consecutive frames.(2)The image segmentation network module generates a semantic segmentation image using U-Net.(3)The macroblock coding module,is a block segmentation-based video encoding and decoding algorithm used to compress images and improve video transmission efficiency.Experimental results show that the proposed image semantic segmentation optimization algorithm can reduce the computational costs,and improve the overall accuracy by 1.00%and the mean intersection over union(IoU)by 1.20%.In addition,the proposed compression algorithm utilizes macroblock fusion,resulting in the image compression rate achieving 80.64%.It has been proven that the proposed algorithm greatly reduces data storage and transmission,and enables fast image compression processing at the millisecond level.展开更多
This study investigates the volumetric behaviors of various soils during freeze-thaw(FT)cycles and subsequent one-dimensional(1D)compression from experimental and theoretical studies.Experimental studies were performe...This study investigates the volumetric behaviors of various soils during freeze-thaw(FT)cycles and subsequent one-dimensional(1D)compression from experimental and theoretical studies.Experimental studies were performed on saturated expansive soil specimens with varying compaction conditions and soil structures under different stress states.Experimental results demonstrate that the specimens expand during freezing and contract during thawing.All specimens converge to the same residual void ratio after seven FT cycles,irrespective of their different initial void ratio,stress state,and soil structure.The compression index of the expansive soil specimens increases with the initial void ratio,whereas their swelling index remains nearly constant.A model extending the disturbed state concept(DSC)is proposed to predict the 1D compression behaviors of FT-impacted soils.The model incorporates a parameter,b,to account for the impacts of FT cycles.Empirical equations have been developed to link the key model parameters(i.e.the normalized yield stress and parameter b)to the soil state parameter(i.e.the normalized void ratio)in order to simplify the prediction approach.The proposed model well predicts the results of the tested expansive soil.In addition,the model’s feasibility for other types of soils,including low-and high-plastic clays,and high-plastic organic soils,has been validated using published data from the literature.The proposed model is simple yet reliable for predicting the compression behaviors of soils subjected to FT cycles.展开更多
Steel cylindrical shells are widely used in engineering structures due to their high strength-to-weight ratio,but they are vulnerable to buckling under axial loads.To address this limitation,fiber-reinforced polymer(F...Steel cylindrical shells are widely used in engineering structures due to their high strength-to-weight ratio,but they are vulnerable to buckling under axial loads.To address this limitation,fiber-reinforced polymer(FRP)composites have emerged as promising materials for structural reinforcement.This study investigates the buckling behavior of steel cylindrical shells reinforced with inner and outer layers of polymer composite materials under axial compression.Using analytical and numerical modeling methods,the critical buckling loads for different reinforcement options were evaluated.Two-sided glass fiber reinforced plastic(GFRP)or carbon fiber reinforced plastic(CFRP)coatings,as well as combined coatings with layers of different composites,were considered.GFRP+CFRPIn the calculations,the coatings were treated as homogeneous orthotropic materials with equivalent averaged elastic characteristics.The numerical analysis revealed that CFRP reinforcement achieved the highest increase in buckling load,with improvements ranging from 9.84%to 47.29%,depending on the composite thickness and steel shell thickness.GFRP reinforcement,while beneficial,demonstrated a lower effectiveness,with buckling load increases between 5.89%and 19.30%.The hybrid reinforcement provided an optimal balance,improving buckling resistance by GFRP+CFRP6.94%to 43.95%.Statistical analysis further identified composite type and thickness as the most significant factors affecting buckling performance.The findings suggest that CFRP is the preferred reinforcement material,especially when applied to thin-walled cylindrical shells,while hybrid reinforcements can be effectively utilized for structures requiring a balance between stiffness and ductility.These insights provide a foundation for optimizing FRP reinforcement strategies to enhance the structural integrity of steel shells in engineering applications.展开更多
In this study,compacted loess samples with varying compaction water content but identical dry density were prepared to investigate the evolution of their hydraulic conductivity and compression behavior.Additionally,en...In this study,compacted loess samples with varying compaction water content but identical dry density were prepared to investigate the evolution of their hydraulic conductivity and compression behavior.Additionally,environmental scanning electron microscopy(ESEM)and nuclear magnetic resonance(NMR)analyses were conducted to gain microstructural insights into loess behavior at the laboratory scale.The results indicate that the maximum saturated hydraulic conductivity is observed at the lowest compaction water content,particularly in the early stage of permeability tests.In particular,for loess compacted at water contents below the optimum(as determined by the modified Proctor compaction test),the hydraulic conductivity decreases throughout the permeability tests.Conversely,when the water content exceeds the optimum level,the hydraulic conductivity shows an increasing trend.In terms of compression behavior,when the as-compacted samples are loaded in oedometer conditions,an increase in material compressibility is observed with increasing compaction water content.Again,a different phenomenological behavior was observed when the compaction water content exceeded the optimum,i.e.an abrupt increase in loess compressibility.ESEM tests provide microstructural confirmation of this evidence,as the surface morphology of the compacted loess changes significantly with increasing compaction water content.The microstructural evolution was also quantified in terms of area ratio using image processing software.Finally,NMR was used to quantify the intra-and inter-aggregate water at different compaction water contents,once again highlighting a threshold for the presence or absence of inter-aggregate water similar to the optimum water content.展开更多
The high stress levels in tall tailings dams can lead to particle crushing.Understanding the compressibility and breakage characteristics of tailings particles will contribute to the advancement to the design and cons...The high stress levels in tall tailings dams can lead to particle crushing.Understanding the compressibility and breakage characteristics of tailings particles will contribute to the advancement to the design and construction processes of high-rise tailings dams,as well as the accurate evaluation of the stability of tailings storage facilities(TSFs).This paper presents the results of a series of detailed one-dimensional oedometer compression tests conducted to investigate the compression behavior and particle breakage of iron ore tailings(IOTs)collected from two typical TSFs,with different initial particle size distributions and a wide range of initial specific volumes,under effective vertical stresses of up to 4.8 MPa.The results show that the compression paths of the IOTs were slowly convergent,and this nontransitional mode of compression behavior experienced a significant amount of particle breakage.The relative breakage(Br)was used to quantify the amount of breakage and the input specific work(W)was adopted to evaluate the factors influencing Br.The initial breakage stress of the IOTs was less than 0.2 MPa.For the finer tailings,Br increased with increasing vertical stresses until it reached a threshold,after which Br tended to remain constant.However,coarser IOTs continued to experience crushing even at 4.8 MPa.The particle breakage in the coarser IOTs is much more significant than it in the finer IOTs overall.It was also observed that the tailings grains within the loose specimens broke more easily than those within the dense specimens.Additionally,three types of particle crushing modes were identified for IOTs under one-dimensional compression,namely,abrasion,chipping,and splitting.展开更多
Basic life support for cardiac arrest associates cardiopulmonary resuscitation(CPR)and defibrillation.CPR relies on chest compressions(CC)and ventilation.Current guidelines on CPR recommend a depth of 5-6 cm at a rhyt...Basic life support for cardiac arrest associates cardiopulmonary resuscitation(CPR)and defibrillation.CPR relies on chest compressions(CC)and ventilation.Current guidelines on CPR recommend a depth of 5-6 cm at a rhythm of 100-120 times/min for CC.[1,2]Interruptions of the CC must be as short as possible and are related to ventilation,defibrillation and turnover of the rescuers.Most of the automated external defibrillators(AEDs)require interruptions of the CC to perform rhythm analysis.Among the numerous marketed models of AEDs,some provide real-time feedback about the quality of the CC.展开更多
Three-dimensional(3D)single molecule localization microscopy(SMLM)plays an important role in biomedical applications,but its data processing is very complicated.Deep learning is a potential tool to solve this problem....Three-dimensional(3D)single molecule localization microscopy(SMLM)plays an important role in biomedical applications,but its data processing is very complicated.Deep learning is a potential tool to solve this problem.As the state of art 3D super-resolution localization algorithm based on deep learning,FD-DeepLoc algorithm reported recently still has a gap with the expected goal of online image processing,even though it has greatly improved the data processing throughput.In this paper,a new algorithm Lite-FD-DeepLoc is developed on the basis of FD-DeepLoc algorithm to meet the online image processing requirements of 3D SMLM.This new algorithm uses the feature compression method to reduce the parameters of the model,and combines it with pipeline programming to accelerate the inference process of the deep learning model.The simulated data processing results show that the image processing speed of Lite-FD-DeepLoc is about twice as fast as that of FD-DeepLoc with a slight decrease in localization accuracy,which can realize real-time processing of 256×256 pixels size images.The results of biological experimental data processing imply that Lite-FD-DeepLoc can successfully analyze the data based on astigmatism and saddle point engineering,and the global resolution of the reconstructed image is equivalent to or even better than FD-DeepLoc algorithm.展开更多
Overpressure prediction for exploratory drilling has become robust in most basins with increasing well control,high-quality seismic datasets,and proactive real-time overpressure monitoring while drilling.However,accur...Overpressure prediction for exploratory drilling has become robust in most basins with increasing well control,high-quality seismic datasets,and proactive real-time overpressure monitoring while drilling.However,accurate overpressure prediction remains challenging in offshore Northwest Borneo despite several decades of drilling experience.This paper focuses on two exploration wells drilled by Brunei Shell Petroleum 40 years apart that faced similar challenges with overpressure prediction and well control.An integrated lookback study is attempted using seismic and well-log data to explore the causes of the unsatisfactory Pore Pressure Prediction(PPP)outcome in pre-drill and real-time operation settings for thesewells.Our study indicates that the misprediction of overpressures is due to real differences in shale pressure(basis of pre-drill work and monitoring)and sand pressure(source of drill kick and well control chal-lenges)due to large-scale vertical leak or expulsion of deep-seated fluids into pre-compacted normally pressured overlying sediments in several regions through a mix of shear and tensile failure mechanisms.Such migrated fluids inflate the sand pressure in the normally compacted shallower sequences with the shale pressure remaining low.A predictive framework for upward fluid expulsion was attempted but found impracticable due to complex spatial and temporal variations in the horizontal stress field responsible for such leakage.As such,it is proposed that these migratory overpressures are essentially'unpredictable'from conventional PPP workflows viewed in the broad bucket of compaction disequi-librium(undercompaction)and fluid expansion(unloading)mechanisms.Further study is recommended to understand if such migrated overpressures in the sand can produce a discernible and predictable geophysical or petrophysical signature in the abutting normally compacted shales.The study highlights the possibility of large lateral variability in the sand overpressure within the same stratigraphic unit in regions with complex tectonostratigraphic evolution like Northwest Borneo.展开更多
The creep deformation and mechanical properties of 2219 aluminum alloy were experimentally investigated under both tension and compression at the temperature of 165℃for different time.The results indicated that the c...The creep deformation and mechanical properties of 2219 aluminum alloy were experimentally investigated under both tension and compression at the temperature of 165℃for different time.The results indicated that the creep deformation under tensile stress was greater than that under compressive stress.As the stress level increases,the compressive creep rate showed more significant increase.The yield strength after compressive stress creep-ageing was higher than that after stress-free ageing,with the lowest strength observed in the tensile-aged sample.Overall,the average phase length after compressive stress creep-ageing was larger than after tensile stress ageing.Under tensile stress,the number and size of precipitates at small angles to the stress direction were larger than those perpendicular to the stress direction.In contrast,under compressive stress,this relationship was reversed,and the preferential orientation of phases became more pronounced with ageing time.A unified,physics-based creep-ageing constitutive model,accounting for the orientation of precipitation,was developed for both tensile and compressive stress conditions.The predicted results were in good agreement with the experimental data.These findings,along with the developed model,provide a theoretical and simulation basis for precise creep-ageing forming of components under complex stresses.展开更多
With the rapid development of digital communication and the widespread use of the Internet of Things,multi-view image compression has attracted increasing attention as a fundamental technology for image data communica...With the rapid development of digital communication and the widespread use of the Internet of Things,multi-view image compression has attracted increasing attention as a fundamental technology for image data communication.Multi-view image compression aims to improve compression efficiency by leveraging correlations between images.However,the requirement of synchronization and inter-image communication at the encoder side poses significant challenges,especially for constrained devices.In this study,we introduce a novel distributed image compression model based on the attention mechanism to address the challenges associated with the availability of side information only during decoding.Our model integrates an encoder network,a quantization module,and a decoder network,to ensure both high compression performance and high-quality image reconstruction.The encoder uses a deep Convolutional Neural Network(CNN)to extract high-level features from the input image,which then pass through the quantization module for further compression before undergoing lossless entropy coding.The decoder of our model consists of three main components that allow us to fully exploit the information within and between images on the decoder side.Specifically,we first introduce a channel-spatial attention module to capture and refine information within individual image feature maps.Second,we employ a semi-coupled convolution module to extract both shared and specific information in images.Finally,a cross-attention module is employed to fuse mutual information extracted from side information.The effectiveness of our model is validated on various datasets,including KITTI Stereo and Cityscapes.The results highlight the superior compression capabilities of our method,surpassing state-of-the-art techniques.展开更多
The accurate prediction of battery pack capacity in electric vehicles(EVs)is crucial for ensuring safety and optimizing performance.Despite extensive research on predicting cell capacity using laboratory data,predicti...The accurate prediction of battery pack capacity in electric vehicles(EVs)is crucial for ensuring safety and optimizing performance.Despite extensive research on predicting cell capacity using laboratory data,predicting the capacity of onboard battery packs from field data remains challenging due to complex operating conditions and irregular EV usage in real-world settings.Most existing methods rely on extracting health feature parameters from raw data for capacity prediction of onboard battery packs,however,selecting specific parameters often results in a loss of critical information,which reduces prediction accuracy.To this end,this paper introduces a novel framework combining deep learning and data compression techniques to accurately predict battery pack capacity onboard.The proposed data compression method converts monthly EV charging data into feature maps,which preserve essential data characteristics while reducing the volume of raw data.To address missing capacity labels in field data,a capacity labeling method is proposed,which calculates monthly battery capacity by transforming the ampere-hour integration formula and applying linear regression.Subsequently,a deep learning model is proposed to build a capacity prediction model,using feature maps from historical months to predict the battery capacity of future months,thus facilitating accurate forecasts.The proposed framework,evaluated using field data from 20 EVs,achieves a mean absolute error of 0.79 Ah,a mean absolute percentage error of 0.65%,and a root mean square error of 1.02 Ah,highlighting its potential for real-world EV applications.展开更多
Cemented tailings backfill(CTB)is a crucial support material for ensuring the long-term stability of underground goafs.A comprehensive understanding of its compressive mechanical behavior is essential for improving en...Cemented tailings backfill(CTB)is a crucial support material for ensuring the long-term stability of underground goafs.A comprehensive understanding of its compressive mechanical behavior is essential for improving engineering safety.Although extensive studies have been conducted on the uniaxial compressive properties of CTB,damage constitutive models that effectively capture its damage evolution process remain underdeveloped,and its failure mechanisms are not yet fully clarified.To address these gaps,this study conducted systematic uniaxial compression tests on CTB specimens prepared with varying cement-tailings ratios.The results revealed distinct compaction and softening phases in the stress−strain curves.A lower cement-tailings ratio significantly reduced the strength and deformation resistance of CTB,along with a decrease in elastic energy accumulation at peak stress and dissipation energy in the post peak stage.Based on these findings,a modified damage constitutive model was developed by introducing a correction factor,enabling accurate simulation of the entire uniaxial compression process of CTB with different cement-tailings ratios.Comparative analysis with classical constitutive models validated the proposed model’s accuracy and applicability in describing the compressive behavior of CTB.Furthermore,particle size distribution and acoustic emission tests were employed to investigate the influence of cement-tailings ratio on failure mechanisms.The results indicated that a lower cement-tailings ratio leads to coarser particle sizes,which intensify shear-related acoustic emission signals and ultimately result in more pronounced macroscopic shear failure.This study provides theoretical support and practical guidance for the optimal design of CTB mix ratios.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.42372312,and 42172299)the Pyramid Talent Training Project of Beijing University of Civil Engineering and Architecture(Grant No.JDYC20220807).
文摘The progressive failure characteristics of geomaterial are a remarkable and challenging topic in geotechnical engineering.To study the effect of salt content and temperature on the progressive failure characteristics of frozen sodium sulfate saline sandy soil,a series of uniaxial compression tests were performed by integrating digital image correlation(DIC)technology into the testing apparatus.The evolution law of the uniaxial compression strength(UCS),the failure strain,and the formation of the shear band of the frozen sodium sulfate saline sandy soil were analyzed.The test results show that within the scope of this study,with the increase of salt content,both the UCS and the shear band angle initially decrease with increasing salt content before showing an increase.In contrast,the failure strain and the width of the shear band exhibit an initial increase followed by a decrease in the samples.In addition,to investigate the brittle failure characteristics of frozen sodium sulfate saline sandy soil,two classic brittleness evaluation methods were employed to quantitatively assess the brittleness level for the soil samples.The findings suggest that the failure characteristics under all test conditions in this study belong to the transition stage between brittle and ductile,indicating that frozen sodium sulfate saline sandy soil exhibits certain brittle behavior under uniaxial compression conditions,and the brittleness index basically decreases and then increases with the rise in salt content.
基金National Natural Science Foundation of China(52305349)Heilongjiang Touyan Team(HITTY-20190036)+2 种基金Heilongjiang Provincial Natural Science Foundation of China(LH2023E033)CGN-HIT Advanced Nuclear and New Energy Research Institute(CGN-HIT202305)Natural Science Basic Research Program of Shaanxi Province(2023-JC-QN-0518)。
文摘The effect of deformation resistance of AlCr_(1.3)TiNi_(2) eutectic high-entropy alloys under various current densities and strain rates was investigated during electrically-assisted compression.Results show that at current density of 60 A/mm^(2) and strain rate of 0.1 s^(−1),the ultimate tensile stress shows a significant decrease from approximately 3000 MPa to 1900 MPa with reduction ratio of about 36.7%.However,as current density increases,elongation decreases due to intermediate temperature embrittlement.This is because the current induces Joule effect,which then leads to stress concentration and more defect formation.Moreover,the flow stress is decreased with the increase in strain rate at constant current density.
基金financially supported by the National Natural Science Foundation of China(Nos.52174092,51904290,and 52374147)the Natural Science Foundation of Jiangsu Province,China(No.BK20220157)+2 种基金the Fundamental Research Funds for the Central Universities,China(No.2022YCPY0202)the National Key Research and Development Program of China(No.2023YFC3804204)the Major Program of Xinjiang Uygur Autonomous Region S cience and Technology(No.2023A01002)。
文摘The mechanical behavior of cemented gangue backfill materials(CGBMs)is closely related to particle size distribution(PSD)of aggregates and properties of cementitious materials.Consequently,the true triaxial compression tests,CT scanning,SEM,and EDS tests were conducted on cemented gangue backfill samples(CGBSs)with various carbon nanotube concentrations(P_(CNT))that satisfied fractal theory for the PSD of aggregates.The mechanical properties,energy dissipations,and failure mechanisms of the CGBSs under true triaxial compression were systematically analyzed.The results indicate that appropriate carbon nanotubes(CNTs)effectively enhance the mechanical properties and energy dissipations of CGBSs through micropore filling and microcrack bridging,and the optimal effect appears at P_(CNT)of 0.08wt%.Taking PSD fractal dimension(D)of 2.500 as an example,compared to that of CGBS without CNT,the peak strength(σ_(p)),axial peak strain(ε_(1,p)),elastic strain energy(Ue),and dissipated energy(U_(d))increased by 12.76%,29.60%,19.05%,and90.39%,respectively.However,excessive CNTs can reduce the mechanical properties of CGBSs due to CNT agglomeration,manifesting a decrease inρ_(p),ε_(1,p),and the volumetric strain increment(Δε_(v))when P_(CNT)increases from 0.08wt%to 0.12wt%.Moreover,the addition of CNTs improved the integrity of CGBS after macroscopic failure,and crack extension in CGBSs appeared in two modes:detour and pass through the aggregates.Theσ_(p)and U_(d)firstly increase and then decrease with increasing D,and porosity shows the opposite trend.Theε_(1,p)andΔε_(v)are negatively correlated with D,and CGBS with D=2.150 has the maximum deformation parameters(ε_(1,p)=0.05079,Δε_(v)=0.01990)due to the frictional slip effect caused by coarse aggregates.With increasing D,the failure modes of CGBSs are sequentially manifested as oblique shear failure,"Y-shaped"shear failure,and conjugate shear failure.
基金National Natural Science Foundation of China(52275308,52301146)Fundamental Research Funds for the Central Universities(2023JG007)Supported by Shi Changxu Innovation Center for Advanced Materials(SCXKFJJ202207)。
文摘AZ31/Al/Ta composites were prepared using the vacuum hot compression bonding(VHCB)method.The effect of hot compressing temperature on the interface microstructure evolution,phase constitution,and shear strength at the interface was investigated.Moreover,the interface bonding mechanisms of the AZ31/Al/Ta composites during the VHCB process were explored.The results demonstrate that as the VHCB temperature increases,the phase composition of the interface between Mg and Al changes from the Mg-Al brittle intermetallic compounds(Al_(12)Mg_(17)and Al_(3)Mg_(2))to the Al-Mg solid solution.Meanwhile,the width of the Al/Ta interface diffusion layer at 450℃increases compared to that at 400℃.The shear strengths are 24 and 46 MPa at 400 and 450℃,respectively.The interfacial bonding mechanism of AZ31/Al/Ta composites involves the coexistence of diffusion and mechanical meshing.Avoiding the formation of brittle phases at the interface can significantly improve interfacial bonding strength.
基金the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025).
文摘Data compression plays a vital role in datamanagement and information theory by reducing redundancy.However,it lacks built-in security features such as secret keys or password-based access control,leaving sensitive data vulnerable to unauthorized access and misuse.With the exponential growth of digital data,robust security measures are essential.Data encryption,a widely used approach,ensures data confidentiality by making it unreadable and unalterable through secret key control.Despite their individual benefits,both require significant computational resources.Additionally,performing them separately for the same data increases complexity and processing time.Recognizing the need for integrated approaches that balance compression ratios and security levels,this research proposes an integrated data compression and encryption algorithm,named IDCE,for enhanced security and efficiency.Thealgorithmoperates on 128-bit block sizes and a 256-bit secret key length.It combines Huffman coding for compression and a Tent map for encryption.Additionally,an iterative Arnold cat map further enhances cryptographic confusion properties.Experimental analysis validates the effectiveness of the proposed algorithm,showcasing competitive performance in terms of compression ratio,security,and overall efficiency when compared to prior algorithms in the field.
基金supported in part by the National Key Laboratory of Science and Technology on Space Microwave(Grant Nos.HTKJ2022KL504009 and HTKJ2022KL5040010).
文摘With the increase in the quantity and scale of Static Random-Access Memory Field Programmable Gate Arrays (SRAM-based FPGAs) for aerospace application, the volume of FPGA configuration bit files that must be stored has increased dramatically. The use of compression techniques for these bitstream files is emerging as a key strategy to alleviate the burden on storage resources. Due to the severe resource constraints of space-based electronics and the unique application environment, the simplicity, efficiency and robustness of the decompression circuitry is also a key design consideration. Through comparative analysis current bitstream file compression technologies, this research suggests that the Lempel Ziv Oberhumer (LZO) compression algorithm is more suitable for satellite applications. This paper also delves into the compression process and format of the LZO compression algorithm, as well as the inherent characteristics of configuration bitstream files. We propose an improved algorithm based on LZO for bitstream file compression, which optimises the compression process by refining the format and reducing the offset. Furthermore, a low-cost, robust decompression hardware architecture is proposed based on this method. Experimental results show that the compression speed of the improved LZO algorithm is increased by 3%, the decompression hardware cost is reduced by approximately 60%, and the compression ratio is slightly reduced by 0.47%.
基金supported in part by the National Natural Science Foundation of China(NSFC)(Grants 62302128 and 624B2049)supported by Shenzhen Science and Technology Innovation Committee(Grant RCBS20231211090749086).
文摘Robotics plays an increasingly important role in all areas of human activity.Teleoperation robots can effectively ensure the safety of operators when operating in difficult and high‐risk industrial scenarios,which obviously requires instant and efficient signal compression and transmission in the system.However,most of the existing algorithms cannot fully explore the correlation within the signal,which mostly limits the compression efficiency.In this paper,a novel prediction‐aided kinaestheticsignal compression framework is proposed,which uses semantic communication methods to explore the temporal and spatial correlations of signals and employs neural network predictions to uncover their internal correlations.Specifically,the signal is first divided into two groups:the base part and the predictable part,and then a series of transformation matrices are introduced to establish the correlation between the two groups of the signal,which can be automatically optimised by a well‐designed neural network.This strategy of using learnable transformation matrices for prediction can not only accurately construct the correlation within the signal through massive data mining but also efficiently execute inference in a simple matrix multiplication computing form.Experimental results demonstrate that the proposed method outperforms the existing traditional tactile codecs and the latest tactile semantic communication methods.
基金financially supported by the National Key Research and Development Program of China(No.2022YFE0109600)the National Natural Science Foundation of China(No.52150710544)。
文摘An additional hot compression process was applied to a dilute Mg−Mn−Zn alloy post-extrusion.The alloy was extruded at 150℃ with an extrusion ratio of 15:1 and subsequently hot-compressed at 180℃ with a true strain of 0.9 along the extrusion direction.The microstructure,mechanical properties and thermal conductivity of as-extruded and as-hot compressed Mg−Mn−Zn alloys were investigated using optical microscopy,scanning electron microscopy,electron backscattering diffraction,and transmission electron microscopy.The aim was to concurrently enhance both strength and thermal conductivity by fostering uniform and refined microstructures while mitigating basal texture intensity.Substantial improvements were observed in yield strength(YS),ultimate tensile strength(UTS),and elongation(EL),with increase of 77%,53% and 10%,respectively.Additionally,thermal conductivity demonstrated a notable enhancement,rising from 111 to 125 W/(m·K).The underlying mechanism driving these improvements through the supplementary hot compression step was thoroughly elucidated.This study presents a promising pathway for the advancement of Mg alloys characterized by superior thermal and mechanical properties.
文摘In recent years,video coding has been widely applied in the field of video image processing to remove redundant information and improve data transmission efficiency.However,during the video coding process,irrelevant objects such as background elements are often encoded due to environmental disturbances,resulting in the wastage of computational resources.Existing research on video coding efficiency optimization primarily focuses on optimizing encoding units during intra-frame or inter frame prediction after the generation of coding units,neglecting the optimization of video images before coding unit generation.To address this challenge,This work proposes an image semantic segmentation compression algorithm based on macroblock encoding,called image semantic segmentation compression algorithm based on macroblock encoding(ISSC-ME),which consists of three modules.(1)The semantic label generation module generates interesting object labels using a grid-based approach to reduce redundant coding of consecutive frames.(2)The image segmentation network module generates a semantic segmentation image using U-Net.(3)The macroblock coding module,is a block segmentation-based video encoding and decoding algorithm used to compress images and improve video transmission efficiency.Experimental results show that the proposed image semantic segmentation optimization algorithm can reduce the computational costs,and improve the overall accuracy by 1.00%and the mean intersection over union(IoU)by 1.20%.In addition,the proposed compression algorithm utilizes macroblock fusion,resulting in the image compression rate achieving 80.64%.It has been proven that the proposed algorithm greatly reduces data storage and transmission,and enables fast image compression processing at the millisecond level.
基金support from the Natural Sciences and Engineering Research Council of Canada(NSERC)through the Discovery Grant(Grant No.5808)received in 2019 for his research programsThe third author appreciates the funding from the National Natural Science Foundation of China(Grant No.52378365)Hubei Key Research&Development Program(Grant No.2023BCB112).
文摘This study investigates the volumetric behaviors of various soils during freeze-thaw(FT)cycles and subsequent one-dimensional(1D)compression from experimental and theoretical studies.Experimental studies were performed on saturated expansive soil specimens with varying compaction conditions and soil structures under different stress states.Experimental results demonstrate that the specimens expand during freezing and contract during thawing.All specimens converge to the same residual void ratio after seven FT cycles,irrespective of their different initial void ratio,stress state,and soil structure.The compression index of the expansive soil specimens increases with the initial void ratio,whereas their swelling index remains nearly constant.A model extending the disturbed state concept(DSC)is proposed to predict the 1D compression behaviors of FT-impacted soils.The model incorporates a parameter,b,to account for the impacts of FT cycles.Empirical equations have been developed to link the key model parameters(i.e.the normalized yield stress and parameter b)to the soil state parameter(i.e.the normalized void ratio)in order to simplify the prediction approach.The proposed model well predicts the results of the tested expansive soil.In addition,the model’s feasibility for other types of soils,including low-and high-plastic clays,and high-plastic organic soils,has been validated using published data from the literature.The proposed model is simple yet reliable for predicting the compression behaviors of soils subjected to FT cycles.
文摘Steel cylindrical shells are widely used in engineering structures due to their high strength-to-weight ratio,but they are vulnerable to buckling under axial loads.To address this limitation,fiber-reinforced polymer(FRP)composites have emerged as promising materials for structural reinforcement.This study investigates the buckling behavior of steel cylindrical shells reinforced with inner and outer layers of polymer composite materials under axial compression.Using analytical and numerical modeling methods,the critical buckling loads for different reinforcement options were evaluated.Two-sided glass fiber reinforced plastic(GFRP)or carbon fiber reinforced plastic(CFRP)coatings,as well as combined coatings with layers of different composites,were considered.GFRP+CFRPIn the calculations,the coatings were treated as homogeneous orthotropic materials with equivalent averaged elastic characteristics.The numerical analysis revealed that CFRP reinforcement achieved the highest increase in buckling load,with improvements ranging from 9.84%to 47.29%,depending on the composite thickness and steel shell thickness.GFRP reinforcement,while beneficial,demonstrated a lower effectiveness,with buckling load increases between 5.89%and 19.30%.The hybrid reinforcement provided an optimal balance,improving buckling resistance by GFRP+CFRP6.94%to 43.95%.Statistical analysis further identified composite type and thickness as the most significant factors affecting buckling performance.The findings suggest that CFRP is the preferred reinforcement material,especially when applied to thin-walled cylindrical shells,while hybrid reinforcements can be effectively utilized for structures requiring a balance between stiffness and ductility.These insights provide a foundation for optimizing FRP reinforcement strategies to enhance the structural integrity of steel shells in engineering applications.
基金the China Postdoctoral Science Foundation(Grant No.2024MD753992)Shaanxi Geotechnical Mechanics and Engineering Young Talent Support Program Project(Grant No.YESS2024005)the National Natural Science Foundation of China(Grant No.41931285).
文摘In this study,compacted loess samples with varying compaction water content but identical dry density were prepared to investigate the evolution of their hydraulic conductivity and compression behavior.Additionally,environmental scanning electron microscopy(ESEM)and nuclear magnetic resonance(NMR)analyses were conducted to gain microstructural insights into loess behavior at the laboratory scale.The results indicate that the maximum saturated hydraulic conductivity is observed at the lowest compaction water content,particularly in the early stage of permeability tests.In particular,for loess compacted at water contents below the optimum(as determined by the modified Proctor compaction test),the hydraulic conductivity decreases throughout the permeability tests.Conversely,when the water content exceeds the optimum level,the hydraulic conductivity shows an increasing trend.In terms of compression behavior,when the as-compacted samples are loaded in oedometer conditions,an increase in material compressibility is observed with increasing compaction water content.Again,a different phenomenological behavior was observed when the compaction water content exceeded the optimum,i.e.an abrupt increase in loess compressibility.ESEM tests provide microstructural confirmation of this evidence,as the surface morphology of the compacted loess changes significantly with increasing compaction water content.The microstructural evolution was also quantified in terms of area ratio using image processing software.Finally,NMR was used to quantify the intra-and inter-aggregate water at different compaction water contents,once again highlighting a threshold for the presence or absence of inter-aggregate water similar to the optimum water content.
基金supported by the National Natural Science Foundation of China(Grant Nos.41630640,41790445)the National Key Research and Development Program of China(Grant No.2022YFC3003205).
文摘The high stress levels in tall tailings dams can lead to particle crushing.Understanding the compressibility and breakage characteristics of tailings particles will contribute to the advancement to the design and construction processes of high-rise tailings dams,as well as the accurate evaluation of the stability of tailings storage facilities(TSFs).This paper presents the results of a series of detailed one-dimensional oedometer compression tests conducted to investigate the compression behavior and particle breakage of iron ore tailings(IOTs)collected from two typical TSFs,with different initial particle size distributions and a wide range of initial specific volumes,under effective vertical stresses of up to 4.8 MPa.The results show that the compression paths of the IOTs were slowly convergent,and this nontransitional mode of compression behavior experienced a significant amount of particle breakage.The relative breakage(Br)was used to quantify the amount of breakage and the input specific work(W)was adopted to evaluate the factors influencing Br.The initial breakage stress of the IOTs was less than 0.2 MPa.For the finer tailings,Br increased with increasing vertical stresses until it reached a threshold,after which Br tended to remain constant.However,coarser IOTs continued to experience crushing even at 4.8 MPa.The particle breakage in the coarser IOTs is much more significant than it in the finer IOTs overall.It was also observed that the tailings grains within the loose specimens broke more easily than those within the dense specimens.Additionally,three types of particle crushing modes were identified for IOTs under one-dimensional compression,namely,abrasion,chipping,and splitting.
文摘Basic life support for cardiac arrest associates cardiopulmonary resuscitation(CPR)and defibrillation.CPR relies on chest compressions(CC)and ventilation.Current guidelines on CPR recommend a depth of 5-6 cm at a rhythm of 100-120 times/min for CC.[1,2]Interruptions of the CC must be as short as possible and are related to ventilation,defibrillation and turnover of the rescuers.Most of the automated external defibrillators(AEDs)require interruptions of the CC to perform rhythm analysis.Among the numerous marketed models of AEDs,some provide real-time feedback about the quality of the CC.
基金supported by the Start-up Fund from Hainan University(No.KYQD(ZR)-20077)。
文摘Three-dimensional(3D)single molecule localization microscopy(SMLM)plays an important role in biomedical applications,but its data processing is very complicated.Deep learning is a potential tool to solve this problem.As the state of art 3D super-resolution localization algorithm based on deep learning,FD-DeepLoc algorithm reported recently still has a gap with the expected goal of online image processing,even though it has greatly improved the data processing throughput.In this paper,a new algorithm Lite-FD-DeepLoc is developed on the basis of FD-DeepLoc algorithm to meet the online image processing requirements of 3D SMLM.This new algorithm uses the feature compression method to reduce the parameters of the model,and combines it with pipeline programming to accelerate the inference process of the deep learning model.The simulated data processing results show that the image processing speed of Lite-FD-DeepLoc is about twice as fast as that of FD-DeepLoc with a slight decrease in localization accuracy,which can realize real-time processing of 256×256 pixels size images.The results of biological experimental data processing imply that Lite-FD-DeepLoc can successfully analyze the data based on astigmatism and saddle point engineering,and the global resolution of the reconstructed image is equivalent to or even better than FD-DeepLoc algorithm.
文摘Overpressure prediction for exploratory drilling has become robust in most basins with increasing well control,high-quality seismic datasets,and proactive real-time overpressure monitoring while drilling.However,accurate overpressure prediction remains challenging in offshore Northwest Borneo despite several decades of drilling experience.This paper focuses on two exploration wells drilled by Brunei Shell Petroleum 40 years apart that faced similar challenges with overpressure prediction and well control.An integrated lookback study is attempted using seismic and well-log data to explore the causes of the unsatisfactory Pore Pressure Prediction(PPP)outcome in pre-drill and real-time operation settings for thesewells.Our study indicates that the misprediction of overpressures is due to real differences in shale pressure(basis of pre-drill work and monitoring)and sand pressure(source of drill kick and well control chal-lenges)due to large-scale vertical leak or expulsion of deep-seated fluids into pre-compacted normally pressured overlying sediments in several regions through a mix of shear and tensile failure mechanisms.Such migrated fluids inflate the sand pressure in the normally compacted shallower sequences with the shale pressure remaining low.A predictive framework for upward fluid expulsion was attempted but found impracticable due to complex spatial and temporal variations in the horizontal stress field responsible for such leakage.As such,it is proposed that these migratory overpressures are essentially'unpredictable'from conventional PPP workflows viewed in the broad bucket of compaction disequi-librium(undercompaction)and fluid expansion(unloading)mechanisms.Further study is recommended to understand if such migrated overpressures in the sand can produce a discernible and predictable geophysical or petrophysical signature in the abutting normally compacted shales.The study highlights the possibility of large lateral variability in the sand overpressure within the same stratigraphic unit in regions with complex tectonostratigraphic evolution like Northwest Borneo.
基金Project(JCKY2023205B003)supported by the Defense Industrial Technology Development Program,China。
文摘The creep deformation and mechanical properties of 2219 aluminum alloy were experimentally investigated under both tension and compression at the temperature of 165℃for different time.The results indicated that the creep deformation under tensile stress was greater than that under compressive stress.As the stress level increases,the compressive creep rate showed more significant increase.The yield strength after compressive stress creep-ageing was higher than that after stress-free ageing,with the lowest strength observed in the tensile-aged sample.Overall,the average phase length after compressive stress creep-ageing was larger than after tensile stress ageing.Under tensile stress,the number and size of precipitates at small angles to the stress direction were larger than those perpendicular to the stress direction.In contrast,under compressive stress,this relationship was reversed,and the preferential orientation of phases became more pronounced with ageing time.A unified,physics-based creep-ageing constitutive model,accounting for the orientation of precipitation,was developed for both tensile and compressive stress conditions.The predicted results were in good agreement with the experimental data.These findings,along with the developed model,provide a theoretical and simulation basis for precise creep-ageing forming of components under complex stresses.
基金supported by the National Natural Science Foundation of China(Key Program)(No.11932013)the Tianjin Science and Technology Plan Project(No.22PTZWHZ00040)。
文摘With the rapid development of digital communication and the widespread use of the Internet of Things,multi-view image compression has attracted increasing attention as a fundamental technology for image data communication.Multi-view image compression aims to improve compression efficiency by leveraging correlations between images.However,the requirement of synchronization and inter-image communication at the encoder side poses significant challenges,especially for constrained devices.In this study,we introduce a novel distributed image compression model based on the attention mechanism to address the challenges associated with the availability of side information only during decoding.Our model integrates an encoder network,a quantization module,and a decoder network,to ensure both high compression performance and high-quality image reconstruction.The encoder uses a deep Convolutional Neural Network(CNN)to extract high-level features from the input image,which then pass through the quantization module for further compression before undergoing lossless entropy coding.The decoder of our model consists of three main components that allow us to fully exploit the information within and between images on the decoder side.Specifically,we first introduce a channel-spatial attention module to capture and refine information within individual image feature maps.Second,we employ a semi-coupled convolution module to extract both shared and specific information in images.Finally,a cross-attention module is employed to fuse mutual information extracted from side information.The effectiveness of our model is validated on various datasets,including KITTI Stereo and Cityscapes.The results highlight the superior compression capabilities of our method,surpassing state-of-the-art techniques.
基金supported in part by the Science and Technology Department of Sichuan Province(No.2025ZNSFSC0427,No.2024ZDZX0035)the Open Project Fund of Vehicle Measurement,Control and Safety Key Laboratory of Sichuan Province(No.QCCK2024-004)the Industrial and Educational Integration Project of Yibin(No.YB-XHU-20240001)。
文摘The accurate prediction of battery pack capacity in electric vehicles(EVs)is crucial for ensuring safety and optimizing performance.Despite extensive research on predicting cell capacity using laboratory data,predicting the capacity of onboard battery packs from field data remains challenging due to complex operating conditions and irregular EV usage in real-world settings.Most existing methods rely on extracting health feature parameters from raw data for capacity prediction of onboard battery packs,however,selecting specific parameters often results in a loss of critical information,which reduces prediction accuracy.To this end,this paper introduces a novel framework combining deep learning and data compression techniques to accurately predict battery pack capacity onboard.The proposed data compression method converts monthly EV charging data into feature maps,which preserve essential data characteristics while reducing the volume of raw data.To address missing capacity labels in field data,a capacity labeling method is proposed,which calculates monthly battery capacity by transforming the ampere-hour integration formula and applying linear regression.Subsequently,a deep learning model is proposed to build a capacity prediction model,using feature maps from historical months to predict the battery capacity of future months,thus facilitating accurate forecasts.The proposed framework,evaluated using field data from 20 EVs,achieves a mean absolute error of 0.79 Ah,a mean absolute percentage error of 0.65%,and a root mean square error of 1.02 Ah,highlighting its potential for real-world EV applications.
基金Project(52374153)supported by the National Natural Science Foundation of ChinaProject(kq2502150)supported by the Natural Science Foundation of Changsha,China。
文摘Cemented tailings backfill(CTB)is a crucial support material for ensuring the long-term stability of underground goafs.A comprehensive understanding of its compressive mechanical behavior is essential for improving engineering safety.Although extensive studies have been conducted on the uniaxial compressive properties of CTB,damage constitutive models that effectively capture its damage evolution process remain underdeveloped,and its failure mechanisms are not yet fully clarified.To address these gaps,this study conducted systematic uniaxial compression tests on CTB specimens prepared with varying cement-tailings ratios.The results revealed distinct compaction and softening phases in the stress−strain curves.A lower cement-tailings ratio significantly reduced the strength and deformation resistance of CTB,along with a decrease in elastic energy accumulation at peak stress and dissipation energy in the post peak stage.Based on these findings,a modified damage constitutive model was developed by introducing a correction factor,enabling accurate simulation of the entire uniaxial compression process of CTB with different cement-tailings ratios.Comparative analysis with classical constitutive models validated the proposed model’s accuracy and applicability in describing the compressive behavior of CTB.Furthermore,particle size distribution and acoustic emission tests were employed to investigate the influence of cement-tailings ratio on failure mechanisms.The results indicated that a lower cement-tailings ratio leads to coarser particle sizes,which intensify shear-related acoustic emission signals and ultimately result in more pronounced macroscopic shear failure.This study provides theoretical support and practical guidance for the optimal design of CTB mix ratios.
