Dear Editor,The letter proposes a tensor low-rank orthogonal compression(TLOC)model for a convolutional neural network(CNN),which facilitates its efficient and highly-accurate low-rank representation.Model compression...Dear Editor,The letter proposes a tensor low-rank orthogonal compression(TLOC)model for a convolutional neural network(CNN),which facilitates its efficient and highly-accurate low-rank representation.Model compression is crucial for deploying deep neural network(DNN)models on resource-constrained embedded devices.展开更多
SiC/Al-based composite foams were prepared by a two-step foaming method.The influence of the SiC content and its distribution uniformity on the foaming stability,cell structure,and mechanical properties of the aluminu...SiC/Al-based composite foams were prepared by a two-step foaming method.The influence of the SiC content and its distribution uniformity on the foaming stability,cell structure,and mechanical properties of the aluminum foams was investigated.The macro/micro-features of the aluminum foams were characterized and analyzed.Results demonstrate that an appropriate increase in SiC content and the uniform distribution of SiC can improve the foaming stability,optimize the cell diameter and cell wall thickness,ameliorate the cell distribution,and enhance the hardness and compressive strength of the aluminum foams.However,either insufficient or excessive SiC leads to uneven distribution of SiC particles,which is unfavorable to foaming stability and good cell structure formation.With 6wt%SiC,both the foaming stability and cell structure of the aluminum foam reach the optimal state,resulting in the highest compressive strength and optimal energy absorption capacity.展开更多
The application and promotion of waste glass powder concrete(WGPC)cansignificantly alleviate the pressure of concrete material scarcity and environmental pollution.Compressive strength(CS)is a critical parameter for e...The application and promotion of waste glass powder concrete(WGPC)cansignificantly alleviate the pressure of concrete material scarcity and environmental pollution.Compressive strength(CS)is a critical parameter for evaluating the efficacy of WGPC.Unlike conventional testing methods,machine learning techniques offer precise and reliable predictions of concrete’s compressive strength,especially in its long-term mechanical properties.In this work,four models,namely Multiple Linear Regression(MLR),Back Propagation Neural Network(BPNN),Support Vector Regression(SVR),and Random Forest Regression(RFR)were employed.Furthermore,particle swarm optimization(PSO)algorithm and cross-validation techniques were applied to fine-tune the model parameters,striving for peak prediction performance.The results indicated that optimized models generally exhibit enhanced predictive accuracy compared to their basic counterparts.Notably,the PSO-RFR model excels among all evaluated models,showcasing superior performance on the testing dataset.It achieves a coefficient of determination(R^(2))of 0.9231,a mean absolute error(MAE)of 2.1073,and a root mean square error(RMSE)of 3.6903.When compared to experimental results,the PSO-RFR and PSO-BPNN models demonstrate exceptional predictive accuracy.Notably,the PSO-BPNN model exhibits the closest R^(2)values between its training and test sets.This close alignment of R^(2)values between the training and testing sets reflects the PSO-BPNN model’s superior generalization ability for unseen data.The findings present an efficient method for predicting concrete’s compressive strength,contributing to the sustainable development of concrete materials,and providing theoretical support for their research and application.展开更多
To achieve the potential performance gain of massive multiple-input multiple-output(MIMO)systems,base stations(BS)require downlink channel state information(CSI)fed back by users to execute beamforming design,especial...To achieve the potential performance gain of massive multiple-input multiple-output(MIMO)systems,base stations(BS)require downlink channel state information(CSI)fed back by users to execute beamforming design,especially in the frequency division duplex(FDD)systems.However,due to the enormous number of antennas in massive MIMO systems,the feedback overhead of downlink CSI acquisition is extremely large.To address this issue,deep learning(DL)techniques have been introduced to de velop high-accuracy feedback strategies under limited backhaul constraints.In this paper,we provide an overview of DL-based CSI compression and feedback approaches in massive MIMO systems.Specifically,we introduce the conventional CSI compression and feedback schemes and the existing problems.Besides,we elaborate on various DL techniques employed in CSI compression from the perspective of network architecture and analyze the advantages of different techniques.We also enumerate the applications of DL-based methods for solving practical challenges in CSI compression and feedback.In addition,we brief the remaining issues in deep CSI compression and indicate potential directions in future wireless networks.展开更多
Rock brittleness is a critical property in geotechnical and energy engineering,as it directly influences the prediction of rock failure and stability assessment.Although numerous methods have been developed to evaluat...Rock brittleness is a critical property in geotechnical and energy engineering,as it directly influences the prediction of rock failure and stability assessment.Although numerous methods have been developed to evaluate brittleness,many fail to comprehensively account for the impacts of microstructural changes,mineralogical characteristics,and stress conditions on energy evolution during failure.This study proposes a novel approach for brittleness evaluation based on the energy evolution throughout the post-peak failure process,integrating two micromechanical mechanisms:crack propagation and frictional sliding.A new brittleness index is defined as the ratio of generated surface energy to released elastic energy,providing a unified framework for assessing both Class I and Class II mechanical behaviors.The brittleness of cyan,white,and gray sandstones was investigated under various confining pressures and moisture conditions using X-ray diffraction(XRD),scanning electron microscopy(SEM),and conventional triaxial compression(CTC)tests.The results demonstrate that brittleness decreases with increasing confining pressure,due to suppressed crack propagation,and increases under saturated conditions,as moisture enhances crack propagation.By establishing connections between mineral composition,microstructural features,and stress-induced responses,the proposed method overcame limitations of previous approaches and offered a more precise tool for evaluating rock brittleness under diverse environmental scenarios.展开更多
Received:06 December 2025;Accepted:25 February 2026;Published:30 March 2026 ABSTRACT:In the last decade,the importance of sustainable construction and artificial intelligence(AI)in civil engineering has been underline...Received:06 December 2025;Accepted:25 February 2026;Published:30 March 2026 ABSTRACT:In the last decade,the importance of sustainable construction and artificial intelligence(AI)in civil engineering has been underlined in many studies.Numerous studies highlighted the superiority of AI techniques over simple and mathematical regression analyses,which suffer from relatively poor generalization and an inability to capture highly non-linear relationships among inputs and output(s)parameters.In this study,to evaluate the compressive strength of concrete with glass powder(GP)and recycled aggregates,600 concrete samples were tested in the laboratory,and their results were evaluated.For intelligent assessment of concrete compressive strength(CCS),the study utilized an improved artificial neural network(ANN)with particle swarm optimization(PSO)algorithm and imperialist competitive algorithm(ICA).For training the models,the experimentally obtained data were used.The concrete ingredients formed the inputs of the AI-based predictive models of CCS.The experimental findings reveal that the implementation of recycled coarse aggregates in concrete from a sustainable construction point of view is advantageous and can enhance the CCS by 11.43%.Apart from that,findings indicate that utilization of 10%GP can lead to a nearly 20%increase in CCS(from 44.6 to 54.1 MPa).Additionally,the experimental observations show almost 40%improvement of CCS when 5%micro silica was used in the concrete mixture.Based on the findings,the study suggests the utilization of waste glass powder to partially replace cement in concrete,which can reduce the amount of cement production.This reduction from economic,energy-saving,and environmental(reduction in greenhouse gas emissions)points of view is of interest.On the other hand,the AI results show that the PSO-based ANN model outperforms the ICA-based ANN for the utilized dataset.According to the findings,the PSO-based ANN predictive model(with a coefficient of determination value of 0.939 and root mean square value of 0.113 for testing data)is a capable tool in predicting the CCS.Hence,this study recommends the implementation of AI-based models in CCS assessment.展开更多
Conglomerate rock's complex and heterogeneous microstructure significantly affects its mechanical properties,especially under dynamic loading.However,research on their dynamic behavior and fracture mechanisms is l...Conglomerate rock's complex and heterogeneous microstructure significantly affects its mechanical properties,especially under dynamic loading.However,research on their dynamic behavior and fracture mechanisms is limited.Through uniaxial compression tests and split Hopkinson pressure bar(SHPB)impact tests,the dynamic compressive mechanical properties and fracture mechanisms of conglomerate rock were studied.Nanoindentation and high-resolution X-ray computed tomography were employed to analyze the micro-mechanical behavior and internal structure of the conglomerate rock.Results indicate significant differences in mechanical properties between different gravel particles and cementing materials,with initial fractures primarily distributed at the gravel-cement interfaces.The dynamic mechanical properties of conglomerate rocks exhibit a clear strain rate dependency.Based on the stress−strain curves and failure characteristics,the dynamic compressive mechanical behavior can be categorized into two types using a critical strain rate.The dynamic compressive strength,peak strain,and toughness of conglomerate rock increased with the strain rate,with the strength at 54 s−1 being 2.6 times that at 6 s−1.The dynamic compressive fracture mechanism of conglomerate rock is related to the strain rate and microstructure;at low strain rates,gravel distribution is the key factor,whereas at high strain rates,gravel content becomes critical.展开更多
The penetration of shaped charge jets into targets at high velocities is significantly influenced by the compressibility effect,while at low velocities,the strength effect becomes predominant.In the latter regime,mate...The penetration of shaped charge jets into targets at high velocities is significantly influenced by the compressibility effect,while at low velocities,the strength effect becomes predominant.In the latter regime,material strength dictates the resistance to plastic deformation and flow,a contrast to the shockwave-dominated interactions where compressibility is key.This paper presents a self-consistent compressible penetration theory that considers both the axial penetration and radial crater growth of shaped charge jets into targets.An integrated approach where the axial and radial dynamics are coupled has been proposed,influencing each other through shared physical principles rather than being treated as separate,empirically linked phenomena.The presented theory is rooted in the compressible Bernoulli equation and the linear Rankine-Hugoniot relation.These foundational equations are employed to accurately model the high-pressure shock state and subsequent material flow at the jet-target interface,providing a robust physical basis for the penetration model.Notably,it considers the target material's compressibility,which elevates the pressure at the jet-target interface beyond that observed with incompressible materials.This pressure increase is directly proportional to the target's degree of compressibility.As such,this model of compressible penetration reorients the analytical approach:rather than merely estimating penetration resistance,it determines this value from the target material's specific compressibility and yield strength.This shift from empirical correlations to a physics-based derivation of penetration resistance enhances the model's predictive power,particularly for novel target materials or engagement conditions outside established experimental datasets.This investigation establishes a quantitative link between the material's yield strength and its penetration resistance.The accuracy of this penetration resistance value is paramount,as it significantly influences the predicted crater diameter;indeed,the crater diameter's sensitivity to this resistance underscores the necessity for its precise determination.Ultimately,by integrating the yield strength of the target material,this framework enables the prediction of both the penetration depth and the resultant crater diameter from a shaped charge jet.The theory's validation involved two experimental sets:the first focused on shaped charge jet penetration into 45#steel at varied stand-offs,while the second utilized targets of high-to ultrahigh-strength steel-fiber reactive powder concrete(RPC)with differing strength characteristics.These experimental campaigns were specifically chosen to test the theory against both ductile metallic alloys,where plastic flow is significant,and advanced quasi-brittle cementitious composites,presenting a broad spectrum of material responses and penetration challenges.Resulting hole profiles derived from theoretical calculations demonstrated a strong correspondence with empirical measurements for both material types.展开更多
Photoacoustic-computed tomography is a novel imaging technique that combines high absorption contrast and deep tissue penetration capability,enabling comprehensive three-dimensional imaging of biological targets.Howev...Photoacoustic-computed tomography is a novel imaging technique that combines high absorption contrast and deep tissue penetration capability,enabling comprehensive three-dimensional imaging of biological targets.However,the increasing demand for higher resolution and real-time imaging results in significant data volume,limiting data storage,transmission and processing efficiency of system.Therefore,there is an urgent need for an effective method to compress the raw data without compromising image quality.This paper presents a photoacoustic-computed tomography 3D data compression method and system based on Wavelet-Transformer.This method is based on the cooperative compression framework that integrates wavelet hard coding with deep learning-based soft decoding.It combines the multiscale analysis capability of wavelet transforms with the global feature modeling advantage of Transformers,achieving high-quality data compression and reconstruction.Experimental results using k-wave simulation suggest that the proposed compression system has advantages under extreme compression conditions,achieving a raw data compression ratio of up to 1:40.Furthermore,three-dimensional data compression experiment using in vivo mouse demonstrated that the maximum peak signal-to-noise ratio(PSNR)and structural similarity index(SSIM)values of reconstructed images reached 38.60 and 0.9583,effectively overcoming detail loss and artifacts introduced by raw data compression.All the results suggest that the proposed system can significantly reduce storage requirements and hardware cost,enhancing computational efficiency and image quality.These advantages support the development of photoacoustic-computed tomography toward higher efficiency,real-time performance and intelligent functionality.展开更多
An in-depth understanding of the behaviours of solid propellants under low-velocity impact loads is crucial for enhancing their safety in applications such as aerospace propulsion.This study investigated the dynamic r...An in-depth understanding of the behaviours of solid propellants under low-velocity impact loads is crucial for enhancing their safety in applications such as aerospace propulsion.This study investigated the dynamic responses of single ammonium perchlorate(AP)/octogen(HMX)particles embedded in a hydroxyl-terminated polybutadiene(HTPB)binder under dynamic compression loading via real-time synchrotron-based X-ray phase contrast imaging and a modified split Hopkinson pressure bar(SHPB)system.The compression of the viscoelastic binder and subsequent dynamic fracturing of the AP/HMX particles were captured.During compression,transverse cracks developed within the AP particles,and their propagation led to particle fracturing,resulting in ductile fracturing.Unlike AP,HMX generated numerous short cracks within the internal and edge regions simultaneously,leading to fragmentation and brittle fracturing.Moreover,particle damage reduced the modulus of the sample,shifting its dynamic stress response from nonlinear elasticity to strain softening and further strain hardening as the binder exhibited plastic deformation.A compression simulation incorporating a real particle microscopic structure was established to study the mechanical response of the interface and particles.The simulation results agreed with the experimental observations.These results indicate that the shear stress at the HTPB-AP interface is greater than that at the HTPB-HMX interface,which is a factor influencing the differences in the mesoscale damage mechanisms of the particles.展开更多
High-performance fiber fabrics and composites experienced transverse compression deformation at ultrahigh strain rates near the impact point when subjected to high-velocity impacts,which significantly affected their b...High-performance fiber fabrics and composites experienced transverse compression deformation at ultrahigh strain rates near the impact point when subjected to high-velocity impacts,which significantly affected their ballistic limits.In this paper,a fiber-scale experimental method for characterizing ultrahigh strain-rate transverse compression behavior was proposed.To begin with,in order to measure the extremely low stress and strain in small specimens,the conventional Hopkinson bar was reduced to the hundred-micron scale,thereby achieving wave impedance matching with single fibers.In addition,tangential and normal laser Doppler velocimetry(LDV)methods were employed to realize non-contact,high-precision,and high-speed axial velocity measurements of micron-scale incident and transmission bars,respectively.Meanwhile,a microscopic observation system was used to facilitate the installation of miniature fiber samples.The experimental setup and procedures were introduced,and the system accuracy was verified through sample-free loading tests based on one-dimensional stress wave propagation theory.Dynamic compression experiments on Graphene-UHMWPE fibers were carried out,followed by post-compression microstructural characterization via scanning electron microscopy(SEM).Results demonstrated that successful mechanical characterization was achieved at strain rates exceeding 105,an order of magnitude higher than the previously reported maximum rates.Furthermore,during the loading process,the fibers underwent uniform compression deformation while exhibiting pronounced strain-rate effects.This method offers a novel approach for dynamic mechanical characterization of microscale single fibers,enabling the development of comprehensive strain-ratedependent material models to guide the design of advanced composites and high-performance fibers.展开更多
Micropillar compression tests were used to investigate the influence of hydrogen on the deformation behavior and hydrogen embrittlement(HE)of nitrogen-alloyed austenitic stainless steel QN_(2)109.Results indicate that...Micropillar compression tests were used to investigate the influence of hydrogen on the deformation behavior and hydrogen embrittlement(HE)of nitrogen-alloyed austenitic stainless steel QN_(2)109.Results indicate that the hydrogen increases the dislocation density,reduces the yield stress,and accelerates the formation and intersection of slip bands,with hydrogen-induced cracks initiating at slip band intersections.X-ray diffraction confirms the absence of martensitic transformation,ruling out the role of martensitic transformation in HE.The micropillar compression technique is highly sensitive for characterizing hydrogen-material interactions,owing to the material’s low hydrogen diffusivity and the small size of its hydrogen-affected zone.These findings align with the hydrogen-enhanced localized plasticity mechanism.展开更多
The deformation and failure of coal walls in front of a working face cause significant difficulties during mining operations.This study reveals the nonuniform distribution of bearing pressure in front of coal walls ba...The deformation and failure of coal walls in front of a working face cause significant difficulties during mining operations.This study reveals the nonuniform distribution of bearing pressure in front of coal walls based on in situ monitoring data and numerical simulation.Therefore,an eccentric compression mechanical model was established to study the deformation and failure characteristics of a coal wall.The slenderness ratio of the compression bar is introduced to define coal walls.The results showed that instability failure occurs when λ>λ_(c) and material failure occurs when λ≤λ_(c).The instability failure-type coal wall spalling was related to the mining height,eccentricity of roof pressure,the horizontal force,and the reaction moment of the floor.The material failure-type coal wall spalling was related to the cohesion,the internal friction angle of the coal,the upper pressure,and the horizontal force of coal walls.Unstable and destructive coal wall peeling usually occurs at a height of 0.5–0.6 times the mining height,while material damage to coal wall peeling is determined to occur within the range of 0.4-0.6 times the mining depth.The findings contribute to the understanding of the deformation and failure of coal walls.展开更多
To promote the application of green recycled construction materials in civil engineering,this study presents a statistical damage constitutive model for polypropylene fiber recycled fine aggregate concrete(PRFAC),base...To promote the application of green recycled construction materials in civil engineering,this study presents a statistical damage constitutive model for polypropylene fiber recycled fine aggregate concrete(PRFAC),based on the strain equivalence principle and the assumption that microelement strength follows a Weibull statistical distribution.The proposed model incorporates the Drucker-Prager failure criterion.By examining the influence of Weibull distribution parameters m and S_(0)on the stress-strain response,empirical relationships were established between the fine aggregate replacement ratio and the distribution parameters.This enabled the derivation of a theoretical stress-strain curve accounting for variable recycled fine aggragate(RFA)replacement ratios.The experimental results show that the proposed model exhibits high agreement with measured data and effectively captures the increased brittleness of PRFAC with higher RFA replacement ratios.Moreover,increasing the replacement rate accelerates internal crack propagation,reduces deformability and toughness,and significantly hastens the accumulation of internal damage in PRFAC.展开更多
To investigate the damage evolution caused by stress-driven and sub-critical crack propagation within the Beishan granite under multi-creep triaxial compressive conditions,the distributed optical fiber sensing and X-r...To investigate the damage evolution caused by stress-driven and sub-critical crack propagation within the Beishan granite under multi-creep triaxial compressive conditions,the distributed optical fiber sensing and X-ray computed tomography were combined to obtain the strain distribution over the sample surface and internal fractures of the samples.The Gini and skewness(G-S)coefficients were used to quantify strain localization during tests,where the Gini coefficient reflects the degree of clustering of elements with high strain values,i.e.,strain localization/delocalization.The strain localization-induced asymmetry of data distribution is quantified by the skewness coefficient.A precursor to granite failure is defined by the rapid and simultaneous increase of the G-S coefficients,which are calculated from strain increment,giving an earlier warning of failure by about 8%peak stress than those from absolute strain values.Moreover,the process of damage accumulation due to stress-driven crack propagation in Beishan granite is different at various confining pressures as the stress exceeds the crack initiation stress.Concretely,strain localization is continuous until brittle failure at higher confining pressure,while both strain localization and delocalization occur at lower confining pressure.Despite the different stress conditions,a similar statistical characteristic of strain localization during the creep stage is observed.The Gini coefficient increases,and the skewness coefficient decreases slightly as the creep stress is below 95%peak stress.When the accelerated strain localization begins,the Gini and skewness coefficients increase rapidly and simultaneously.展开更多
We present the first systematic experimental validation of return-current-driven cylindrical implosion scaling in micrometer-sized Cu and Al wires irradiated by J-class femtosecond laser pulses.Employing XFEL-based im...We present the first systematic experimental validation of return-current-driven cylindrical implosion scaling in micrometer-sized Cu and Al wires irradiated by J-class femtosecond laser pulses.Employing XFEL-based imaging with sub-micrometer spatial and femtosecond temporal resolution,supported by hydrodynamic and particle-in-cell simulations,we reveal how return current density depends precisely on wire diameter,material properties,and incident laser energy.We identify deviations from simple theoretical predictions due to geometrically influenced electron escape dynamics.These results refine and confirm the scaling laws essential for predictive modeling in high-energy-density physics and inertial fusion research.展开更多
This study proposes to use the unconfined compressive strength(UCS)and the bender element(BE)tests for determining the strength and the initial small-strain shear modulus of Bangkok soft marine clay improved by cement...This study proposes to use the unconfined compressive strength(UCS)and the bender element(BE)tests for determining the strength and the initial small-strain shear modulus of Bangkok soft marine clay improved by cement and polyester fibers.This study varies the content of admixed cement(1%–20%)and polyester fibers(0–20%),including the curing time(3–28 d)for preparing 360 samples.Moreover,this study uses the Michaelis-Menten kinetics concept to model cement hydration saturation.From the study,it is concluded as follows.The modelled results reveals that at least 10%cement and 1%polyester fiber are recommended to attain the 28-d UCS standards(294 kPa)for highway subgrade materials in Thailand.This also fulfils sustainable construction due to reducing normal-use cement from 20%to 10%.Unfortunately,the addition of polyester fibers into the Bangkok clay with at least 5%cement reduces shear modulus by 1.12–1.32 times.The Abram's relationship between shear modulus and the mixing-water-to-cement ratio is found time-dependent.From the composite theory,the BE detects the polyester fiber zone as a defect in the Bangkok clay(matrix)with 5%–20%cement.So,the 28-d shear modulus in the polyester fiber zone is negative(up to0.034 MPa for 20%fiber),similar to softening phenomenon in concrete cracking(negative stiffness).For the 28-d shear modulus of fiber zone,the optimum cement content is around 2%for the positive influences of polyester fibers.Experimentally,the timedependent normalized UCS for 10%and 20%cement is compatible with other studies,and its development rate increases with the cement content as 0.3017,0.3172 and 0.3204 for 5%,10%and 20%cement,respectively.The 28-d relationship between shear modulus and UCS shows that low-cement soft clay requires high polyester fiber content(5%–20%)to activate UCS improvement.However,the soft clay with enough cement(20%)causes the uniformly distributed UCS improvement.展开更多
Replacing cement clinker with solid residue is a highly promising decarbonization strategy in soil improvement.Waste clay was improved by desulfurized gypsum and carbide slag using eco-friendly low-temperature hydroth...Replacing cement clinker with solid residue is a highly promising decarbonization strategy in soil improvement.Waste clay was improved by desulfurized gypsum and carbide slag using eco-friendly low-temperature hydrothermal solidification technology in this study.The compressive strength of the hydrothermally solidified waste clay was investigated,and four hybrid prediction models(PSO-RF,PSO-GPR,PSO-GBR,and PSO-AdaBoost)were developed to predict its compressive strength.The results showed that the strength of the hydrothermally solidified waste clay significantly increased but then decreased when the Ca/Si ratio exceeded 0.8–0.9.Water has a dual effect on the strength of hydrothermally solidified waste clay,with an optimum range of approximately 10%–20%.Among the strength prediction models developed for hydrothermally solidified waste clay,the optimization performance and prediction accuracy of PSO-GBR are superior,and the UCS prediction results of other studies with various precursor types have been verified.SHapley Additive exPlanation(SHAP)analysis of the PSO-GBR model revealed that the pressed dry density contributes most significantly to the compressive strength of hydrothermally solidified waste clay,followed by the autoclave temperature,water content,Ca/Si ratio,and autoclave temperature.The impact of each input feature of the prediction model is consistent with the experimental results and previous studies.展开更多
In the field of rock engineering,the influence of water is a dynamic process that exhibits varying effects over time and across different locations.To further understand how water influences the mechanical properties ...In the field of rock engineering,the influence of water is a dynamic process that exhibits varying effects over time and across different locations.To further understand how water influences the mechanical properties and acoustic emission(AE)behavior of rocks,this study conducted uniaxial compression experiments on sandstones with varying degrees of wetting under both natural conditions and water-chemical environments.In addition,the study combined AE equipment with digital image correlation(DIC)to monitor the entire failure process.Using the sliding window algorithm,the variation in the variance of AE characteristic parameters during the process of sandstone loading to failure is analyzed from the perspective of critical slowing down.This analysis enables the effective identification of the early warning signal before failure.The experimental findings suggest that an increase in wetting height results in a gradual decrease in peak stress,accompanied by a concomitant increase in the percentage of shear cracks.The characteristic parameters,including energy,amplitude,and ringing count,all exhibit critical slowing phenomena.The waveform of AE characteristic parameters of the same sample is similar,and the mutation time of the precursor signal is roughly the same.All signals appear in the irreversible plastic deformation stage of microcrack initiation.The integration of critical slowing down theory and the b-value early warning method facilitates a more comprehensive evaluation of the stability of rock mass,thereby significantly enhancing the efficiency and safety of disaster prevention measures.展开更多
The accumulation and circulation of carbon and hydrogen contribute to the chemical evolution of ice giant planets.Species separation and diamond precipitation have been reported in carbon-hydrogen systems and have bee...The accumulation and circulation of carbon and hydrogen contribute to the chemical evolution of ice giant planets.Species separation and diamond precipitation have been reported in carbon-hydrogen systems and have been verified by static and shock compression experiments.Nevertheless,the dynamic formation processes underlying these phenomena remain insufficiently understood.In combination with a deep learning model,we demonstrate that diamonds form through a three-step process involving dissociation,species separation,and nucleation processes.Under shock conditions of 125 GPa and 4590 K,hydrocarbons decompose to give hydrogen and low-molecular-weight alkanes(CH_(4) and C_(2)H_(6)),which escape from the carbon chains,resulting in C/H species separation.The remaining carbon atoms without C-H bonds accumulate and nucleate to form diamond crystals.The process of diamond growth is associated with a critical nucleus size at which the dynamic energy barrier plays a key role.These dynamic processes of diamond formation provide insight into the establishment of a model for the evolution of ice giant planets.展开更多
基金supported by the Science and Technology Innovation Key R&D Program of Chongqing(CSTB2025TIAD-STX0032)National Key Research and Development Program of China(2024YFF0908200)+1 种基金the Chongqing Technology Innovation and Application Development Special Key Project(CSTB2024TIAD-KPX0018)the Southwest University Graduate Student Research Innovation(SWUB24051)。
文摘Dear Editor,The letter proposes a tensor low-rank orthogonal compression(TLOC)model for a convolutional neural network(CNN),which facilitates its efficient and highly-accurate low-rank representation.Model compression is crucial for deploying deep neural network(DNN)models on resource-constrained embedded devices.
基金Doctoral Startup Fund(20192066,20212028)Laijin Excellent Doctoral Fund(20202021)+1 种基金Scientific and Technological Innovation of Colleges and Universities in Shanxi Province(2020L0342)Fundamental Research Program of Shanxi Province(202303021222178)。
文摘SiC/Al-based composite foams were prepared by a two-step foaming method.The influence of the SiC content and its distribution uniformity on the foaming stability,cell structure,and mechanical properties of the aluminum foams was investigated.The macro/micro-features of the aluminum foams were characterized and analyzed.Results demonstrate that an appropriate increase in SiC content and the uniform distribution of SiC can improve the foaming stability,optimize the cell diameter and cell wall thickness,ameliorate the cell distribution,and enhance the hardness and compressive strength of the aluminum foams.However,either insufficient or excessive SiC leads to uneven distribution of SiC particles,which is unfavorable to foaming stability and good cell structure formation.With 6wt%SiC,both the foaming stability and cell structure of the aluminum foam reach the optimal state,resulting in the highest compressive strength and optimal energy absorption capacity.
文摘The application and promotion of waste glass powder concrete(WGPC)cansignificantly alleviate the pressure of concrete material scarcity and environmental pollution.Compressive strength(CS)is a critical parameter for evaluating the efficacy of WGPC.Unlike conventional testing methods,machine learning techniques offer precise and reliable predictions of concrete’s compressive strength,especially in its long-term mechanical properties.In this work,four models,namely Multiple Linear Regression(MLR),Back Propagation Neural Network(BPNN),Support Vector Regression(SVR),and Random Forest Regression(RFR)were employed.Furthermore,particle swarm optimization(PSO)algorithm and cross-validation techniques were applied to fine-tune the model parameters,striving for peak prediction performance.The results indicated that optimized models generally exhibit enhanced predictive accuracy compared to their basic counterparts.Notably,the PSO-RFR model excels among all evaluated models,showcasing superior performance on the testing dataset.It achieves a coefficient of determination(R^(2))of 0.9231,a mean absolute error(MAE)of 2.1073,and a root mean square error(RMSE)of 3.6903.When compared to experimental results,the PSO-RFR and PSO-BPNN models demonstrate exceptional predictive accuracy.Notably,the PSO-BPNN model exhibits the closest R^(2)values between its training and test sets.This close alignment of R^(2)values between the training and testing sets reflects the PSO-BPNN model’s superior generalization ability for unseen data.The findings present an efficient method for predicting concrete’s compressive strength,contributing to the sustainable development of concrete materials,and providing theoretical support for their research and application.
基金supported by ZTE Industry-University-Institute Cooperation Funds under Grant No.IA20240319003the NSFC under Grant No.62571112。
文摘To achieve the potential performance gain of massive multiple-input multiple-output(MIMO)systems,base stations(BS)require downlink channel state information(CSI)fed back by users to execute beamforming design,especially in the frequency division duplex(FDD)systems.However,due to the enormous number of antennas in massive MIMO systems,the feedback overhead of downlink CSI acquisition is extremely large.To address this issue,deep learning(DL)techniques have been introduced to de velop high-accuracy feedback strategies under limited backhaul constraints.In this paper,we provide an overview of DL-based CSI compression and feedback approaches in massive MIMO systems.Specifically,we introduce the conventional CSI compression and feedback schemes and the existing problems.Besides,we elaborate on various DL techniques employed in CSI compression from the perspective of network architecture and analyze the advantages of different techniques.We also enumerate the applications of DL-based methods for solving practical challenges in CSI compression and feedback.In addition,we brief the remaining issues in deep CSI compression and indicate potential directions in future wireless networks.
基金supported by the National Natural Science Foundation of China(Grant No.42277147)Ningbo Public Welfare Research Program(Grant No.2024S081)Ningbo Natural Science Foundation(Grant No.2024J186).
文摘Rock brittleness is a critical property in geotechnical and energy engineering,as it directly influences the prediction of rock failure and stability assessment.Although numerous methods have been developed to evaluate brittleness,many fail to comprehensively account for the impacts of microstructural changes,mineralogical characteristics,and stress conditions on energy evolution during failure.This study proposes a novel approach for brittleness evaluation based on the energy evolution throughout the post-peak failure process,integrating two micromechanical mechanisms:crack propagation and frictional sliding.A new brittleness index is defined as the ratio of generated surface energy to released elastic energy,providing a unified framework for assessing both Class I and Class II mechanical behaviors.The brittleness of cyan,white,and gray sandstones was investigated under various confining pressures and moisture conditions using X-ray diffraction(XRD),scanning electron microscopy(SEM),and conventional triaxial compression(CTC)tests.The results demonstrate that brittleness decreases with increasing confining pressure,due to suppressed crack propagation,and increases under saturated conditions,as moisture enhances crack propagation.By establishing connections between mineral composition,microstructural features,and stress-induced responses,the proposed method overcame limitations of previous approaches and offered a more precise tool for evaluating rock brittleness under diverse environmental scenarios.
文摘Received:06 December 2025;Accepted:25 February 2026;Published:30 March 2026 ABSTRACT:In the last decade,the importance of sustainable construction and artificial intelligence(AI)in civil engineering has been underlined in many studies.Numerous studies highlighted the superiority of AI techniques over simple and mathematical regression analyses,which suffer from relatively poor generalization and an inability to capture highly non-linear relationships among inputs and output(s)parameters.In this study,to evaluate the compressive strength of concrete with glass powder(GP)and recycled aggregates,600 concrete samples were tested in the laboratory,and their results were evaluated.For intelligent assessment of concrete compressive strength(CCS),the study utilized an improved artificial neural network(ANN)with particle swarm optimization(PSO)algorithm and imperialist competitive algorithm(ICA).For training the models,the experimentally obtained data were used.The concrete ingredients formed the inputs of the AI-based predictive models of CCS.The experimental findings reveal that the implementation of recycled coarse aggregates in concrete from a sustainable construction point of view is advantageous and can enhance the CCS by 11.43%.Apart from that,findings indicate that utilization of 10%GP can lead to a nearly 20%increase in CCS(from 44.6 to 54.1 MPa).Additionally,the experimental observations show almost 40%improvement of CCS when 5%micro silica was used in the concrete mixture.Based on the findings,the study suggests the utilization of waste glass powder to partially replace cement in concrete,which can reduce the amount of cement production.This reduction from economic,energy-saving,and environmental(reduction in greenhouse gas emissions)points of view is of interest.On the other hand,the AI results show that the PSO-based ANN model outperforms the ICA-based ANN for the utilized dataset.According to the findings,the PSO-based ANN predictive model(with a coefficient of determination value of 0.939 and root mean square value of 0.113 for testing data)is a capable tool in predicting the CCS.Hence,this study recommends the implementation of AI-based models in CCS assessment.
基金Project(51978674)supported by the National Natural Science Foundation of China。
文摘Conglomerate rock's complex and heterogeneous microstructure significantly affects its mechanical properties,especially under dynamic loading.However,research on their dynamic behavior and fracture mechanisms is limited.Through uniaxial compression tests and split Hopkinson pressure bar(SHPB)impact tests,the dynamic compressive mechanical properties and fracture mechanisms of conglomerate rock were studied.Nanoindentation and high-resolution X-ray computed tomography were employed to analyze the micro-mechanical behavior and internal structure of the conglomerate rock.Results indicate significant differences in mechanical properties between different gravel particles and cementing materials,with initial fractures primarily distributed at the gravel-cement interfaces.The dynamic mechanical properties of conglomerate rocks exhibit a clear strain rate dependency.Based on the stress−strain curves and failure characteristics,the dynamic compressive mechanical behavior can be categorized into two types using a critical strain rate.The dynamic compressive strength,peak strain,and toughness of conglomerate rock increased with the strain rate,with the strength at 54 s−1 being 2.6 times that at 6 s−1.The dynamic compressive fracture mechanism of conglomerate rock is related to the strain rate and microstructure;at low strain rates,gravel distribution is the key factor,whereas at high strain rates,gravel content becomes critical.
基金the Fundamental Research Funds for the Central Universities of Nanjing University of Science and Technology(CN)under Grant No.30924010803。
文摘The penetration of shaped charge jets into targets at high velocities is significantly influenced by the compressibility effect,while at low velocities,the strength effect becomes predominant.In the latter regime,material strength dictates the resistance to plastic deformation and flow,a contrast to the shockwave-dominated interactions where compressibility is key.This paper presents a self-consistent compressible penetration theory that considers both the axial penetration and radial crater growth of shaped charge jets into targets.An integrated approach where the axial and radial dynamics are coupled has been proposed,influencing each other through shared physical principles rather than being treated as separate,empirically linked phenomena.The presented theory is rooted in the compressible Bernoulli equation and the linear Rankine-Hugoniot relation.These foundational equations are employed to accurately model the high-pressure shock state and subsequent material flow at the jet-target interface,providing a robust physical basis for the penetration model.Notably,it considers the target material's compressibility,which elevates the pressure at the jet-target interface beyond that observed with incompressible materials.This pressure increase is directly proportional to the target's degree of compressibility.As such,this model of compressible penetration reorients the analytical approach:rather than merely estimating penetration resistance,it determines this value from the target material's specific compressibility and yield strength.This shift from empirical correlations to a physics-based derivation of penetration resistance enhances the model's predictive power,particularly for novel target materials or engagement conditions outside established experimental datasets.This investigation establishes a quantitative link between the material's yield strength and its penetration resistance.The accuracy of this penetration resistance value is paramount,as it significantly influences the predicted crater diameter;indeed,the crater diameter's sensitivity to this resistance underscores the necessity for its precise determination.Ultimately,by integrating the yield strength of the target material,this framework enables the prediction of both the penetration depth and the resultant crater diameter from a shaped charge jet.The theory's validation involved two experimental sets:the first focused on shaped charge jet penetration into 45#steel at varied stand-offs,while the second utilized targets of high-to ultrahigh-strength steel-fiber reactive powder concrete(RPC)with differing strength characteristics.These experimental campaigns were specifically chosen to test the theory against both ductile metallic alloys,where plastic flow is significant,and advanced quasi-brittle cementitious composites,presenting a broad spectrum of material responses and penetration challenges.Resulting hole profiles derived from theoretical calculations demonstrated a strong correspondence with empirical measurements for both material types.
基金supported by the National Key R&D Program of China[Grant No.2023YFF0713600]the National Natural Science Foundation of China[Grant No.62275062]+3 种基金Project of Shandong Innovation and Startup Community of High-end Medical Apparatus and Instruments[Grant No.2023-SGTTXM-002 and 2024-SGTTXM-005]the Shandong Province Technology Innovation Guidance Plan(Central Leading Local Science and Technology Development Fund)[Grant No.YDZX2023115]the Taishan Scholar Special Funding Project of Shandong Provincethe Shandong Laboratory of Advanced Biomaterials and Medical Devices in Weihai[Grant No.ZL202402].
文摘Photoacoustic-computed tomography is a novel imaging technique that combines high absorption contrast and deep tissue penetration capability,enabling comprehensive three-dimensional imaging of biological targets.However,the increasing demand for higher resolution and real-time imaging results in significant data volume,limiting data storage,transmission and processing efficiency of system.Therefore,there is an urgent need for an effective method to compress the raw data without compromising image quality.This paper presents a photoacoustic-computed tomography 3D data compression method and system based on Wavelet-Transformer.This method is based on the cooperative compression framework that integrates wavelet hard coding with deep learning-based soft decoding.It combines the multiscale analysis capability of wavelet transforms with the global feature modeling advantage of Transformers,achieving high-quality data compression and reconstruction.Experimental results using k-wave simulation suggest that the proposed compression system has advantages under extreme compression conditions,achieving a raw data compression ratio of up to 1:40.Furthermore,three-dimensional data compression experiment using in vivo mouse demonstrated that the maximum peak signal-to-noise ratio(PSNR)and structural similarity index(SSIM)values of reconstructed images reached 38.60 and 0.9583,effectively overcoming detail loss and artifacts introduced by raw data compression.All the results suggest that the proposed system can significantly reduce storage requirements and hardware cost,enhancing computational efficiency and image quality.These advantages support the development of photoacoustic-computed tomography toward higher efficiency,real-time performance and intelligent functionality.
基金supported by the National Natural Science Foundation of China(U2341288 and 12302492)。
文摘An in-depth understanding of the behaviours of solid propellants under low-velocity impact loads is crucial for enhancing their safety in applications such as aerospace propulsion.This study investigated the dynamic responses of single ammonium perchlorate(AP)/octogen(HMX)particles embedded in a hydroxyl-terminated polybutadiene(HTPB)binder under dynamic compression loading via real-time synchrotron-based X-ray phase contrast imaging and a modified split Hopkinson pressure bar(SHPB)system.The compression of the viscoelastic binder and subsequent dynamic fracturing of the AP/HMX particles were captured.During compression,transverse cracks developed within the AP particles,and their propagation led to particle fracturing,resulting in ductile fracturing.Unlike AP,HMX generated numerous short cracks within the internal and edge regions simultaneously,leading to fragmentation and brittle fracturing.Moreover,particle damage reduced the modulus of the sample,shifting its dynamic stress response from nonlinear elasticity to strain softening and further strain hardening as the binder exhibited plastic deformation.A compression simulation incorporating a real particle microscopic structure was established to study the mechanical response of the interface and particles.The simulation results agreed with the experimental observations.These results indicate that the shear stress at the HTPB-AP interface is greater than that at the HTPB-HMX interface,which is a factor influencing the differences in the mesoscale damage mechanisms of the particles.
基金financial support provided by the National Natural Science Foundation of China(Grant No.12302472)the Science and Technology Support Program of Jiangsu Province(Grant No.BK20230874)+2 种基金the Aeronautical Science Fund(ASF)(Grant No.2023Z057052005)the Research Fund of State Key Laboratory of Mechanics and Control for Aerospace Structures(Nanjing University of Aeronautics and Astronautics)(Grant No.MCAS-I-0124G02)the funding received from Jiangsu Hanvo Safety Product Co.,Ltd。
文摘High-performance fiber fabrics and composites experienced transverse compression deformation at ultrahigh strain rates near the impact point when subjected to high-velocity impacts,which significantly affected their ballistic limits.In this paper,a fiber-scale experimental method for characterizing ultrahigh strain-rate transverse compression behavior was proposed.To begin with,in order to measure the extremely low stress and strain in small specimens,the conventional Hopkinson bar was reduced to the hundred-micron scale,thereby achieving wave impedance matching with single fibers.In addition,tangential and normal laser Doppler velocimetry(LDV)methods were employed to realize non-contact,high-precision,and high-speed axial velocity measurements of micron-scale incident and transmission bars,respectively.Meanwhile,a microscopic observation system was used to facilitate the installation of miniature fiber samples.The experimental setup and procedures were introduced,and the system accuracy was verified through sample-free loading tests based on one-dimensional stress wave propagation theory.Dynamic compression experiments on Graphene-UHMWPE fibers were carried out,followed by post-compression microstructural characterization via scanning electron microscopy(SEM).Results demonstrated that successful mechanical characterization was achieved at strain rates exceeding 105,an order of magnitude higher than the previously reported maximum rates.Furthermore,during the loading process,the fibers underwent uniform compression deformation while exhibiting pronounced strain-rate effects.This method offers a novel approach for dynamic mechanical characterization of microscale single fibers,enabling the development of comprehensive strain-ratedependent material models to guide the design of advanced composites and high-performance fibers.
基金support from the National Natural Science Foundation of China(Grant No.U24A20105 and 52071209)the Major Scientific and Technological Innovation Project of CITIC Group(Grant No.2022ZXKYA06100,with Hongzhou Lu as the principal grant recipient)the Program of Shanghai Academic and Technology Research Leader(Grant No.18XD1402200).
文摘Micropillar compression tests were used to investigate the influence of hydrogen on the deformation behavior and hydrogen embrittlement(HE)of nitrogen-alloyed austenitic stainless steel QN_(2)109.Results indicate that the hydrogen increases the dislocation density,reduces the yield stress,and accelerates the formation and intersection of slip bands,with hydrogen-induced cracks initiating at slip band intersections.X-ray diffraction confirms the absence of martensitic transformation,ruling out the role of martensitic transformation in HE.The micropillar compression technique is highly sensitive for characterizing hydrogen-material interactions,owing to the material’s low hydrogen diffusivity and the small size of its hydrogen-affected zone.These findings align with the hydrogen-enhanced localized plasticity mechanism.
基金Youth Innovation Team of Shandong Higher Education Institutions,Grant/Award Number:2022KJ214Shandong Postdoctoral Science Foundation,Grant/Award Number:SDCXZG‐202303031+2 种基金China Postdoctoral Science Foundation,Grant/Award Number:2023M732109National Natural Science Foundation of China,Grant/Award Number:52209141Natural Science Foundation of Shandong Province,China,Grant/Award Number:ZR2021QE069。
文摘The deformation and failure of coal walls in front of a working face cause significant difficulties during mining operations.This study reveals the nonuniform distribution of bearing pressure in front of coal walls based on in situ monitoring data and numerical simulation.Therefore,an eccentric compression mechanical model was established to study the deformation and failure characteristics of a coal wall.The slenderness ratio of the compression bar is introduced to define coal walls.The results showed that instability failure occurs when λ>λ_(c) and material failure occurs when λ≤λ_(c).The instability failure-type coal wall spalling was related to the mining height,eccentricity of roof pressure,the horizontal force,and the reaction moment of the floor.The material failure-type coal wall spalling was related to the cohesion,the internal friction angle of the coal,the upper pressure,and the horizontal force of coal walls.Unstable and destructive coal wall peeling usually occurs at a height of 0.5–0.6 times the mining height,while material damage to coal wall peeling is determined to occur within the range of 0.4-0.6 times the mining depth.The findings contribute to the understanding of the deformation and failure of coal walls.
基金The National Natural Science Foundation of China(No.52168022).
文摘To promote the application of green recycled construction materials in civil engineering,this study presents a statistical damage constitutive model for polypropylene fiber recycled fine aggregate concrete(PRFAC),based on the strain equivalence principle and the assumption that microelement strength follows a Weibull statistical distribution.The proposed model incorporates the Drucker-Prager failure criterion.By examining the influence of Weibull distribution parameters m and S_(0)on the stress-strain response,empirical relationships were established between the fine aggregate replacement ratio and the distribution parameters.This enabled the derivation of a theoretical stress-strain curve accounting for variable recycled fine aggragate(RFA)replacement ratios.The experimental results show that the proposed model exhibits high agreement with measured data and effectively captures the increased brittleness of PRFAC with higher RFA replacement ratios.Moreover,increasing the replacement rate accelerates internal crack propagation,reduces deformability and toughness,and significantly hastens the accumulation of internal damage in PRFAC.
基金supported by the National Natural Science Foundation of China(Grant No.52339001).
文摘To investigate the damage evolution caused by stress-driven and sub-critical crack propagation within the Beishan granite under multi-creep triaxial compressive conditions,the distributed optical fiber sensing and X-ray computed tomography were combined to obtain the strain distribution over the sample surface and internal fractures of the samples.The Gini and skewness(G-S)coefficients were used to quantify strain localization during tests,where the Gini coefficient reflects the degree of clustering of elements with high strain values,i.e.,strain localization/delocalization.The strain localization-induced asymmetry of data distribution is quantified by the skewness coefficient.A precursor to granite failure is defined by the rapid and simultaneous increase of the G-S coefficients,which are calculated from strain increment,giving an earlier warning of failure by about 8%peak stress than those from absolute strain values.Moreover,the process of damage accumulation due to stress-driven crack propagation in Beishan granite is different at various confining pressures as the stress exceeds the crack initiation stress.Concretely,strain localization is continuous until brittle failure at higher confining pressure,while both strain localization and delocalization occur at lower confining pressure.Despite the different stress conditions,a similar statistical characteristic of strain localization during the creep stage is observed.The Gini coefficient increases,and the skewness coefficient decreases slightly as the creep stress is below 95%peak stress.When the accelerated strain localization begins,the Gini and skewness coefficients increase rapidly and simultaneously.
基金partially supported by the Center for Advanced Systems Understanding(CASUS)financed by Germany’s Federal Ministry of Education and Research(BMBF)+2 种基金the Saxon State Government out of the State Budget approved by the Saxon State Parliamentfunding from the European Union’s Just Transition Fund(JTF)within the project Röntgenlaser-Optimierung der Laserfusion(ROLF),Contract No.5086999001co-financed by the Saxon State Government out of the State Budget approved by the Saxon State Parliament.
文摘We present the first systematic experimental validation of return-current-driven cylindrical implosion scaling in micrometer-sized Cu and Al wires irradiated by J-class femtosecond laser pulses.Employing XFEL-based imaging with sub-micrometer spatial and femtosecond temporal resolution,supported by hydrodynamic and particle-in-cell simulations,we reveal how return current density depends precisely on wire diameter,material properties,and incident laser energy.We identify deviations from simple theoretical predictions due to geometrically influenced electron escape dynamics.These results refine and confirm the scaling laws essential for predictive modeling in high-energy-density physics and inertial fusion research.
基金allocated by National Science,Research and Innovation Fund(NSRF)King Mongkut's University of Technology North Bangkok(project no.KMUTNB-FF-67-B-44 and KMUTNB-FF-67-B-45)supported by the NSRF through the Program Management Unit for Human Resources&Institutional Development,Research and Innovation(grant no.B40G660036).
文摘This study proposes to use the unconfined compressive strength(UCS)and the bender element(BE)tests for determining the strength and the initial small-strain shear modulus of Bangkok soft marine clay improved by cement and polyester fibers.This study varies the content of admixed cement(1%–20%)and polyester fibers(0–20%),including the curing time(3–28 d)for preparing 360 samples.Moreover,this study uses the Michaelis-Menten kinetics concept to model cement hydration saturation.From the study,it is concluded as follows.The modelled results reveals that at least 10%cement and 1%polyester fiber are recommended to attain the 28-d UCS standards(294 kPa)for highway subgrade materials in Thailand.This also fulfils sustainable construction due to reducing normal-use cement from 20%to 10%.Unfortunately,the addition of polyester fibers into the Bangkok clay with at least 5%cement reduces shear modulus by 1.12–1.32 times.The Abram's relationship between shear modulus and the mixing-water-to-cement ratio is found time-dependent.From the composite theory,the BE detects the polyester fiber zone as a defect in the Bangkok clay(matrix)with 5%–20%cement.So,the 28-d shear modulus in the polyester fiber zone is negative(up to0.034 MPa for 20%fiber),similar to softening phenomenon in concrete cracking(negative stiffness).For the 28-d shear modulus of fiber zone,the optimum cement content is around 2%for the positive influences of polyester fibers.Experimentally,the timedependent normalized UCS for 10%and 20%cement is compatible with other studies,and its development rate increases with the cement content as 0.3017,0.3172 and 0.3204 for 5%,10%and 20%cement,respectively.The 28-d relationship between shear modulus and UCS shows that low-cement soft clay requires high polyester fiber content(5%–20%)to activate UCS improvement.However,the soft clay with enough cement(20%)causes the uniformly distributed UCS improvement.
基金supported by the National Natural Science Foundation of China(Grant No.52178327).
文摘Replacing cement clinker with solid residue is a highly promising decarbonization strategy in soil improvement.Waste clay was improved by desulfurized gypsum and carbide slag using eco-friendly low-temperature hydrothermal solidification technology in this study.The compressive strength of the hydrothermally solidified waste clay was investigated,and four hybrid prediction models(PSO-RF,PSO-GPR,PSO-GBR,and PSO-AdaBoost)were developed to predict its compressive strength.The results showed that the strength of the hydrothermally solidified waste clay significantly increased but then decreased when the Ca/Si ratio exceeded 0.8–0.9.Water has a dual effect on the strength of hydrothermally solidified waste clay,with an optimum range of approximately 10%–20%.Among the strength prediction models developed for hydrothermally solidified waste clay,the optimization performance and prediction accuracy of PSO-GBR are superior,and the UCS prediction results of other studies with various precursor types have been verified.SHapley Additive exPlanation(SHAP)analysis of the PSO-GBR model revealed that the pressed dry density contributes most significantly to the compressive strength of hydrothermally solidified waste clay,followed by the autoclave temperature,water content,Ca/Si ratio,and autoclave temperature.The impact of each input feature of the prediction model is consistent with the experimental results and previous studies.
基金support from the National Natural Science Foundation of China(Grant Nos.52104207 and 52374214)the Shandong Provincial Youth Innovation Team Development Program for Higher Education Institutions(Grant No.2023KJ305).
文摘In the field of rock engineering,the influence of water is a dynamic process that exhibits varying effects over time and across different locations.To further understand how water influences the mechanical properties and acoustic emission(AE)behavior of rocks,this study conducted uniaxial compression experiments on sandstones with varying degrees of wetting under both natural conditions and water-chemical environments.In addition,the study combined AE equipment with digital image correlation(DIC)to monitor the entire failure process.Using the sliding window algorithm,the variation in the variance of AE characteristic parameters during the process of sandstone loading to failure is analyzed from the perspective of critical slowing down.This analysis enables the effective identification of the early warning signal before failure.The experimental findings suggest that an increase in wetting height results in a gradual decrease in peak stress,accompanied by a concomitant increase in the percentage of shear cracks.The characteristic parameters,including energy,amplitude,and ringing count,all exhibit critical slowing phenomena.The waveform of AE characteristic parameters of the same sample is similar,and the mutation time of the precursor signal is roughly the same.All signals appear in the irreversible plastic deformation stage of microcrack initiation.The integration of critical slowing down theory and the b-value early warning method facilitates a more comprehensive evaluation of the stability of rock mass,thereby significantly enhancing the efficiency and safety of disaster prevention measures.
基金supported by the National Natural Science Foundation of China(Grant Nos.12534013,12047561,and 12104507)the Science and Technology Innovation Program of Hunan Province(Grant Nos.2025ZYJ001 and 2021RC4026)the National University of Defense Technology Research Fund Project.
文摘The accumulation and circulation of carbon and hydrogen contribute to the chemical evolution of ice giant planets.Species separation and diamond precipitation have been reported in carbon-hydrogen systems and have been verified by static and shock compression experiments.Nevertheless,the dynamic formation processes underlying these phenomena remain insufficiently understood.In combination with a deep learning model,we demonstrate that diamonds form through a three-step process involving dissociation,species separation,and nucleation processes.Under shock conditions of 125 GPa and 4590 K,hydrocarbons decompose to give hydrogen and low-molecular-weight alkanes(CH_(4) and C_(2)H_(6)),which escape from the carbon chains,resulting in C/H species separation.The remaining carbon atoms without C-H bonds accumulate and nucleate to form diamond crystals.The process of diamond growth is associated with a critical nucleus size at which the dynamic energy barrier plays a key role.These dynamic processes of diamond formation provide insight into the establishment of a model for the evolution of ice giant planets.
