Activation pruning reduces neural network complexity by eliminating low-importance neuron activations,yet identifying the critical pruning threshold—beyond which accuracy rapidly deteriorates—remains computationally...Activation pruning reduces neural network complexity by eliminating low-importance neuron activations,yet identifying the critical pruning threshold—beyond which accuracy rapidly deteriorates—remains computationally expensive and typically requires exhaustive search.We introduce a thermodynamics-inspired framework that treats activation distributions as energy-filtered physical systems and employs the free energy of activations as a principled evaluation metric.Phase-transition-like phenomena in the free-energy profile—such as extrema,inflection points,and curvature changes—yield reliable estimates of the critical pruning threshold,providing a theoretically grounded means of predicting sharp accuracy degradation.To further enhance efficiency,we propose a renormalized free energy technique that approximates full-evaluation free energy using only the activation distribution of the unpruned network.This eliminates repeated forward passes,dramatically reducing computational overhead and achieving speedups of up to 550×for MLPs.Extensive experiments across diverse vision architectures(MLP,CNN,ResNet,MobileNet,Vision Transformer)and text models(LSTM,BERT,ELECTRA,T5,GPT-2)on multiple datasets validate the generality,robustness,and computational efficiency of our approach.Overall,this work establishes a theoretically grounded and practically effective framework for activation pruning,bridging the gap between analytical understanding and efficient deployment of sparse neural 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
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
This study investigates the performance enhancement of super-sulfated cement(SSC)derived from arsenic-containing bio-oxidation waste(BW)through the incorporation of carbonated recycled concrete fines(CRCF).The finding...This study investigates the performance enhancement of super-sulfated cement(SSC)derived from arsenic-containing bio-oxidation waste(BW)through the incorporation of carbonated recycled concrete fines(CRCF).The findings revealed that the addition of 5wt%CRCF yields optimal performance,with compressive strengths reaching approximately 1.83,12.59,and 42.81 MPa at 1,3,and 28 d,respectively.These values represented significant increases of 408.3%,10.0%,and 14.3%compared to the reference sample.The improvement was attributed to the synergistic effects of ultrafine CRCF particles acting as fillers and nucleation sites,as well as the high reactivity of silica gels,which promoted the formation of additional hydration gels.Microstructural analysis confirmed that CRCF addition refined pore structure,and enhanced the stiffness of C-S-H gels.Furthermore,CRCF served as a net CO_(2) sink,sequestering 0.268 kg CO_(2) per kilogram of CRCF and thereby reducing the carbon footprint of SSC.In addition,the feasibility of applying CRCF-modified SSC in cemented paste backfill(CPB)is highlighted,given the high cement-related carbon footprint of conventional CPB.When 5wt%CRCFmodified SSC was employed in CPB,its 3-d compressive strength attained over 70%of that of ordinary Portland cement(OPC),while the 28-d strength was comparable to that of OPC.The proposed binder thus provides a sustainable pathway for BW valorization,combining waste utilization,carbon sequestration,and improved engineering performance.展开更多
Dynamic disturbances with various frequencies could trigger different failure modes of deep excavations.Superimposed on this static stress are dynamic disturbances due to various dynamic vibrations,e.g.excavation blas...Dynamic disturbances with various frequencies could trigger different failure modes of deep excavations.Superimposed on this static stress are dynamic disturbances due to various dynamic vibrations,e.g.excavation blasting,blasting,tunnel boring machine(TBM)vibration,rockburst wave,earthquakes.Specifically,these dynamic sources are characterized by a wide range of wave frequencies f,resulting in differences in failure modes.A series of true-triaxial compression tests were conducted on granite to simulate the excavation-induced stress path in three-dimensional(3D)stresses.Subsequently,a dynamic disturbance with various frequencies was applied to a cuboid specimen,to reveal the behavior associated with brittle failure.The dynamic disturbance with frequencies f of 5 Hz,10 Hz,and 40 Hz generates less disturbed energy components in the granite together with higher peak strength.However,dynamic disturbances with f of 20 Hz and 30 Hz resulted in a lower peak strength;the peak strength of the rock increases sp albeit it decreases at first,then increases.This U-shaped phenomenon relates to the natural frequency of the granite under such stress conditions.Different rock lithologies consisting of diverse mineral composition,respond differently to each sensitive resonance frequency.Interestingly,the weak disturbance stress with a high frequency f and low amplitude A increases the ratio of crack damage to peak strength(scd/sp)in the granite.This leads to the inhibition of the expansion of the granite during the dynamic disturbance process.Multiple penetrating tensileeshear cracks appear in the s3-direction as the disturbance frequency f increases.展开更多
In complex geological environments,the analysis of drill cores to determine rock strength can be challenging due to the wide variability in the degree of fracturing,leading to subjectivity in the collection of represe...In complex geological environments,the analysis of drill cores to determine rock strength can be challenging due to the wide variability in the degree of fracturing,leading to subjectivity in the collection of representative samples for uniaxial compressive strength testing.This study evaluates non-destructive techniques on calcareous rocks with different tectonic deformations,including Equotip hardness,ultrasound P-wave velocity,thin section analysis,and calcimetry,integrated with photogrammetric fracture analysis.The investigated carbonate rock samples are sourced from drill cores derived from the Umbria-Marche fold and thrust belt(northern Apennines,Italy),including a gently dipping limb of an anticline,a hinge zone of an anticline,and a fault zone associated with a thrust.Fracture intensity,quantified by the P21 parameter using photogrammetric techniques on pre-loading rock samples,is assessed alongside macroscopic identification of discontinuities(such as stylolites,veins,and joints)using marker colours to monitor failures during uniaxial compression testing.Empirical correlations depicted by single and multi-linear relationships indicate a strong dependence between the mechanical and physical properties of limestones.Both Equotip and P-wave velocity are influenced by fracture intensity,but P-wave velocity varies significantly with discontinuity orientation,especially at 45°-90°.To refine uniaxial compressive strength predictions and mitigate multicollinearity,statistical approaches,including linear and multilinear regression,Principal Component Analysis and Gaussian Process Regression,were tested.Findings improve the reliability of non-destructive techniques for assessing rock strength in structurally complex settings,with implications for geotechnical applications.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
Unconfined Compressive Strength(UCS)is a key parameter for the assessment of the stability and performance of stabilized soils,yet traditional laboratory testing is both time and resource intensive.In this study,an in...Unconfined Compressive Strength(UCS)is a key parameter for the assessment of the stability and performance of stabilized soils,yet traditional laboratory testing is both time and resource intensive.In this study,an interpretable machine learning approach to UCS prediction is presented,pairing five models(Random Forest(RF),Gradient Boosting(GB),Extreme Gradient Boosting(XGB),CatBoost,and K-Nearest Neighbors(KNN))with SHapley Additive exPlanations(SHAP)for enhanced interpretability and to guide feature removal.A complete dataset of 12 geotechnical and chemical parameters,i.e.,Atterberg limits,compaction properties,stabilizer chemistry,dosage,curing time,was used to train and test the models.R2,RMSE,MSE,and MAE were used to assess performance.Initial results with all 12 features indicated that boosting-based models(GB,XGB,CatBoost)exhibited the highest predictive accuracy(R^(2)=0.93)with satisfactory generalization on test data,followed by RF and KNN.SHAP analysis consistently picked CaO content,curing time,stabilizer dosage,and compaction parameters as the most important features,aligning with established soil stabilization mechanisms.Models were then re-trained on the top 8 and top 5 SHAP-ranked features.Interestingly,GB,XGB,and CatBoost maintained comparable accuracy with reduced input sets,while RF was moderately sensitive and KNN was somewhat better owing to reduced dimensionality.The findings confirm that feature reduction through SHAP enables cost-effective UCS prediction through the reduction of laboratory test requirements without significant accuracy loss.The suggested hybrid approach offers an explainable,interpretable,and cost-effective tool for geotechnical engineering practice.展开更多
This study presents and verifies a hybrid methodology for reliable determination of parameters in structural rheological models(Zener,Burgers,and Maxwell)describing the viscoelastic behavior of polyurethane specimens ...This study presents and verifies a hybrid methodology for reliable determination of parameters in structural rheological models(Zener,Burgers,and Maxwell)describing the viscoelastic behavior of polyurethane specimens manufactured using extrusion-based 3D printing.Through comprehensive testing,including cyclic compression at strain rates ranging from 0.12 to 120 mm/min(0%-15%strain)and creep/relaxation experiments(10%-30%strain),the lumped parameters were independently determined using both analytical and numerical solutions of the models’differential equations,followed by cross-verification in additional experiments.Numerical solutions for creep and relaxation problems were obtained using finite element analysis,with the three-parameter Mooney-Rivlin model and Prony series employed to simulate elastic and viscous stress components,respectively.Energy dissipation per cycle was quantified during cyclic compression tests.The results demonstrate that all three models adequately describe material behavior within the 0%-15%strain range across various strain rates.Comparative analysis revealed the Burgers model’s superior performance in characterizing creep and stress relaxation at low strain levels.While Zener and Burgers model parameters from uniaxial compression showed limited applicability for energy dissipation calculations,the generalized Maxwell model effectively captured viscoelastic properties across different strain rates.Notably,parameters derived from creep tests provided a more universal assessment of dissipative properties due to optimization based on characteristic curve regions.Both parameter sets described polyurethane’s elastic-hysteretic behavior with approximately 20%error,proving significantly more accurate than the linear strain-time dependence hypothesis.Finite element analysis(FEA)complemented numerical modeling by demonstrating that while the generalized Maxwell model effectively describes initial rapid stress-strain changes,FEA provides superior characterization of steady-state processes.This computational approach yields more physically representative results compared to simplified analytical solutions,despite certain limitations in transient analysis.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
Deep neural networks have achieved excellent classification results on several computer vision benchmarks.This has led to the popularity of machine learning as a service,where trained algorithms are hosted on the clou...Deep neural networks have achieved excellent classification results on several computer vision benchmarks.This has led to the popularity of machine learning as a service,where trained algorithms are hosted on the cloud and inference can be obtained on real-world data.In most applications,it is important to compress the vision data due to the enormous bandwidth and memory requirements.Video codecs exploit spatial and temporal correlations to achieve high compression ratios,but they are computationally expensive.This work computes the motion fields between consecutive frames to facilitate the efficient classification of videos.However,contrary to the normal practice of reconstructing the full-resolution frames through motion compensation,this work proposes to infer the class label from the block-based computed motion fields directly.Motion fields are a richer and more complex representation of motion vectors,where each motion vector carries the magnitude and direction information.This approach has two advantages:the cost of motion compensation and video decoding is avoided,and the dimensions of the input signal are highly reduced.This results in a shallower network for classification.The neural network can be trained using motion vectors in two ways:complex representations and magnitude-direction pairs.The proposed work trains a convolutional neural network on the direction and magnitude tensors of the motion fields.Our experimental results show 20×faster convergence during training,reduced overfitting,and accelerated inference on a hand gesture recognition dataset compared to full-resolution and downsampled frames.We validate the proposed methodology on the HGds dataset,achieving a testing accuracy of 99.21%,on the HMDB51 dataset,achieving 82.54%accuracy,and on the UCF101 dataset,achieving 97.13%accuracy,outperforming state-of-the-art methods in computational efficiency.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
Internal structural defects in engineering rock masses vary in size,exhibit complex shapes,and are unevenly distributed.Dominant fractures within a rock mass often play a critical to its mechanical behavior,directly a...Internal structural defects in engineering rock masses vary in size,exhibit complex shapes,and are unevenly distributed.Dominant fractures within a rock mass often play a critical to its mechanical behavior,directly affecting the macromechanical properties and failure modes.These fractures affect the instability and failure of the surrounding rock,significantlyimpacting the overall stability of engineering structures.Herein,sand-powder three-dimensional(3D)printing technology was used to prepare rock-like specimens with internal fracture networks.Triaxial compression testing,post-failure fracture mapping,and fractal dimension analysis of the fracture surfaces were conducted to investigate the effects of dominant fracture angles on the strength and deformation of rocks with internal fracture networks under triaxial stress.The results indicate that the dominant fracture angle has a pronounced effect on the mechanical behavior of rock.With increasing angle,both compressive strength and elastic modulus exhibit an initial decline followed by an increase.Moreover,higher confiningpressure significantlyimproves the compressive strength of fractured rock.This enhancement weakens as the confiningpressure further increases.Moreover,with increasing confiningpressure,the differences between the maximum and minimum values of elastic moduli and lateral strain ratios in fractured rock gradually decrease.Thus,the impact of the dominant fracture angle on rock mass deformation decreases with increasing confiningpressure.This research elucidates the effects of dominant fracture angles on the mechanical and failure properties of complex fractured rock masses and the influenceof the confiningpressure on these relationships.It provides valuable theoretical insights and practical guidance for stability analyses in engineering rock masses.展开更多
Convex feasibility problems are widely used in image reconstruction, sparse signal recovery, and other areas. This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recov...Convex feasibility problems are widely used in image reconstruction, sparse signal recovery, and other areas. This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recovery. We first derive the projection formulas for a vector onto the feasible sets. The centralized circumcentered-reflection method is designed to solve the convex feasibility problem. Some numerical experiments demonstrate the feasibility and effectiveness of the proposed algorithm, showing superior performance compared to conventional alternating projection methods.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
Soft clay treatment with all industrial by-product(IBP)binder has great economic and environmental benefits,yet its geomechanics and mechanisms still need to be well probed.With the activation by calcium carbide resid...Soft clay treatment with all industrial by-product(IBP)binder has great economic and environmental benefits,yet its geomechanics and mechanisms still need to be well probed.With the activation by calcium carbide residue(CCR)and phosphogypsum(PG),the strength,structure,and mechanisms of soft clay treated by aluminosilicate-rich IBP(AS-IBP,such as ground granulated blast furnace slag(GGBS),fly ash(FA),coal gangue(CG),Bayer red mud(BR),and sintered red mud(SR))are comparatively investigated.The strength characteristics of solidified clay exhibit significant differences as AS-IBP changes.When GGBS is adopted,the strength is sensitive to the change in PG content,while the impact of CCR is insignificant.After 90 d,the strength of the optimal sample(G23)reaches 1.40 MPa,35.9%higher than cement solidified clay(CSC),while that achieved by other AS-IBPs is less than 0.3 MPa.In the compression test,the structure's evolutionary trend of G23 has a sudden change as the strength increases from 1.81 MPa to 2.29 MPa,suggesting the transformation in material properties.Besides,the structure of G23 is stronger than CSC,which contributes more to the compressive performance.The total amount of main products(C-S-H and ettringite)of all-IBP solidified clay determines the strength,and ettringite is only significant when calcium-rich AS-IBP is adopted.The total amount of minor products(C-A-H and C-A-S-H)is similar for different samples,equivalent to 28.9%-46.3%of the main products.The relationship between the strength and the product amount can be presented using an exponential function.展开更多
The biological stabilization of soil using microbially induced carbonate precipitation(MICP)employs ureolytic bacteria to precipitate calcium carbonate(CaCO3),which binds soil particles,enhancing strength,stiffness,an...The biological stabilization of soil using microbially induced carbonate precipitation(MICP)employs ureolytic bacteria to precipitate calcium carbonate(CaCO3),which binds soil particles,enhancing strength,stiffness,and erosion resistance.The unconfinedcompressive strength(UCS),a key measure of soil strength,is critical in geotechnical engineering as it directly reflectsthe mechanical stability of treated soils.This study integrates explainable artificialintelligence(XAI)with geotechnical insights to model the UCS of MICP-treated sands.Using 517 experimental data points and a combination of various input variables—including median grain size(D50),coefficientof uniformity(Cu),void ratio(e),urea concentration(Mu),calcium concentration(Mc),optical density(OD)of bacterial solution,pH,and total injection volume(Vt)—fivemachine learning(ML)models,including eXtreme gradient boosting(XGBoost),Light gradient boosting machine(LightGBM),random forest(RF),gene expression programming(GEP),and multivariate adaptive regression splines(MARS),were developed and optimized.The ensemble models(XGBoost,LightGBM,and RF)were optimized using the Chernobyl disaster optimizer(CDO),a recently developed metaheuristic algorithm.Of these,LightGBM-CDO achieved the highest accuracy for UCS prediction.XAI techniques like feature importance analysis(FIA),SHapley additive exPlanations(SHAP),and partial dependence plots(PDPs)were also used to investigate the complex non-linear relationships between the input and output variables.The results obtained have demonstrated that the XAI-driven models can enhance the predictive accuracy and interpretability of MICP processes,offering a sustainable pathway for optimizing geotechnical applications.展开更多
基金output of a research project implemented as part of the Basic Research Program at HSE University。
文摘Activation pruning reduces neural network complexity by eliminating low-importance neuron activations,yet identifying the critical pruning threshold—beyond which accuracy rapidly deteriorates—remains computationally expensive and typically requires exhaustive search.We introduce a thermodynamics-inspired framework that treats activation distributions as energy-filtered physical systems and employs the free energy of activations as a principled evaluation metric.Phase-transition-like phenomena in the free-energy profile—such as extrema,inflection points,and curvature changes—yield reliable estimates of the critical pruning threshold,providing a theoretically grounded means of predicting sharp accuracy degradation.To further enhance efficiency,we propose a renormalized free energy technique that approximates full-evaluation free energy using only the activation distribution of the unpruned network.This eliminates repeated forward passes,dramatically reducing computational overhead and achieving speedups of up to 550×for MLPs.Extensive experiments across diverse vision architectures(MLP,CNN,ResNet,MobileNet,Vision Transformer)and text models(LSTM,BERT,ELECTRA,T5,GPT-2)on multiple datasets validate the generality,robustness,and computational efficiency of our approach.Overall,this work establishes a theoretically grounded and practically effective framework for activation pruning,bridging the gap between analytical understanding and efficient deployment of sparse neural 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.
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supports from the National Natural Science Foundation of China(No.52304148)the Youth Project of Shanxi Basic Research Program(No.202203021212262).
文摘This study investigates the performance enhancement of super-sulfated cement(SSC)derived from arsenic-containing bio-oxidation waste(BW)through the incorporation of carbonated recycled concrete fines(CRCF).The findings revealed that the addition of 5wt%CRCF yields optimal performance,with compressive strengths reaching approximately 1.83,12.59,and 42.81 MPa at 1,3,and 28 d,respectively.These values represented significant increases of 408.3%,10.0%,and 14.3%compared to the reference sample.The improvement was attributed to the synergistic effects of ultrafine CRCF particles acting as fillers and nucleation sites,as well as the high reactivity of silica gels,which promoted the formation of additional hydration gels.Microstructural analysis confirmed that CRCF addition refined pore structure,and enhanced the stiffness of C-S-H gels.Furthermore,CRCF served as a net CO_(2) sink,sequestering 0.268 kg CO_(2) per kilogram of CRCF and thereby reducing the carbon footprint of SSC.In addition,the feasibility of applying CRCF-modified SSC in cemented paste backfill(CPB)is highlighted,given the high cement-related carbon footprint of conventional CPB.When 5wt%CRCFmodified SSC was employed in CPB,its 3-d compressive strength attained over 70%of that of ordinary Portland cement(OPC),while the 28-d strength was comparable to that of OPC.The proposed binder thus provides a sustainable pathway for BW valorization,combining waste utilization,carbon sequestration,and improved engineering performance.
基金supported by the National Natural Science Foundation of China(Grant Nos.52222810 and 52178383).
文摘Dynamic disturbances with various frequencies could trigger different failure modes of deep excavations.Superimposed on this static stress are dynamic disturbances due to various dynamic vibrations,e.g.excavation blasting,blasting,tunnel boring machine(TBM)vibration,rockburst wave,earthquakes.Specifically,these dynamic sources are characterized by a wide range of wave frequencies f,resulting in differences in failure modes.A series of true-triaxial compression tests were conducted on granite to simulate the excavation-induced stress path in three-dimensional(3D)stresses.Subsequently,a dynamic disturbance with various frequencies was applied to a cuboid specimen,to reveal the behavior associated with brittle failure.The dynamic disturbance with frequencies f of 5 Hz,10 Hz,and 40 Hz generates less disturbed energy components in the granite together with higher peak strength.However,dynamic disturbances with f of 20 Hz and 30 Hz resulted in a lower peak strength;the peak strength of the rock increases sp albeit it decreases at first,then increases.This U-shaped phenomenon relates to the natural frequency of the granite under such stress conditions.Different rock lithologies consisting of diverse mineral composition,respond differently to each sensitive resonance frequency.Interestingly,the weak disturbance stress with a high frequency f and low amplitude A increases the ratio of crack damage to peak strength(scd/sp)in the granite.This leads to the inhibition of the expansion of the granite during the dynamic disturbance process.Multiple penetrating tensileeshear cracks appear in the s3-direction as the disturbance frequency f increases.
文摘In complex geological environments,the analysis of drill cores to determine rock strength can be challenging due to the wide variability in the degree of fracturing,leading to subjectivity in the collection of representative samples for uniaxial compressive strength testing.This study evaluates non-destructive techniques on calcareous rocks with different tectonic deformations,including Equotip hardness,ultrasound P-wave velocity,thin section analysis,and calcimetry,integrated with photogrammetric fracture analysis.The investigated carbonate rock samples are sourced from drill cores derived from the Umbria-Marche fold and thrust belt(northern Apennines,Italy),including a gently dipping limb of an anticline,a hinge zone of an anticline,and a fault zone associated with a thrust.Fracture intensity,quantified by the P21 parameter using photogrammetric techniques on pre-loading rock samples,is assessed alongside macroscopic identification of discontinuities(such as stylolites,veins,and joints)using marker colours to monitor failures during uniaxial compression testing.Empirical correlations depicted by single and multi-linear relationships indicate a strong dependence between the mechanical and physical properties of limestones.Both Equotip and P-wave velocity are influenced by fracture intensity,but P-wave velocity varies significantly with discontinuity orientation,especially at 45°-90°.To refine uniaxial compressive strength predictions and mitigate multicollinearity,statistical approaches,including linear and multilinear regression,Principal Component Analysis and Gaussian Process Regression,were tested.Findings improve the reliability of non-destructive techniques for assessing rock strength in structurally complex settings,with implications for geotechnical applications.
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.
文摘Unconfined Compressive Strength(UCS)is a key parameter for the assessment of the stability and performance of stabilized soils,yet traditional laboratory testing is both time and resource intensive.In this study,an interpretable machine learning approach to UCS prediction is presented,pairing five models(Random Forest(RF),Gradient Boosting(GB),Extreme Gradient Boosting(XGB),CatBoost,and K-Nearest Neighbors(KNN))with SHapley Additive exPlanations(SHAP)for enhanced interpretability and to guide feature removal.A complete dataset of 12 geotechnical and chemical parameters,i.e.,Atterberg limits,compaction properties,stabilizer chemistry,dosage,curing time,was used to train and test the models.R2,RMSE,MSE,and MAE were used to assess performance.Initial results with all 12 features indicated that boosting-based models(GB,XGB,CatBoost)exhibited the highest predictive accuracy(R^(2)=0.93)with satisfactory generalization on test data,followed by RF and KNN.SHAP analysis consistently picked CaO content,curing time,stabilizer dosage,and compaction parameters as the most important features,aligning with established soil stabilization mechanisms.Models were then re-trained on the top 8 and top 5 SHAP-ranked features.Interestingly,GB,XGB,and CatBoost maintained comparable accuracy with reduced input sets,while RF was moderately sensitive and KNN was somewhat better owing to reduced dimensionality.The findings confirm that feature reduction through SHAP enables cost-effective UCS prediction through the reduction of laboratory test requirements without significant accuracy loss.The suggested hybrid approach offers an explainable,interpretable,and cost-effective tool for geotechnical engineering practice.
文摘This study presents and verifies a hybrid methodology for reliable determination of parameters in structural rheological models(Zener,Burgers,and Maxwell)describing the viscoelastic behavior of polyurethane specimens manufactured using extrusion-based 3D printing.Through comprehensive testing,including cyclic compression at strain rates ranging from 0.12 to 120 mm/min(0%-15%strain)and creep/relaxation experiments(10%-30%strain),the lumped parameters were independently determined using both analytical and numerical solutions of the models’differential equations,followed by cross-verification in additional experiments.Numerical solutions for creep and relaxation problems were obtained using finite element analysis,with the three-parameter Mooney-Rivlin model and Prony series employed to simulate elastic and viscous stress components,respectively.Energy dissipation per cycle was quantified during cyclic compression tests.The results demonstrate that all three models adequately describe material behavior within the 0%-15%strain range across various strain rates.Comparative analysis revealed the Burgers model’s superior performance in characterizing creep and stress relaxation at low strain levels.While Zener and Burgers model parameters from uniaxial compression showed limited applicability for energy dissipation calculations,the generalized Maxwell model effectively captured viscoelastic properties across different strain rates.Notably,parameters derived from creep tests provided a more universal assessment of dissipative properties due to optimization based on characteristic curve regions.Both parameter sets described polyurethane’s elastic-hysteretic behavior with approximately 20%error,proving significantly more accurate than the linear strain-time dependence hypothesis.Finite element analysis(FEA)complemented numerical modeling by demonstrating that while the generalized Maxwell model effectively describes initial rapid stress-strain changes,FEA provides superior characterization of steady-state processes.This computational approach yields more physically representative results compared to simplified analytical solutions,despite certain limitations in transient analysis.
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Supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R896).
文摘Deep neural networks have achieved excellent classification results on several computer vision benchmarks.This has led to the popularity of machine learning as a service,where trained algorithms are hosted on the cloud and inference can be obtained on real-world data.In most applications,it is important to compress the vision data due to the enormous bandwidth and memory requirements.Video codecs exploit spatial and temporal correlations to achieve high compression ratios,but they are computationally expensive.This work computes the motion fields between consecutive frames to facilitate the efficient classification of videos.However,contrary to the normal practice of reconstructing the full-resolution frames through motion compensation,this work proposes to infer the class label from the block-based computed motion fields directly.Motion fields are a richer and more complex representation of motion vectors,where each motion vector carries the magnitude and direction information.This approach has two advantages:the cost of motion compensation and video decoding is avoided,and the dimensions of the input signal are highly reduced.This results in a shallower network for classification.The neural network can be trained using motion vectors in two ways:complex representations and magnitude-direction pairs.The proposed work trains a convolutional neural network on the direction and magnitude tensors of the motion fields.Our experimental results show 20×faster convergence during training,reduced overfitting,and accelerated inference on a hand gesture recognition dataset compared to full-resolution and downsampled frames.We validate the proposed methodology on the HGds dataset,achieving a testing accuracy of 99.21%,on the HMDB51 dataset,achieving 82.54%accuracy,and on the UCF101 dataset,achieving 97.13%accuracy,outperforming state-of-the-art methods in computational efficiency.
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supported by the National Key Research and Development Program Young Scientist Project(Grant No.2024YFC2911000)the National Natural Science Foundation of China(Grant No.52474103)the Major Basic Research Project of the Natural Science Foundation of Shandong Province(Grant No.ZR2024ZD22).
文摘Internal structural defects in engineering rock masses vary in size,exhibit complex shapes,and are unevenly distributed.Dominant fractures within a rock mass often play a critical to its mechanical behavior,directly affecting the macromechanical properties and failure modes.These fractures affect the instability and failure of the surrounding rock,significantlyimpacting the overall stability of engineering structures.Herein,sand-powder three-dimensional(3D)printing technology was used to prepare rock-like specimens with internal fracture networks.Triaxial compression testing,post-failure fracture mapping,and fractal dimension analysis of the fracture surfaces were conducted to investigate the effects of dominant fracture angles on the strength and deformation of rocks with internal fracture networks under triaxial stress.The results indicate that the dominant fracture angle has a pronounced effect on the mechanical behavior of rock.With increasing angle,both compressive strength and elastic modulus exhibit an initial decline followed by an increase.Moreover,higher confiningpressure significantlyimproves the compressive strength of fractured rock.This enhancement weakens as the confiningpressure further increases.Moreover,with increasing confiningpressure,the differences between the maximum and minimum values of elastic moduli and lateral strain ratios in fractured rock gradually decrease.Thus,the impact of the dominant fracture angle on rock mass deformation decreases with increasing confiningpressure.This research elucidates the effects of dominant fracture angles on the mechanical and failure properties of complex fractured rock masses and the influenceof the confiningpressure on these relationships.It provides valuable theoretical insights and practical guidance for stability analyses in engineering rock masses.
基金Supported by the Natural Science Foundation of Guangxi Province(Grant Nos.2023GXNSFAA026067,2024GXN SFAA010521)the National Natural Science Foundation of China(Nos.12361079,12201149,12261026).
文摘Convex feasibility problems are widely used in image reconstruction, sparse signal recovery, and other areas. This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recovery. We first derive the projection formulas for a vector onto the feasible sets. The centralized circumcentered-reflection method is designed to solve the convex feasibility problem. Some numerical experiments demonstrate the feasibility and effectiveness of the proposed algorithm, showing superior performance compared to conventional alternating projection methods.
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 No.U24A20183)Natural Science Fund for Distinguished Young Scholars of Hubei Province,China(Grant No.2024AFA051)Youth Science Fund(A-class)of Hunan Natural Science Foundation of China(Grant No.2025JJ20049).
文摘Soft clay treatment with all industrial by-product(IBP)binder has great economic and environmental benefits,yet its geomechanics and mechanisms still need to be well probed.With the activation by calcium carbide residue(CCR)and phosphogypsum(PG),the strength,structure,and mechanisms of soft clay treated by aluminosilicate-rich IBP(AS-IBP,such as ground granulated blast furnace slag(GGBS),fly ash(FA),coal gangue(CG),Bayer red mud(BR),and sintered red mud(SR))are comparatively investigated.The strength characteristics of solidified clay exhibit significant differences as AS-IBP changes.When GGBS is adopted,the strength is sensitive to the change in PG content,while the impact of CCR is insignificant.After 90 d,the strength of the optimal sample(G23)reaches 1.40 MPa,35.9%higher than cement solidified clay(CSC),while that achieved by other AS-IBPs is less than 0.3 MPa.In the compression test,the structure's evolutionary trend of G23 has a sudden change as the strength increases from 1.81 MPa to 2.29 MPa,suggesting the transformation in material properties.Besides,the structure of G23 is stronger than CSC,which contributes more to the compressive performance.The total amount of main products(C-S-H and ettringite)of all-IBP solidified clay determines the strength,and ettringite is only significant when calcium-rich AS-IBP is adopted.The total amount of minor products(C-A-H and C-A-S-H)is similar for different samples,equivalent to 28.9%-46.3%of the main products.The relationship between the strength and the product amount can be presented using an exponential function.
文摘The biological stabilization of soil using microbially induced carbonate precipitation(MICP)employs ureolytic bacteria to precipitate calcium carbonate(CaCO3),which binds soil particles,enhancing strength,stiffness,and erosion resistance.The unconfinedcompressive strength(UCS),a key measure of soil strength,is critical in geotechnical engineering as it directly reflectsthe mechanical stability of treated soils.This study integrates explainable artificialintelligence(XAI)with geotechnical insights to model the UCS of MICP-treated sands.Using 517 experimental data points and a combination of various input variables—including median grain size(D50),coefficientof uniformity(Cu),void ratio(e),urea concentration(Mu),calcium concentration(Mc),optical density(OD)of bacterial solution,pH,and total injection volume(Vt)—fivemachine learning(ML)models,including eXtreme gradient boosting(XGBoost),Light gradient boosting machine(LightGBM),random forest(RF),gene expression programming(GEP),and multivariate adaptive regression splines(MARS),were developed and optimized.The ensemble models(XGBoost,LightGBM,and RF)were optimized using the Chernobyl disaster optimizer(CDO),a recently developed metaheuristic algorithm.Of these,LightGBM-CDO achieved the highest accuracy for UCS prediction.XAI techniques like feature importance analysis(FIA),SHapley additive exPlanations(SHAP),and partial dependence plots(PDPs)were also used to investigate the complex non-linear relationships between the input and output variables.The results obtained have demonstrated that the XAI-driven models can enhance the predictive accuracy and interpretability of MICP processes,offering a sustainable pathway for optimizing geotechnical applications.
