Carbon aerogels have attracted considerable attention due to their high specific surface area,ultra-high porosity,and low density.With advances in fiber materials research and nanotechnology,fiber-based carbon aerogels have demonstrated superior tensile strength,compressive resistance,and fatigue resistance compared to conventional carbon aerogels,broadening both the preparation routes and functional applications of this material family.This review classifies fiber-based carbon aerogels according to their preparation methods,and systematically summarizes the preparation principles,methods,and research progress of four categories:direct carbonization,sol-gel,electrospinning,and three-dimensional(3D)printing.The key factors influencing each preparation method and their roles in regulating the functional performance of the resulting materials are also analyzed.Finally,future development directions for fiber-based carbon aerogels are discussed.Guided by the concept of green research and development,this review proposes a research framework centered on process efficiency,product sustainability,and multidisciplinary functional integration.
Background knowledge attacks pose serious threats to trajectory privacy by exploiting prior knowledge to infer user behavior patterns.Existing trajectory reconstruction methods,however,suffer from two major limitations.First,they fail to address semantic location information leakage effectively,and their deep learning models lack opti-mization under noisy conditions,leading to inadequate reconstruction accuracy and weak semantic extraction.Second,their poor generalization ability hinders efficient reconstruction across heterogeneous datasets,thereby limiting the comprehensiveness of privacy protection.To address these limitations,this study proposes a deep learning-based se-mantic encoding method for synthetic trajectory reconstruction(DL-SESTR),a false trajectory reconstruction method based on semantic information encoding.The method integrates a bidirectional long short-term memory network(Bi-LSTM)with an attention mechanism to capture spatiotemporal dependencies and dynamically identify key trajectory points,thereby improving noise resistance.It also introduces a point-of-interest semantic annotation algorithm(PSA)that matches multi-source point-of-interest(POI)data efficiently to enhance annotation performance.Furthermore,a hierarchical semantic encoding algorithm based on the Hasse diagram(HDSE)is proposed,constructing a semantic sensitivity weight model to distinguish high-priority semantic information from noise.Experiments on the T-Drive and GeoLife datasets evaluated model performance across dense and sparse regions,varying privacy budgets,and day-and-night scenarios.DL-SESTR consistently outperforms baseline methods in balancing privacy protection and data utility:Hausdorff distance is reduced by 0.3％,dynamic time warping(DTW)efficiency improves by 1.2 times,and root mean square(RMS)improves by 1.18 times.Under a low privacy budget(ε=0.01),the method still achieves a 95％Euclidean distance reduction rate,demonstrating strong robustness and generalization ability.
Alumina(Al2O3)nanofiber membranes are promising high-temperature thermal insulation materials with broad applications in aerospace,firefighting,and rescue operations.However,rapid grain growth during phase transfor-mation tends to cause brittle cracking,limiting their practical use.Element doping is an effective strategy to suppress excessive grain growth and improve the high-temperature flexibility of Al2O3-based fiber membranes.In this study,two-dimensional Al2O3-based nanofiber membranes with good flexibility were fabricated by combining sol-gel and electrospinning techniques with the incorporation of Zr and Si as dopants.Scanning electron microscopy(SEM),trans-mission electron microscopy(TEM),and X-ray diffraction(XRD)were employed to investigate the effects of dopant type,doping ratio,and calcination temperature on fiber morphology and crystal structure.Tensile strength and flexural performance were also systematically characterized.The results show that Zr doping significantly reduces grain size and improves flexibility.However,calcination at 1 400 ℃ leads to noticeable grain coarsening and a marked decline in flexibility.In contrast,when Si is used as the dopant at an Al∶Si molar ratio of 6∶1,the resulting Al2O3-SiO2 nanofiber membrane exhibits uniform morphology and a stable mullite phase.This membrane retains good flexibility after calcination at 1 400 ℃.After calcination at 1 000 ℃,it achieves a tensile strength of 1.03 MPa,maintains a flexural stiffness of 70 mN after 500 bending cycles,and shows a low room-temperature thermal conductivity of 0.029 9 W/(m·K),demonstrating excellent overall performance.
Melt-blown air filtration materials can capture harmful microorganisms but risk releasing them as secondary pollutants.To address this problem,polypropylene(PP)melt-blown material was used as a substrate,onto which the quaternary ammonium salt antibacterial agent 2-(dimethylamino)ethyl methacrylate hexadecyl bromide(DEHMA),acrylic acid(AA),and silver(Ag)ions were sequentially grafted via chemical grafting,yielding two antibacterial ma-terials:PP-DEHMA-AA and PP-DEHMA-AA-Ag.Successful grafting was confirmed by scanning electron mi-croscopy(SEM),energy dispersive spectroscopy(EDS),Fourier transform infrared spectroscopy(FTIR),and X-ray photoelectron spectroscopy(XPS).After modification,distinct particles appeared on the material surface,and Br and Ag elements were detected by EDS.The modification did not significantly alter the crystalline structure of the PP substrate,as its characteristic diffraction peaks remained at 14.1°,17.9°,and 22.0°.Antibacterial tests showed that both modified materials exhibited excellent efficacy against Escherichia coli(E.coli)and Staphylococcus aureus(S.aureus).PP-DEHMA-AA achieved antibacterial rates of 98.95％and 99.15％against the two bacteria,respec-tively.PP-DEHMA-AA-Ag further improved these rates to 99.43％and 99.69％,and showed a faster bactericidal rate against S.aureus.This enhancement is attributed to a synergistic effect:DEHMA disrupts bacterial cell membranes via electrostatic interactions,while silver ions penetrate cells and impair enzyme activity.This study offers a viable ap-proach to developing high-efficiency antibacterial air filtration materials.
To prepare piezoelectric sensors with good mechanical and piezoelectric properties,BC/CS and BC/CS/BT-OH composite aerogels were fabricated using bacterial cellulose(BC)and chitosan(CS)as the aerogel matrix and hydroxylated barium titanate nanoparticles(BT-OH)as the piezoelectric material via freeze-drying.The surface mor-pho-logy,chemical structure,mechanical properties,and piezoelectric properties of the composite aerogels were cha-racte-rized by scanning electron microscopy(SEM),Fourier transform infrared spectroscopy(FTIR),X-ray diffrac-tion(XRD),a universal testing machine,and an electrometer.The results showed that the incorporation of BT-OH into the BC/CS composite aerogel rendered the internal structure more porous and the surface microstructure rougher,with BT-OH nanoparticles uniformly distributed throughout the composite.FTIR and XRD analyses confirmed the success-ful hydroxylation of BT nanoparticles.When the BT-OH mass fraction was 2.0％,the BC/CS/BT-OH composite aero-gel exhibited optimal mechanical performance,achieving a compressive stress of 77.69 kPa at 70％strain,which was 1.93 times that of the BC/CS composite aerogel under the same strain condition,demonstrating excellent fatigue resis-tance.The introduction of BT-OH also enhanced the piezoelectric output.At a BT-OH mass fraction of 2.0％,the output voltage and current of the BC/CS/BT-OH aerogel both reached 3.56 times those of the BC/CS composite aerogel.
To meet the demand for efficient vehicle passage at unsignalized intersections in intelligent connected envi-ronments,this study proposes a new vehicle scheduling optimization method for unsignalized intersections based on a Petri net model,a deadlock avoidance strategy,and an improved black-winged kite algorithm(BKA),with the objec-tive of minimizing the maximum vehicle passing time.The proposed method first encodes the vehicle passing se-quences and establishes a mapping between vehicle numbers and BKA individuals.Then,a real-time online deadlock detection and repair strategy is applied to each individual to ensure control feasibility.Furthermore,two improvement strategies are developed for the BKA,the improved Circle chaotic mapping and the Levy flight strategy,to improve the algorithm's solving speed and solution accuracy.Finally,experiments are conducted on a two-way four-lane inter-section under multiple typical scenarios,and comparisons are made between the improved BKA,the original BKA,and the genetic algorithm to verify the significant advantage of the proposed method in minimizing the maximum passing time.Statistical analysis further demonstrates that the proposed method achieves the best performance in terms of con-vergence speed,stability,and optimization effectiveness.The experimental results show that the improved BKA ex-hibits strong optimization search capability in solving the vehicle scheduling optimization problem at unsignalized in-tersections.
Flake carbonyl iron powder(CIP)is a typical magnetic-loss electromagnetic wave absorber,but its high density limits practical application.In this study,CIP was compounded with waterborne polyurethane(PU)and polyester fiber(PET)to prepare CIP/PET/PU composites,and their performance was systematically investigated.Two CIP sizes were each dispersed at different mass ratios into PU solutions to form impregnation solutions,into which PET fibers were subsequently immersed to yield CIP/PET/PU.Characterization of the microstructure,microwave ab-sorption properties,and mechanical performance revealed distinct differences between the front and back sides of the composite.The cross-section exhibited a gradient distribution of CIP,transitioning from a dense concentration at the back side to a sparse distribution at the front side,with larger CIP particles being more prone to forming a dense struc-ture on the back side.The microwave absorption performance of the back side was significantly superior to that of the front side.For composites containing larger CIP at a mass ratio of m(CIP)∶m(PU)=1.5,the minimum reflection loss reached-25 dB at 18 GHz.Effective absorption was still achieved at a low mass ratio of m(CIP)∶m(PU)=0.15,indi-cating promising potential for lightweight composites.Regarding mechanical properties,composites with smaller CIP at m(CIP)∶m(PU)=0.015 showed mechanical performance slightly higher than or comparable to that of the CIP-free composite.Similarly,composites with larger CIP at m(CIP)∶m(PU)=1.5 exhibited slightly better mechanical properties than the CIP-free composite.However,all other samples showed inferior mechanical performance compared with the CIP-free composite.
To investigate the preparation process and X-ray shielding performance of bismuth oxide/polyurethane/tungsten wire(Bi2O3/TPU/W)sheathed yarn fabrics,using a spinning solution of polyurethane(TPU)and bismuth oxi-de(Bi2O3)with tungsten wire(W)as the core layer,Bi2O3/TPU/W sheathed yarn was fabricated via core-sheath com-posite electrospinning technology and subsequently woven into a plain-woven fabric.The effects of Bi2O3 addition on the surface morphology,chemical composition,mechanical properties,air permeability,and X-ray shielding perfor-mance of the nanofiber membrane were investigated.The results indicated that:1)when the Bi2O3 addition was 75％,the Bi2O3/TPU fiber membrane exhibited uniform particle distribution and well-defined morphology;2)when the dia-meter of the Bi2O3/TPU/W sheathed yarn was 0.7 mm,the yarn structure was stable with satisfactory tensile strength.The prepared Bi2O3/TPU/W sheathed yarn fabric,with a thickness of 1.4 mm,achieved an air permeability of 1 220 mm/s,a moisture vapor transmission rate of 7 040 g/(m2·24 h),and an X-ray shielding lead equivalent of 0.27 mmPb at an incident energy of 83 keV.
Path planning for mobile robots is considered one of the fundamental research areas in robotics.It involves determining an optimal,collision-free path from a start point to a target based on the assigned task and environmental perception.To address the limitations of the standard ant colony optimization(ACO)algorithm,including slow conver-gence,redundant paths,and susceptibility to local optima,this study proposes an improved ACO algorithm.Firstly,goal-oriented Euclidean and Chebyshev distances are fused to enhance early-stage search efficiency,and a normal distribution(Gaussian distribution)is introduced into the heuristic function to improve path search precision.Secondly,a reward-penalty strategy is incorporated into the pheromone update mechanism to reinforce the influence of high-quality paths and accelerate convergence.Thirdly,an adaptive pheromone evaporation factor is applied to dynamically adjust the search behavior,thereby enhancing global exploration and reducing the risk of becoming trapped in local op-tima.Finally,a pruning strategy is employed to reduce the number of turns and shorten the overall path length.Com-parative simulation experiments with other algorithms in both two-dimensional and three-dimensional environments demonstrate that the proposed algorithm not only yields shorter paths but also exhibits higher search efficiency in terms of running time.
Soil selenium bioavailability is significantly influenced by phosphorus(P)fractions,yet the regional varia-bility of P components and their key driving factors in Se-rich agricultural soils remain poorly understood.In this study,36 farmland soil samples were collected from nine representative selenium-rich regions across China,covering both upland and paddy fields.Seven P fractions were determined using the Hedley sequential extraction method,in-cluding ammonium chloride-extractable P(AP),sodium bicarbonate-extractable P(BP),sodium hydroxide-soluble P(NIP),apatite-type P(HP),intra-aggregate P(NIIP),organic P(OP),and residual P(ResP).Soil physicochemical properties were analyzed,and redundancy analysis(RDA)was applied to identify the major environmental controls.The results showed that P pool structure differed markedly among regions.Northern weakly alkaline soils(e.g.,Nan-tong,NT)were characterized by higher proportions of BP,whereas acidic southern soils were dominated by NIP and OP,indicating strong stabilization of P by Fe/Al oxides and soil organic matter.Several fractions reached peak levels in Bama upland soils in Guangxi.RDA revealed soil pH,available Fe(AFe),NH4+-N,and total nitrogen(TN)as the primary drivers,with the first two axes explaining 57.1％of total variance.Soil pH was positively correlated with AP and negatively associated with NIP and HP.This study provides a scientific basis for understanding phosphorus-sele-nium coupling processes and for region-specific nutrient management in selenium-rich farmlands.
As essential primary consumers and secondary producers in freshwater lake ecosystems,the composition and abundance of Cladocera directly reflect the status of lake ecosystems.Bosten Lake is one of the most important fresh-water lakes in northwestern China.This study analyzes the zooplankton Cladocera subfossils in a sediment core from the central point of Bosten Lake,combined with measurements of 210Pb and 137Cs activity to establish an accurate chronological sequence for the core.The study reveals the succession characteristics and ecological significance of the Cladocera population structure in Bosten Lake over the past century.The results show that 17 genera and 25 species of Cladocera were identified in the sediments of the lake.The dominant species include Bosmina spp.,Monospilus dispar,Alona spp.,and Chydorus sphaericus s.l.Over the past century,the population structure and diversity of Cladocera in Bosten Lake exhibited notable phase changes.Prior to the 1867,the total abundance of Cladocera was low,with dominance by littoral species and high diversity indices,indicating that the lake was in a low water-level,grass-dominated environment.From the 1884-1909,the total abundance of Cladocera increased rapidly,reaching its hig-hest level in the core,with dominant species still being littoral types,but with an increase in the concentration of planktonic Bosmina spp.and rising diversity,suggesting increased water levels and nutrient levels in the lake.From the 1909-1963,Cladocera abundance and diversity levels decreased,with the dominant species shifting from Monospilus dispar to Chydorus sphaericus s.l.This indicates the increased nutrient levels and turbidity in the lake.Since the 1963,the total abundance of Cladocera has rapidly increased,with Bosmina spp.becoming the dominant species and further declines in diversity,reflecting significant degradation of the lake's water quality.The plankto-nic-to-littoral species ratio(P/L)significantly increased,indicating rising water levels in the lake.This study provides effective biological indicators to support the reconstruction of freshwater lake ecosystems in arid and semia-rid regions.
Circularly polarized organic light-emitting diodes(CP-OLEDs)have demonstrated significant application potential in areas such as 3D displays and optical information encryption,owing to their intrinsic capability to directly generate circularly polarized electroluminescence.However,achieving both high device efficiency and a high electro-luminescent dissymmetry factor(gEL)remains a major challenge and a focal research topic in this field.Recent advances in chiral supramolecular assembly demonstrate that this system can construct long-range ordered helical nanostructures by precisely regulating intermolecular interactions,such as π-π stacking and hydrogen bonding.This approach facili-tates the attainment of a high gEL value while maintaining favorable device efficiency.Consequently,chiral supramole-cular assembly systems have emerged as one of the most effective strategies for realizing CP-OLEDs featuring both high device efficiency and elevated gEL values.Furthermore,the processes of chiral self-assembly or co-assembly fre-quently involve chiral transfer,chiral induction,and intermolecular Förster resonance energy transfer.These processes are advantageous for inducing achiral dyes to achieve circularly polarized electroluminescence,thereby effectively re-ducing the synthetic complexity of chiral luminescent materials.This paper analyzes the influence of intermolecular forces on the chiral supramolecular assembly process from two perspectives:Chiral supramolecular self-assembly and chiral supramolecular co-assembly.It investigates the role of highly ordered helical structures in the mechanisms of chirality transfer,chirality induction,and chirality amplification.Additionally,it summarizes the most recent research advancements in CP-OLEDs:Through precise regulation of intermolecular interactions such as π-π stacking and hy-drogen bonding,chiral molecules can self-assemble into helical nanostructures or co-assemble with achiral lu-minophores to achieve chirality induction.Experiments demonstrate that the synergistic effect of lamellar ordering and energy transfer in chiral liquid crystal materials can significantly enhance device efficiency,allowing external fields to dynamically tune the helical pitch and polarization direction.This review provides theoretical guidance for the future development of CP-OLEDs with both high gEL values and high efficiency.
This paper focuses on stock index futures and designs an integrated reinforcement learning quantitative trading strategy based on advantage actor critic(A2C)model and proximal policy optimization(PPO)model.First,the extreme gradient boosting(XGBoost)model is used to select key technical factors as state inputs,and the reward function is designed based on transaction cost optimization.Second,parameter tuning is conducted for both A2C and PPO models to determine key hyperparameters such as the hidden layer structure,learning rate,and batch processing parameters.On this basis,an ensemble model framework is designed,and dynamic selection of base models is achieved by comparing the Sharpe ratios on the validation set.The backtesting results show that the integrated model yielded cumulative returns of 106 766 RMB,84 739 RMB,and 78 408 RMB,alongside annualized returns of 32.03％,25.42％,and 23.52％,and Sharpe ratios of 1.95,0.63,and 1.39 for the CSI 300,SSE 50,and CSI 500 indices,respectively,significantly outperforming single A2C and PPO models,as well as benchmark buy-and-hold and momentum strategies.By dynamically blending the distinct advantages of each base model based on validation-set performance,the proposed integrated strategy achieves lower maximum drawdowns and more robust returns amid market volatility.In particular,it can still maintain positive returns during the downward trend of the CSI 500 index,fully validating its risk mitigation capabilities and market adaptability.
Prediction of forward reactions in organic chemistry as a critical artificial intelligence(AI)application has attracted more attention from researchers in recent years.The simplified molecular-input line-entry system(SMILES)provides a method to linearize the chemical molecular formula.Thus,based on SMILES encoding,reaction prediction can be converted to the task of sequence-to-sequence generation in a neural machine translation(NMT).The tradi-tional Transformer model focuses only on the inter-atomic attention weights in the chemical formula and ignores the global information within the molecule.Moreover,the traditional Transformers suffer from performance degradation and limited generalization when encountering diverse representations of identical molecules.To address these points,we propose a reaction prediction method for multilevel organic chemistry based on dual encoders.Firstly,our model uses two encoders to process the information at the molecular level and the atomic level,respectively.Next,a molecu-lar feature algorithm is proposed to obtain the interaction between molecules by averaging atom embeddings.Finally,a gating unit for automatic adjustment is utilized to perform multi-level feature fusion between the outputs of the atomic and molecular encoders.The fusion result is input to the decoder.Our results illustrate the method proposed obtains better results than the baseline on the three USPTO datasets and improves the generalization ability and long sequence processing ability of the model.
In this paper,a comprehensive computational framework is established based on multiscale asymptotic anal-ysis for analyzing the heat conduction performances of quasi-periodic composite structures,integrating lower-and higher-order microscopic unit cell models,a homogenized macroscopic model,and a second-order two-scale asymp-totic solution with macro-micro correlations.Subsequently,local error analysis demonstrates that the second-order two-scale solution ensures local heat flux balance,accurately capturing the micro-scale oscillating behavior of quasi-periodic composite structures.Furthermore,global error analysis in the integral sense provides explicit error estimates for the second-order two-scale solution.Additionally,a multi-scale numerical algorithm is developed,combining the finite element method,finite difference method,and interpolation method,to effectively solve the heat conduction problem.Finally,numerical experiments confirm the effectiveness of the proposed method,in particular,its high-pre-cision computational performance is thoroughly validated.
To improve the comprehensive performance of Q890D,the influence mechanism of different quenching temperatures on microstructure,properties,and fatigue life was analyzed.The microstructure and mechanical properties of Q890D low-alloy high-strength steel subjected to various quenching temperatures(870,900,and 930 ℃)and tem-pering processes were characterized via optical microscopy,hardness testing,universal tensile testing,low-temperature impact testing,fatigue testing,and scanning electron microscopy(SEM).The results showed that when the tempering conditions were consistent(tempering at 550 ℃ for 2 hours),Q890D had the best mechanical properties after quenc-hing at 900℃,with a tensile strength of 1 206 MPa,a specified plastic elongation strength of 1 025 MPa,a fracture elongation of 18.5％,and impact energies of 229 J(20 ℃)and 122 J(-40 ℃),respectively.Its performance was superior to the requirements of the national standard for Q890D.After quenching at(870～930 ℃)for 1 hour and tempering at 550 ℃ for 2 hours,the microstructure of Q890D was tempered sorbite and a small amount of ferrite,and Q890D maintained high strength and toughness.All tensile fractures were microvoid coalescence features fractures.From 20 ℃to-30℃,the impact energy of Q890D decreased less with the temperature decreasing.The impact energy decreased sharply below-30℃,and ductile-to-brittle transition temperature was between-40 ℃ and-50℃.The axial fatigue cycle times of Q890D after heat treatment optimization were 1.87 times,3.47 times,and 2.36 times higher than before optimization,indicating that quenching for 1 hour at 870～930 ℃ and tempering for 2 hours at 550 ℃ could significant-ly improve the fatigue performance of Q890D.The instantaneous fracture zone of the fatigue fracture surface showed dimples,indicating that Q890D had good toughness.
To enhance the absorption rate of new energy within the power dispatching of new energy systems,the un-certainty of new energy output must be addressed,and an appropriate low-carbon management mechanism should be designed properly.In this paper,the adaptive kernel density estimation method is used to model the output characteris-tics of wind power and photovoltaic systems.The correlation between wind power and photovoltaic systems is de-scribed using the Copula function,and Monte Carlo simulations are integrated to illustrate wind-solar uncertainties.By obtaining the joint output scenario of wind and solar power and their probability characteristics,a collaborative opti-mization power dispatching model for wind-solar-thermal power systems is established.Subsequently,the ladder-type carbon price mechanism is introduced into the dispatching model to further reduce carbon emissions,transforming the dual-objective optimization problem into a single-objective optimization problem.A case study confirms that carbon emissions are reduced by 4.02％after the stepped carbon price mechanism is implemented,ultimately increasing the new energy absorption rate from 14.04％to 71.06％,validating the rationality and validity of the model and methods developed in this work.
In order to further improve the post evaluation system of the"Four New"technologies(new materials,new technologies,new processes,and new equipment)for road maintenance,the study adopts an index weight vector method that incorporates decision-makers' preference factors,and proposes an improved fuzzy clustering algorithm based on slack variables and extended Lagrange multipliers.By introducing slack variables,the equality constraints re-flecting the decision maker's preference are transformed into equality constraints,and a new optimization objective function is constructed.On this basis,the explicit analytic expressions of the weight vectors under the preference set-ting are derived,and a complete theoretical solution framework is established to derive the exact analytic expressions of the weight vectors under the given preference conditions.Finally,the model is applied to the actual project of the"Four New"technologies,and the weights of each index are obtained under the constraints of the preference of pave-ment performance:material performance w1=0.072 0,pavement condition w2=0.204 9,service life w3=0.144 8,degree of adaptation w4=0.164 9,managerial costs w5=0.188 8,user costs w6=0.045 4,carbon emission w7=0.179 2.Comparing this method with other methods further validates the rationality and effectiveness of the paper's model.
In view of the widespread existence of cracks in rocks and their geometric characteristics affecting rock me-chanical properties,and the previous studies on the interaction between tunnels and cracks mostly focused on straight cracks,this study aims to explore the interaction mechanism between curved cracks and tunnels,and provide references for tunnel engineering design,construction and safe operation.By using discrete element method and PFC2D software,a tunnel model with curved cracks was established.Six calculation schemes without curved cracks(scheme A)and curved cracks with different azimuthing angles(scheme B1-B5,β=0°,60°,90°,135°,180°)were set up to simulate the loading process.Crack growth and stress-strain curves were analyzed.The location of the curved fracture signifi-cantly affects the failure mode,stress-strain curve characteristics and peak strength of the tunnel.When there is no crack,the failure mode is symmetrical,and when there is a crack,the crack propagation is complicated.The intact model has high elastic stiffness and sudden failure,while the model with cracks has low elastic stiffness and the curve change of plastic stage is related to the crack orientation.The peak strength is the highest when there is no crack,β=90° is relatively high in the scheme with crack,β=60° is the lowest.When there is no crack,the crack growth of tunnel is controlled by its own shape and load,and is symmetrical and progressive.The crack propagation direction and shape are different under different azimuths.When β=0°,crack propagation occurs merely around the tunnel;when β=90°,curved fissures interconnect with the tunnel via coalesced cracks.The characteristics of each stage of the stress-strain curve vary with the existence and orientation of cracks.The results of this study are helpful to further understand the tunnel-curve fracture interaction,provide critical theoretical insights and practical references for the de-sign,construction,and safety assessment of tunnel engineering structures.
To understand the influence of high temperatures on the mechanical properties of fiber reinforced polymer(FRP)rebars,a large batch of shear and compression tests were conducted after high temperatures to study the ef-fects of different factors such as high temperature,constant temperature time,and protective layer thickness on glass fiber reinforced polymer(GFRP)bars and basalt fiber reinforced polymer(BFRP)bars with different diameters.The damage of GFRP and BFRP reinforcement due to high temperatures was revealed at the microscopic level through scanning electron microscopy(SEM).The test results show that the strength degradation of BFRP bars is slightly higher than that of GFRP bars.The smaller the diameter of the FRP bars,the higher their residual strength after high temperatures.However,when the diameter reaches above 16 mm,the impact of diameter on strength is not significant.The strength of FRP bars decreased limitedly before 300 ℃ high temperature,and then rapidly decreases with increas-ing temperature.When reaching 300℃,the strength of GFRP and BFRP bars decreases by 37.7％and 36.4％,respec-tively.The degree of compressive strength degradation after high temperature was higher than that of shear strength,and the larger the diameter of FRP bars,the more significant the strength degradation.The reduction in shear strength of FRP bars was similar for a constant temperature of 1 hour and 2 hours,and was larger after 3 hours.The mortar protective layer can effectively protect the reinforcement material within 300℃.After 300℃,the rapid development of cracks in the specimen caused the disappearance of the protective effect.The shear strength of the internal FRP bars showed a degradation trend close to that of bare bars.Based on experimental results,shear and compressive strength prediction formulas for GFRP and BFRP bars were established after high temperature.A method for establishing prob-abilistic strength model of FRP bar after high temperatures was proposed by combining Bayesian information criteria and probability testing methods.Finally,suitable probability models for the shear and compressive strength of GFRP and BFRP bars after high temperatures were established,and their variability was also quantified.These findings pro-vide critical material models for evaluating the mechanical performance of FRP-reinforced concrete structures after high-temperature exposure.
