Anti-tank intelligent mine is a kind of new intelligent anti-tank bomb relying on high precision detector.It can effectively capture and damage targets with wind resistance coefficient and other factors affecting its ...Anti-tank intelligent mine is a kind of new intelligent anti-tank bomb relying on high precision detector.It can effectively capture and damage targets with wind resistance coefficient and other factors affecting its flight characteristics under consideration.This article is based on the three-dimensional model of intelligent mine.To analyze its subsonic and transonic flow fields and the change law of aerodynamic force factor with the growth of the angle of attack,computational fluid dynamics software is used for intelligent mine flow field numerical calculation and the change law of pressure center.The results show that the large drag coefficient is conducive to the stability of scanning.Drastic changes of the flow field near the intelligent mine will disable its scanning movement.The simulation results can provide a reference for scanning stability analysis,overall performance optimization and appearance improvement.展开更多
It is crucial to develop arsenic removal adsorbents with strong sulfur resistance under middle-low-temperature flue gas conditions(<400℃).In this work,five Fe-Ce-La oxides were prepared by co-precipitation method,...It is crucial to develop arsenic removal adsorbents with strong sulfur resistance under middle-low-temperature flue gas conditions(<400℃).In this work,five Fe-Ce-La oxides were prepared by co-precipitation method,and FeCeLaO/SiO_(2)-Al_(2)O_(3) composite adsorbents were prepared by coupling fly ash-based Si-Al carriers.The active components Fe-Ce-La oxides and Si-Al carriers were characterized by TPD,TG,XRF,BET and XPS,respectively.The effects of temperature,Si/Al ratio and FeCeLaO loading rate on the sulfur resistance were investigated.Results show that the SO_(2) promotes the arsenic removal of Fe_(2)O_(3),CeLaO and FeCeLaO.At 400℃,the arsenic removal efficiencies of the three oxides increase from 45.3%,72.5% and 81.3% without SO_(2) to 62.6%,80.5%and 91.0%,respectively.The SO_(2) inhibits the arsenic removal of La_(2)O_(2)CO_(3) and FeLaO,and the inhibition effect is pronounced at high temperatures.The sulfur poisoning resistance of Si-Al carriers increases with the increase of Si/Al ratio.When the Si/Al ratio is increased to 9.74,the arsenic removal efficiency in the SO_(2) environment is 13.9% higher than that in the absence of SO_(2).Introducing FeCeLaO active components is beneficial for enhancing the SO_(2) poisoning resistance of Si-Al carriers.The strong sulfur resistance of the FeCeLaO/SiO_(2)-Al_(2)O_(3) composite adsorbent results from multiple factors:protective effects of Ce on Fe,La and Al;sulfation-induced generation of Ce^(3+)and surface-adsorbed oxygen;and strong surface acidity of SiO_(2).展开更多
Unmanned Aerial Vehicles(UAVs)in Flying Ad-Hoc Networks(FANETs)are widely used in both civilian and military fields,but they face severe security,trust,and privacy vulnerabilities due to their high mobility,dynamic to...Unmanned Aerial Vehicles(UAVs)in Flying Ad-Hoc Networks(FANETs)are widely used in both civilian and military fields,but they face severe security,trust,and privacy vulnerabilities due to their high mobility,dynamic topology,and open wireless channels.Existing security protocols for Mobile Ad-Hoc Networks(MANETs)cannot be directly applied to FANETs,as FANETs require lightweight,high real-time performance,and strong anonymity.The current FANETs security protocol cannot simultaneously meet the requirements of strong anonymity,high security,and low overhead in high dynamic and resource-constrained scenarios.To address these challenges,this paper proposes an Anonymous Authentication and Key Exchange Protocol(AAKE-OWA)for UAVs in FANETs based on OneWay Accumulators(OWA).During the UAV registration phase,the Key Management Center(KMC)generates an identity ticket for each UAV using OWA and transmits it securely to the UAV’s on-board tamper-proof module.In the key exchange phase,UAVs generate temporary authentication tickets with random numbers and compute the same session key leveraging the quasi-commutativity of OWA.For mutual anonymous authentication,UAVs encrypt random numbers with the session key and verify identities by comparing computed values with authentication values.Formal analysis using the Scyther tool confirms that the protocol resists identity spoofing,man-in-the-middle,and replay attacks.Through Burrows Abadi Needham(BAN)logic proof,it achieves mutual anonymity,prevents simulation and physical capture attacks,and ensures secure connectivity of 1.Experimental comparisons with existing protocols prove that the AAKE-OWA protocol has lower computational overhead,communication overhead,and storage overhead,making it more suitable for resource-constrained FANET scenarios.Performance comparison experiments show that,compared with other schemes,this scheme only requires 8 one-way accumulator operations and 4 symmetric encryption/decryption operations,with a total computational overhead as low as 2.3504 ms,a communication overhead of merely 1216 bits,and a storage overhead of 768 bits.We have achieved a reduction in computational costs from 6.3%to 90.3%,communication costs from 5.0%to 69.1%,and overall storage costs from 33%to 68%compared to existing solutions.It can meet the performance requirements of lightweight,real-time,and anonymity for unmanned aerial vehicles(UAVs)networks.展开更多
Freeze–thaw(F–T)cycle-induced cracking in silty clays poses a significant risk to engineering stability.Although the individual addition of fly ash(FA)or sisal fiber(SF)provides partial solutions,their simultaneous ...Freeze–thaw(F–T)cycle-induced cracking in silty clays poses a significant risk to engineering stability.Although the individual addition of fly ash(FA)or sisal fiber(SF)provides partial solutions,their simultaneous application may result in a synergistic effect to compensate for their respective shortcomings.In this study,the effects of SF and FA on the mechanical properties,crack resistance,water retention,and erosion resistance of improved soil were systematically investigated through unconfined compressive strength(UCS)tests,crack evolution analysis,simulated rainfall erosion tests,and microscopic characterization(laser particle size analysis and nitrogen adsorption).The results reveal that the volumetric stability of FA particles significantly inhibits cracking in soil after F–T cycles.However,FA contributes only slightly to soil strength and erosion resistance.SF,on the other hand,plays a substantial role in increasing both soil strength and erosion resistance.The synergy between FA and SF results in the simultaneous increase in crack resistance,erosion resistance,and strength.FA improves the aggregate stability during F–T cycles,whereas SF reinforces the bonds between these aggregates.A comprehensive evaluation of the improved soil during F–T cycles using the entropy weight-TOPSIS method reveal that the combination of 10%FA+18 mm SF performed the best,achieving a 246%higher composite score than the unmodified soil did.With respect to this optimal combination,compared with the unmodified soil,the SF–FA-improved soil exhibits a 30%reduction in the average crack width,a 30%reduction in the erosion rate,and a 46%increase in strength.The findings of this study provide a scientific basis for the design of soil improvement in disaster mitigation engineering in seasonally frozen soil regions.展开更多
This study aims to develop an accurate and robust machine learning model to predict the carbonation depth of fly ash concrete,overcoming the limitations of traditional predictive methods.Five ensemble-based models,suc...This study aims to develop an accurate and robust machine learning model to predict the carbonation depth of fly ash concrete,overcoming the limitations of traditional predictive methods.Five ensemble-based models,such as adaptive boosting(AdaBoost),categorical boosting(CatBoost),gradient boosting regressor(GBR),hist gradient boosting regressor(HistGBR),and extreme gradient boosting(XGBoost),were developed and optimized using 729 high-quality dataset points incorporating seven input parameters,including cement,CO_(2),exposure time,water-binder ratio,fly ash,curing time,and compressive strength.Several performance evaluation metrics were used to compare the models.The GBR model emerged as the best-performing model,based on high coefficient of determination(R^(2))values and balanced error metrics across both validation and testing datasets.While all models performed exceptionally well on the training data,GBR demonstrated superior generalization capability,with R^(2) values of 0.9438 on the validation set and 0.9310 on the testing set.Furthermore,its low mean squared error(MSE),root mean square error(RMSE),mean absolute error(MAE),and median absolute error(MdAE)confirmed its robustness and accuracy.Moreover,shapley additive explanations(SHAP)analysis enhanced the interpretability of predictions,highlighting the curing time and exposure time as the most critical drivers of carbonation depth.展开更多
In this study,Bacillus mojavensis and Lactiplantibacillus herbarum were used to co-treat kitchen waste(KW)with Black soldier fly larvae(BSFL).The effects on the physicochemical properties,heavy metal content,and micro...In this study,Bacillus mojavensis and Lactiplantibacillus herbarum were used to co-treat kitchen waste(KW)with Black soldier fly larvae(BSFL).The effects on the physicochemical properties,heavy metal content,and microbial community of the BSFL sand were determined.Compared to the control group,the L.herbarum inoculation reduced 19.04%of the soluble salt(TSS),15.48%of Ni,and 13.04%of Zn in the residues;the B.mojavensis inoculation reduced 23.84%of TSS,13.61%of Pb,and 20.32%of the Ni in the residues;the L.herbarum and B.mojavensis inoculation reduced 29.53%of Cr,20.23%of Pb,18.06%of Ni,and 25.68%of the Zn in the residues.The microbial inoculants significantly enhanced the BSFL sand microbial diversity(Tukey,P<0.05).The dominant phylum and genus in the BSFL sand were Firmicutes(53.08%)and Corynebacterium(47.01%),respectively.The microbial inoculants resulted in an approximate 12%reduction in Corynebacterium.The linear discriminant analysis effective size analysis showed that the Corynebacterium abundance was significantly reduced.The microbial inoculants significantly affected the Corynebacterium relative abundance by significantly altering the substrate TSS,moisture content,and Ni.In conclusion,the effect of B.mojavensis and L.herbarum on the BSFL treatment of KW was beneficial,and their potential should be further exploited.展开更多
Semantic segmentation for mixed scenes of aerial remote sensing and road traffic is one of the key technologies for visual perception of flying cars.The State-of-the-Art(SOTA)semantic segmentation methods have made re...Semantic segmentation for mixed scenes of aerial remote sensing and road traffic is one of the key technologies for visual perception of flying cars.The State-of-the-Art(SOTA)semantic segmentation methods have made remarkable achievements in both fine-grained segmentation and real-time performance.However,when faced with the huge differences in scale and semantic categories brought about by the mixed scenes of aerial remote sensing and road traffic,they still face great challenges and there is little related research.Addressing the above issue,this paper proposes a semantic segmentation model specifically for mixed datasets of aerial remote sensing and road traffic scenes.First,a novel decoding-recoding multi-scale feature iterative refinement structure is proposed,which utilizes the re-integration and continuous enhancement of multi-scale information to effectively deal with the huge scale differences between cross-domain scenes,while using a fully convolutional structure to ensure the lightweight and real-time requirements.Second,a welldesigned cross-window attention mechanism combined with a global information integration decoding block forms an enhanced global context perception,which can effectively capture the long-range dependencies and multi-scale global context information of different scenes,thereby achieving fine-grained semantic segmentation.The proposed method is tested on a large-scale mixed dataset of aerial remote sensing and road traffic scenes.The results confirm that it can effectively deal with the problem of large-scale differences in cross-domain scenes.Its segmentation accuracy surpasses that of the SOTA methods,which meets the real-time requirements.展开更多
Recycling rare earth elements(REEs)from waste is necessary for an environmentally sustainable reuse and wastewater management approach.Na-A zeolite was synthesized from coal fly ash(CFA)and applied for Ce^(3+)adsorpti...Recycling rare earth elements(REEs)from waste is necessary for an environmentally sustainable reuse and wastewater management approach.Na-A zeolite was synthesized from coal fly ash(CFA)and applied for Ce^(3+)adsorption.Fourier transform infrared(FTIR)spectra show peaks at 790,500 and 467 cm^(-1),which are bond vibrations of Si-O-Si,Si with Al-O and Si-O-.The surface area is 15.88 m^(2)/g,with a pore size of 2.14 nm.SEM images show a cubic shape,which indicates the formation of zeolite.Field emission and energy disperse spectroscopy(EDS)shows the formation of Si,Al,Na,and O.Na-A zeolite was applied for Ce^(3+)adsorption.The optimum conditions for Ce^(3+)adsorption are 50 ppm concentration,360 min,and pH 6.The maximum adsorption capacity is 176.49 mg/g.Based on the results,it is found that the adsorption of Ce^(3+)by Na-A zeolite is pseudo-second-order.The desorption test using HNO_(3) is more effective than using HCl and H_(2)SO_(4).A desorption efficiency of 97.22%is obtained at 4 cycles.Adsorption test using real sample wastewater demonstrates an adsorption efficiency of 83.35%.展开更多
Teacher–student relationships play a vital role in improving college students’academic performance and the quality of higher education.However,empirical studies with substantial data-driven insights remain limited.T...Teacher–student relationships play a vital role in improving college students’academic performance and the quality of higher education.However,empirical studies with substantial data-driven insights remain limited.To address this gap,this study collected 3278 questionnaires from seven universities across four provinces in China to analyze the key factors affecting college students’academic performance.A machine learning framework,CQFOA-KELM,was developed by enhancing the Fruit Fly Optimization Algorithm(FOA)with Covariance Matrix Adaptation Evolution Strategy(CMAES)and Quadratic Approximation(QA).CQFOA significantly improved population diversity and was validated on the IEEE CEC2017 benchmark functions.The CQFOA-KELM model achieved an accuracy of 98.15%and a sensitivity of 98.53%in predicting college students’academic performance.Additionally,it effectively identified the key factors influencing academic performance through the feature selection process.展开更多
Three types of activators such as sodium hydroxide,calcium oxide and triethanolamine(TEA)are used to establish different activation environments to address the problems associated with the process of activating fly as...Three types of activators such as sodium hydroxide,calcium oxide and triethanolamine(TEA)are used to establish different activation environments to address the problems associated with the process of activating fly ash paste.We conducted mechanical tests and numerical simulations to understand the evolution of microstructure,and used environmental scanning electron microscopy(ESEM)and energy dispersive spectroscopy(EDS)techniques to analyze the microenvironments of the samples.The mechanical properties of fly ash paste under different activation conditions and the changes in the microstructure and composition were investigated.The results revealed that under conditions of low NaOH content(1%-3%),the strength of the sample increased significantly.When the content exceeded 4%,the rate of increase in strength decreased.Based on the results,the optimal NaOH content was identified,which was about 4%.A good activation effect,especially for short-term activation(3-7 d),was achieved using TEA under high doping conditions.The activation effect was poor for long-term strength after 28 days.The CaO content did not significantly affect the degree of activation achieved.The maximum effect was exerted when the content of CaO was 2%.The virtual cement and concrete testing laboratory(VCCTL)was used to simulate the hydration process,and the results revealed that the use of the three types of activators accelerated the formation of Ca(OH)_(2) in the system.The activators also corroded the surface of the fly ash particles,resulting in a pozzolanic reaction.The active substances in fly ash were released efficiently,and hydration was realized.The pores were filled with hydration products,and the microstructure changed to form a new frame of paste filling that helped improve the strength of fly ash paste.展开更多
In order to study the characteristics of pure fly ash-based geopolymer concrete(PFGC)conveniently,we used a machine learning method that can quantify the perception of characteristics to predict its compressive streng...In order to study the characteristics of pure fly ash-based geopolymer concrete(PFGC)conveniently,we used a machine learning method that can quantify the perception of characteristics to predict its compressive strength.In this study,505 groups of data were collected,and a new database of compressive strength of PFGC was constructed.In order to establish an accurate prediction model of compressive strength,five different types of machine learning networks were used for comparative analysis.The five machine learning models all showed good compressive strength prediction performance on PFGC.Among them,R2,MSE,RMSE and MAE of decision tree model(DT)are 0.99,1.58,1.25,and 0.25,respectively.While R2,MSE,RMSE and MAE of random forest model(RF)are 0.97,5.17,2.27 and 1.38,respectively.The two models have high prediction accuracy and outstanding generalization ability.In order to enhance the interpretability of model decision-making,we used importance ranking to obtain the perception of machine learning model to 13 variables.These 13 variables include chemical composition of fly ash(SiO_(2)/Al_(2)O_(3),Si/Al),the ratio of alkaline liquid to the binder,curing temperature,curing durations inside oven,fly ash dosage,fine aggregate dosage,coarse aggregate dosage,extra water dosage and sodium hydroxide dosage.Curing temperature,specimen ages and curing durations inside oven have the greatest influence on the prediction results,indicating that curing conditions have more prominent influence on the compressive strength of PFGC than ordinary Portland cement concrete.The importance of curing conditions of PFGC even exceeds that of the concrete mix proportion,due to the low reactivity of pure fly ash.展开更多
This paper investigates the configuration design associated with boundary-constrained swarm flying.An analytic swarm configuration is identified to ensure the passive safety between each pair of spacecraft in the radi...This paper investigates the configuration design associated with boundary-constrained swarm flying.An analytic swarm configuration is identified to ensure the passive safety between each pair of spacecraft in the radial-cross-track plane.For the first time,this work derives the explicit configurable spacecraft amount to clarify the configuration's accommodation capacity while considering the maximum inter-spacecraft separation constraint.For larger-scale design problem that involves hundreds of spacecraft,this paper proposes an optimization framework that integrates a Relative Orbit Element(ROE)affine transformation operation and successional convex optimization.The framework establishes a multi-subcluster swarm structure,allowing decoupling the maintenance issues of each subcluster.Compared with previous design methods,it ensures that the computational cost for constraints verification only scales linearly with the swarm size,while also preserving the configuration optimization capacities.Numerical simulations demonstrate that the proposed analytic configuration strictly meets the design constraints.It is also shown that the proposed framework reduces the handled constraint amount by two orders compared with direct optimization,while achieving a remarkable swarm safety enhancement based on the existing analytic configuration.展开更多
In order to adjust some properties of cement grout or concrete,some mineral admixtures are usually added in the preparation.Admixtures can reduce the cement consumption and save the cost,and also adjust the workabilit...In order to adjust some properties of cement grout or concrete,some mineral admixtures are usually added in the preparation.Admixtures can reduce the cement consumption and save the cost,and also adjust the workability of the material,improve the strength and durability of the cement stone,or reduce hydration heat of the composite cement.At present,the content of fly ash or slag is generally less than 50%among the composite cementitious materials that have been studied more,but there is little research on composite cementitious materials with large mineral admixture.In this paper,XRD,SEM,and adiabatic temperature rise tests were used to discuss hydration products and mechanism of composite cement grout with 90%content of fly ash and slag.The results show that the hydration of the composite cement grout is an alkali-activated hydration reaction,and the hydration products are mainly amorphous substances such as hydrated calcium silicate or hydrated calcium aluminate gel.The hydration reaction temperature rise is much lower than that of ordinary cement grout,and the time of the temperature peak is significantly delayed.展开更多
Microwave-curing and mechanical grinding of fly ash have both beenadopted as effective methods for improving the early-age strength of alkali-activated fly ash(AAFA)binders.This study combined these two approaches by ...Microwave-curing and mechanical grinding of fly ash have both beenadopted as effective methods for improving the early-age strength of alkali-activated fly ash(AAFA)binders.This study combined these two approaches by synthesizing AAFA using original,medium-fine,and ultrafine fly ash as precursors,and then specimens were cured with a five-stage temperature-controlled microwave.The compressive strength results indicate that the original AAFA develops the highest strength initially during microwave-curing,reaching 28 MPa at stage 2.Medium-fine AAFA exhibits the highest strength of 60 MPa when cured to stage 4-I,which is 26%higher than the peak strength of original AAFA.It is attributed to the significant rise in their specific surface area,which accelerates the dissolution of Si and Al from the precursor and facilitates the subsequent formation of N-A-S-H gels.Additionally,nanoscale zeolite crystals formed as secondary products fill the tiny gaps between amorphous products,thereby significantly improving their microstructure.In contrast,ultrafine fly ash,primarily composed of fragmented particles,necessitated a substantial amount of water,which adversely affects the absorption efficiency for microwave of AAFA specimens.Thus,ultrafine AAFA specimens consistently exhibit the lowest compressive strength.Specifically,at the end of curing,the compressive strength of these three specimens with microwave-curing is approximately 32%,59%,and 172%higher than that of the steam-cured sample,respectively.These findings demonstrate the compatibility of microwave-curing and fly ash refinement in enhancing the early compressive strength development of AAFA.展开更多
To address the issues of low accuracy,long time consumption,and high cost of the traditional temperature prediction methods for laser directed energy deposition(LDED),a machine learning model combined with numerical s...To address the issues of low accuracy,long time consumption,and high cost of the traditional temperature prediction methods for laser directed energy deposition(LDED),a machine learning model combined with numerical simulation was proposed to predict the temperature during LDED.A finite element(FE)thermal analysis model was established.The model's accuracy was verified through in-situ monitoring experiments,and a basic database for the predictive model was obtained based on FE simulations.Temperature prediction was performed using a generalized regression neural network(GRNN).To reduce dependence on human experience during GRNN parameter tuning and to enhance model prediction performance,an improved adaptive step-size fruit fly optimization algorithm(ASSFOA)was introduced.Finally,the prediction performance of ASSFOA-GRNN model was compared with that of back-propagation neural network model,GRNN model,and fruit fly optimization algorithm(FOA)-GRNN model.The evaluation metrics included the root mean square error(RMSE),mean absolute error(MAE),coefficient of determination(R^(2)),training time,and prediction time.Results show that the ASSFOA-GRNN model exhibits optimal performance regarding RMSE,MAE,and R^(2) indexes.Although its prediction efficiency is slightly lower than that of the FOA-GRNN model,its prediction accuracy is significantly better than that of the other models.This proposed method can be used for temperature prediction in LDED process and also provide a reference for similar methods.展开更多
On September 12,2023,in a reply letter to Jeffrey Greene,Chairman of the Sino-American Aviation Heritage Foundation,and Flying Tigers veterans Harry Moyer and Mel McMullen,President Xi Jinping noted,"In the past,...On September 12,2023,in a reply letter to Jeffrey Greene,Chairman of the Sino-American Aviation Heritage Foundation,and Flying Tigers veterans Harry Moyer and Mel McMullen,President Xi Jinping noted,"In the past,our two peoples fought the Japanese fascists together,and forged a deep friendship that stood the test of blood and fre."展开更多
Municipal solid waste incineration fly ash(MSWI)is considered as one of the hazardous wastes and requires to be well disposed to reduce the contaminant to the environment.Reference to the production of coal fly ash(FA...Municipal solid waste incineration fly ash(MSWI)is considered as one of the hazardous wastes and requires to be well disposed to reduce the contaminant to the environment.Reference to the production of coal fly ash(FA)bricks,MSWI and FA were utilized to prepare autoclaved MSWI-FA block samples.Ultrasonic-assisted hydrothermal synthesis technology was used for production to explore the effect of ultrasonic pre-treatment.Compressive strength,dry density,and water absorption tests were conducted to determine the optimal ultrasonic parameters.Ultrasonic pre-treating mechanisms were investigated by SEM,FT-IR,particle size analysis,and BET.Furthermore,the micro-analyses of block samples were conducted.The heavy metal leaching concentration was studied to assess the environmental safety.The experimental results show that the ultrasonic pre-treating time,water bath temperature,and ultrasonic power of 3 h,30℃,and 840 W are the optimal,under which the compressive strength,dry density,and water absorption were 8.14 MPa,1417.48 kg/m^(3),and 0.38,respectively.It is shown that ultrasound destroys the surface structure of raw materials and smaller FA particles embed into MSWI.The particle size distribution of pre-treated raw materials mixture is wider and total pore volume is decreased by 6.3%.During hydrothermal processing,more Al-substituted tobermorite crystals are generated,which is the main source of higher strength and smaller pore volume of prepared block samples.The solidification/stabilization rates of Cu,Pb,and Zn increased by 30.77%,4.76%,and 35.29%,respectively.This study shows a feasible way to utilize MSWI as raw material for construction.展开更多
The rapid change in CO_(2) concentration levels,due to climate change,will lead to a significant reduction in the durability and safety of the vital reinforced concrete(RC)structures.Utilizing supplementary cementitio...The rapid change in CO_(2) concentration levels,due to climate change,will lead to a significant reduction in the durability and safety of the vital reinforced concrete(RC)structures.Utilizing supplementary cementitious materials,such as low calcium fly ash(LCFA)or slag,etc.,with larger percentages in concrete mixes,would lead to an increase in the carbonation depth and risk of corrosion,especially for cracked concrete sections subjected to severe CO_(2) concentration levels.This research aims to compare the carbonation depth values using two different mathematical models across various CO_(2) concentrations and crack widths,for concrete mixes composed of different percentages and types of fly ash for both uncracked and cracked RC members,at a specific time of CO_(2) exposure.Moreover,the main objective is to assess the probability of corrosion(PC)across various percentages and types of fly ash used in cracked RC decks subjected to a severe CO_(2) level.The PC would be investigated through the Montecarlo simulation method.A Crack width of 0.1 mm in the RC decks would lead to a severe impact on the PC conducted using the Al-Ameeri model compared to the Kwon and Na model,when the percentages of LCFA vary from 5%to 30%in concrete mixes.It is recommended in this research to reduce the amount of high calcium fly ash in the mixes for RC decks to a percentage below 15%instead of LCFA to inhibit the carbonation-induced corrosion and enhance the durability and serviceability of RC structures.展开更多
More than seventy years before airplanes were invented,a twelve⁃year⁃old girl named Ada Lovelace dreamed of flying.She studied birds and experimented with materials to make wings,even writing a guide called Flyology.B...More than seventy years before airplanes were invented,a twelve⁃year⁃old girl named Ada Lovelace dreamed of flying.She studied birds and experimented with materials to make wings,even writing a guide called Flyology.But her curiosity didnt stop there.展开更多
基金National Natural Science Foundation of China(No.1157229)Graduate Student Education Innovation Project of Shanxi Province(No.2015SY58)
文摘Anti-tank intelligent mine is a kind of new intelligent anti-tank bomb relying on high precision detector.It can effectively capture and damage targets with wind resistance coefficient and other factors affecting its flight characteristics under consideration.This article is based on the three-dimensional model of intelligent mine.To analyze its subsonic and transonic flow fields and the change law of aerodynamic force factor with the growth of the angle of attack,computational fluid dynamics software is used for intelligent mine flow field numerical calculation and the change law of pressure center.The results show that the large drag coefficient is conducive to the stability of scanning.Drastic changes of the flow field near the intelligent mine will disable its scanning movement.The simulation results can provide a reference for scanning stability analysis,overall performance optimization and appearance improvement.
文摘It is crucial to develop arsenic removal adsorbents with strong sulfur resistance under middle-low-temperature flue gas conditions(<400℃).In this work,five Fe-Ce-La oxides were prepared by co-precipitation method,and FeCeLaO/SiO_(2)-Al_(2)O_(3) composite adsorbents were prepared by coupling fly ash-based Si-Al carriers.The active components Fe-Ce-La oxides and Si-Al carriers were characterized by TPD,TG,XRF,BET and XPS,respectively.The effects of temperature,Si/Al ratio and FeCeLaO loading rate on the sulfur resistance were investigated.Results show that the SO_(2) promotes the arsenic removal of Fe_(2)O_(3),CeLaO and FeCeLaO.At 400℃,the arsenic removal efficiencies of the three oxides increase from 45.3%,72.5% and 81.3% without SO_(2) to 62.6%,80.5%and 91.0%,respectively.The SO_(2) inhibits the arsenic removal of La_(2)O_(2)CO_(3) and FeLaO,and the inhibition effect is pronounced at high temperatures.The sulfur poisoning resistance of Si-Al carriers increases with the increase of Si/Al ratio.When the Si/Al ratio is increased to 9.74,the arsenic removal efficiency in the SO_(2) environment is 13.9% higher than that in the absence of SO_(2).Introducing FeCeLaO active components is beneficial for enhancing the SO_(2) poisoning resistance of Si-Al carriers.The strong sulfur resistance of the FeCeLaO/SiO_(2)-Al_(2)O_(3) composite adsorbent results from multiple factors:protective effects of Ce on Fe,La and Al;sulfation-induced generation of Ce^(3+)and surface-adsorbed oxygen;and strong surface acidity of SiO_(2).
基金supported in part by National Natural Science Foundation of China(under Grant 61902163)the Jiangsu“Qing Lan Project”,Natural Science Foundation of the Jiangsu Higher Education Institutions of China(Major Research Project:23KJA520007)Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.SJCX25_1303).
文摘Unmanned Aerial Vehicles(UAVs)in Flying Ad-Hoc Networks(FANETs)are widely used in both civilian and military fields,but they face severe security,trust,and privacy vulnerabilities due to their high mobility,dynamic topology,and open wireless channels.Existing security protocols for Mobile Ad-Hoc Networks(MANETs)cannot be directly applied to FANETs,as FANETs require lightweight,high real-time performance,and strong anonymity.The current FANETs security protocol cannot simultaneously meet the requirements of strong anonymity,high security,and low overhead in high dynamic and resource-constrained scenarios.To address these challenges,this paper proposes an Anonymous Authentication and Key Exchange Protocol(AAKE-OWA)for UAVs in FANETs based on OneWay Accumulators(OWA).During the UAV registration phase,the Key Management Center(KMC)generates an identity ticket for each UAV using OWA and transmits it securely to the UAV’s on-board tamper-proof module.In the key exchange phase,UAVs generate temporary authentication tickets with random numbers and compute the same session key leveraging the quasi-commutativity of OWA.For mutual anonymous authentication,UAVs encrypt random numbers with the session key and verify identities by comparing computed values with authentication values.Formal analysis using the Scyther tool confirms that the protocol resists identity spoofing,man-in-the-middle,and replay attacks.Through Burrows Abadi Needham(BAN)logic proof,it achieves mutual anonymity,prevents simulation and physical capture attacks,and ensures secure connectivity of 1.Experimental comparisons with existing protocols prove that the AAKE-OWA protocol has lower computational overhead,communication overhead,and storage overhead,making it more suitable for resource-constrained FANET scenarios.Performance comparison experiments show that,compared with other schemes,this scheme only requires 8 one-way accumulator operations and 4 symmetric encryption/decryption operations,with a total computational overhead as low as 2.3504 ms,a communication overhead of merely 1216 bits,and a storage overhead of 768 bits.We have achieved a reduction in computational costs from 6.3%to 90.3%,communication costs from 5.0%to 69.1%,and overall storage costs from 33%to 68%compared to existing solutions.It can meet the performance requirements of lightweight,real-time,and anonymity for unmanned aerial vehicles(UAVs)networks.
基金supported by the Jilin Science and Technology Program(20230203130SF)。
文摘Freeze–thaw(F–T)cycle-induced cracking in silty clays poses a significant risk to engineering stability.Although the individual addition of fly ash(FA)or sisal fiber(SF)provides partial solutions,their simultaneous application may result in a synergistic effect to compensate for their respective shortcomings.In this study,the effects of SF and FA on the mechanical properties,crack resistance,water retention,and erosion resistance of improved soil were systematically investigated through unconfined compressive strength(UCS)tests,crack evolution analysis,simulated rainfall erosion tests,and microscopic characterization(laser particle size analysis and nitrogen adsorption).The results reveal that the volumetric stability of FA particles significantly inhibits cracking in soil after F–T cycles.However,FA contributes only slightly to soil strength and erosion resistance.SF,on the other hand,plays a substantial role in increasing both soil strength and erosion resistance.The synergy between FA and SF results in the simultaneous increase in crack resistance,erosion resistance,and strength.FA improves the aggregate stability during F–T cycles,whereas SF reinforces the bonds between these aggregates.A comprehensive evaluation of the improved soil during F–T cycles using the entropy weight-TOPSIS method reveal that the combination of 10%FA+18 mm SF performed the best,achieving a 246%higher composite score than the unmodified soil did.With respect to this optimal combination,compared with the unmodified soil,the SF–FA-improved soil exhibits a 30%reduction in the average crack width,a 30%reduction in the erosion rate,and a 46%increase in strength.The findings of this study provide a scientific basis for the design of soil improvement in disaster mitigation engineering in seasonally frozen soil regions.
文摘This study aims to develop an accurate and robust machine learning model to predict the carbonation depth of fly ash concrete,overcoming the limitations of traditional predictive methods.Five ensemble-based models,such as adaptive boosting(AdaBoost),categorical boosting(CatBoost),gradient boosting regressor(GBR),hist gradient boosting regressor(HistGBR),and extreme gradient boosting(XGBoost),were developed and optimized using 729 high-quality dataset points incorporating seven input parameters,including cement,CO_(2),exposure time,water-binder ratio,fly ash,curing time,and compressive strength.Several performance evaluation metrics were used to compare the models.The GBR model emerged as the best-performing model,based on high coefficient of determination(R^(2))values and balanced error metrics across both validation and testing datasets.While all models performed exceptionally well on the training data,GBR demonstrated superior generalization capability,with R^(2) values of 0.9438 on the validation set and 0.9310 on the testing set.Furthermore,its low mean squared error(MSE),root mean square error(RMSE),mean absolute error(MAE),and median absolute error(MdAE)confirmed its robustness and accuracy.Moreover,shapley additive explanations(SHAP)analysis enhanced the interpretability of predictions,highlighting the curing time and exposure time as the most critical drivers of carbonation depth.
文摘In this study,Bacillus mojavensis and Lactiplantibacillus herbarum were used to co-treat kitchen waste(KW)with Black soldier fly larvae(BSFL).The effects on the physicochemical properties,heavy metal content,and microbial community of the BSFL sand were determined.Compared to the control group,the L.herbarum inoculation reduced 19.04%of the soluble salt(TSS),15.48%of Ni,and 13.04%of Zn in the residues;the B.mojavensis inoculation reduced 23.84%of TSS,13.61%of Pb,and 20.32%of the Ni in the residues;the L.herbarum and B.mojavensis inoculation reduced 29.53%of Cr,20.23%of Pb,18.06%of Ni,and 25.68%of the Zn in the residues.The microbial inoculants significantly enhanced the BSFL sand microbial diversity(Tukey,P<0.05).The dominant phylum and genus in the BSFL sand were Firmicutes(53.08%)and Corynebacterium(47.01%),respectively.The microbial inoculants resulted in an approximate 12%reduction in Corynebacterium.The linear discriminant analysis effective size analysis showed that the Corynebacterium abundance was significantly reduced.The microbial inoculants significantly affected the Corynebacterium relative abundance by significantly altering the substrate TSS,moisture content,and Ni.In conclusion,the effect of B.mojavensis and L.herbarum on the BSFL treatment of KW was beneficial,and their potential should be further exploited.
基金supported by the National Key Research and Development of China(No.2022YFB2503400).
文摘Semantic segmentation for mixed scenes of aerial remote sensing and road traffic is one of the key technologies for visual perception of flying cars.The State-of-the-Art(SOTA)semantic segmentation methods have made remarkable achievements in both fine-grained segmentation and real-time performance.However,when faced with the huge differences in scale and semantic categories brought about by the mixed scenes of aerial remote sensing and road traffic,they still face great challenges and there is little related research.Addressing the above issue,this paper proposes a semantic segmentation model specifically for mixed datasets of aerial remote sensing and road traffic scenes.First,a novel decoding-recoding multi-scale feature iterative refinement structure is proposed,which utilizes the re-integration and continuous enhancement of multi-scale information to effectively deal with the huge scale differences between cross-domain scenes,while using a fully convolutional structure to ensure the lightweight and real-time requirements.Second,a welldesigned cross-window attention mechanism combined with a global information integration decoding block forms an enhanced global context perception,which can effectively capture the long-range dependencies and multi-scale global context information of different scenes,thereby achieving fine-grained semantic segmentation.The proposed method is tested on a large-scale mixed dataset of aerial remote sensing and road traffic scenes.The results confirm that it can effectively deal with the problem of large-scale differences in cross-domain scenes.Its segmentation accuracy surpasses that of the SOTA methods,which meets the real-time requirements.
基金Project supported by Rumah Program 2023 and Net Zero Emission Program(1507/Ⅱ.7/HK.01.00/6/2023)a research facility from the National Research and Innovation Agency of Republic of Indonesia。
文摘Recycling rare earth elements(REEs)from waste is necessary for an environmentally sustainable reuse and wastewater management approach.Na-A zeolite was synthesized from coal fly ash(CFA)and applied for Ce^(3+)adsorption.Fourier transform infrared(FTIR)spectra show peaks at 790,500 and 467 cm^(-1),which are bond vibrations of Si-O-Si,Si with Al-O and Si-O-.The surface area is 15.88 m^(2)/g,with a pore size of 2.14 nm.SEM images show a cubic shape,which indicates the formation of zeolite.Field emission and energy disperse spectroscopy(EDS)shows the formation of Si,Al,Na,and O.Na-A zeolite was applied for Ce^(3+)adsorption.The optimum conditions for Ce^(3+)adsorption are 50 ppm concentration,360 min,and pH 6.The maximum adsorption capacity is 176.49 mg/g.Based on the results,it is found that the adsorption of Ce^(3+)by Na-A zeolite is pseudo-second-order.The desorption test using HNO_(3) is more effective than using HCl and H_(2)SO_(4).A desorption efficiency of 97.22%is obtained at 4 cycles.Adsorption test using real sample wastewater demonstrates an adsorption efficiency of 83.35%.
文摘Teacher–student relationships play a vital role in improving college students’academic performance and the quality of higher education.However,empirical studies with substantial data-driven insights remain limited.To address this gap,this study collected 3278 questionnaires from seven universities across four provinces in China to analyze the key factors affecting college students’academic performance.A machine learning framework,CQFOA-KELM,was developed by enhancing the Fruit Fly Optimization Algorithm(FOA)with Covariance Matrix Adaptation Evolution Strategy(CMAES)and Quadratic Approximation(QA).CQFOA significantly improved population diversity and was validated on the IEEE CEC2017 benchmark functions.The CQFOA-KELM model achieved an accuracy of 98.15%and a sensitivity of 98.53%in predicting college students’academic performance.Additionally,it effectively identified the key factors influencing academic performance through the feature selection process.
基金Supported by Yunnan Major Scientific and Technological Projects(No.202403AA080001)National Natural Science Foundation of China(No.52074137)Yunnan Fundamental Research Projects(No.202201AT070151)。
文摘Three types of activators such as sodium hydroxide,calcium oxide and triethanolamine(TEA)are used to establish different activation environments to address the problems associated with the process of activating fly ash paste.We conducted mechanical tests and numerical simulations to understand the evolution of microstructure,and used environmental scanning electron microscopy(ESEM)and energy dispersive spectroscopy(EDS)techniques to analyze the microenvironments of the samples.The mechanical properties of fly ash paste under different activation conditions and the changes in the microstructure and composition were investigated.The results revealed that under conditions of low NaOH content(1%-3%),the strength of the sample increased significantly.When the content exceeded 4%,the rate of increase in strength decreased.Based on the results,the optimal NaOH content was identified,which was about 4%.A good activation effect,especially for short-term activation(3-7 d),was achieved using TEA under high doping conditions.The activation effect was poor for long-term strength after 28 days.The CaO content did not significantly affect the degree of activation achieved.The maximum effect was exerted when the content of CaO was 2%.The virtual cement and concrete testing laboratory(VCCTL)was used to simulate the hydration process,and the results revealed that the use of the three types of activators accelerated the formation of Ca(OH)_(2) in the system.The activators also corroded the surface of the fly ash particles,resulting in a pozzolanic reaction.The active substances in fly ash were released efficiently,and hydration was realized.The pores were filled with hydration products,and the microstructure changed to form a new frame of paste filling that helped improve the strength of fly ash paste.
基金Funded by the Natural Science Foundation of China(No.52109168)。
文摘In order to study the characteristics of pure fly ash-based geopolymer concrete(PFGC)conveniently,we used a machine learning method that can quantify the perception of characteristics to predict its compressive strength.In this study,505 groups of data were collected,and a new database of compressive strength of PFGC was constructed.In order to establish an accurate prediction model of compressive strength,five different types of machine learning networks were used for comparative analysis.The five machine learning models all showed good compressive strength prediction performance on PFGC.Among them,R2,MSE,RMSE and MAE of decision tree model(DT)are 0.99,1.58,1.25,and 0.25,respectively.While R2,MSE,RMSE and MAE of random forest model(RF)are 0.97,5.17,2.27 and 1.38,respectively.The two models have high prediction accuracy and outstanding generalization ability.In order to enhance the interpretability of model decision-making,we used importance ranking to obtain the perception of machine learning model to 13 variables.These 13 variables include chemical composition of fly ash(SiO_(2)/Al_(2)O_(3),Si/Al),the ratio of alkaline liquid to the binder,curing temperature,curing durations inside oven,fly ash dosage,fine aggregate dosage,coarse aggregate dosage,extra water dosage and sodium hydroxide dosage.Curing temperature,specimen ages and curing durations inside oven have the greatest influence on the prediction results,indicating that curing conditions have more prominent influence on the compressive strength of PFGC than ordinary Portland cement concrete.The importance of curing conditions of PFGC even exceeds that of the concrete mix proportion,due to the low reactivity of pure fly ash.
基金co-supported by the National Natural Science Foundation of China(Nos.52272408,U21B2008)the Guangdong Basic and Applied Basic Research Foundation,China(No.2023B1515120018)。
文摘This paper investigates the configuration design associated with boundary-constrained swarm flying.An analytic swarm configuration is identified to ensure the passive safety between each pair of spacecraft in the radial-cross-track plane.For the first time,this work derives the explicit configurable spacecraft amount to clarify the configuration's accommodation capacity while considering the maximum inter-spacecraft separation constraint.For larger-scale design problem that involves hundreds of spacecraft,this paper proposes an optimization framework that integrates a Relative Orbit Element(ROE)affine transformation operation and successional convex optimization.The framework establishes a multi-subcluster swarm structure,allowing decoupling the maintenance issues of each subcluster.Compared with previous design methods,it ensures that the computational cost for constraints verification only scales linearly with the swarm size,while also preserving the configuration optimization capacities.Numerical simulations demonstrate that the proposed analytic configuration strictly meets the design constraints.It is also shown that the proposed framework reduces the handled constraint amount by two orders compared with direct optimization,while achieving a remarkable swarm safety enhancement based on the existing analytic configuration.
文摘In order to adjust some properties of cement grout or concrete,some mineral admixtures are usually added in the preparation.Admixtures can reduce the cement consumption and save the cost,and also adjust the workability of the material,improve the strength and durability of the cement stone,or reduce hydration heat of the composite cement.At present,the content of fly ash or slag is generally less than 50%among the composite cementitious materials that have been studied more,but there is little research on composite cementitious materials with large mineral admixture.In this paper,XRD,SEM,and adiabatic temperature rise tests were used to discuss hydration products and mechanism of composite cement grout with 90%content of fly ash and slag.The results show that the hydration of the composite cement grout is an alkali-activated hydration reaction,and the hydration products are mainly amorphous substances such as hydrated calcium silicate or hydrated calcium aluminate gel.The hydration reaction temperature rise is much lower than that of ordinary cement grout,and the time of the temperature peak is significantly delayed.
文摘Microwave-curing and mechanical grinding of fly ash have both beenadopted as effective methods for improving the early-age strength of alkali-activated fly ash(AAFA)binders.This study combined these two approaches by synthesizing AAFA using original,medium-fine,and ultrafine fly ash as precursors,and then specimens were cured with a five-stage temperature-controlled microwave.The compressive strength results indicate that the original AAFA develops the highest strength initially during microwave-curing,reaching 28 MPa at stage 2.Medium-fine AAFA exhibits the highest strength of 60 MPa when cured to stage 4-I,which is 26%higher than the peak strength of original AAFA.It is attributed to the significant rise in their specific surface area,which accelerates the dissolution of Si and Al from the precursor and facilitates the subsequent formation of N-A-S-H gels.Additionally,nanoscale zeolite crystals formed as secondary products fill the tiny gaps between amorphous products,thereby significantly improving their microstructure.In contrast,ultrafine fly ash,primarily composed of fragmented particles,necessitated a substantial amount of water,which adversely affects the absorption efficiency for microwave of AAFA specimens.Thus,ultrafine AAFA specimens consistently exhibit the lowest compressive strength.Specifically,at the end of curing,the compressive strength of these three specimens with microwave-curing is approximately 32%,59%,and 172%higher than that of the steam-cured sample,respectively.These findings demonstrate the compatibility of microwave-curing and fly ash refinement in enhancing the early compressive strength development of AAFA.
基金National Key Research and Development Program of China(2022YFB4602200)。
文摘To address the issues of low accuracy,long time consumption,and high cost of the traditional temperature prediction methods for laser directed energy deposition(LDED),a machine learning model combined with numerical simulation was proposed to predict the temperature during LDED.A finite element(FE)thermal analysis model was established.The model's accuracy was verified through in-situ monitoring experiments,and a basic database for the predictive model was obtained based on FE simulations.Temperature prediction was performed using a generalized regression neural network(GRNN).To reduce dependence on human experience during GRNN parameter tuning and to enhance model prediction performance,an improved adaptive step-size fruit fly optimization algorithm(ASSFOA)was introduced.Finally,the prediction performance of ASSFOA-GRNN model was compared with that of back-propagation neural network model,GRNN model,and fruit fly optimization algorithm(FOA)-GRNN model.The evaluation metrics included the root mean square error(RMSE),mean absolute error(MAE),coefficient of determination(R^(2)),training time,and prediction time.Results show that the ASSFOA-GRNN model exhibits optimal performance regarding RMSE,MAE,and R^(2) indexes.Although its prediction efficiency is slightly lower than that of the FOA-GRNN model,its prediction accuracy is significantly better than that of the other models.This proposed method can be used for temperature prediction in LDED process and also provide a reference for similar methods.
文摘On September 12,2023,in a reply letter to Jeffrey Greene,Chairman of the Sino-American Aviation Heritage Foundation,and Flying Tigers veterans Harry Moyer and Mel McMullen,President Xi Jinping noted,"In the past,our two peoples fought the Japanese fascists together,and forged a deep friendship that stood the test of blood and fre."
基金Funded by the National Natural Science Foundation of China(No.52178241)the National Key Research and Development Program of China during the Fourteenth Five-Year Plan Period(No.2021YFB3802001)+1 种基金the Shanghai Science and Technology Innovation Action Plan(No.23D21201401)the Key Research and Development of the Shaanxi Province of China(No.2022GY-163)。
文摘Municipal solid waste incineration fly ash(MSWI)is considered as one of the hazardous wastes and requires to be well disposed to reduce the contaminant to the environment.Reference to the production of coal fly ash(FA)bricks,MSWI and FA were utilized to prepare autoclaved MSWI-FA block samples.Ultrasonic-assisted hydrothermal synthesis technology was used for production to explore the effect of ultrasonic pre-treatment.Compressive strength,dry density,and water absorption tests were conducted to determine the optimal ultrasonic parameters.Ultrasonic pre-treating mechanisms were investigated by SEM,FT-IR,particle size analysis,and BET.Furthermore,the micro-analyses of block samples were conducted.The heavy metal leaching concentration was studied to assess the environmental safety.The experimental results show that the ultrasonic pre-treating time,water bath temperature,and ultrasonic power of 3 h,30℃,and 840 W are the optimal,under which the compressive strength,dry density,and water absorption were 8.14 MPa,1417.48 kg/m^(3),and 0.38,respectively.It is shown that ultrasound destroys the surface structure of raw materials and smaller FA particles embed into MSWI.The particle size distribution of pre-treated raw materials mixture is wider and total pore volume is decreased by 6.3%.During hydrothermal processing,more Al-substituted tobermorite crystals are generated,which is the main source of higher strength and smaller pore volume of prepared block samples.The solidification/stabilization rates of Cu,Pb,and Zn increased by 30.77%,4.76%,and 35.29%,respectively.This study shows a feasible way to utilize MSWI as raw material for construction.
文摘The rapid change in CO_(2) concentration levels,due to climate change,will lead to a significant reduction in the durability and safety of the vital reinforced concrete(RC)structures.Utilizing supplementary cementitious materials,such as low calcium fly ash(LCFA)or slag,etc.,with larger percentages in concrete mixes,would lead to an increase in the carbonation depth and risk of corrosion,especially for cracked concrete sections subjected to severe CO_(2) concentration levels.This research aims to compare the carbonation depth values using two different mathematical models across various CO_(2) concentrations and crack widths,for concrete mixes composed of different percentages and types of fly ash for both uncracked and cracked RC members,at a specific time of CO_(2) exposure.Moreover,the main objective is to assess the probability of corrosion(PC)across various percentages and types of fly ash used in cracked RC decks subjected to a severe CO_(2) level.The PC would be investigated through the Montecarlo simulation method.A Crack width of 0.1 mm in the RC decks would lead to a severe impact on the PC conducted using the Al-Ameeri model compared to the Kwon and Na model,when the percentages of LCFA vary from 5%to 30%in concrete mixes.It is recommended in this research to reduce the amount of high calcium fly ash in the mixes for RC decks to a percentage below 15%instead of LCFA to inhibit the carbonation-induced corrosion and enhance the durability and serviceability of RC structures.
文摘More than seventy years before airplanes were invented,a twelve⁃year⁃old girl named Ada Lovelace dreamed of flying.She studied birds and experimented with materials to make wings,even writing a guide called Flyology.But her curiosity didnt stop there.
