Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters accordi...Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.展开更多
In a humid environment,active metal magnesium is susceptible to the hydrogen evolution reaction with water,which significantly increases the risk of explosions in areas where magnesium is produced and used.In this pap...In a humid environment,active metal magnesium is susceptible to the hydrogen evolution reaction with water,which significantly increases the risk of explosions in areas where magnesium is produced and used.In this paper,the effects of equilibrium relative humidity(ERH) on the explosion characteristics parameters of magnesium dust under various initial conditions (concentration,particle size and temperature) were studied using a 20 L explosion device.Additionally,the explosion mechanism was thoroughly analyzed by incorporating the oxygen content results of the explosion products.The research revealed that explosion characteristics parameters (P_(max),(dp/dt)_(max)) of magnesium dust cloud initially increased and then decreased with rising ERH when the explosion system was in an“oxygen-rich”state.The maximum increments in P_(max)and (dp/dt)_(max)are 130 k Pa and 10.73 k Pa/ms,respectively.Moreover,a decrease in particle size and an increase in temperature facilitated the generation of more hydrogen from the humid magnesium dust.This phenomenon effectively improved the explosion characteristics parameters of the humid magnesium dust,thereby increasing the sensitivity and risk of the explosion system.However,in the case of a high degree of“oxygen-poor”state,the derived hydrogen instead became burdensome,resulting in an excessive amount of magnesium dust that was unavailable for reaction.This led to a decrease in the explosion characteristics parameters of humid magnesium dust,with the maximum decreases in P_(max)and (dp/dt)_(max)being 45.8 k Pa and 2.1 k Pa/ms respectively.展开更多
Gas explosion in confined space often leads to significant pressure oscillation.It is widely recognized that structural damage can be severe when the oscillation frequency of the load resonates with the natural vibrat...Gas explosion in confined space often leads to significant pressure oscillation.It is widely recognized that structural damage can be severe when the oscillation frequency of the load resonates with the natural vibration frequency of the structure.To reveal the oscillation mechanism of gas explosion load,the experiment of gas explosion was conducted in a large-scale confined tube with the length of 30 m,and the explosion process was numerically analyzed using FLACS.The results show that the essential cause of oscillation effect is the reflection of the pressure wave.In addition,due to the difference in the propagation path of the pressure wave,the load oscillation frequency at the middle position of the tunnel is twice that at the end position.The average sound velocity can be used to calculate the oscillation frequency of overpressure accurately,and the error is less than 15%.The instability of the flame surface and the increase of flame turbulence caused by the interaction between the pressure wave and the flame surface are the main contributors to the increase in overpressure and amplitude.The overpressure peaks calculated by the existing flame instability model and turbulence disturbance model are 31.7%and 34.7%lower than the numerical results,respectively.The turbulence factor model established in this work can describe the turbulence enhancement effect caused by flame instability and oscillatory load,and the difference between the theoretical and numerical results is only 4.6%.In the theoretical derivation of the overpressure model,an improved model of dynamic turbulence factor is established,which can describe the enhancement effect of turbulence factor caused by flame instability and self-turbulence.Based on the one-dimensional propagation theory of pressure wave,the oscillatory effect of the load is derived to calculate the frequency and amplitude of pressure oscillation.The average error of amplitude and frequency is less than 20%.展开更多
While the moisture content of soil affects significantly the blast impulse of shallow buried explosives,the role of surface-covering water(SCW)on soil in such blast impulse remains elusive.A combined experimental and ...While the moisture content of soil affects significantly the blast impulse of shallow buried explosives,the role of surface-covering water(SCW)on soil in such blast impulse remains elusive.A combined experimental and numerical study has been carried out to characterize the effect of SCW on transferred impulse and loading magnitude of shallow buried explosives.Firstly,blast tests of shallow buried explosives were conducted,with and without the SCW,to quantitatively assess the blast loading impulse.Subsequently,finite element(FE)simulations were performed and validated against experimental measurement,with good agreement achieved.The validated FE model was then employed to predict the dynamic response of a fully-clamped metallic circular target,subjected to the explosive impact of shallow buried explosives with SCW,and explore the corresponding physical mechanisms.It was demonstrated that shallow buried explosives in saturated soil generate a greater impulse transferred towards the target relative to those in dry soil.The deformation displacement of the target plate is doubled.Increasing the height of SCW results in enhanced center peak deflection of the loaded target,accompanied by subsequent fall,due to the variation of deformation pattern of the loaded target from concentrated load to uniform load.Meanwhile,the presence of SCW increases the blast impulse transferred towards the target by three times.In addition,there exists a threshold value of the burial depth that maximizes the impact impulse.This threshold exhibits a strong sensitivity to SCW height,decreasing with increasing SCW height.An empirical formula for predicting threshold has been provided.Similar conclusions can be drawn for different explosive masses.The results provide technical guidance on blast loading intensity and its spatial distribution considering shallow buried explosives in coast-land battlefields,which can ultimately contribute to better protective designs.展开更多
Atlantic Meridional Overturning Circulation(AMOC)plays a central role in long-term climate variations through its heat and freshwater transports,which can collapse under a rapid increase of greenhouse gas forcing in c...Atlantic Meridional Overturning Circulation(AMOC)plays a central role in long-term climate variations through its heat and freshwater transports,which can collapse under a rapid increase of greenhouse gas forcing in climate models.Previous studies have suggested that the deviation of model parameters is one of the major factors in inducing inaccurate AMOC simulations.In this work,with a low-resolution earth system model,the authors try to explore whether a reasonable adjustment of the key model parameter can help to re-establish the AMOC after its collapse.Through a new optimization strategy,the extra freshwater flux(FWF)parameter is determined to be the dominant one affecting the AMOC’s variability.The traditional ensemble optimal interpolation(EnOI)data assimilation and new machine learning methods are adopted to optimize the FWF parameter in an abrupt 4×CO_(2) forcing experiment to improve the adaptability of model parameters and accelerate the recovery of AMOC.The results show that,under an abrupt 4×CO_(2) forcing in millennial simulations,the AMOC will first collapse and then re-establish by the default FWF parameter slowly.However,during the parameter adjustment process,the saltier and colder sea water over the North Atlantic region are the dominant factors in usefully improving the adaptability of the FWF parameter and accelerating the recovery of AMOC,according to their physical relationship with FWF on the interdecadal timescale.展开更多
The seismic data of the Laoshan Uplift in the South Yellow Sea Basin reveal a low signal-tonoise ratio and low refl ection signal energy in the deep Mesozoic–Paleozoic strata.The main reason is that the Mesozoic-Pale...The seismic data of the Laoshan Uplift in the South Yellow Sea Basin reveal a low signal-tonoise ratio and low refl ection signal energy in the deep Mesozoic–Paleozoic strata.The main reason is that the Mesozoic-Paleozoic marine carbonate rock strata are directly covered by the Cenozoic terrestrial clastic rock strata,which form a strong shielding layer.To obtain the reflection signals of the strata below the strong shielding layer,a one-way wave equation bidirectional illumination analysis of the main observation system parameters was conducted by analyzing the mechanism of the strong shielding layer.Low-frequency seismic sources are assumed to have a high illumination intensity on the reflection layer below the strong shielding layer.Accordingly,optimized acquisition parameter suggestions were proposed,and reacquisition was performed at the existing survey line locations in the Laoshan Uplift area.The imaging of the newly acquired data in the middle and deep layers was drastically improved.It revealed the unconformity between the Sinian and Cambrian under the strong shielding layer.The study yielded new insights into the tectonic and sedimentary evolution of the Lower Paleozoic in the South Yellow Sea.展开更多
A conceptual model of intermittent joints is introduced to the cyclic shear test in the laboratory to explore the effects of loading parameters on its shear behavior under cyclic shear loading.The results show that th...A conceptual model of intermittent joints is introduced to the cyclic shear test in the laboratory to explore the effects of loading parameters on its shear behavior under cyclic shear loading.The results show that the loading parameters(initial normal stress,normal stiffness,and shear velocity)determine propagation paths of the wing and secondary cracks in rock bridges during the initial shear cycle,creating different morphologies of macroscopic step-path rupture surfaces and asperities on them.The differences in stress state and rupture surface induce different cyclic shear responses.It shows that high initial normal stress accelerates asperity degradation,raises shear resistance,and promotes compression of intermittent joints.In addition,high normal stiffness provides higher normal stress and shear resistance during the initial cycles and inhibits the dilation and compression of intermittent joints.High shear velocity results in a higher shear resistance,greater dilation,and greater compression.Finally,shear strength is most sensitive to initial normal stress,followed by shear velocity and normal stiffness.Moreover,average dilation angle is most sensitive to initial normal stress,followed by normal stiffness and shear velocity.During the shear cycles,frictional coefficient is affected by asperity degradation,backfilling of rock debris,and frictional area,exhibiting a non-monotonic behavior.展开更多
To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is deve...To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is developed to identify the geometric parameters.The study utilizes a common precast element for highway bridges as the research subject.First,edge feature points of the bridge component section are extracted from images of the precast component cross-sections by combining the Canny operator with mathematical morphology.Subsequently,a deep learning model is developed to identify the geometric parameters of the precast components using the extracted edge coordinates from the images as input and the predefined control parameters of the bridge section as output.A dataset is generated by varying the control parameters and noise levels for model training.Finally,field measurements are conducted to validate the accuracy of the developed method.The results indicate that the developed method effectively identifies the geometric parameters of bridge precast components,with an error rate maintained within 5%.展开更多
The concept of TNT(Trinitrotoluene,C_7H_5N_3O_6)equivalence is often invoked to evaluate the performance and predict the explosion parameters of different types of explosives.However,due to its low prediction accuracy...The concept of TNT(Trinitrotoluene,C_7H_5N_3O_6)equivalence is often invoked to evaluate the performance and predict the explosion parameters of different types of explosives.However,due to its low prediction accuracy and limited application range,the use of TNT equivalence for predicting explosion parameters in a confined space is rare.Compared with explosions in free fields,the process of explosive energy release in a confined space is closely related to various factors such as oxygen balance,combustible components content,and surrounding oxygen content.Studies have shown that in a confined space,negative oxygen balance explosives react with surrounding oxygen during afterburning,resulting in additional energy release and enhanced blast effects.The mechanism of energy release during afterburning is highly complex,making it challenging to determine the TNT equivalence for blast effects in a confined space.Therefore,this remains an active area of research.In this study,internal blast experiments were conducted using TNT and three other explosives under both air and N_2(Nitrogen)conditions to obtain explosion parameters including blast wave overpressure,quasi-static pressure,and temperature.The influences of oxygen balance and external oxygen content on energy release are analyzed.The author proposes principles for determining TNT equivalence for internal explosions while verifying the accuracy of obtained blast parameters through calculations based on TNT equivalence.These findings can serve as references for predicting blast performance.展开更多
The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can caus...The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.展开更多
In complex systems,there is a kind of parameters having only a minor impact on the outputs in most cases,but their accurate values are still critical for the operation of systems.In this paper,the authors focus on the...In complex systems,there is a kind of parameters having only a minor impact on the outputs in most cases,but their accurate values are still critical for the operation of systems.In this paper,the authors focus on the identification of these weak influence parameters in the complex systems and propose a identification model based on the parameter recursion.As an application,three parameters of the steam generator are identified,that is,the valve opening,the valve CV value,and the reference water level,in which the valve opening and the reference water level are weak influence parameters under most operating conditions.Numerical simulation results show that,in comparison with the multi-layer perceptron(MLP),the identification error rate is decreased.Actually,the average identification error rate for the valve opening decreases by 0.96%,for the valve CV decreases by 0.002%,and for the reference water level decreases by 12%after one recursion.After two recursions,the average identification error rate for the valve opening decreases by 11.07%,for the valve CV decreases by 2.601%,and for the reference water level decreases by 95.79%.This method can help to improve the control of the steam generator.展开更多
Accurately predicting environmental parameters in solar greenhouses is crucial for achieving precise environmental control.In solar greenhouses,temperature,humidity,and light intensity are crucial environmental parame...Accurately predicting environmental parameters in solar greenhouses is crucial for achieving precise environmental control.In solar greenhouses,temperature,humidity,and light intensity are crucial environmental parameters.The monitoring platform collected data on the internal environment of the solar greenhouse for one year,including temperature,humidity,and light intensity.Additionally,meteorological data,comprising outdoor temperature,outdoor humidity,and outdoor light intensity,was gathered during the same time frame.The characteristics and interrelationships among these parameters were investigated by a thorough analysis.The analysis revealed that environmental parameters in solar greenhouses displayed characteristics such as temporal variability,non-linearity,and periodicity.These parameters exhibited complex coupling relationships.Notably,these characteristics and coupling relationships exhibited pronounced seasonal variations.The multi-parameter multi-step prediction model for solar greenhouse(MPMS-SGH)was introduced,aiming to accurately predict three key greenhouse environmental parameters,and the model had certain seasonal adaptability.MPMS-SGH was structured with multiple layers,including an input layer,a preprocessing layer,a feature extraction layer,and a prediction layer.The input layer was used to generate the original sequence matrix,which included indoor temperature,indoor humidity,indoor light intensity,as well as outdoor temperature and outdoor light intensity.Then the preprocessing layer normalized,decomposed,and positionally encoded the original sequence matrix.In the feature extraction layer,the time attention mechanism and frequency attention mechanism were used to extract features from the trend component and the seasonal component,respectively.Finally,the prediction layer used a multi-layer perceptron to perform multi-step prediction of indoor environmental parameters(i.e.temperature,humidity,and light intensity).The parameter selection experiment evaluated the predictive performance of MPMS-SGH on input and output sequences of different lengths.The results indicated that with a constant output sequence length,the prediction accuracy of MPMS-SGH was firstly increased and then decreased with the increase of input sequence length.Specifically,when the input sequence length was 100,MPMS-SGH had the highest prediction accuracy,with RMSE of 0.22℃,0.28%,and 250lx for temperature,humidity,and light intensity,respectively.When the length of the input sequence remained constant,as the length of the output sequence increased,the accuracy of the model in predicting the three environmental parameters was continuously decreased.When the length of the output sequence exceeded 45,the prediction accuracy of MPMS-SGH was significantly decreased.In order to achieve the best balance between model size and performance,the input sequence length of MPMS-SGH was set to be 100,while the output sequence length was set to be 35.To assess MPMS-SGH’s performance,comparative experiments with four prediction models were conducted:SVR,STL-SVR,LSTM,and STL-LSTM.The results demonstrated that MPMS-SGH surpassed all other models,achieving RMSE of 0.15℃for temperature,0.38%for humidity,and 260lx for light intensity.Additionally,sequence decomposition can contribute to enhancing MPMS-SGH’s prediction performance.To further evaluate MPMS-SGH’s capabilities,its prediction accuracy was tested across different seasons for greenhouse environmental parameters.MPMS-SGH had the highest accuracy in predicting indoor temperature and the lowest accuracy in predicting humidity.And the accuracy of MPMS-SGH in predicting environmental parameters of the solar greenhouse fluctuated with seasons.MPMS-SGH had the highest accuracy in predicting the temperature inside the greenhouse on sunny days in spring(R^(2)=0.91),the highest accuracy in predicting the humidity inside the greenhouse on sunny days in winter(R^(2)=0.83),and the highest accuracy in predicting the light intensity inside the greenhouse on cloudy days in autumm(R^(2)=0.89).MPMS-SGH had the lowest accuracy in predicting three environmental parameters in a sunny summer greenhouse.展开更多
Due to the presence of nitro groups, the dust generated during the production and utilization of energetic materials may potentially lead to dust explosion even under low-oxygen or anaerobic conditions.Considering the...Due to the presence of nitro groups, the dust generated during the production and utilization of energetic materials may potentially lead to dust explosion even under low-oxygen or anaerobic conditions.Considering the high energy density of energetic materials, dust explosion can cause serious production safety accidents. Therefore, it is necessary to understand the dust explosion characteristics of energetic materials and the mechanism of dust explosion. According to the literature review, among various influencing factors, the physical and chemical properties of dust are the decisive factors affecting the explosion characteristics of dust. In addition to experimental studies, numerical simulation is another important tool. However, it is subjected to certain limitations. Moreover, it is essential but challenging to fully understand the underlying mechanism. In addition, given the safety hazards posed by dust explosion, explosion suppression has attracted extensive attention for research. Depending on the medium used, there are different forms of suppression, including powder explosion suppression, water spray explosion suppression, inert gas explosion suppression, porous material explosion suppression, and vacuum chamber explosion suppression. As for the selection of explosion suppression agent, consideration must be given to the characteristics of the material. Furthermore, the above research has laid a foundation for discussing the future progress in studying dust explosion of energetic materials, with nano dust and the constraints of existing technology as the focal point.展开更多
In this paper,we propose a neural network approach to learn the parameters of a class of stochastic Lotka-Volterra systems.Approximations of the mean and covariance matrix of the observational variables are obtained f...In this paper,we propose a neural network approach to learn the parameters of a class of stochastic Lotka-Volterra systems.Approximations of the mean and covariance matrix of the observational variables are obtained from the Euler-Maruyama discretization of the underlying stochastic differential equations(SDEs),based on which the loss function is built.The stochastic gradient descent method is applied in the neural network training.Numerical experiments demonstrate the effectiveness of our method.展开更多
To overcome the shortage of complex equipment,large volume,and high energy consumption in space capsule manufacturing,a novel sliding pressure Joule heat fuse additive manufacturing technique with reduced volume and l...To overcome the shortage of complex equipment,large volume,and high energy consumption in space capsule manufacturing,a novel sliding pressure Joule heat fuse additive manufacturing technique with reduced volume and low energy consumption was proposed.But the unreasonable process parameters may lead to the inferior consistency of the forming quality of single-channel multilayer in Joule heat additive manufacturing process,and it is difficult to reach the condition for forming thinwalled parts.Orthogonal experiments were designed to fabricate single-channel multilayer samples with varying numbers of layers,and their forming quality was evaluated.The influence of printing current,forming speed,and contact pressure on the forming quality of the single-channel multilayer was analyzed.The optimal process parameters were obtained and the quality characterization of the experiment results was conducted.Results show that the printing current has the most significant influence on the forming quality of the single-channel multilayer.Under the optimal process parameters,the forming section is well fused and the surface is continuously smooth.The surface roughness of a single-channel 3-layer sample is 0.16μm,and the average Vickers hardness of cross section fusion zone is 317 HV,which lays a foundation for the subsequent use of Joule heat additive manufacturing technique to form thinwall parts.展开更多
Urban growth has promoted the use of underground spaces,where explosion accidents can be catastrophic.In this study,we investigated the effect of placing flexible construction in front of rigid obstacles on methane ex...Urban growth has promoted the use of underground spaces,where explosion accidents can be catastrophic.In this study,we investigated the effect of placing flexible construction in front of rigid obstacles on methane explosion protection by using an experimental platform and adjusting the blockage rate and spacing of the obstacles.It aims to reduce the risk of gas explosions in urban underground spaces.The results of the study show that the flame propagation peak speed and peak overpressure are reduced with the decrease in the blocking rate of the flexible obstacle when the blocking rate of the flexible obstacle is less than or equal to the blocking rate of the rigid obstacle,with the decrease in the spacing,the better the protection effect of the methane explosion.When the blockage rate of the flexible obstacle is greater than the blockage rate of the rigid obstacle and spacing is less than the height of the flexible obstacle,rigid and flexible obstacles are connected as a whole,increasing the strength of the explosion.This study can provide a theoretical basis and scientific guidance for optimizing rigid and flexible object hybrid layouts and methane explosion protection technology in urban underground spaces.展开更多
The gas explosion in residential building has always been a highly concerned problem.Explosions in homogeneous mixtures have been extensively studied.However,mixtures are often inhomogeneous in the practical scenarios...The gas explosion in residential building has always been a highly concerned problem.Explosions in homogeneous mixtures have been extensively studied.However,mixtures are often inhomogeneous in the practical scenarios due to the differences in the densities of methane and air.In order to investigate the effects of gas explosions in inhomogeneous mixtures,experimental studies involving gas leakage and explosion are conducted in a full-scale residential building to reproduce the process of gas explosion.By fitting the dimensionless buoyancy as a function of dimensionless height and dimensionless time,a distribution model of gas in large-scale spaces is established,and the mechanism of inhomogeneous distribution of methane is also be revealed.Furthermore,the stratified reconstruction method(SRM)is introduced for efficiently setting up inhomogeneous concentration fields in FLACS.The simulation results highlight that for the internal overpressure,the distribution of methane has no effect on the first overpressure peak(ΔP1),while it significantly influences the subsequent overpressure peak(ΔP2),and the maximum difference between the overpressure of homogeneous and inhomogeneous distribution is174.3%.Moreover,the initial concentration distribution also has a certain impact on the external overpressure.展开更多
Coal dust explosions are severe safety accidents in coal mine production,posing significant threats to life and property.Predicting the maximum explosion pressure(Pm)of coal dust using deep learning models can effecti...Coal dust explosions are severe safety accidents in coal mine production,posing significant threats to life and property.Predicting the maximum explosion pressure(Pm)of coal dust using deep learning models can effectively assess potential risks and provide a scientific basis for preventing coal dust explosions.In this study,a 20-L explosion sphere apparatus was used to test the maximum explosion pressure of coal dust under seven different particle sizes and ten mass concentrations(Cdust),resulting in a dataset of 70 experimental groups.Through Spearman correlation analysis and random forest feature selection methods,particle size(D_(10),D_(20),D_(50))and mass concentration(Cdust)were identified as critical feature parameters from the ten initial parameters of the coal dust samples.Based on this,a hybrid Long Short-Term Memory(LSTM)network model incorporating a Multi-Head Attention Mechanism and the Sparrow Search Algorithm(SSA)was proposed to predict the maximum explosion pressure of coal dust.The results demonstrate that the SSA-LSTM-Multi-Head Attention model excels in predicting the maximum explosion pressure of coal dust.The four evaluation metrics indicate that the model achieved a coefficient of determination(R^(2)),root mean square error(RMSE),mean absolute percentage error(MAPE),and mean absolute error(MAE)of 0.9841,0.0030,0.0074,and 0.0049,respectively,in the training set.In the testing set,these values were 0.9743,0.0087,0.0108,and 0.0069,respectively.Compared to artificial neural networks(ANN),random forest(RF),support vector machines(SVM),particle swarm optimized-SVM(PSO-SVM)neural networks,and the traditional single-model LSTM,the SSA-LSTM-Multi-Head Attention model demonstrated superior generalization capability and prediction accuracy.The findings of this study not only advance the application of deep learning in coal dust explosion prediction but also provide robust technical support for the prevention and risk assessment of coal dust explosions.展开更多
BACKGROUND Sagittal spinopelvic alignment(SSA)is essential for preserving a stable and effective upright posture and locomotion.Although alterations in the SSA are recognised to induce compensatory modifications in th...BACKGROUND Sagittal spinopelvic alignment(SSA)is essential for preserving a stable and effective upright posture and locomotion.Although alterations in the SSA are recognised to induce compensatory modifications in the pelvis,hips,and knees,the inverse relationship concerning knee pathology undergoing total knee arthroplasty(TKA)has been examined by a limited number of studies,yielding inconclusive results.AIM To generate evidence of the effect of TKA on the SSA from existing literature.METHODS Databases like PubMed,EMBASE,and Scopus were used to identify articles related to the“knee spine syndrome”phenomenon using a combination of subject terms and keywords such as“spinopelvic parameters”,“sagittal spinal balance”,and“total knee arthroplasty”were used with appropriate Boolean operators.Studies measuring the SSA following TKA were included,and research was conducted as per preferred reporting items for systematic review and metaanalysis guidelines.RESULTS A total of 475 participants had undergone TKA,and six studies measuring SSA were analysed.Following TKA,pelvic tilt was the only parameter that showed significant changes,while lumbar lordosis(LL),pelvic incidence,and sacral slope were non-significant,as evident from the forest plots.CONCLUSION The body's sagittal alignment is a complex balance between pelvic,spine,and lower extremity parameters.TKA,while having the potential to correct the flexion contracture,can also correct it.Still,the primary SSA for spinal pathology,i.e.,LL,may not be corrected in patients with co-existent spinal degenerative disease.展开更多
RDX/Al mixtures are widely utilized in energetic materials,yet their hybrid dust generated during production and application poses potential explosion hazards.Moreover,the synergistic explosion mechanisms remain poorl...RDX/Al mixtures are widely utilized in energetic materials,yet their hybrid dust generated during production and application poses potential explosion hazards.Moreover,the synergistic explosion mechanisms remain poorly understood,particularly at varying dust concentrations.This study systematically investigates the effects of different aluminum powder mass percentages and dust concentrations(300 g/m^(3),600 g/m^(3),900 g/m^(3))on RDX dust explosion severity,flame propagation behavior,and gaseous products.The results indicate that the maximum explosion pressure peaks at 35%RDX,65%RDX,and 80%RDX at 300 g/m^(3),600 g/m^(3),and 900 g/m^(3),respectively.Concurrently,the time for the flame to propagate to the wall(t1)reaches minimum values of 34.8 ms,25.66 ms,and 23.93 ms.The maximum rate of pressure rise is observed for pure RDX at 900 g/m^(3).Aluminum powder enhances flame propagation velocity and combustion duration,as validated by the flame propagation system.Overall,the concentrations of carbon oxides(CO+CO_(2))decrease significantly with increasing aluminum mass percentage.At 20%RDX,the concentrations decreased by 51.64%,72.31%,and 79.55%compared to pure RDX at 300 g/m^(3),600 g/m^(3),and 900 g/m^(3),respectively.Notably,N_(2)O concentration only at 300 g/m^(3)showed such a trend.It rises first and then falls at 35%RDX at 600 g/m^(3)and 900 g/m^(3).These findings elucidate the synergistic explosion mechanisms and provide critical guidelines for safe production and handling.展开更多
基金supported by the Innovation Foundation of Provincial Education Department of Gansu(2024B-005)the Gansu Province National Science Foundation(22YF7GA182)the Fundamental Research Funds for the Central Universities(No.lzujbky2022-kb01)。
文摘Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.
基金financial support of the China Postdoctoral Science Foundation (2022M721631)Key Laboratory of Safety Engineering and Technology Research of Zhejiang Province (No. 202307)+1 种基金Jiangsu Natural Science Foundation (SBK2023042272)Jiangsu Funding Program for Excellent Postdoctoral Talent (No. 2023827)。
文摘In a humid environment,active metal magnesium is susceptible to the hydrogen evolution reaction with water,which significantly increases the risk of explosions in areas where magnesium is produced and used.In this paper,the effects of equilibrium relative humidity(ERH) on the explosion characteristics parameters of magnesium dust under various initial conditions (concentration,particle size and temperature) were studied using a 20 L explosion device.Additionally,the explosion mechanism was thoroughly analyzed by incorporating the oxygen content results of the explosion products.The research revealed that explosion characteristics parameters (P_(max),(dp/dt)_(max)) of magnesium dust cloud initially increased and then decreased with rising ERH when the explosion system was in an“oxygen-rich”state.The maximum increments in P_(max)and (dp/dt)_(max)are 130 k Pa and 10.73 k Pa/ms,respectively.Moreover,a decrease in particle size and an increase in temperature facilitated the generation of more hydrogen from the humid magnesium dust.This phenomenon effectively improved the explosion characteristics parameters of the humid magnesium dust,thereby increasing the sensitivity and risk of the explosion system.However,in the case of a high degree of“oxygen-poor”state,the derived hydrogen instead became burdensome,resulting in an excessive amount of magnesium dust that was unavailable for reaction.This led to a decrease in the explosion characteristics parameters of humid magnesium dust,with the maximum decreases in P_(max)and (dp/dt)_(max)being 45.8 k Pa and 2.1 k Pa/ms respectively.
基金financial support from National Natural Science Foundation of China(Grant No.52378488)Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX22_0222).
文摘Gas explosion in confined space often leads to significant pressure oscillation.It is widely recognized that structural damage can be severe when the oscillation frequency of the load resonates with the natural vibration frequency of the structure.To reveal the oscillation mechanism of gas explosion load,the experiment of gas explosion was conducted in a large-scale confined tube with the length of 30 m,and the explosion process was numerically analyzed using FLACS.The results show that the essential cause of oscillation effect is the reflection of the pressure wave.In addition,due to the difference in the propagation path of the pressure wave,the load oscillation frequency at the middle position of the tunnel is twice that at the end position.The average sound velocity can be used to calculate the oscillation frequency of overpressure accurately,and the error is less than 15%.The instability of the flame surface and the increase of flame turbulence caused by the interaction between the pressure wave and the flame surface are the main contributors to the increase in overpressure and amplitude.The overpressure peaks calculated by the existing flame instability model and turbulence disturbance model are 31.7%and 34.7%lower than the numerical results,respectively.The turbulence factor model established in this work can describe the turbulence enhancement effect caused by flame instability and oscillatory load,and the difference between the theoretical and numerical results is only 4.6%.In the theoretical derivation of the overpressure model,an improved model of dynamic turbulence factor is established,which can describe the enhancement effect of turbulence factor caused by flame instability and self-turbulence.Based on the one-dimensional propagation theory of pressure wave,the oscillatory effect of the load is derived to calculate the frequency and amplitude of pressure oscillation.The average error of amplitude and frequency is less than 20%.
基金supported by the National Natural Science Foundation of China(Grant Nos.12002156,11972185,12372136)Research Fund of State Key Laboratory of Mechanics and Control for Aerospace Structures(Grant No.MCMS-I-0222K01)。
文摘While the moisture content of soil affects significantly the blast impulse of shallow buried explosives,the role of surface-covering water(SCW)on soil in such blast impulse remains elusive.A combined experimental and numerical study has been carried out to characterize the effect of SCW on transferred impulse and loading magnitude of shallow buried explosives.Firstly,blast tests of shallow buried explosives were conducted,with and without the SCW,to quantitatively assess the blast loading impulse.Subsequently,finite element(FE)simulations were performed and validated against experimental measurement,with good agreement achieved.The validated FE model was then employed to predict the dynamic response of a fully-clamped metallic circular target,subjected to the explosive impact of shallow buried explosives with SCW,and explore the corresponding physical mechanisms.It was demonstrated that shallow buried explosives in saturated soil generate a greater impulse transferred towards the target relative to those in dry soil.The deformation displacement of the target plate is doubled.Increasing the height of SCW results in enhanced center peak deflection of the loaded target,accompanied by subsequent fall,due to the variation of deformation pattern of the loaded target from concentrated load to uniform load.Meanwhile,the presence of SCW increases the blast impulse transferred towards the target by three times.In addition,there exists a threshold value of the burial depth that maximizes the impact impulse.This threshold exhibits a strong sensitivity to SCW height,decreasing with increasing SCW height.An empirical formula for predicting threshold has been provided.Similar conclusions can be drawn for different explosive masses.The results provide technical guidance on blast loading intensity and its spatial distribution considering shallow buried explosives in coast-land battlefields,which can ultimately contribute to better protective designs.
基金supported by the National Key R&D Program of China [grant number 2023YFF0805202]the National Natural Science Foun-dation of China [grant number 42175045]the Strategic Priority Research Program of the Chinese Academy of Sciences [grant number XDB42000000]。
文摘Atlantic Meridional Overturning Circulation(AMOC)plays a central role in long-term climate variations through its heat and freshwater transports,which can collapse under a rapid increase of greenhouse gas forcing in climate models.Previous studies have suggested that the deviation of model parameters is one of the major factors in inducing inaccurate AMOC simulations.In this work,with a low-resolution earth system model,the authors try to explore whether a reasonable adjustment of the key model parameter can help to re-establish the AMOC after its collapse.Through a new optimization strategy,the extra freshwater flux(FWF)parameter is determined to be the dominant one affecting the AMOC’s variability.The traditional ensemble optimal interpolation(EnOI)data assimilation and new machine learning methods are adopted to optimize the FWF parameter in an abrupt 4×CO_(2) forcing experiment to improve the adaptability of model parameters and accelerate the recovery of AMOC.The results show that,under an abrupt 4×CO_(2) forcing in millennial simulations,the AMOC will first collapse and then re-establish by the default FWF parameter slowly.However,during the parameter adjustment process,the saltier and colder sea water over the North Atlantic region are the dominant factors in usefully improving the adaptability of the FWF parameter and accelerating the recovery of AMOC,according to their physical relationship with FWF on the interdecadal timescale.
基金“High precision prestack reverse time depth migration imaging of long array seismic data in the East China Sea Shelf Basin”of the National Natural Science Foundation of China(No.42106207)“Seismic acquisition technology for deep strata under strong shielding layers in the sea and rugged seabed”of Laoshan Laboratory Science and Technology Innovation Project(No.LSKJ202203404)“Research on the compensation methods of the middledeep weak seismic reflections in the South Yellow Sea based on multi-resolution HHT time-frequency analysis”of the National Natural Science Foundation of China(No.42106208).
文摘The seismic data of the Laoshan Uplift in the South Yellow Sea Basin reveal a low signal-tonoise ratio and low refl ection signal energy in the deep Mesozoic–Paleozoic strata.The main reason is that the Mesozoic-Paleozoic marine carbonate rock strata are directly covered by the Cenozoic terrestrial clastic rock strata,which form a strong shielding layer.To obtain the reflection signals of the strata below the strong shielding layer,a one-way wave equation bidirectional illumination analysis of the main observation system parameters was conducted by analyzing the mechanism of the strong shielding layer.Low-frequency seismic sources are assumed to have a high illumination intensity on the reflection layer below the strong shielding layer.Accordingly,optimized acquisition parameter suggestions were proposed,and reacquisition was performed at the existing survey line locations in the Laoshan Uplift area.The imaging of the newly acquired data in the middle and deep layers was drastically improved.It revealed the unconformity between the Sinian and Cambrian under the strong shielding layer.The study yielded new insights into the tectonic and sedimentary evolution of the Lower Paleozoic in the South Yellow Sea.
基金financially supported by the National Natural Science Foundation of China(Grant No.42172292)Taishan Scholars Project Special Funding,and Shandong Energy Group(Grant No.SNKJ 2022A01-R26).
文摘A conceptual model of intermittent joints is introduced to the cyclic shear test in the laboratory to explore the effects of loading parameters on its shear behavior under cyclic shear loading.The results show that the loading parameters(initial normal stress,normal stiffness,and shear velocity)determine propagation paths of the wing and secondary cracks in rock bridges during the initial shear cycle,creating different morphologies of macroscopic step-path rupture surfaces and asperities on them.The differences in stress state and rupture surface induce different cyclic shear responses.It shows that high initial normal stress accelerates asperity degradation,raises shear resistance,and promotes compression of intermittent joints.In addition,high normal stiffness provides higher normal stress and shear resistance during the initial cycles and inhibits the dilation and compression of intermittent joints.High shear velocity results in a higher shear resistance,greater dilation,and greater compression.Finally,shear strength is most sensitive to initial normal stress,followed by shear velocity and normal stiffness.Moreover,average dilation angle is most sensitive to initial normal stress,followed by normal stiffness and shear velocity.During the shear cycles,frictional coefficient is affected by asperity degradation,backfilling of rock debris,and frictional area,exhibiting a non-monotonic behavior.
基金The National Natural Science Foundation of China(No.52338011,52378291)Young Elite Scientists Sponsorship Program by CAST(No.2022-2024QNRC0101).
文摘To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is developed to identify the geometric parameters.The study utilizes a common precast element for highway bridges as the research subject.First,edge feature points of the bridge component section are extracted from images of the precast component cross-sections by combining the Canny operator with mathematical morphology.Subsequently,a deep learning model is developed to identify the geometric parameters of the precast components using the extracted edge coordinates from the images as input and the predefined control parameters of the bridge section as output.A dataset is generated by varying the control parameters and noise levels for model training.Finally,field measurements are conducted to validate the accuracy of the developed method.The results indicate that the developed method effectively identifies the geometric parameters of bridge precast components,with an error rate maintained within 5%.
文摘The concept of TNT(Trinitrotoluene,C_7H_5N_3O_6)equivalence is often invoked to evaluate the performance and predict the explosion parameters of different types of explosives.However,due to its low prediction accuracy and limited application range,the use of TNT equivalence for predicting explosion parameters in a confined space is rare.Compared with explosions in free fields,the process of explosive energy release in a confined space is closely related to various factors such as oxygen balance,combustible components content,and surrounding oxygen content.Studies have shown that in a confined space,negative oxygen balance explosives react with surrounding oxygen during afterburning,resulting in additional energy release and enhanced blast effects.The mechanism of energy release during afterburning is highly complex,making it challenging to determine the TNT equivalence for blast effects in a confined space.Therefore,this remains an active area of research.In this study,internal blast experiments were conducted using TNT and three other explosives under both air and N_2(Nitrogen)conditions to obtain explosion parameters including blast wave overpressure,quasi-static pressure,and temperature.The influences of oxygen balance and external oxygen content on energy release are analyzed.The author proposes principles for determining TNT equivalence for internal explosions while verifying the accuracy of obtained blast parameters through calculations based on TNT equivalence.These findings can serve as references for predicting blast performance.
基金Projects(U22B2084,52275483,52075142)supported by the National Natural Science Foundation of ChinaProject(2023ZY01050)supported by the Ministry of Industry and Information Technology High Quality Development,China。
文摘The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.
文摘In complex systems,there is a kind of parameters having only a minor impact on the outputs in most cases,but their accurate values are still critical for the operation of systems.In this paper,the authors focus on the identification of these weak influence parameters in the complex systems and propose a identification model based on the parameter recursion.As an application,three parameters of the steam generator are identified,that is,the valve opening,the valve CV value,and the reference water level,in which the valve opening and the reference water level are weak influence parameters under most operating conditions.Numerical simulation results show that,in comparison with the multi-layer perceptron(MLP),the identification error rate is decreased.Actually,the average identification error rate for the valve opening decreases by 0.96%,for the valve CV decreases by 0.002%,and for the reference water level decreases by 12%after one recursion.After two recursions,the average identification error rate for the valve opening decreases by 11.07%,for the valve CV decreases by 2.601%,and for the reference water level decreases by 95.79%.This method can help to improve the control of the steam generator.
文摘Accurately predicting environmental parameters in solar greenhouses is crucial for achieving precise environmental control.In solar greenhouses,temperature,humidity,and light intensity are crucial environmental parameters.The monitoring platform collected data on the internal environment of the solar greenhouse for one year,including temperature,humidity,and light intensity.Additionally,meteorological data,comprising outdoor temperature,outdoor humidity,and outdoor light intensity,was gathered during the same time frame.The characteristics and interrelationships among these parameters were investigated by a thorough analysis.The analysis revealed that environmental parameters in solar greenhouses displayed characteristics such as temporal variability,non-linearity,and periodicity.These parameters exhibited complex coupling relationships.Notably,these characteristics and coupling relationships exhibited pronounced seasonal variations.The multi-parameter multi-step prediction model for solar greenhouse(MPMS-SGH)was introduced,aiming to accurately predict three key greenhouse environmental parameters,and the model had certain seasonal adaptability.MPMS-SGH was structured with multiple layers,including an input layer,a preprocessing layer,a feature extraction layer,and a prediction layer.The input layer was used to generate the original sequence matrix,which included indoor temperature,indoor humidity,indoor light intensity,as well as outdoor temperature and outdoor light intensity.Then the preprocessing layer normalized,decomposed,and positionally encoded the original sequence matrix.In the feature extraction layer,the time attention mechanism and frequency attention mechanism were used to extract features from the trend component and the seasonal component,respectively.Finally,the prediction layer used a multi-layer perceptron to perform multi-step prediction of indoor environmental parameters(i.e.temperature,humidity,and light intensity).The parameter selection experiment evaluated the predictive performance of MPMS-SGH on input and output sequences of different lengths.The results indicated that with a constant output sequence length,the prediction accuracy of MPMS-SGH was firstly increased and then decreased with the increase of input sequence length.Specifically,when the input sequence length was 100,MPMS-SGH had the highest prediction accuracy,with RMSE of 0.22℃,0.28%,and 250lx for temperature,humidity,and light intensity,respectively.When the length of the input sequence remained constant,as the length of the output sequence increased,the accuracy of the model in predicting the three environmental parameters was continuously decreased.When the length of the output sequence exceeded 45,the prediction accuracy of MPMS-SGH was significantly decreased.In order to achieve the best balance between model size and performance,the input sequence length of MPMS-SGH was set to be 100,while the output sequence length was set to be 35.To assess MPMS-SGH’s performance,comparative experiments with four prediction models were conducted:SVR,STL-SVR,LSTM,and STL-LSTM.The results demonstrated that MPMS-SGH surpassed all other models,achieving RMSE of 0.15℃for temperature,0.38%for humidity,and 260lx for light intensity.Additionally,sequence decomposition can contribute to enhancing MPMS-SGH’s prediction performance.To further evaluate MPMS-SGH’s capabilities,its prediction accuracy was tested across different seasons for greenhouse environmental parameters.MPMS-SGH had the highest accuracy in predicting indoor temperature and the lowest accuracy in predicting humidity.And the accuracy of MPMS-SGH in predicting environmental parameters of the solar greenhouse fluctuated with seasons.MPMS-SGH had the highest accuracy in predicting the temperature inside the greenhouse on sunny days in spring(R^(2)=0.91),the highest accuracy in predicting the humidity inside the greenhouse on sunny days in winter(R^(2)=0.83),and the highest accuracy in predicting the light intensity inside the greenhouse on cloudy days in autumm(R^(2)=0.89).MPMS-SGH had the lowest accuracy in predicting three environmental parameters in a sunny summer greenhouse.
基金the financial support of the Shanxi Fire & Explosion-Proofing Safety Engineering and Technology Research Center, North University of China。
文摘Due to the presence of nitro groups, the dust generated during the production and utilization of energetic materials may potentially lead to dust explosion even under low-oxygen or anaerobic conditions.Considering the high energy density of energetic materials, dust explosion can cause serious production safety accidents. Therefore, it is necessary to understand the dust explosion characteristics of energetic materials and the mechanism of dust explosion. According to the literature review, among various influencing factors, the physical and chemical properties of dust are the decisive factors affecting the explosion characteristics of dust. In addition to experimental studies, numerical simulation is another important tool. However, it is subjected to certain limitations. Moreover, it is essential but challenging to fully understand the underlying mechanism. In addition, given the safety hazards posed by dust explosion, explosion suppression has attracted extensive attention for research. Depending on the medium used, there are different forms of suppression, including powder explosion suppression, water spray explosion suppression, inert gas explosion suppression, porous material explosion suppression, and vacuum chamber explosion suppression. As for the selection of explosion suppression agent, consideration must be given to the characteristics of the material. Furthermore, the above research has laid a foundation for discussing the future progress in studying dust explosion of energetic materials, with nano dust and the constraints of existing technology as the focal point.
基金Supported by the National Natural Science Foundation of China(11971458,11471310)。
文摘In this paper,we propose a neural network approach to learn the parameters of a class of stochastic Lotka-Volterra systems.Approximations of the mean and covariance matrix of the observational variables are obtained from the Euler-Maruyama discretization of the underlying stochastic differential equations(SDEs),based on which the loss function is built.The stochastic gradient descent method is applied in the neural network training.Numerical experiments demonstrate the effectiveness of our method.
基金Shaanxi Province Qin Chuangyuan“Scientist+Engineer”Team Construction Project(2022KXJ-071)2022 Qin Chuangyuan Achievement Transformation Incubation Capacity Improvement Project(2022JH-ZHFHTS-0012)+1 种基金Shaanxi Province Key Research and Development Plan-“Two Chains”Integration Key Project-Qin Chuangyuan General Window Industrial Cluster Project(2023QCY-LL-02)Xixian New Area Science and Technology Plan(2022-YXYJ-003,2022-XXCY-010)。
文摘To overcome the shortage of complex equipment,large volume,and high energy consumption in space capsule manufacturing,a novel sliding pressure Joule heat fuse additive manufacturing technique with reduced volume and low energy consumption was proposed.But the unreasonable process parameters may lead to the inferior consistency of the forming quality of single-channel multilayer in Joule heat additive manufacturing process,and it is difficult to reach the condition for forming thinwalled parts.Orthogonal experiments were designed to fabricate single-channel multilayer samples with varying numbers of layers,and their forming quality was evaluated.The influence of printing current,forming speed,and contact pressure on the forming quality of the single-channel multilayer was analyzed.The optimal process parameters were obtained and the quality characterization of the experiment results was conducted.Results show that the printing current has the most significant influence on the forming quality of the single-channel multilayer.Under the optimal process parameters,the forming section is well fused and the surface is continuously smooth.The surface roughness of a single-channel 3-layer sample is 0.16μm,and the average Vickers hardness of cross section fusion zone is 317 HV,which lays a foundation for the subsequent use of Joule heat additive manufacturing technique to form thinwall parts.
基金supported by the National Natural Science Foundation of China(Grant No.52274177)Science and Technology Research Program of Chongqing Municipal Education Commission(Grant No.KJZD-K202401501)+1 种基金Chongqing Graduate Student Research Innovation Program(Grant No.CYS240800)The Science and Technology Innovation Project for Graduate Students of Chongqing University of Science and Technology(Grant No.YKJCX2420702).
文摘Urban growth has promoted the use of underground spaces,where explosion accidents can be catastrophic.In this study,we investigated the effect of placing flexible construction in front of rigid obstacles on methane explosion protection by using an experimental platform and adjusting the blockage rate and spacing of the obstacles.It aims to reduce the risk of gas explosions in urban underground spaces.The results of the study show that the flame propagation peak speed and peak overpressure are reduced with the decrease in the blocking rate of the flexible obstacle when the blocking rate of the flexible obstacle is less than or equal to the blocking rate of the rigid obstacle,with the decrease in the spacing,the better the protection effect of the methane explosion.When the blockage rate of the flexible obstacle is greater than the blockage rate of the rigid obstacle and spacing is less than the height of the flexible obstacle,rigid and flexible obstacles are connected as a whole,increasing the strength of the explosion.This study can provide a theoretical basis and scientific guidance for optimizing rigid and flexible object hybrid layouts and methane explosion protection technology in urban underground spaces.
基金the financial support from National Natural Science Foundation of China(Grant No.52378488)Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX22_0222)。
文摘The gas explosion in residential building has always been a highly concerned problem.Explosions in homogeneous mixtures have been extensively studied.However,mixtures are often inhomogeneous in the practical scenarios due to the differences in the densities of methane and air.In order to investigate the effects of gas explosions in inhomogeneous mixtures,experimental studies involving gas leakage and explosion are conducted in a full-scale residential building to reproduce the process of gas explosion.By fitting the dimensionless buoyancy as a function of dimensionless height and dimensionless time,a distribution model of gas in large-scale spaces is established,and the mechanism of inhomogeneous distribution of methane is also be revealed.Furthermore,the stratified reconstruction method(SRM)is introduced for efficiently setting up inhomogeneous concentration fields in FLACS.The simulation results highlight that for the internal overpressure,the distribution of methane has no effect on the first overpressure peak(ΔP1),while it significantly influences the subsequent overpressure peak(ΔP2),and the maximum difference between the overpressure of homogeneous and inhomogeneous distribution is174.3%.Moreover,the initial concentration distribution also has a certain impact on the external overpressure.
基金funded by the Research on Intelligent Mining Geological Model and Ventilation Model for Extremely Thin Coal Seam in Heilongjiang Province,China(2021ZXJ02A03)the Demonstration of Intelligent Mining for Comprehensive Mining Face in Extremely Thin Coal Seam in Heilongjiang Province,China(2021ZXJ02A04)the Natural Science Foundation of Heilongjiang Province,China(LH2024E112).
文摘Coal dust explosions are severe safety accidents in coal mine production,posing significant threats to life and property.Predicting the maximum explosion pressure(Pm)of coal dust using deep learning models can effectively assess potential risks and provide a scientific basis for preventing coal dust explosions.In this study,a 20-L explosion sphere apparatus was used to test the maximum explosion pressure of coal dust under seven different particle sizes and ten mass concentrations(Cdust),resulting in a dataset of 70 experimental groups.Through Spearman correlation analysis and random forest feature selection methods,particle size(D_(10),D_(20),D_(50))and mass concentration(Cdust)were identified as critical feature parameters from the ten initial parameters of the coal dust samples.Based on this,a hybrid Long Short-Term Memory(LSTM)network model incorporating a Multi-Head Attention Mechanism and the Sparrow Search Algorithm(SSA)was proposed to predict the maximum explosion pressure of coal dust.The results demonstrate that the SSA-LSTM-Multi-Head Attention model excels in predicting the maximum explosion pressure of coal dust.The four evaluation metrics indicate that the model achieved a coefficient of determination(R^(2)),root mean square error(RMSE),mean absolute percentage error(MAPE),and mean absolute error(MAE)of 0.9841,0.0030,0.0074,and 0.0049,respectively,in the training set.In the testing set,these values were 0.9743,0.0087,0.0108,and 0.0069,respectively.Compared to artificial neural networks(ANN),random forest(RF),support vector machines(SVM),particle swarm optimized-SVM(PSO-SVM)neural networks,and the traditional single-model LSTM,the SSA-LSTM-Multi-Head Attention model demonstrated superior generalization capability and prediction accuracy.The findings of this study not only advance the application of deep learning in coal dust explosion prediction but also provide robust technical support for the prevention and risk assessment of coal dust explosions.
文摘BACKGROUND Sagittal spinopelvic alignment(SSA)is essential for preserving a stable and effective upright posture and locomotion.Although alterations in the SSA are recognised to induce compensatory modifications in the pelvis,hips,and knees,the inverse relationship concerning knee pathology undergoing total knee arthroplasty(TKA)has been examined by a limited number of studies,yielding inconclusive results.AIM To generate evidence of the effect of TKA on the SSA from existing literature.METHODS Databases like PubMed,EMBASE,and Scopus were used to identify articles related to the“knee spine syndrome”phenomenon using a combination of subject terms and keywords such as“spinopelvic parameters”,“sagittal spinal balance”,and“total knee arthroplasty”were used with appropriate Boolean operators.Studies measuring the SSA following TKA were included,and research was conducted as per preferred reporting items for systematic review and metaanalysis guidelines.RESULTS A total of 475 participants had undergone TKA,and six studies measuring SSA were analysed.Following TKA,pelvic tilt was the only parameter that showed significant changes,while lumbar lordosis(LL),pelvic incidence,and sacral slope were non-significant,as evident from the forest plots.CONCLUSION The body's sagittal alignment is a complex balance between pelvic,spine,and lower extremity parameters.TKA,while having the potential to correct the flexion contracture,can also correct it.Still,the primary SSA for spinal pathology,i.e.,LL,may not be corrected in patients with co-existent spinal degenerative disease.
基金the financial support of the Shanxi Fire&Explosion-Proofing Safety Engineering and Technology Research Center,North University of China。
文摘RDX/Al mixtures are widely utilized in energetic materials,yet their hybrid dust generated during production and application poses potential explosion hazards.Moreover,the synergistic explosion mechanisms remain poorly understood,particularly at varying dust concentrations.This study systematically investigates the effects of different aluminum powder mass percentages and dust concentrations(300 g/m^(3),600 g/m^(3),900 g/m^(3))on RDX dust explosion severity,flame propagation behavior,and gaseous products.The results indicate that the maximum explosion pressure peaks at 35%RDX,65%RDX,and 80%RDX at 300 g/m^(3),600 g/m^(3),and 900 g/m^(3),respectively.Concurrently,the time for the flame to propagate to the wall(t1)reaches minimum values of 34.8 ms,25.66 ms,and 23.93 ms.The maximum rate of pressure rise is observed for pure RDX at 900 g/m^(3).Aluminum powder enhances flame propagation velocity and combustion duration,as validated by the flame propagation system.Overall,the concentrations of carbon oxides(CO+CO_(2))decrease significantly with increasing aluminum mass percentage.At 20%RDX,the concentrations decreased by 51.64%,72.31%,and 79.55%compared to pure RDX at 300 g/m^(3),600 g/m^(3),and 900 g/m^(3),respectively.Notably,N_(2)O concentration only at 300 g/m^(3)showed such a trend.It rises first and then falls at 35%RDX at 600 g/m^(3)and 900 g/m^(3).These findings elucidate the synergistic explosion mechanisms and provide critical guidelines for safe production and handling.
