Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effectiv...Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effective defense planning and interception strategies.In recent years,HGV trajectory prediction methods based on deep learning have the great potential to significantly enhance prediction accuracy and efficiency.However,it's still challenging to strike a balance between improving prediction performance and reducing computation costs of the deep learning trajectory prediction models.To solve this problem,we propose a new deep learning framework(FECA-LSMN)for efficient HGV trajectory prediction.The model first uses a Frequency Enhanced Channel Attention(FECA)module to facilitate the fusion of different HGV trajectory features,and then subsequently employs a Light Sampling-oriented Multi-Layer Perceptron Network(LSMN)based on simple MLP-based structures to extract long/shortterm HGV trajectory features for accurate trajectory prediction.Also,we employ a new data normalization method called reversible instance normalization(RevIN)to enhance the prediction accuracy and training stability of the network.Compared to other popular trajectory prediction models based on LSTM,GRU and Transformer,our FECA-LSMN model achieves leading or comparable performance in terms of RMSE,MAE and MAPE metrics while demonstrating notably faster computation time.The ablation experiments show that the incorporation of the FECA module significantly improves the prediction performance of the network.The RevIN data normalization technique outperforms traditional min-max normalization as well.展开更多
The afterburning of TNT and structural constraints in confined spaces significantly amplify the blast load,leading to severe structural damage. This study investigates the mechanisms underlying the enhanced dynamic re...The afterburning of TNT and structural constraints in confined spaces significantly amplify the blast load,leading to severe structural damage. This study investigates the mechanisms underlying the enhanced dynamic response of reinforced concrete blast doors with four-sided restraints in confined space. Explosion tests with TNT charges ranging from 0.15 kg to 0.4 kg were conducted in a confined space,capturing overpressure loads and the dynamic response of the blast door. An internal explosion model incorporating the afterburning effect was developed using LS-DYNA software and validated against experimental data. The results reveal that the TNT afterburning effect amplifies both the initial peak overpressure and the quasi-static overpressure, resulting in increased deformation of the blast door.Within the 0.15-0.4 kg charge range, the initial overpressure peak and quasi-static overpressure increased by an average of 1.79 times and 2.21 times, respectively. Additionally, the afterburning effect enhanced the blast door's deflection by 177%. Compared to open-space scenarios, the cumulative deflection of the blast door due to repeated shock wave impacts is significantly greater in confined spaces. Furthermore, the quasi-static pressure arising from the structural constraints sustains the blast door's deflection at a high level.展开更多
Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a gro...Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.展开更多
A series of ballistic experiments were performed to investigate the damage behavior of high velocity reactive material projectiles(RMPs) impacting liquid-filled tanks,and the corresponding hydrodynamic ram(HRAM) was s...A series of ballistic experiments were performed to investigate the damage behavior of high velocity reactive material projectiles(RMPs) impacting liquid-filled tanks,and the corresponding hydrodynamic ram(HRAM) was studied in detail.PTFE/Al/W RMPs with steel-like and aluminum-like densities were prepared by a pressing/sintering process.The projectiles impacted a liquid-filled steel tank with front aluminum panel at approximately 1250 m/s.The corresponding cavity evolution characteristics and HRAM pressure were recorded by high-speed camera and pressure acquisition system,and further compared to those of steel and aluminum projectiles.Significantly different from the conical cavity formed by the inert metal projectile,the cavity formed by the RMP appeared as an ellipsoid with a conical front.The RMPs were demonstrated to enhance the radial growth velocity of cavity,the global HRAM pressure amplitude and the front panel damage,indicating the enhanced HRAM and structural damage behavior.Furthermore,combining the impact-induced fragmentation and deflagration characteristics,the cavity evolution of RMPs under the combined effect of kinetic energy impact and chemical energy release was analyzed.The mechanism of enhanced HRAM pressure induced by the RMPs was further revealed based on the theoretical model of the initial impact wave and the impulse analysis.Finally,the linear correlation between the deformation-thickness ratio and the non-dimensional impulse for the front panel was obtained and analyzed.It was determined that the enhanced near-field impulse induced by the RMPs was the dominant reason for the enhanced structural damage behavior.展开更多
Compared with PELE with inert fillings such as polyethylene and nylon,reactive PELE(RPELE)shows excellent damage effects when impacting concrete targets due to the filling deflagration reaction.In present work,an anal...Compared with PELE with inert fillings such as polyethylene and nylon,reactive PELE(RPELE)shows excellent damage effects when impacting concrete targets due to the filling deflagration reaction.In present work,an analytical model describing the jacket deformation and concrete target damage impacted by RPELE was presented,in which the radial rarefaction and filling deflagration reaction were considered.The impact tests of RPELE on concrete target in the 592-1012 m/s were carried out to verify the analytical model.Based on the analytical model,the angle-length evolution mechanism of the jacket bending-curling deformation was revealed,and the concrete target damage was further analyzed.One can find out that the average prediction errors of the front crater,opening and back crater are 6.8%,8.5%and 7.1%,respectively.Moreover,the effects of radial rarefaction and deflagration were discussed.It was found that the neglect of radial rarefaction overestimates the jacket deformation and concrete target damage,while the deflagration reaction of filling increases the diameter of the front crater,opening and back crater by 25.4%,24.3%and 31.1%,respectively.The research provides a valuable reference for understanding and predicting the jacket deformation and concrete target damage impacted by RPELE.展开更多
Enhanced damage to the full-filled fuel tank,impacted by the cold pressed and sintered PTFE/Al/W reactive material projectile(RMP)with a density of 7.8 g/cm3,is investigated experimentally and theoretically.The fuel t...Enhanced damage to the full-filled fuel tank,impacted by the cold pressed and sintered PTFE/Al/W reactive material projectile(RMP)with a density of 7.8 g/cm3,is investigated experimentally and theoretically.The fuel tank is a rectangular structure,welded by six pieces of 2024 aluminum plate with a thickness of 6 mm,and filled with RP-3 aviation kerosene.Experimental results show that the kerosene is ignited by the RMP impact at a velocity above 1062 m/s,and a novel interior ignition phenomenon which is closely related to the rupture effect of the fuel tank is observed.However,the traditional steel projectile with the same mass and dimension requires a velocity up to 1649 m/s to ignite the kerosene.Based on the experimental results,the radial pressure field is considered to be the main reason for the shear failure of weld.For mechanism considerations,the chemical energy released by the RMP enhances the hydrodynamic ram(HRAM)effect and provides additional ignition sources inside the fuel tank,thereby enhancing both rupture and ignition effects.Moreover,to further understand the enhanced ignition effect of RMP,the reactive debris temperature inside the kerosene is analyzed theoretically.The initiated reactive debris with high temperature provides effective interior ignition sources to ignite the kerosene,resulting in the enhanced ignition of the kerosene.展开更多
In this review, excerpts from the literature of thermobaric(TBX) and enhanced blast explosives(EBX) that are concentrated on studies that include their compositions, properties, reactive metal components, modeling and...In this review, excerpts from the literature of thermobaric(TBX) and enhanced blast explosives(EBX) that are concentrated on studies that include their compositions, properties, reactive metal components, modeling and computations are presented.展开更多
The present study proposed an enhanced cuckoo search(ECS) algorithm combined with artificial neural network(ANN) as the surrogate model to solve structural reliability problems. In order to enhance the accuracy and co...The present study proposed an enhanced cuckoo search(ECS) algorithm combined with artificial neural network(ANN) as the surrogate model to solve structural reliability problems. In order to enhance the accuracy and convergence rate of the original cuckoo search(CS) algorithm, the main parameters namely, abandon probability of worst nests paand search step sizeα0 are dynamically adjusted via nonlinear control equations. In addition, a global-best guided equation incorporating the information of global best nest is introduced to the ECS to enhance its exploitation. Then, the proposed ECS is linked to the well-trained ANN model for structural reliability analysis. The computational capability of the proposed algorithm is validated using five typical structural reliability problems and an engineering application. The comparison results show the efficiency and accuracy of the proposed algorithm.展开更多
This paper presents an enhanced multi-baseline phase unwrapping algorithm by combining an unscented Kalman filter with an enhanced joint phase gradient estimator based on the amended matrix pencil model, and an optima...This paper presents an enhanced multi-baseline phase unwrapping algorithm by combining an unscented Kalman filter with an enhanced joint phase gradient estimator based on the amended matrix pencil model, and an optimal path-following strategy based on phase quality estimate function. The enhanced joint phase gradient estimator can accurately and effectively extract the phase gradient information of wrapped pixels from noisy interferograms, which greatly increases the performances of the proposed method. The optimal path-following strategy ensures that the proposed algorithm simultaneously performs noise suppression and phase unwrapping along the pixels with high-reliance to the pixels with low-reliance. Accordingly, the proposed algorithm can be predicted to obtain better results, with respect to some other algorithms, as will be demonstrated by the results obtained from synthetic data.展开更多
Oxy fuel combustion and conventional cycle(currently working cycle) in Kazeroon plant are modeled using commercial thermodynamic modeling software. Economic evaluation of the two models regarding the resources of tran...Oxy fuel combustion and conventional cycle(currently working cycle) in Kazeroon plant are modeled using commercial thermodynamic modeling software. Economic evaluation of the two models regarding the resources of transport and injection of carbon dioxide into oil fields at Gachsaran for enhanced oil recovery in the various oil price indices is conducted and indices net present value(NPV) and internal rate of return on investment(IRR) are calculated. The results of the two models reveal that gross efficiency of the oxy fuel cycle is more than reference cycle(62% compared to 49.03%), but the net efficiency is less(41.85% compared to 47.92%) because of the high-energy consumption of the components, particularly air separation unit(ASU) in the oxy fuel cycle. In this model, pure carbon dioxide with pressure of 20×105 Pa and purity of 96.84% was captured. NOX emissions also decrease by 4289.7 tons per year due to separation of nitrogen in ASU. In this model, none of the components of oxy fuel cycle is a major engineering challenge. With increasing oil price, economic justification of oxy fuel combustion model increases. With the price of oil at $ 80 per barrel in mind and $ 31 per ton fines for emissions of carbon dioxide in the atmosphere, IRR is the same for both models.展开更多
Enhanced boiling experiments of two different enhanced structures were carried out in a thermosyphon loop evaporator chamber. One was micro-columns array structure (MCAS), which was fabricated on copper plate surface ...Enhanced boiling experiments of two different enhanced structures were carried out in a thermosyphon loop evaporator chamber. One was micro-columns array structure (MCAS), which was fabricated on copper plate surface with interaction high speed wire electrode discharge machining (HS-WEDM). The other was the ramification of MCAS, named micro-column-array and sintered-copper compound structure (MSCS), which was fabricated with sintered method on micro-column array structure. Considering the wall superheat and critical heat flux (CHF), comparisons were made between them. The results show that both MCAS and MSCS can enhance the boiling heat transfer. It is also found that the enhanced boiling heat transfer ability of MSCS is changed obviously while the porosity of the sintered copper layer is changed.展开更多
Recently,thousands of SSR and now SNP markers have been discovered in cotton.Each of these markers provides a valuable molecular tool applying genetic and genomic research to cotton improvement.Cotton DNA marker datab...Recently,thousands of SSR and now SNP markers have been discovered in cotton.Each of these markers provides a valuable molecular tool applying genetic and genomic research to cotton improvement.Cotton DNA marker database(CMD) continues to serve as a molecular marker resource for展开更多
The structural evolution and optical characterization of hydrogenated silicon(Si:H) thin films obtained by conventional radio frequency(RF) plasma enhanced chemical vapor deposition(PECVD) through decomposition of sil...The structural evolution and optical characterization of hydrogenated silicon(Si:H) thin films obtained by conventional radio frequency(RF) plasma enhanced chemical vapor deposition(PECVD) through decomposition of silane diluted with argon were studied by X-ray diffractometry(XRD),Fourier transform infrared(FTIR) spectroscopy,Raman spectroscopy,transmission electron microscopy(TEM),and ultraviolet and visible(UV-vis) spectroscopy,respectively.The influence of argon dilution on the optical properties of the thin films was also studied.It is found that argon as dilution gas plays a significant role in the growth of nano-crystal grains and amorphous network in Si:H thin films.The structural evolution of the thin films with different argon dilution ratios is observed and it is suggested that argon plasma leads to the nanocrystallization in the thin films during the deposition process.The nanocrystallization initiating at a relatively low dilution ratio is also observed.With the increase of argon portion in the mixed precursor gases,nano-crystal grains in the thin films evolve regularly.The structural evolution is explained by a proposed model based on the energy exchange between the argon plasma constituted with Ar* and Ar+ radicals and the growth regions of the thin films.It is observed that both the absorption of UV-vis light and the optical gap decrease with the increase of dilution ratio.展开更多
Flammable ionic liquids exhibit high conductivity and a broad electrochemical window,enabling the generation of combustible gases for combustion via electrochemical decomposition and thermal decomposition.This charact...Flammable ionic liquids exhibit high conductivity and a broad electrochemical window,enabling the generation of combustible gases for combustion via electrochemical decomposition and thermal decomposition.This characteristic holds significant implications in the realm of novel satellite propulsion.Introducing a fraction of the electrical energy into energetic ionic liquid fuels,the thermal decomposition process is facilitated by reducing the apparent activation energy required,and electrical energy can trigger the electrochemical decomposition of ionic liquids,presenting a promising approach to enhance combustion efficiency and energy release.This study applied an external voltage during the thermal decomposition of 1-ethyl-3-methylimidazole nitrate([EMIm]NO_(3)),revealing the effective alteration of the activation energy of[EMIm]NO_(3).The pyrolysis,electrochemical decomposition,and electron assisted enhancement products were identified through Thermogravimetry-Differential scanning calorimetry-Fourier transform infrared-Mass spectrometry(TG-DSC-FTIR-MS)and gas chromatography(GC)analyses,elucidating the degradation mechanism of[EMIm]NO_(3).Furthermore,an external voltage was introduced during the combustion of[EMIm]NO_(3),demonstrating the impact of voltage on the combustion process.展开更多
In this paper,a fusion model based on a long short-term memory(LSTM)neural network and enhanced search ant colony optimization(ENSACO)is proposed to predict the power degradation trend of proton exchange membrane fuel...In this paper,a fusion model based on a long short-term memory(LSTM)neural network and enhanced search ant colony optimization(ENSACO)is proposed to predict the power degradation trend of proton exchange membrane fuel cells(PEMFC).Firstly,the Shapley additive explanations(SHAP)value method is used to select external characteristic parameters with high contributions as inputs for the data-driven approach.Next,a novel swarm optimization algorithm,the enhanced search ant colony optimization,is proposed.This algorithm improves the ant colony optimization(ACO)algorithm based on a reinforcement factor to avoid premature convergence and accelerate the convergence speed.Comparative experiments are set up to compare the performance differences between particle swarm optimization(PSO),ACO,and ENSACO.Finally,a data-driven method based on ENSACO-LSTM is proposed to predict the power degradation trend of PEMFCs.And actual aging data is used to validate the method.The results show that,within a limited number of iterations,the optimization capability of ENSACO is significantly stronger than that of PSO and ACO.Additionally,the prediction accuracy of the ENSACO-LSTM method is greatly improved,with an average increase of approximately 50.58%compared to LSTM,PSO-LSTM,and ACO-LSTM.展开更多
This study was designed to enhance the soft clayey soil treatment effects using an innovative mechanochemically activated geopolymer(GP)through the optimized inclusion of nano-metakaolin(NM)and polypropylene fiber.The...This study was designed to enhance the soft clayey soil treatment effects using an innovative mechanochemically activated geopolymer(GP)through the optimized inclusion of nano-metakaolin(NM)and polypropylene fiber.The study also investigated the possible improvements in the binding ability of GP stabilization under different curing regimes.To this end,binders including lime alone,LG(slag-based geopolymer),LGNM(nano-modified LG with NM)and LGNMF(LGNM/fiber)mixture were separately added to soft soil samples.The fabricated composites were then subjected to a set of macro and micro level tests.The results indicated that,adding LG binary with a 20%NM replacement can lead to a significant increase(by nearly 21 times)in soil strength and a remarkable decline(about 70%)in the compression index.In fact,NM can play a great role in accelerating the rate of hydration reactions and forming a densely packed fabric,which staggeringly improve the soil hydromechanical attributes.It was also observed that raising the curing temperature will effectively augment the polymerization kinetics,leading to a substantial increase(~2 times)in the soil solidification process.However,the stabilized composites containing NM may reveal a brittle nature under more intense stress.Such a potential drawback seems to be resolved by the integration of fibers within the matrix.LGNM combined with fiber would boost(≥10 times)the energy absorption capacity of the soil,notably enhancing its residual strength.Overall,LGNMF may not only feature a broader range of benefits(inc.economic,technical,environmental)compared to traditional binders but also promote the ductility of the GP materials.展开更多
DNAN-based insensitive melt-cast explosives have been widely utilized in insensitive munition in recent years. When constrained DNAN-based melt-cast explosives are ignited under thermal stimulation, the base explosive...DNAN-based insensitive melt-cast explosives have been widely utilized in insensitive munition in recent years. When constrained DNAN-based melt-cast explosives are ignited under thermal stimulation, the base explosive exists in a molten liquid state, where high-temperature gases expand and react in the form of bubble clouds within the liquid explosive;this process is distinctly different from the dynamic crack propagation process observed in the case of solid explosives. In this study, a control model for the reaction evolution of burning-bubble clouds was established to describe the reaction process and quantify the reaction violence of DNAN-based melt-cast explosives, considering the size distribution and activation mechanism of the burning-bubble clouds. The feasibility of the model was verified through experimental results. The results revealed that under geometrically similar conditions, with identical confinement strength and aspect ratio, larger charge structures led to extended initial gas flow and surface burning processes, resulting in greater reaction equivalence and violence at the casing fracture.Under constant charge volume and size, a stronger casing confinement accelerated self-enhanced burning, increasing the internal pressure, reaction degree, and reaction violence. Under a constant casing thickness and radius, higher aspect ratios led to a greater reaction violence at the casing fracture.Moreover, under a constant charge volume and casing thickness, higher aspect ratios resulted in a higher internal pressure, increased reaction degree, and greater reaction violence at the casing fracture. Further,larger ullage volumes extended the reaction evolution time and increased the reaction violence under constant casing dimensions. Through a matching design of the opening threshold of the pressure relief holes and the relief structure area, a stable burning reaction could be maintained until completion,thereby achieving a control of the reaction violence. The proposed model could effectively reflect the effects of the intrinsic burning rate, casing confinement strength, charge size, ullage volume, and pressure relief structure on the reaction evolution process and reaction violence, providing a theoretical method for the thermal safety design and reaction violence evaluation of melt-cast explosives.展开更多
Low-light image enhancement is one of the most active research areas in the field of computer vision in recent years.In the low-light image enhancement process,loss of image details and increase in noise occur inevita...Low-light image enhancement is one of the most active research areas in the field of computer vision in recent years.In the low-light image enhancement process,loss of image details and increase in noise occur inevitably,influencing the quality of enhanced images.To alleviate this problem,a low-light image enhancement model called RetinexNet model based on Retinex theory was proposed in this study.The model was composed of an image decomposition module and a brightness enhancement module.In the decomposition module,a convolutional block attention module(CBAM)was incorporated to enhance feature representation capacity of the network,focusing on crucial features and suppressing irrelevant ones.A multifeature fusion denoising module was designed within the brightness enhancement module,circumventing the issue of feature loss during downsampling.The proposed model outperforms the existing algorithms in terms of PSNR and SSIM metrics on the publicly available datasets LOL and MIT-Adobe FiveK,as well as gives superior results in terms of NIQE metrics on the publicly available dataset LIME.展开更多
文摘Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effective defense planning and interception strategies.In recent years,HGV trajectory prediction methods based on deep learning have the great potential to significantly enhance prediction accuracy and efficiency.However,it's still challenging to strike a balance between improving prediction performance and reducing computation costs of the deep learning trajectory prediction models.To solve this problem,we propose a new deep learning framework(FECA-LSMN)for efficient HGV trajectory prediction.The model first uses a Frequency Enhanced Channel Attention(FECA)module to facilitate the fusion of different HGV trajectory features,and then subsequently employs a Light Sampling-oriented Multi-Layer Perceptron Network(LSMN)based on simple MLP-based structures to extract long/shortterm HGV trajectory features for accurate trajectory prediction.Also,we employ a new data normalization method called reversible instance normalization(RevIN)to enhance the prediction accuracy and training stability of the network.Compared to other popular trajectory prediction models based on LSTM,GRU and Transformer,our FECA-LSMN model achieves leading or comparable performance in terms of RMSE,MAE and MAPE metrics while demonstrating notably faster computation time.The ablation experiments show that the incorporation of the FECA module significantly improves the prediction performance of the network.The RevIN data normalization technique outperforms traditional min-max normalization as well.
基金financially supported by the National Natural Science Foundation of China (Grant No. 52278504)the Natural Science Foundation of Jiangsu Province (Grant No. BK20220141)。
文摘The afterburning of TNT and structural constraints in confined spaces significantly amplify the blast load,leading to severe structural damage. This study investigates the mechanisms underlying the enhanced dynamic response of reinforced concrete blast doors with four-sided restraints in confined space. Explosion tests with TNT charges ranging from 0.15 kg to 0.4 kg were conducted in a confined space,capturing overpressure loads and the dynamic response of the blast door. An internal explosion model incorporating the afterburning effect was developed using LS-DYNA software and validated against experimental data. The results reveal that the TNT afterburning effect amplifies both the initial peak overpressure and the quasi-static overpressure, resulting in increased deformation of the blast door.Within the 0.15-0.4 kg charge range, the initial overpressure peak and quasi-static overpressure increased by an average of 1.79 times and 2.21 times, respectively. Additionally, the afterburning effect enhanced the blast door's deflection by 177%. Compared to open-space scenarios, the cumulative deflection of the blast door due to repeated shock wave impacts is significantly greater in confined spaces. Furthermore, the quasi-static pressure arising from the structural constraints sustains the blast door's deflection at a high level.
文摘Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.
基金supported by the Youth Foundation of State Key Laboratory of Explosion Science and Technology (Grant No.QNKT22-12)the State Key Program of National Natural Science Foundation of China (Grant No.12132003)。
文摘A series of ballistic experiments were performed to investigate the damage behavior of high velocity reactive material projectiles(RMPs) impacting liquid-filled tanks,and the corresponding hydrodynamic ram(HRAM) was studied in detail.PTFE/Al/W RMPs with steel-like and aluminum-like densities were prepared by a pressing/sintering process.The projectiles impacted a liquid-filled steel tank with front aluminum panel at approximately 1250 m/s.The corresponding cavity evolution characteristics and HRAM pressure were recorded by high-speed camera and pressure acquisition system,and further compared to those of steel and aluminum projectiles.Significantly different from the conical cavity formed by the inert metal projectile,the cavity formed by the RMP appeared as an ellipsoid with a conical front.The RMPs were demonstrated to enhance the radial growth velocity of cavity,the global HRAM pressure amplitude and the front panel damage,indicating the enhanced HRAM and structural damage behavior.Furthermore,combining the impact-induced fragmentation and deflagration characteristics,the cavity evolution of RMPs under the combined effect of kinetic energy impact and chemical energy release was analyzed.The mechanism of enhanced HRAM pressure induced by the RMPs was further revealed based on the theoretical model of the initial impact wave and the impulse analysis.Finally,the linear correlation between the deformation-thickness ratio and the non-dimensional impulse for the front panel was obtained and analyzed.It was determined that the enhanced near-field impulse induced by the RMPs was the dominant reason for the enhanced structural damage behavior.
基金funding from the National Natural Science Foundation of China(Grant Nos.12132003 and 12302460)。
文摘Compared with PELE with inert fillings such as polyethylene and nylon,reactive PELE(RPELE)shows excellent damage effects when impacting concrete targets due to the filling deflagration reaction.In present work,an analytical model describing the jacket deformation and concrete target damage impacted by RPELE was presented,in which the radial rarefaction and filling deflagration reaction were considered.The impact tests of RPELE on concrete target in the 592-1012 m/s were carried out to verify the analytical model.Based on the analytical model,the angle-length evolution mechanism of the jacket bending-curling deformation was revealed,and the concrete target damage was further analyzed.One can find out that the average prediction errors of the front crater,opening and back crater are 6.8%,8.5%and 7.1%,respectively.Moreover,the effects of radial rarefaction and deflagration were discussed.It was found that the neglect of radial rarefaction overestimates the jacket deformation and concrete target damage,while the deflagration reaction of filling increases the diameter of the front crater,opening and back crater by 25.4%,24.3%and 31.1%,respectively.The research provides a valuable reference for understanding and predicting the jacket deformation and concrete target damage impacted by RPELE.
文摘Enhanced damage to the full-filled fuel tank,impacted by the cold pressed and sintered PTFE/Al/W reactive material projectile(RMP)with a density of 7.8 g/cm3,is investigated experimentally and theoretically.The fuel tank is a rectangular structure,welded by six pieces of 2024 aluminum plate with a thickness of 6 mm,and filled with RP-3 aviation kerosene.Experimental results show that the kerosene is ignited by the RMP impact at a velocity above 1062 m/s,and a novel interior ignition phenomenon which is closely related to the rupture effect of the fuel tank is observed.However,the traditional steel projectile with the same mass and dimension requires a velocity up to 1649 m/s to ignite the kerosene.Based on the experimental results,the radial pressure field is considered to be the main reason for the shear failure of weld.For mechanism considerations,the chemical energy released by the RMP enhances the hydrodynamic ram(HRAM)effect and provides additional ignition sources inside the fuel tank,thereby enhancing both rupture and ignition effects.Moreover,to further understand the enhanced ignition effect of RMP,the reactive debris temperature inside the kerosene is analyzed theoretically.The initiated reactive debris with high temperature provides effective interior ignition sources to ignite the kerosene,resulting in the enhanced ignition of the kerosene.
文摘In this review, excerpts from the literature of thermobaric(TBX) and enhanced blast explosives(EBX) that are concentrated on studies that include their compositions, properties, reactive metal components, modeling and computations are presented.
基金supported by the National Natural Science Foundation of China(51875465)
文摘The present study proposed an enhanced cuckoo search(ECS) algorithm combined with artificial neural network(ANN) as the surrogate model to solve structural reliability problems. In order to enhance the accuracy and convergence rate of the original cuckoo search(CS) algorithm, the main parameters namely, abandon probability of worst nests paand search step sizeα0 are dynamically adjusted via nonlinear control equations. In addition, a global-best guided equation incorporating the information of global best nest is introduced to the ECS to enhance its exploitation. Then, the proposed ECS is linked to the well-trained ANN model for structural reliability analysis. The computational capability of the proposed algorithm is validated using five typical structural reliability problems and an engineering application. The comparison results show the efficiency and accuracy of the proposed algorithm.
基金supported by the National Natural Science Foundation of China(4120147961261033+2 种基金61461011)the Guangxi Natural Science Foundation(2014GXNSFBA118273)the Dean Project of Guangxi Key Laboratory of Wireless Broadband Communication and Signal Processing(GXKL061503)
文摘This paper presents an enhanced multi-baseline phase unwrapping algorithm by combining an unscented Kalman filter with an enhanced joint phase gradient estimator based on the amended matrix pencil model, and an optimal path-following strategy based on phase quality estimate function. The enhanced joint phase gradient estimator can accurately and effectively extract the phase gradient information of wrapped pixels from noisy interferograms, which greatly increases the performances of the proposed method. The optimal path-following strategy ensures that the proposed algorithm simultaneously performs noise suppression and phase unwrapping along the pixels with high-reliance to the pixels with low-reliance. Accordingly, the proposed algorithm can be predicted to obtain better results, with respect to some other algorithms, as will be demonstrated by the results obtained from synthetic data.
文摘Oxy fuel combustion and conventional cycle(currently working cycle) in Kazeroon plant are modeled using commercial thermodynamic modeling software. Economic evaluation of the two models regarding the resources of transport and injection of carbon dioxide into oil fields at Gachsaran for enhanced oil recovery in the various oil price indices is conducted and indices net present value(NPV) and internal rate of return on investment(IRR) are calculated. The results of the two models reveal that gross efficiency of the oxy fuel cycle is more than reference cycle(62% compared to 49.03%), but the net efficiency is less(41.85% compared to 47.92%) because of the high-energy consumption of the components, particularly air separation unit(ASU) in the oxy fuel cycle. In this model, pure carbon dioxide with pressure of 20×105 Pa and purity of 96.84% was captured. NOX emissions also decrease by 4289.7 tons per year due to separation of nitrogen in ASU. In this model, none of the components of oxy fuel cycle is a major engineering challenge. With increasing oil price, economic justification of oxy fuel combustion model increases. With the price of oil at $ 80 per barrel in mind and $ 31 per ton fines for emissions of carbon dioxide in the atmosphere, IRR is the same for both models.
基金Projects(50605023 50436010) supported by the National Natural Science Foundation of China
文摘Enhanced boiling experiments of two different enhanced structures were carried out in a thermosyphon loop evaporator chamber. One was micro-columns array structure (MCAS), which was fabricated on copper plate surface with interaction high speed wire electrode discharge machining (HS-WEDM). The other was the ramification of MCAS, named micro-column-array and sintered-copper compound structure (MSCS), which was fabricated with sintered method on micro-column array structure. Considering the wall superheat and critical heat flux (CHF), comparisons were made between them. The results show that both MCAS and MSCS can enhance the boiling heat transfer. It is also found that the enhanced boiling heat transfer ability of MSCS is changed obviously while the porosity of the sintered copper layer is changed.
文摘Recently,thousands of SSR and now SNP markers have been discovered in cotton.Each of these markers provides a valuable molecular tool applying genetic and genomic research to cotton improvement.Cotton DNA marker database(CMD) continues to serve as a molecular marker resource for
基金Project(60425101) supported by the National Outstanding Young Scientists Foundation of ChinaProject(06DZ0241) supported by the Science Foundation of General Armament Department of China
文摘The structural evolution and optical characterization of hydrogenated silicon(Si:H) thin films obtained by conventional radio frequency(RF) plasma enhanced chemical vapor deposition(PECVD) through decomposition of silane diluted with argon were studied by X-ray diffractometry(XRD),Fourier transform infrared(FTIR) spectroscopy,Raman spectroscopy,transmission electron microscopy(TEM),and ultraviolet and visible(UV-vis) spectroscopy,respectively.The influence of argon dilution on the optical properties of the thin films was also studied.It is found that argon as dilution gas plays a significant role in the growth of nano-crystal grains and amorphous network in Si:H thin films.The structural evolution of the thin films with different argon dilution ratios is observed and it is suggested that argon plasma leads to the nanocrystallization in the thin films during the deposition process.The nanocrystallization initiating at a relatively low dilution ratio is also observed.With the increase of argon portion in the mixed precursor gases,nano-crystal grains in the thin films evolve regularly.The structural evolution is explained by a proposed model based on the energy exchange between the argon plasma constituted with Ar* and Ar+ radicals and the growth regions of the thin films.It is observed that both the absorption of UV-vis light and the optical gap decrease with the increase of dilution ratio.
基金supported by the National Natural Science Foundation of China(Grant No.52206165)。
文摘Flammable ionic liquids exhibit high conductivity and a broad electrochemical window,enabling the generation of combustible gases for combustion via electrochemical decomposition and thermal decomposition.This characteristic holds significant implications in the realm of novel satellite propulsion.Introducing a fraction of the electrical energy into energetic ionic liquid fuels,the thermal decomposition process is facilitated by reducing the apparent activation energy required,and electrical energy can trigger the electrochemical decomposition of ionic liquids,presenting a promising approach to enhance combustion efficiency and energy release.This study applied an external voltage during the thermal decomposition of 1-ethyl-3-methylimidazole nitrate([EMIm]NO_(3)),revealing the effective alteration of the activation energy of[EMIm]NO_(3).The pyrolysis,electrochemical decomposition,and electron assisted enhancement products were identified through Thermogravimetry-Differential scanning calorimetry-Fourier transform infrared-Mass spectrometry(TG-DSC-FTIR-MS)and gas chromatography(GC)analyses,elucidating the degradation mechanism of[EMIm]NO_(3).Furthermore,an external voltage was introduced during the combustion of[EMIm]NO_(3),demonstrating the impact of voltage on the combustion process.
基金Supported by the Major Science and Technology Project of Jilin Province(20220301010GX)the International Scientific and Technological Cooperation(20240402071GH).
文摘In this paper,a fusion model based on a long short-term memory(LSTM)neural network and enhanced search ant colony optimization(ENSACO)is proposed to predict the power degradation trend of proton exchange membrane fuel cells(PEMFC).Firstly,the Shapley additive explanations(SHAP)value method is used to select external characteristic parameters with high contributions as inputs for the data-driven approach.Next,a novel swarm optimization algorithm,the enhanced search ant colony optimization,is proposed.This algorithm improves the ant colony optimization(ACO)algorithm based on a reinforcement factor to avoid premature convergence and accelerate the convergence speed.Comparative experiments are set up to compare the performance differences between particle swarm optimization(PSO),ACO,and ENSACO.Finally,a data-driven method based on ENSACO-LSTM is proposed to predict the power degradation trend of PEMFCs.And actual aging data is used to validate the method.The results show that,within a limited number of iterations,the optimization capability of ENSACO is significantly stronger than that of PSO and ACO.Additionally,the prediction accuracy of the ENSACO-LSTM method is greatly improved,with an average increase of approximately 50.58%compared to LSTM,PSO-LSTM,and ACO-LSTM.
文摘This study was designed to enhance the soft clayey soil treatment effects using an innovative mechanochemically activated geopolymer(GP)through the optimized inclusion of nano-metakaolin(NM)and polypropylene fiber.The study also investigated the possible improvements in the binding ability of GP stabilization under different curing regimes.To this end,binders including lime alone,LG(slag-based geopolymer),LGNM(nano-modified LG with NM)and LGNMF(LGNM/fiber)mixture were separately added to soft soil samples.The fabricated composites were then subjected to a set of macro and micro level tests.The results indicated that,adding LG binary with a 20%NM replacement can lead to a significant increase(by nearly 21 times)in soil strength and a remarkable decline(about 70%)in the compression index.In fact,NM can play a great role in accelerating the rate of hydration reactions and forming a densely packed fabric,which staggeringly improve the soil hydromechanical attributes.It was also observed that raising the curing temperature will effectively augment the polymerization kinetics,leading to a substantial increase(~2 times)in the soil solidification process.However,the stabilized composites containing NM may reveal a brittle nature under more intense stress.Such a potential drawback seems to be resolved by the integration of fibers within the matrix.LGNM combined with fiber would boost(≥10 times)the energy absorption capacity of the soil,notably enhancing its residual strength.Overall,LGNMF may not only feature a broader range of benefits(inc.economic,technical,environmental)compared to traditional binders but also promote the ductility of the GP materials.
基金supported by the National Natural Science Foundation of China (Grant No. 12002044)。
文摘DNAN-based insensitive melt-cast explosives have been widely utilized in insensitive munition in recent years. When constrained DNAN-based melt-cast explosives are ignited under thermal stimulation, the base explosive exists in a molten liquid state, where high-temperature gases expand and react in the form of bubble clouds within the liquid explosive;this process is distinctly different from the dynamic crack propagation process observed in the case of solid explosives. In this study, a control model for the reaction evolution of burning-bubble clouds was established to describe the reaction process and quantify the reaction violence of DNAN-based melt-cast explosives, considering the size distribution and activation mechanism of the burning-bubble clouds. The feasibility of the model was verified through experimental results. The results revealed that under geometrically similar conditions, with identical confinement strength and aspect ratio, larger charge structures led to extended initial gas flow and surface burning processes, resulting in greater reaction equivalence and violence at the casing fracture.Under constant charge volume and size, a stronger casing confinement accelerated self-enhanced burning, increasing the internal pressure, reaction degree, and reaction violence. Under a constant casing thickness and radius, higher aspect ratios led to a greater reaction violence at the casing fracture.Moreover, under a constant charge volume and casing thickness, higher aspect ratios resulted in a higher internal pressure, increased reaction degree, and greater reaction violence at the casing fracture. Further,larger ullage volumes extended the reaction evolution time and increased the reaction violence under constant casing dimensions. Through a matching design of the opening threshold of the pressure relief holes and the relief structure area, a stable burning reaction could be maintained until completion,thereby achieving a control of the reaction violence. The proposed model could effectively reflect the effects of the intrinsic burning rate, casing confinement strength, charge size, ullage volume, and pressure relief structure on the reaction evolution process and reaction violence, providing a theoretical method for the thermal safety design and reaction violence evaluation of melt-cast explosives.
文摘Low-light image enhancement is one of the most active research areas in the field of computer vision in recent years.In the low-light image enhancement process,loss of image details and increase in noise occur inevitably,influencing the quality of enhanced images.To alleviate this problem,a low-light image enhancement model called RetinexNet model based on Retinex theory was proposed in this study.The model was composed of an image decomposition module and a brightness enhancement module.In the decomposition module,a convolutional block attention module(CBAM)was incorporated to enhance feature representation capacity of the network,focusing on crucial features and suppressing irrelevant ones.A multifeature fusion denoising module was designed within the brightness enhancement module,circumventing the issue of feature loss during downsampling.The proposed model outperforms the existing algorithms in terms of PSNR and SSIM metrics on the publicly available datasets LOL and MIT-Adobe FiveK,as well as gives superior results in terms of NIQE metrics on the publicly available dataset LIME.
