Improving knowledge on the ability of bioengineering structures made of willow cuttings to enhance efficient and sustainable sediment trapping in marly gullies in the Southern French Alps under a mountainous Mediterra...Improving knowledge on the ability of bioengineering structures made of willow cuttings to enhance efficient and sustainable sediment trapping in marly gullies in the Southern French Alps under a mountainous Mediterranean climate, to decreasesediment trapped per experiment, the mean annual values reached 0.25, 0.14 and 0.08 m3 yr-1 in experiments C, A and B, respectively. Maximum values for one structure reached 1.94 m3 per year in experiment C. The significance of the volumes ofsediment yield at their outlets, is a key issue today for the international scientific community working in geosciences and ecology. This study therefore aims to assess three real-size experiments(A, B and C) carried out between 2003 and 2013 in this environment. A total of 157 bioengineering structures using purple and white willow(Salix purpurea and Salix incana)cuttings – which have been shown to resprout and survive more than 2 years after their installation,corresponding to brush layers with brush mats on wooden sills(BLM), 1.2 m wide and 2 m long,installed on the floors of 33 experimental marly gullies, were monitored. The results showed that sediment trapping occurred upstream of the vegetation barriers from the 1 st year onwards.Considering the depth of sediment trapped per experiment, the mean annual values reached 11.2 cm yr-1 after 3 years in experiment A, 7.7 cm yr-1 after 2–4 years in experiment C and 5.1 cm yr-1 after 5 years in experiment B. Occasionally, BLMs showed that they could trap up to 16 and 15 cm yr-1 in experiments A and C, respectively. Considering the volumes oftrapped sediment and the sustainability of sediment trapping are discussed, and rules for bioengineering strategies are proposed.展开更多
该文运用Dlib人脸检测模型与人脸检测模板匹配方法,通过计算EAR、MAR、pitch、yaw和roll参数,采用多阈值判定研究疲驾驶员疲劳状态,并将该算法在Raspberry Pi 5硬件平台实现,搭建疲劳驾驶检测预警系统,最后通过公开数据集验证该系统对...该文运用Dlib人脸检测模型与人脸检测模板匹配方法,通过计算EAR、MAR、pitch、yaw和roll参数,采用多阈值判定研究疲驾驶员疲劳状态,并将该算法在Raspberry Pi 5硬件平台实现,搭建疲劳驾驶检测预警系统,最后通过公开数据集验证该系统对于驾驶员面部疲劳状态检测及提醒的准确性和良好的系统性能。EAR、MAR、HPE 3种判断准则在公开数据集Drowsiness、YawDD及自制数据集上分别达到95.6%、96%与96%的平均正确率;在面部无遮挡的情况下,该系统实时帧率达到20 FPS,基本可实时对驾驶员疲劳状态作出相应提醒,同时具备较高的准确率。展开更多
Oxygen(O_(2))is essential for life support and rocket propulsion in Mars exploration missions,and in situ oxygen production from the Martian atmosphere is of profound scientific and engineering significance.In this ar...Oxygen(O_(2))is essential for life support and rocket propulsion in Mars exploration missions,and in situ oxygen production from the Martian atmosphere is of profound scientific and engineering significance.In this article,we propose a novel method for O_(2) production from the Martian atmosphere by using glow discharge ionization combined with a self-developed oxygen-permeable membrane(OPM).Experiments under simulated Martian atmospheric conditions examined parameter impacts on the O_(2) production rate and assessed the operating characteristics and glow discharge plasma tolerance of the OPM.Results indicate that(1)the proportion of O_(2) produced positively correlates with the ionization voltage under fixed discharge electrode spacing,pressure,and flow rate,reaching a maximum of 8.18%(saturating at 4600–5400 V);(2)O_(2) yield rises with the carbon dioxide(CO_(2))flow rate at a constant pressure,with the maximum value reaching 0.5 g/h;(3)titanium(Ti)and molybdenum(Mo)electrodes exhibit higher application potential under high voltage conditions;(4)the OPM operates at temperatures above 800℃ and shows few changes in the main body sections after 24 h of plasma tolerance testing.This study lays the foundation for future development of a mature Mars oxygen production prototype with lower energy consumption and higher efficiency.展开更多
This study investigates the uncertain dynamic characterization of hybrid composite plates by employing advanced machine-assisted finite element methodologies.Hybrid composites,widely used in aerospace,automotive,and s...This study investigates the uncertain dynamic characterization of hybrid composite plates by employing advanced machine-assisted finite element methodologies.Hybrid composites,widely used in aerospace,automotive,and structural applications,often face variability in material properties,geometric configurations,and manufacturing processes,leading to uncertainty in their dynamic response.To address this,three surrogate-based machine learning approaches like radial basis function(RBF),multivariate adaptive regression splines(MARS),and polynomial neural networks(PNN)are integrated with a finite element framework to efficiently capture the stochastic behavior of these plates.The research focuses on predicting the first three natural frequencies under material uncertainties,which are critical to ensuring structural reliability.Monte Carlo simulation(MCS)is used as a benchmark for generating probabilistic datasets,including mean values,standard deviations,and probability density functions.The surrogate models are then trained and validated against these datasets,enabling accurate representation of uncertainty with substantially fewer samples compared to conventionalMCS.Among the methods studied,the RBFmodel demonstrates superior performance,closely approximating MCS results with a reduced sample size,thereby achieving significant computational savings.The proposed framework not only reduces computational time and costs but also maintains high predictive accuracy,making it well-suited for complex engineering systems.Beyond free vibration analysis,the methodology can be extended to more sophisticated scenarios,such as forced vibration,damping effects,and nonlinear structural responses.Overall,this work presents a computationally efficient and robust approach for surrogate-based uncertainty quantification,advancing the analysis and design of hybrid composite structures under uncertainty.展开更多
The parachute deployment conditions during the terminal entry phase in Mars landing missions exhibit critical impact on landing precision.In this article,aiming at the requirements of safe parachute deployment and acc...The parachute deployment conditions during the terminal entry phase in Mars landing missions exhibit critical impact on landing precision.In this article,aiming at the requirements of safe parachute deployment and accurate landing,a multidimensional parachute deployment box for determining deployment condition during Mars landing was proposed.First,an extremerange optimization model was established,synthesizing the dynamics and constraints of both parachute descent and powered descent phases.Then,on the basis of the two-dimensional altitude-velocity deployment box,a multi-dimensional parachute deployment box characterized by altitude,velocity,flight-path angle,and extreme range was constructed through the integration of extreme range information.Furthermore,an evaluation index for landing precision was formulated and a deployment control logic was proposed for minimizing landing deviation.Finally,the proposed deployment box was simulated in a Mars landing mission.The results demonstrate that the proposed box effectively satisfies safe deployment and landing precision demands,eliminating the range-to-go error at the terminal of the entry phase.展开更多
Dear Editor,This letter proposes a convex optimization-based model predictive control(MPC)autonomous guidance method for the Mars ascent vehicle(MAV).We use the modified chebyshev-picard iteration(MCPI)to solve optimi...Dear Editor,This letter proposes a convex optimization-based model predictive control(MPC)autonomous guidance method for the Mars ascent vehicle(MAV).We use the modified chebyshev-picard iteration(MCPI)to solve optimization sub-problems within the MPC framework,eliminating the dynamic constraints in solving the optimal control problem and enhancing the convergence performance of the algorithm.Moreover,this method can repeatedly perform trajectory optimization calculations at a high frequency,achieving timely correction of the optimal control command.Numerical simulations demonstrate that the method can satisfy the requirements of rapid computation and reliability for the MAV system when considering uncertainties and perturbations.展开更多
Medically assisted reproduction(MAR)techniques are highly dependent on the sperm quantity and quality.Low sperm concentrations can be bypassed at least to some point by the usage of more sophisticated MAR techniques l...Medically assisted reproduction(MAR)techniques are highly dependent on the sperm quantity and quality.Low sperm concentrations can be bypassed at least to some point by the usage of more sophisticated MAR techniques like intracytoplasmic sperm injection(ICSI).Compared to this,disruptions in established indicators of sperm quality like motility or morphology pose greater challenges for the therapy of couple infertility.展开更多
基金Electricitéde France(EDF)Agence de l’eau Rh?ne+3 种基金Méditerranée et CorseRégion Provence-Alpes-Cote-d’Azurthe European Union("L’Europe s’engage en PACA avec le Fonds Européen de Développement Régional"FEDER program)the Ministère de l’environnement,de l’énergie et de la mer(MEEM)
文摘Improving knowledge on the ability of bioengineering structures made of willow cuttings to enhance efficient and sustainable sediment trapping in marly gullies in the Southern French Alps under a mountainous Mediterranean climate, to decreasesediment trapped per experiment, the mean annual values reached 0.25, 0.14 and 0.08 m3 yr-1 in experiments C, A and B, respectively. Maximum values for one structure reached 1.94 m3 per year in experiment C. The significance of the volumes ofsediment yield at their outlets, is a key issue today for the international scientific community working in geosciences and ecology. This study therefore aims to assess three real-size experiments(A, B and C) carried out between 2003 and 2013 in this environment. A total of 157 bioengineering structures using purple and white willow(Salix purpurea and Salix incana)cuttings – which have been shown to resprout and survive more than 2 years after their installation,corresponding to brush layers with brush mats on wooden sills(BLM), 1.2 m wide and 2 m long,installed on the floors of 33 experimental marly gullies, were monitored. The results showed that sediment trapping occurred upstream of the vegetation barriers from the 1 st year onwards.Considering the depth of sediment trapped per experiment, the mean annual values reached 11.2 cm yr-1 after 3 years in experiment A, 7.7 cm yr-1 after 2–4 years in experiment C and 5.1 cm yr-1 after 5 years in experiment B. Occasionally, BLMs showed that they could trap up to 16 and 15 cm yr-1 in experiments A and C, respectively. Considering the volumes oftrapped sediment and the sustainability of sediment trapping are discussed, and rules for bioengineering strategies are proposed.
文摘该文运用Dlib人脸检测模型与人脸检测模板匹配方法,通过计算EAR、MAR、pitch、yaw和roll参数,采用多阈值判定研究疲驾驶员疲劳状态,并将该算法在Raspberry Pi 5硬件平台实现,搭建疲劳驾驶检测预警系统,最后通过公开数据集验证该系统对于驾驶员面部疲劳状态检测及提醒的准确性和良好的系统性能。EAR、MAR、HPE 3种判断准则在公开数据集Drowsiness、YawDD及自制数据集上分别达到95.6%、96%与96%的平均正确率;在面部无遮挡的情况下,该系统实时帧率达到20 FPS,基本可实时对驾驶员疲劳状态作出相应提醒,同时具备较高的准确率。
基金supported by the Open Fund of the National Key Laboratory of Deep Space Exploration(No.NKDSEL2024004-2)the National Natural Science Foundation of China(No.42173045)supported by the Shandong Provincial Natural Science Foundation(No.ZR2025QC448).
文摘Oxygen(O_(2))is essential for life support and rocket propulsion in Mars exploration missions,and in situ oxygen production from the Martian atmosphere is of profound scientific and engineering significance.In this article,we propose a novel method for O_(2) production from the Martian atmosphere by using glow discharge ionization combined with a self-developed oxygen-permeable membrane(OPM).Experiments under simulated Martian atmospheric conditions examined parameter impacts on the O_(2) production rate and assessed the operating characteristics and glow discharge plasma tolerance of the OPM.Results indicate that(1)the proportion of O_(2) produced positively correlates with the ionization voltage under fixed discharge electrode spacing,pressure,and flow rate,reaching a maximum of 8.18%(saturating at 4600–5400 V);(2)O_(2) yield rises with the carbon dioxide(CO_(2))flow rate at a constant pressure,with the maximum value reaching 0.5 g/h;(3)titanium(Ti)and molybdenum(Mo)electrodes exhibit higher application potential under high voltage conditions;(4)the OPM operates at temperatures above 800℃ and shows few changes in the main body sections after 24 h of plasma tolerance testing.This study lays the foundation for future development of a mature Mars oxygen production prototype with lower energy consumption and higher efficiency.
文摘This study investigates the uncertain dynamic characterization of hybrid composite plates by employing advanced machine-assisted finite element methodologies.Hybrid composites,widely used in aerospace,automotive,and structural applications,often face variability in material properties,geometric configurations,and manufacturing processes,leading to uncertainty in their dynamic response.To address this,three surrogate-based machine learning approaches like radial basis function(RBF),multivariate adaptive regression splines(MARS),and polynomial neural networks(PNN)are integrated with a finite element framework to efficiently capture the stochastic behavior of these plates.The research focuses on predicting the first three natural frequencies under material uncertainties,which are critical to ensuring structural reliability.Monte Carlo simulation(MCS)is used as a benchmark for generating probabilistic datasets,including mean values,standard deviations,and probability density functions.The surrogate models are then trained and validated against these datasets,enabling accurate representation of uncertainty with substantially fewer samples compared to conventionalMCS.Among the methods studied,the RBFmodel demonstrates superior performance,closely approximating MCS results with a reduced sample size,thereby achieving significant computational savings.The proposed framework not only reduces computational time and costs but also maintains high predictive accuracy,making it well-suited for complex engineering systems.Beyond free vibration analysis,the methodology can be extended to more sophisticated scenarios,such as forced vibration,damping effects,and nonlinear structural responses.Overall,this work presents a computationally efficient and robust approach for surrogate-based uncertainty quantification,advancing the analysis and design of hybrid composite structures under uncertainty.
基金Supported by the National Natural Science Foundation of China(62073034)。
文摘The parachute deployment conditions during the terminal entry phase in Mars landing missions exhibit critical impact on landing precision.In this article,aiming at the requirements of safe parachute deployment and accurate landing,a multidimensional parachute deployment box for determining deployment condition during Mars landing was proposed.First,an extremerange optimization model was established,synthesizing the dynamics and constraints of both parachute descent and powered descent phases.Then,on the basis of the two-dimensional altitude-velocity deployment box,a multi-dimensional parachute deployment box characterized by altitude,velocity,flight-path angle,and extreme range was constructed through the integration of extreme range information.Furthermore,an evaluation index for landing precision was formulated and a deployment control logic was proposed for minimizing landing deviation.Finally,the proposed deployment box was simulated in a Mars landing mission.The results demonstrate that the proposed box effectively satisfies safe deployment and landing precision demands,eliminating the range-to-go error at the terminal of the entry phase.
基金supported by the National Defense Basic Scientific Research Program(JCKY2021603B030)the National Natural Science Foundation of China(62273118,12150008)the Natural Science Foundation of Heilongjiang Province(LH2022F023).
文摘Dear Editor,This letter proposes a convex optimization-based model predictive control(MPC)autonomous guidance method for the Mars ascent vehicle(MAV).We use the modified chebyshev-picard iteration(MCPI)to solve optimization sub-problems within the MPC framework,eliminating the dynamic constraints in solving the optimal control problem and enhancing the convergence performance of the algorithm.Moreover,this method can repeatedly perform trajectory optimization calculations at a high frequency,achieving timely correction of the optimal control command.Numerical simulations demonstrate that the method can satisfy the requirements of rapid computation and reliability for the MAV system when considering uncertainties and perturbations.
文摘Medically assisted reproduction(MAR)techniques are highly dependent on the sperm quantity and quality.Low sperm concentrations can be bypassed at least to some point by the usage of more sophisticated MAR techniques like intracytoplasmic sperm injection(ICSI).Compared to this,disruptions in established indicators of sperm quality like motility or morphology pose greater challenges for the therapy of couple infertility.
