Whipple shields as sacrificial bumpers,safeguard the satellites against extremely fast,different-sized projectiles traveling through space in the low earth orbit.Typical Whipple shields comprise a front and rear plate...Whipple shields as sacrificial bumpers,safeguard the satellites against extremely fast,different-sized projectiles traveling through space in the low earth orbit.Typical Whipple shields comprise a front and rear plate,separated by a gap or space.Recent advancements have explored the use of foam,cellular cores,and alternative materials such as ceramics instead of aluminium for the plates.In the current work,the effect of including fluid cores(air/water)sandwiched between the front and rear plates,on the response to hypervelocity impact was explored through a numerical approach.The numerical simulation consisted of hypervelocity impact by a 2 mm diameter,stainless steel projectile,launched at speeds of 3 e9 km/s with a normal impact trajectory towards the Whipple shield.The front and rear bumpers,made of AA6061-T6,were each 1 mm thick.A space of 10 mm was taken between the plates(occupied by fluid).The key metrics analyzed were the perforation characteristics,stages of the debris cloud generation and propagation,energy variations(internal,kinetic and plastic work),temperature variations,and the fragmentation summary.From the computational analysis,employing water-core in Whipple shields could prevent the rear bumper perforation till 6 km/s,lower the peak temperatures at the front bumper perforation zones and debris tip,and generate fewer,larger fragments.展开更多
A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,wh...A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,which reduces the risk of penetrating the bulkhead.In the realm of hypervelocity impact,strain rate(>10^(5)s^(-1))effects are negligible,and fluid dynamics is employed to describe the impact process.Efficient numerical tools for precisely predicting the damage degree can greatly accelerate the design and optimization of advanced protective structures.Current hypervelocity impact research primarily focuses on the interaction between projectile and front plate and the movement of debris cloud.However,the damage mechanism of debris cloud impacts on rear plates-the critical threat component-remains underexplored owing to complex multi-physics processes and prohibitive computational costs.Existing approaches,ranging from semi-empirical equations to a machine learningbased ballistic limit prediction method,are constrained to binary penetration classification.Alternatively,the uneven data from experiments and simulations caused these methods to be ineffective when the projectile has irregular shapes and complicate flight attitude.Therefore,it is urgent to develop a new damage prediction method for predicting the rear plate damage,which can help to gain a deeper understanding of the damage mechanism.In this study,a machine learning(ML)method is developed to predict the damage distribution in the rear plate.Based on the unit velocity space,the discretized information of debris cloud and rear plate damage from rare simulation cases is used as input data for training the ML models,while the generalization ability for damage distribution prediction is tested by other simulation cases with different attack angles.The results demonstrate that the training and prediction accuracies using the Random Forest(RF)algorithm significantly surpass those using Artificial Neural Networks(ANNs)and Support Vector Machine(SVM).The RF-based model effectively identifies damage features in sparsely distributed debris cloud and cumulative effect.This study establishes an expandable new dataset that accommodates additional parameters to improve the prediction accuracy.Results demonstrate the model's ability to overcome data imbalance limitations through debris cloud features,enabling rapid and accurate rear plate damage prediction across wider scenarios with minimal data requirements.展开更多
BACKGROUND Whipple’s disease is a rare systemic infection caused by Tropheryma whipplei.Most patients present with nonspecific symptoms,and routine laboratory and imaging examination results also lack specificity.The...BACKGROUND Whipple’s disease is a rare systemic infection caused by Tropheryma whipplei.Most patients present with nonspecific symptoms,and routine laboratory and imaging examination results also lack specificity.The diagnosis often relies on invasive manipulation,pathological examination,and molecular techniques.These difficulties in diagnosing Whipple’s disease often result in misdiagnosis and inappropriate treatments.CASE SUMMARY This paper reports on the case of a 58-year-old male patient who complained of fatigue and decreased exercise capacity.The results of routine blood tests indicated hypochromic microcytic anemia.Results of gastroscopy and capsule endoscopy showed multiple polypoid bulges distributed in the duodenal and proximal jejunum.A diagnosis of small intestinal adenomatosis was initially considered;hence,the Whipple procedure,a pylorus-preserving pancreaticoduodenectomy,was performed.Pathological manifestations showed many periodic acid-Schiff-positive macrophages aggregated in the intestinal mucosa of the duodenum,upper jejunum,and surrounding lymph nodes.Based on comprehensive analysis of symptoms,laboratory findings,and pathological manifestations,the patient was finally diagnosed with Whipple’s disease.After receiving 1 mo of antibiotic treatment,the fatigue and anemia were significantly improved.CONCLUSION This case presented with atypical gastrointestinal manifestations and small intestinal polypoid bulges,which provided new insight on the diagnosis of Whipple’s disease.展开更多
文摘Whipple shields as sacrificial bumpers,safeguard the satellites against extremely fast,different-sized projectiles traveling through space in the low earth orbit.Typical Whipple shields comprise a front and rear plate,separated by a gap or space.Recent advancements have explored the use of foam,cellular cores,and alternative materials such as ceramics instead of aluminium for the plates.In the current work,the effect of including fluid cores(air/water)sandwiched between the front and rear plates,on the response to hypervelocity impact was explored through a numerical approach.The numerical simulation consisted of hypervelocity impact by a 2 mm diameter,stainless steel projectile,launched at speeds of 3 e9 km/s with a normal impact trajectory towards the Whipple shield.The front and rear bumpers,made of AA6061-T6,were each 1 mm thick.A space of 10 mm was taken between the plates(occupied by fluid).The key metrics analyzed were the perforation characteristics,stages of the debris cloud generation and propagation,energy variations(internal,kinetic and plastic work),temperature variations,and the fragmentation summary.From the computational analysis,employing water-core in Whipple shields could prevent the rear bumper perforation till 6 km/s,lower the peak temperatures at the front bumper perforation zones and debris tip,and generate fewer,larger fragments.
基金supported by National Natural Science Foundation of China(Grant No.12432018,12372346)the Innovative Research Groups of the National Natural Science Foundation of China(Grant No.12221002).
文摘A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,which reduces the risk of penetrating the bulkhead.In the realm of hypervelocity impact,strain rate(>10^(5)s^(-1))effects are negligible,and fluid dynamics is employed to describe the impact process.Efficient numerical tools for precisely predicting the damage degree can greatly accelerate the design and optimization of advanced protective structures.Current hypervelocity impact research primarily focuses on the interaction between projectile and front plate and the movement of debris cloud.However,the damage mechanism of debris cloud impacts on rear plates-the critical threat component-remains underexplored owing to complex multi-physics processes and prohibitive computational costs.Existing approaches,ranging from semi-empirical equations to a machine learningbased ballistic limit prediction method,are constrained to binary penetration classification.Alternatively,the uneven data from experiments and simulations caused these methods to be ineffective when the projectile has irregular shapes and complicate flight attitude.Therefore,it is urgent to develop a new damage prediction method for predicting the rear plate damage,which can help to gain a deeper understanding of the damage mechanism.In this study,a machine learning(ML)method is developed to predict the damage distribution in the rear plate.Based on the unit velocity space,the discretized information of debris cloud and rear plate damage from rare simulation cases is used as input data for training the ML models,while the generalization ability for damage distribution prediction is tested by other simulation cases with different attack angles.The results demonstrate that the training and prediction accuracies using the Random Forest(RF)algorithm significantly surpass those using Artificial Neural Networks(ANNs)and Support Vector Machine(SVM).The RF-based model effectively identifies damage features in sparsely distributed debris cloud and cumulative effect.This study establishes an expandable new dataset that accommodates additional parameters to improve the prediction accuracy.Results demonstrate the model's ability to overcome data imbalance limitations through debris cloud features,enabling rapid and accurate rear plate damage prediction across wider scenarios with minimal data requirements.
文摘BACKGROUND Whipple’s disease is a rare systemic infection caused by Tropheryma whipplei.Most patients present with nonspecific symptoms,and routine laboratory and imaging examination results also lack specificity.The diagnosis often relies on invasive manipulation,pathological examination,and molecular techniques.These difficulties in diagnosing Whipple’s disease often result in misdiagnosis and inappropriate treatments.CASE SUMMARY This paper reports on the case of a 58-year-old male patient who complained of fatigue and decreased exercise capacity.The results of routine blood tests indicated hypochromic microcytic anemia.Results of gastroscopy and capsule endoscopy showed multiple polypoid bulges distributed in the duodenal and proximal jejunum.A diagnosis of small intestinal adenomatosis was initially considered;hence,the Whipple procedure,a pylorus-preserving pancreaticoduodenectomy,was performed.Pathological manifestations showed many periodic acid-Schiff-positive macrophages aggregated in the intestinal mucosa of the duodenum,upper jejunum,and surrounding lymph nodes.Based on comprehensive analysis of symptoms,laboratory findings,and pathological manifestations,the patient was finally diagnosed with Whipple’s disease.After receiving 1 mo of antibiotic treatment,the fatigue and anemia were significantly improved.CONCLUSION This case presented with atypical gastrointestinal manifestations and small intestinal polypoid bulges,which provided new insight on the diagnosis of Whipple’s disease.
