Myocardial infarction (MI), the most serious of the ischemic heart diseases, is accompanied by myocardial metabolic disorders and the loss of cardiomyocytes. Increasing evidence has shown that long noncoding RNAs (lnc...Myocardial infarction (MI), the most serious of the ischemic heart diseases, is accompanied by myocardial metabolic disorders and the loss of cardiomyocytes. Increasing evidence has shown that long noncoding RNAs (lncRNAs) are involved in various pathological conditions such as cancer and cardiovascular diseases (CVDs), and are emerging as a novel biomarker for these disorders. This study aims to investigate the regulatory role and mechanisms of lncRNAs in myocardial remodeling in the setting of MI. We find that post-infarcted hearts exhibit a reduction of adenosine triphosphate (ATP) and an alteration of the glucose and lipid metabolism genes cluster of differentiation 36 (CD36), hexokinase 1 (HK1), and clucose transporter 4 (GLUT4), accompanied by cardiomyocyte pyroptosis. We then identify a previously unknown conserved lncRNA, AK009126 (cardiomyocyte pyroptosis-associated lncRNA, CPAL), which is remarkably upregulated in the myocardial border zone of MI mice. Importantly, the adeno-associated virus 9 (AAV9)-mediated silencing of endogenous CPAL by its short hairpin RNA (shRNA) partially abrogates myocardial metabolic alterations and cardiomyocyte pyroptosis during MI in mice. Mechanistically, CPAL is shown to bind directly to nuclear factor kappa B (NFκB) and to act as an activator of NFκB to induce NFκB phosphorylation in cardiomyocytes. We also find that CPAL upregulates caspase-1 expression at the transcriptional level and consequently promotes the release of interleukin (IL)-18 and IL-1β from cardiomyocytes. Collectively, our findings reveal the conserved lncRNA CPAL as a new regulator of cardiac metabolic abnormalities and cardiomyocyte pyroptosis in the setting of MI and suggest CPAL as a new therapeutic target to protect cardiomyocytes against ischemic injury in infarcted hearts.展开更多
Nanocarbons,widely and commonly used as supports for supported Pt-based electrocatalysts in PEMFCs,play a significant role in Pt dispersion and accessibility,further determining their corresponding electrocatalytic pe...Nanocarbons,widely and commonly used as supports for supported Pt-based electrocatalysts in PEMFCs,play a significant role in Pt dispersion and accessibility,further determining their corresponding electrocatalytic performance.This paper provides an overview of the nanoarchitectures and surface physicochemical properties of nanocarbons affecting the electrocatalyst performance,with an emphasis on both physical characteristics,including pore structure,and chemical properties,including heteroatom doping and functional carbon-based supports.This review discusses the recent progress in nanocarbon supports,guides the future development direction of PEMFC supports,and provides our own viewpoints for the future research and design of PEMFCs catalysts,advancing the commercialization of PEMFCs.展开更多
Almost half of all flight accidents caused by inflight icing occur at the approach and landing phases when high-lift devices are deployed.The present study focuses on the optimization of an ice-tolerant multi-element ...Almost half of all flight accidents caused by inflight icing occur at the approach and landing phases when high-lift devices are deployed.The present study focuses on the optimization of an ice-tolerant multi-element airfoil.Dual-objective optimization is carried out with critical hornshaped ice accumulated during the holding phase.The optimization results show that the present optimization method significantly enhances the iced-state and clean-state performance.The optimal multi-element airfoil has a larger deflection angle and wider gap at the slat and the flap compared with the baseline configuration.The sensitivity of each design parameter is analyzed,which verifies the robustness of the design.The design is further assessed when ice is accreted during the approach and landing phases,which also shows performance improvement.展开更多
Machine learning has been widely utilized in flow field modeling and aerodynamic optimization.However,most applications are limited to two-dimensional problems.The dimensionality and the cost per simulation of three-d...Machine learning has been widely utilized in flow field modeling and aerodynamic optimization.However,most applications are limited to two-dimensional problems.The dimensionality and the cost per simulation of three-dimensional problems are so high that it is often too expensive to prepare sufficient samples.Therefore,transfer learning has become a promising approach to reuse well-trained two-dimensional models and greatly reduce the need for samples for threedimensional problems.This paper proposes to reuse the baseline models trained on supercritical airfoils to predict finite-span swept supercritical wings,where the simple swept theory is embedded to improve the prediction accuracy.Two baseline models are investigated:one is commonly referred to as the forward problem of predicting the pressure coefficient distribution based on the geometry,and the other is the inverse problem that predicts the geometry based on the pressure coefficient distribution.Two transfer learning strategies are compared for both baseline models.The transferred models are then tested on complete wings.The results show that transfer learning requires only approximately 500 wing samples to achieve good prediction accuracy on different wing planforms and different free stream conditions.Compared to the two baseline models,the transferred models reduce the prediction error by 60%and 80%,respectively.展开更多
Pressure distribution is important information for engineers during an aerodynamic design process. Pressure Distribution Oriented(PDO) optimization design has been proposed to introduce pressure distribution manipulat...Pressure distribution is important information for engineers during an aerodynamic design process. Pressure Distribution Oriented(PDO) optimization design has been proposed to introduce pressure distribution manipulation into traditional performance dominated optimization.In previous PDO approaches, constraints or manual manipulation have been used to obtain a desirable pressure distribution. In the present paper, a new Pressure Distribution Guided(PDG) method is developed to enable better pressure distribution manipulation while maintaining optimization efficiency. Based on the RBF-Assisted Differential Evolution(RADE) algorithm, a surrogate model is built for target pressure distribution features. By introducing individuals suggested by suboptimization on the surrogate model into the population, the direction of optimal searching can be guided. Pressure distribution expectation and aerodynamic performance improvement can be achieved at the same time. The improvements of the PDG method are illustrated by comparing its design results and efficiency on airfoil optimization test cases with those obtained using other methods. Then the PDG method is applied on a dual-aisle airplane’s inner-board wing design. A total drag reduction of 8 drag counts is achieved.展开更多
Natural ice accretion on the lifting surface of an aircraft is detrimental to its aerodynamic performance, as it changes the effective streamlined body. The main focus of this work considers the optimization design of...Natural ice accretion on the lifting surface of an aircraft is detrimental to its aerodynamic performance, as it changes the effective streamlined body. The main focus of this work considers the optimization design of airfoils under atmospheric icing conditions for the Unmanned Aerial Vehicle(UAV). The ice formation process is simulated by the Eulerian approach and the three-dimensional Myers model. A three-equation turbulence model is implemented to accurately predict the stall performance of the iced airfoil. In recognition of the real atmospheric variability in the icing parameters, the medium volume diameter of supercooled water droplets is treated as an uncertainty with an assumed probability density function. A technique of polynomial chaos expansion is used to propagate the input uncertainty through the deterministic system. The numerical results show that the multipoint/multiobjective optimization strategy can efficiently improve both the ice tolerance and the cruise performance of an airfoil. The reason for the focus on robust optimization is that the ice angle of the optimized airfoil becomes less critical to the incoming flow.The optimized airfoils are applied to a UAV platform, in which the performance improvement and the relevant key flow feature are both preserved.展开更多
Inverse design has long been an efficient and powerful design tool in the aircraft industry.In this paper,a novel inverse design method for supercritical airfoils is proposed based on generative models in deep learnin...Inverse design has long been an efficient and powerful design tool in the aircraft industry.In this paper,a novel inverse design method for supercritical airfoils is proposed based on generative models in deep learning.A Conditional Variational Auto Encoder(CVAE)and an integrated generative network CVAE-GAN that combines the CVAE with the Wasserstein Generative Adversarial Networks(WGAN),are conducted as generative models.They are used to generate target wall Mach distributions for the inverse design that matches specified features,such as locations of suction peak,shock and aft loading.Qualitative and quantitative results show that both adopted generative models can generate diverse and realistic wall Mach number distributions satisfying the given features.The CVAE-GAN model outperforms the CVAE model and achieves better reconstruction accuracies for all the samples in the dataset.Furthermore,a deep neural network for nonlinear mapping is adopted to obtain the airfoil shape corresponding to the target wall Mach number distribution.The performances of the designed deep neural network are fully demonstrated and a smoothness measurement is proposed to quantify small oscillations in the airfoil surface,proving the authenticity and accuracy of the generated airfoil shapes.展开更多
Variable-camber technology is considered an effective way to adaptively improve the aerodynamic performance of aircraft under various flight conditions.This paper studies the aerodynamic characteristics of the trailin...Variable-camber technology is considered an effective way to adaptively improve the aerodynamic performance of aircraft under various flight conditions.This paper studies the aerodynamic characteristics of the trailing-edge variable-camber technology by means of Computational Fluid Dynamics(CFD)and a drag decomposition method.Trailing-edge variable-camber technology can be simply realized by the continuous deflection of the flaps and ailerons of a wing.A supercritical airfoil is used to study the two-dimensional effect of variable-camber technology,and a wide-body airplane model is used to validate the three-dimensional improvement in the wing’s airfoil made by variable-camber technology.An optimization strategy for airfoil that incorporates variable-camber technology is proposed.The optimization results demonstrate that the proposed method can obtain better results than the traditional segregated shape optimization.展开更多
The electrochemical oxygen evolution reaction(OER)plays an important role in many clean electrochemical energy storage and conversion systems,such as electrochemical water splitting,rechargeable metal–air batteries,a...The electrochemical oxygen evolution reaction(OER)plays an important role in many clean electrochemical energy storage and conversion systems,such as electrochemical water splitting,rechargeable metal–air batteries,and electrochemical CO_(2) reduction.However,the OER involves a complex four-electron process and suffers from intrinsically sluggish kinetics,which greatly impairs the efficiency of electrochemical systems.In addition,state-of-the-art RuO2-based OER electrocatalysts are too expensive and scarce for practical applications.The development of highly active,cost-effective,and durable electrocatalysts that can improve OER performance(activity and durability)is of significant importance in realizing the widespread application of these advanced technologies.To date,considerable progress has been made in the development of alternative,noble metal-free OER electrocatalysts.Among these alternative catalysts,transition metal compounds have received particular attention and have shown activities comparable to or even higher than those of their precious metal counterparts.In contrast to many other electrocatalysts,such as carbon-based materials,transition metal compounds often exhibit a surface reconstruction phenomenon that is accompanied by the transformation of valence states during electrochemical OER processes.This surface reconstruction results in changes to the true active sites and an improvement or reduction in OER catalytic performance.Therefore,understanding the self-reconstruction process and precisely identifying the true active sites on electrocatalyst surfaces will help us to finely tune the properties and activities of OER catalysts.This review provides a comprehensive summary of recent progress made in understanding the surface reconstruction phenomena of various transition metal-based OER electrocatalysts,focusing on uncovering the correlations among structure,surface reconstruction and intrinsic activity.Recent advances in OER electrocatalysts that exhibit a surface self-reconstruction capability are also discussed.We identify possible challenges and perspectives for the development of OER electrocatalysts based on surface reconstruction.We hope this review will provide readers with some guidance on the rational design of catalysts for various electrochemical reactions.展开更多
Propeller aircraft are widely used in general aviation.The rotating propeller has a strong effect on the aerodynamic performance of the wing.This paper uses an actuator disc to model the effect of the propeller.A wing...Propeller aircraft are widely used in general aviation.The rotating propeller has a strong effect on the aerodynamic performance of the wing.This paper uses an actuator disc to model the effect of the propeller.A wing optimization method is developed with the actuator disc method.Several wing optimizations with different slipstream settings are studied.The twist angle and airfoils of the wing are used as the design variables.The results show that the propeller slipstream and slipstream directions have a strong influence on the optimization process.Powered-on optimization with a slipstream can obtain better drag reduction results than unpowered optimization.The drag decomposition results show that most of the drag reduction comes from the form drag reduction.The symmetric"inboard-up"slipstream configuration is found to have the highest lift-to-drag ratios,which are 18.87 for the twist angle optimization and 19.15 for the airfoil optimization.展开更多
The Adaptive Dropped Hinge Flap(ADHF) is a novel trailing edge high-lift device characterized by the integration of downward deflection spoiler and simple hinge flap, with excellent aerodynamic and mechanism performan...The Adaptive Dropped Hinge Flap(ADHF) is a novel trailing edge high-lift device characterized by the integration of downward deflection spoiler and simple hinge flap, with excellent aerodynamic and mechanism performance. In this paper, aerodynamic optimization design of an ADHF high-lift system is conducted considering the mechanism performance. Shape and settings of both takeoff and landing configurations are optimized and analyzed, with considering the kinematic constraints of ADHF mechanism, and the desired optimization results were obtained after optimization. Sensitivity analysis proves the robustness of the optimal design. Comparison shows that the ADHF design has better comprehensive performance of both mechanism and aerodynamics than the conventional Fowler flap and simple hinge flap design.展开更多
In the field of supercritical wing design, various principles and rules have been summarized through theoretical and experimental analyses. Compared with black-box relationships between geometry parameters and perform...In the field of supercritical wing design, various principles and rules have been summarized through theoretical and experimental analyses. Compared with black-box relationships between geometry parameters and performances, quantitative physical laws about pressure distributions and performances are clearer and more beneficial to designers. With the advancement of computational fluid dynamics and computational intelligence, discovering new rules through statistical analysis on computers has become increasingly attractive and affordable. This paper proposes a novel sampling method for the statistical study on pressure distribution features and performances, so that new physical laws can be revealed. It utilizes an adaptive sampling algorithm, of which the criteria are developed based on Kullback–Leibler divergence and Euclidean distance.In this paper, the proposed method is employed to generate airfoil samples to study the relationships between the supercritical pressure distribution features and the drag divergence Mach number as well as the drag creep characteristic. Compared with conventional sampling methods, the proposed method can efficiently distribute samples in the pressure distribution feature space rather than directly sampling airfoil geometry parameters. The corresponding geometry parameters are searched and found under constraints, so that supercritical airfoil samples that are well distributed in the pressure distribution space are obtained. These samples allow statistical studies to obtain more reliable and universal aerodynamic rules that can be applied to supercritical airfoil designs.展开更多
Background:Infiltration is important for the surgical planning and prognosis of pituitary adenomas.Differences in preoperative diagnosis have been noted.The aim of this article is to assess the accuracy of machine lea...Background:Infiltration is important for the surgical planning and prognosis of pituitary adenomas.Differences in preoperative diagnosis have been noted.The aim of this article is to assess the accuracy of machine learning analysis of texture-derived parameters of pituitary adenoma obtained from preoperative MRI for the prediction of high infiltration.Methods:A total of 196 pituitary adenoma patients(training set:n=176;validation set:n=20)were enrolled in this retrospective study.In total,4120 quantitative imaging features were extracted from CE-T1 MR images.To select the most informative features,the least absolute shrinkage and selection operator(LASSO)and variance threshold method were performed.The linear support vector machine(SVM)was used to fit the predictive model based on infiltration features.Furthermore,the receiver operating characteristic curve(ROC)was generated,and the diagnostic performance of the model was evaluated by calculating the area under the curve(AUC),accuracy,precision,recall,and F1 value.Results:A variance threshold of 0.85 was used to exclude 16 features with small differences using the LASSO algorithm,and 19 optimal features were finally selected.The SVM models for predicting high infiltration yielded an AUC of 0.86(sensitivity:0.81,specificity 0.79)in the training set and 0.73(sensitivity:0.87,specificity:0.80)in the validation set.The four evaluation indicators of the predictive model achieved good diagnostic capabilities in the training set(accuracy:0.80,precision:0.82,recall:0.81,F1 score:0.81)and independent verification set(accuracy:0.85,precision:0.93,recall:0.87,F1 score:0.90).Conclusions:The radiomics model developed in this study demonstrates efficacy for the prediction of pituitary adenoma infiltration.This model could potentially aid neurosurgeons in the preoperative prediction of infiltration in PAs and contribute to the selection of ideal surgical strategies.展开更多
A hybrid noise computation method is presented in this paper.Large-eddy simulation with wall-model equation is proposed to compute the flow field.With a stress-balanced wall-model equation,the near-wall computation co...A hybrid noise computation method is presented in this paper.Large-eddy simulation with wall-model equation is proposed to compute the flow field.With a stress-balanced wall-model equation,the near-wall computation cost of large eddy simulation was effectively reduced.The instantaneous flow variables obtained by the large-eddy simulation were used to compute the noise source terms of the Ffowcs Williams-Hawkings equation.The present method was investigated with two test cases:a single cylinder at Re=10,000 and a rod-airfoil at Re=480,000.The flow quantities and aeroacoustic characteristics were compared with the reference data.The mean velocity profiles and spectra of the flow fluctuations were consistent with data from the literature.When compared with the reference data,the noise computation error was less than 3 dB.The computation results demonstrate the present wall-modeled large eddy simulation is efficient for the noise computation of complex vortex shedding flows.展开更多
This paper studies the riblet drag reduction effect for an infinite swept wing under a low Reynolds number using a large-eddy simulation.The results show that the drag reduction ratio is not linear under different swe...This paper studies the riblet drag reduction effect for an infinite swept wing under a low Reynolds number using a large-eddy simulation.The results show that the drag reduction ratio is not linear under different sweep angles.The maximum drag reduction ratio in this study is 9.5%for a wing with a 45°sweep angle.The local surface streamline angle and turbulence quantities are calculated to analyze the drag reduction mechanism.The results demonstrate that the riblets considerably suppress the Reynolds stresses above the wing upper surface,while the turbulence kinetic energy in the near wake is increased.A possible relaminarization phenomenon is observed at the middle part of the wing.Quasi-two-dimensional flow structures are observed near the wall,and a peak frequency is considered as the dominant frequency of the region.展开更多
文摘Myocardial infarction (MI), the most serious of the ischemic heart diseases, is accompanied by myocardial metabolic disorders and the loss of cardiomyocytes. Increasing evidence has shown that long noncoding RNAs (lncRNAs) are involved in various pathological conditions such as cancer and cardiovascular diseases (CVDs), and are emerging as a novel biomarker for these disorders. This study aims to investigate the regulatory role and mechanisms of lncRNAs in myocardial remodeling in the setting of MI. We find that post-infarcted hearts exhibit a reduction of adenosine triphosphate (ATP) and an alteration of the glucose and lipid metabolism genes cluster of differentiation 36 (CD36), hexokinase 1 (HK1), and clucose transporter 4 (GLUT4), accompanied by cardiomyocyte pyroptosis. We then identify a previously unknown conserved lncRNA, AK009126 (cardiomyocyte pyroptosis-associated lncRNA, CPAL), which is remarkably upregulated in the myocardial border zone of MI mice. Importantly, the adeno-associated virus 9 (AAV9)-mediated silencing of endogenous CPAL by its short hairpin RNA (shRNA) partially abrogates myocardial metabolic alterations and cardiomyocyte pyroptosis during MI in mice. Mechanistically, CPAL is shown to bind directly to nuclear factor kappa B (NFκB) and to act as an activator of NFκB to induce NFκB phosphorylation in cardiomyocytes. We also find that CPAL upregulates caspase-1 expression at the transcriptional level and consequently promotes the release of interleukin (IL)-18 and IL-1β from cardiomyocytes. Collectively, our findings reveal the conserved lncRNA CPAL as a new regulator of cardiac metabolic abnormalities and cardiomyocyte pyroptosis in the setting of MI and suggest CPAL as a new therapeutic target to protect cardiomyocytes against ischemic injury in infarcted hearts.
文摘Nanocarbons,widely and commonly used as supports for supported Pt-based electrocatalysts in PEMFCs,play a significant role in Pt dispersion and accessibility,further determining their corresponding electrocatalytic performance.This paper provides an overview of the nanoarchitectures and surface physicochemical properties of nanocarbons affecting the electrocatalyst performance,with an emphasis on both physical characteristics,including pore structure,and chemical properties,including heteroatom doping and functional carbon-based supports.This review discusses the recent progress in nanocarbon supports,guides the future development direction of PEMFC supports,and provides our own viewpoints for the future research and design of PEMFCs catalysts,advancing the commercialization of PEMFCs.
基金supported by the National Key Project of China(No.GJXM92579)National Natural Science Foundation of China(Nos.92052203,11872230 and 91852108)。
文摘Almost half of all flight accidents caused by inflight icing occur at the approach and landing phases when high-lift devices are deployed.The present study focuses on the optimization of an ice-tolerant multi-element airfoil.Dual-objective optimization is carried out with critical hornshaped ice accumulated during the holding phase.The optimization results show that the present optimization method significantly enhances the iced-state and clean-state performance.The optimal multi-element airfoil has a larger deflection angle and wider gap at the slat and the flap compared with the baseline configuration.The sensitivity of each design parameter is analyzed,which verifies the robustness of the design.The design is further assessed when ice is accreted during the approach and landing phases,which also shows performance improvement.
基金supported by the National Natural Science Foundation of China(Nos.92052203,12202243 and 11872230).
文摘Machine learning has been widely utilized in flow field modeling and aerodynamic optimization.However,most applications are limited to two-dimensional problems.The dimensionality and the cost per simulation of three-dimensional problems are so high that it is often too expensive to prepare sufficient samples.Therefore,transfer learning has become a promising approach to reuse well-trained two-dimensional models and greatly reduce the need for samples for threedimensional problems.This paper proposes to reuse the baseline models trained on supercritical airfoils to predict finite-span swept supercritical wings,where the simple swept theory is embedded to improve the prediction accuracy.Two baseline models are investigated:one is commonly referred to as the forward problem of predicting the pressure coefficient distribution based on the geometry,and the other is the inverse problem that predicts the geometry based on the pressure coefficient distribution.Two transfer learning strategies are compared for both baseline models.The transferred models are then tested on complete wings.The results show that transfer learning requires only approximately 500 wing samples to achieve good prediction accuracy on different wing planforms and different free stream conditions.Compared to the two baseline models,the transferred models reduce the prediction error by 60%and 80%,respectively.
基金co-supported by the National Key Basic Research Program of China(No.2014CB744806)Tsinghua University Initiative Scientific Research Program(No.2015Z22003)
文摘Pressure distribution is important information for engineers during an aerodynamic design process. Pressure Distribution Oriented(PDO) optimization design has been proposed to introduce pressure distribution manipulation into traditional performance dominated optimization.In previous PDO approaches, constraints or manual manipulation have been used to obtain a desirable pressure distribution. In the present paper, a new Pressure Distribution Guided(PDG) method is developed to enable better pressure distribution manipulation while maintaining optimization efficiency. Based on the RBF-Assisted Differential Evolution(RADE) algorithm, a surrogate model is built for target pressure distribution features. By introducing individuals suggested by suboptimization on the surrogate model into the population, the direction of optimal searching can be guided. Pressure distribution expectation and aerodynamic performance improvement can be achieved at the same time. The improvements of the PDG method are illustrated by comparing its design results and efficiency on airfoil optimization test cases with those obtained using other methods. Then the PDG method is applied on a dual-aisle airplane’s inner-board wing design. A total drag reduction of 8 drag counts is achieved.
基金supported by the National Key Project of China(No.GJXM92579)the National Natural Science Foundation of China(Nos.92052203 and 11872230 and 91852108)。
文摘Natural ice accretion on the lifting surface of an aircraft is detrimental to its aerodynamic performance, as it changes the effective streamlined body. The main focus of this work considers the optimization design of airfoils under atmospheric icing conditions for the Unmanned Aerial Vehicle(UAV). The ice formation process is simulated by the Eulerian approach and the three-dimensional Myers model. A three-equation turbulence model is implemented to accurately predict the stall performance of the iced airfoil. In recognition of the real atmospheric variability in the icing parameters, the medium volume diameter of supercooled water droplets is treated as an uncertainty with an assumed probability density function. A technique of polynomial chaos expansion is used to propagate the input uncertainty through the deterministic system. The numerical results show that the multipoint/multiobjective optimization strategy can efficiently improve both the ice tolerance and the cruise performance of an airfoil. The reason for the focus on robust optimization is that the ice angle of the optimized airfoil becomes less critical to the incoming flow.The optimized airfoils are applied to a UAV platform, in which the performance improvement and the relevant key flow feature are both preserved.
基金co-supported by the National Key Project of China(No.GJXM92579)the National Natural Science Foundation of China(Nos.92052203,61903178 and61906081)。
文摘Inverse design has long been an efficient and powerful design tool in the aircraft industry.In this paper,a novel inverse design method for supercritical airfoils is proposed based on generative models in deep learning.A Conditional Variational Auto Encoder(CVAE)and an integrated generative network CVAE-GAN that combines the CVAE with the Wasserstein Generative Adversarial Networks(WGAN),are conducted as generative models.They are used to generate target wall Mach distributions for the inverse design that matches specified features,such as locations of suction peak,shock and aft loading.Qualitative and quantitative results show that both adopted generative models can generate diverse and realistic wall Mach number distributions satisfying the given features.The CVAE-GAN model outperforms the CVAE model and achieves better reconstruction accuracies for all the samples in the dataset.Furthermore,a deep neural network for nonlinear mapping is adopted to obtain the airfoil shape corresponding to the target wall Mach number distribution.The performances of the designed deep neural network are fully demonstrated and a smoothness measurement is proposed to quantify small oscillations in the airfoil surface,proving the authenticity and accuracy of the generated airfoil shapes.
基金supported by the National Natural Science Foundation of China(Nos.11872230 and 91852108)。
文摘Variable-camber technology is considered an effective way to adaptively improve the aerodynamic performance of aircraft under various flight conditions.This paper studies the aerodynamic characteristics of the trailing-edge variable-camber technology by means of Computational Fluid Dynamics(CFD)and a drag decomposition method.Trailing-edge variable-camber technology can be simply realized by the continuous deflection of the flaps and ailerons of a wing.A supercritical airfoil is used to study the two-dimensional effect of variable-camber technology,and a wide-body airplane model is used to validate the three-dimensional improvement in the wing’s airfoil made by variable-camber technology.An optimization strategy for airfoil that incorporates variable-camber technology is proposed.The optimization results demonstrate that the proposed method can obtain better results than the traditional segregated shape optimization.
基金Acknowledgements The authors would like to thank the National Natural Science Foundation of China(21975292,21978331,21905311,92061124)the Guangzhou Science and Technology Project(201707010079)+2 种基金the Guangdong Province Nature Science Foundation(2020A1515010343)the Tip-top Scientific and Technical Innovative Youth Talents of Guangdong Special Support Program(No.2016TQ03N322)the Fundamental Research Funds for Central Universities(No19lgpy136,19lgpy116)for financial support.Prof.Tongwen Yu would like to give special thanks to the support of the startup grant provided by the“Hundred Talents Program”at Sun Yatsen University(No.76110-18841219).
文摘The electrochemical oxygen evolution reaction(OER)plays an important role in many clean electrochemical energy storage and conversion systems,such as electrochemical water splitting,rechargeable metal–air batteries,and electrochemical CO_(2) reduction.However,the OER involves a complex four-electron process and suffers from intrinsically sluggish kinetics,which greatly impairs the efficiency of electrochemical systems.In addition,state-of-the-art RuO2-based OER electrocatalysts are too expensive and scarce for practical applications.The development of highly active,cost-effective,and durable electrocatalysts that can improve OER performance(activity and durability)is of significant importance in realizing the widespread application of these advanced technologies.To date,considerable progress has been made in the development of alternative,noble metal-free OER electrocatalysts.Among these alternative catalysts,transition metal compounds have received particular attention and have shown activities comparable to or even higher than those of their precious metal counterparts.In contrast to many other electrocatalysts,such as carbon-based materials,transition metal compounds often exhibit a surface reconstruction phenomenon that is accompanied by the transformation of valence states during electrochemical OER processes.This surface reconstruction results in changes to the true active sites and an improvement or reduction in OER catalytic performance.Therefore,understanding the self-reconstruction process and precisely identifying the true active sites on electrocatalyst surfaces will help us to finely tune the properties and activities of OER catalysts.This review provides a comprehensive summary of recent progress made in understanding the surface reconstruction phenomena of various transition metal-based OER electrocatalysts,focusing on uncovering the correlations among structure,surface reconstruction and intrinsic activity.Recent advances in OER electrocatalysts that exhibit a surface self-reconstruction capability are also discussed.We identify possible challenges and perspectives for the development of OER electrocatalysts based on surface reconstruction.We hope this review will provide readers with some guidance on the rational design of catalysts for various electrochemical reactions.
基金supported by the National Natural Science Foundation of China(Nos.91852108 and 11872230)。
文摘Propeller aircraft are widely used in general aviation.The rotating propeller has a strong effect on the aerodynamic performance of the wing.This paper uses an actuator disc to model the effect of the propeller.A wing optimization method is developed with the actuator disc method.Several wing optimizations with different slipstream settings are studied.The twist angle and airfoils of the wing are used as the design variables.The results show that the propeller slipstream and slipstream directions have a strong influence on the optimization process.Powered-on optimization with a slipstream can obtain better drag reduction results than unpowered optimization.The drag decomposition results show that most of the drag reduction comes from the form drag reduction.The symmetric"inboard-up"slipstream configuration is found to have the highest lift-to-drag ratios,which are 18.87 for the twist angle optimization and 19.15 for the airfoil optimization.
基金supported by the National Natural Science Foundation of China(Nos.11872230,91852108,91952302,92052203)the Aeronautical Science Foundation of China(No.2020Z006058002)。
文摘The Adaptive Dropped Hinge Flap(ADHF) is a novel trailing edge high-lift device characterized by the integration of downward deflection spoiler and simple hinge flap, with excellent aerodynamic and mechanism performance. In this paper, aerodynamic optimization design of an ADHF high-lift system is conducted considering the mechanism performance. Shape and settings of both takeoff and landing configurations are optimized and analyzed, with considering the kinematic constraints of ADHF mechanism, and the desired optimization results were obtained after optimization. Sensitivity analysis proves the robustness of the optimal design. Comparison shows that the ADHF design has better comprehensive performance of both mechanism and aerodynamics than the conventional Fowler flap and simple hinge flap design.
基金supported by the National Natural Science Foundation of China(Nos.91852108 and 11872230)。
文摘In the field of supercritical wing design, various principles and rules have been summarized through theoretical and experimental analyses. Compared with black-box relationships between geometry parameters and performances, quantitative physical laws about pressure distributions and performances are clearer and more beneficial to designers. With the advancement of computational fluid dynamics and computational intelligence, discovering new rules through statistical analysis on computers has become increasingly attractive and affordable. This paper proposes a novel sampling method for the statistical study on pressure distribution features and performances, so that new physical laws can be revealed. It utilizes an adaptive sampling algorithm, of which the criteria are developed based on Kullback–Leibler divergence and Euclidean distance.In this paper, the proposed method is employed to generate airfoil samples to study the relationships between the supercritical pressure distribution features and the drag divergence Mach number as well as the drag creep characteristic. Compared with conventional sampling methods, the proposed method can efficiently distribute samples in the pressure distribution feature space rather than directly sampling airfoil geometry parameters. The corresponding geometry parameters are searched and found under constraints, so that supercritical airfoil samples that are well distributed in the pressure distribution space are obtained. These samples allow statistical studies to obtain more reliable and universal aerodynamic rules that can be applied to supercritical airfoil designs.
基金Postdoctoral Innovation Program of Shandong Province(NO.202103064)Linyi People’s Hospital Doctoral Research Foundation(NO.2021LYBS05)
文摘Background:Infiltration is important for the surgical planning and prognosis of pituitary adenomas.Differences in preoperative diagnosis have been noted.The aim of this article is to assess the accuracy of machine learning analysis of texture-derived parameters of pituitary adenoma obtained from preoperative MRI for the prediction of high infiltration.Methods:A total of 196 pituitary adenoma patients(training set:n=176;validation set:n=20)were enrolled in this retrospective study.In total,4120 quantitative imaging features were extracted from CE-T1 MR images.To select the most informative features,the least absolute shrinkage and selection operator(LASSO)and variance threshold method were performed.The linear support vector machine(SVM)was used to fit the predictive model based on infiltration features.Furthermore,the receiver operating characteristic curve(ROC)was generated,and the diagnostic performance of the model was evaluated by calculating the area under the curve(AUC),accuracy,precision,recall,and F1 value.Results:A variance threshold of 0.85 was used to exclude 16 features with small differences using the LASSO algorithm,and 19 optimal features were finally selected.The SVM models for predicting high infiltration yielded an AUC of 0.86(sensitivity:0.81,specificity 0.79)in the training set and 0.73(sensitivity:0.87,specificity:0.80)in the validation set.The four evaluation indicators of the predictive model achieved good diagnostic capabilities in the training set(accuracy:0.80,precision:0.82,recall:0.81,F1 score:0.81)and independent verification set(accuracy:0.85,precision:0.93,recall:0.87,F1 score:0.90).Conclusions:The radiomics model developed in this study demonstrates efficacy for the prediction of pituitary adenoma infiltration.This model could potentially aid neurosurgeons in the preoperative prediction of infiltration in PAs and contribute to the selection of ideal surgical strategies.
基金National Natural Science Foundation of China under grant Nos.11872230,91952302 and 92052203National Science and Technology Major Project(J2019-II-0006-0026).
文摘A hybrid noise computation method is presented in this paper.Large-eddy simulation with wall-model equation is proposed to compute the flow field.With a stress-balanced wall-model equation,the near-wall computation cost of large eddy simulation was effectively reduced.The instantaneous flow variables obtained by the large-eddy simulation were used to compute the noise source terms of the Ffowcs Williams-Hawkings equation.The present method was investigated with two test cases:a single cylinder at Re=10,000 and a rod-airfoil at Re=480,000.The flow quantities and aeroacoustic characteristics were compared with the reference data.The mean velocity profiles and spectra of the flow fluctuations were consistent with data from the literature.When compared with the reference data,the noise computation error was less than 3 dB.The computation results demonstrate the present wall-modeled large eddy simulation is efficient for the noise computation of complex vortex shedding flows.
基金supported by the National Natural Science Foundation of China(Nos.:91852108 and 11872230)Open Fund of Key Laboratory of Icing and Anti/De-icing of China(No.:IADL20190201)。
文摘This paper studies the riblet drag reduction effect for an infinite swept wing under a low Reynolds number using a large-eddy simulation.The results show that the drag reduction ratio is not linear under different sweep angles.The maximum drag reduction ratio in this study is 9.5%for a wing with a 45°sweep angle.The local surface streamline angle and turbulence quantities are calculated to analyze the drag reduction mechanism.The results demonstrate that the riblets considerably suppress the Reynolds stresses above the wing upper surface,while the turbulence kinetic energy in the near wake is increased.A possible relaminarization phenomenon is observed at the middle part of the wing.Quasi-two-dimensional flow structures are observed near the wall,and a peak frequency is considered as the dominant frequency of the region.
