The reverse design of solid rocket motor(SRM)propellant grain involves determining the grain geometry to closely match a predefined internal ballistic curve.While existing reverse design methods are feasible,they ofte...The reverse design of solid rocket motor(SRM)propellant grain involves determining the grain geometry to closely match a predefined internal ballistic curve.While existing reverse design methods are feasible,they often face challenges such as lengthy computation times and limited accuracy.To achieve rapid and accurate matching between the targeted ballistic curve and complex grain shape,this paper proposes a novel reverse design method for SRM propellant grain based on time-series data imaging and convolutional neural network(CNN).First,a finocyl grain shape-internal ballistic curve dataset is created using parametric modeling techniques to comprehensively cover the design space.Next,the internal ballistic time-series data is encoded into three-channel images,establishing a potential relationship between the ballistic curves and their image representations.A CNN is then constructed and trained using these encoded images.Once trained,the model enables efficient inference of propellant grain dimensions from a target internal ballistic curve.This paper conducts comparative experiments across various neural network models,validating the effectiveness of the feature extraction method that transforms internal ballistic time-series data into images,as well as its generalization capability across different CNN architectures.Ignition tests were performed based on the predicted propellant grain.The results demonstrate that the relative error between the experimental internal ballistic curves and the target curves is less than 5%,confirming the validity and feasibility of the proposed reverse design methodology.展开更多
For the purpose of obtaining satisfactory performance of the non-circular gear & crank-rocker & gear trains (NCCRG) weft insertion mechanism which was proposed in this paper, the ideal kinematic curve of this ...For the purpose of obtaining satisfactory performance of the non-circular gear & crank-rocker & gear trains (NCCRG) weft insertion mechanism which was proposed in this paper, the ideal kinematic curve of this weft insertion mechanism was given, and the reverse solution models of this mechanism were established. A reverse design and simulation software was compiled based on Visual Basic 6.0 to obtain the mechanism parameters, including the pitch curves and tooth profiles of the non-circular gears. A test-bed of this mechanism was developed according to these parameters. The kinematic performance of this weft insertion mechanism was tested by high-speed video tape recorder with its corresponding video analytical software Blaster's MAS. And the test results were identical with the theoretical calculation. Compared with the conjugate cam weft insertion mechanism which is applied on TT96 rapier loom, under the condition of same weft insertion rate, the variation of acceleration of this mechanism is smaller. This novel weft insertion mechanism can meet the requirements of weft insertion on rapier looms with smooth and steady motion.展开更多
In the previous research,the seedling pick-up mechanism of the planetary gear train with incomplete eccentric circular gear and non-circular gears for vegetable plug seedlings still has two shortcomings.One is that no...In the previous research,the seedling pick-up mechanism of the planetary gear train with incomplete eccentric circular gear and non-circular gears for vegetable plug seedlings still has two shortcomings.One is that not enough seedling pick-up depth leads to a low success ratio of seedling pick-up at high rotation speeds,the other is that the smaller seedling pushing angle results in poor seedling pushing effect.Therefore,the reverse design of the seedling pick-up mechanism based on its motion trajectory was carried out.The local trajectory of seedling pick-up and seedling pushing sections was adjusted to obtain the theoretical motion trajectory of the seedling pick-up mechanism.The cubic non-uniform B-spline curve was used to fit the adjusted trajectory.A novel seedling pick-up mechanism of the planetary gear train with non-circular gears was proposed,including three combined non-circular gears,four non-circular gears,one planetary carrier,and two seedling pick-up arms.The reverse design model of the mechanism was established.The analysis and design software of the mechanism was developed to obtain the mechanism parameters meeting design requirements.The virtual prototype of the mechanism was established and its physical prototype was manufactured.Through the virtual motion simulation and high-speed photographic kinematics bench tests of the mechanism,the kinematic model and results of reverse design of the mechanism were verified,with the kinematic performances of the mechanism prototype studied.The seedling pick-up tests of the mechanism were conducted in the laboratory.The success ratios of seedling pick-up were 94.2%,95.6% and 90.2% while the seedling pick-up efficiencies of the mechanism were 60,80 and 100 plants per minute per row,respectively.Besides,the seedling pushing effect was improved mush because of the greater seedling pushing angle.The seedling pick-up mechanism through revise design is of high value to be applied in the practical vegetable plug seedling transplanters.展开更多
As a kind of nature-derived bioactive materials, polyphenol-based hydrogels possess many unique and outstanding properties such as adhesion, toughness, and self-healing due to their specific crosslinking structures, w...As a kind of nature-derived bioactive materials, polyphenol-based hydrogels possess many unique and outstanding properties such as adhesion, toughness, and self-healing due to their specific crosslinking structures, which have been widely used in biomedical fields including wound healing, antitumor, treatment of motor system injury, digestive system disease, oculopathy, and bioelectronics. In this review, starting with the classi-fication of common polyphenol-based hydrogels, the pyramid evolution process of polyphenol-based hydrogels from crosslinking structures to derived properties and then to biomedical applications is elaborated, as well as the efficient reverse design considerations of polyphenol-based hydrogel systems are proposed. Finally, the existing problems and development prospects of these hydrogel materials are discussed. It is hoped that the unique perspective of the review can promote further innovation and breakthroughs of polyphenol-based hydrogels in the future.展开更多
The Qi Tai Telescope(QTT),which has a 110 m aperture,is planned to be the largest scale steerable tele-scope in the world.Ideally,the telescope’s repeated pointing accuracy error should be less than 2.5 arc seconds(a...The Qi Tai Telescope(QTT),which has a 110 m aperture,is planned to be the largest scale steerable tele-scope in the world.Ideally,the telescope’s repeated pointing accuracy error should be less than 2.5 arc seconds(arcsec);thus,the telescope structure must satisfy ultra-high precision requirements.In this pur-suit,the present research envisages a reverse-design method for the track surface to reduce the difficulty of the telescope’s design and manufacture.First,the distribution characteristics of the test data for the track error were verified using the skewness coefficient and kurtosis coefficient methods.According to the distribution characteristics,the azimuth track error was simulated by a two-scale model.The error of the long period and short amplitude was characterized as large-scale and described by a trigonometric function,while the short period and high amplitude error was characterized as small-scale and simulated by a fractal function.Based on the two-scale model,effect of the error on the pointing accuracy was deduced.Subsequently,the relationship between the root mean square(RMS)of the track error and the RMS of the pointing accuracy error of the telescope was deduced.Finally,the allowable RMS value of the track error was derived from the allowable pointing accuracy errors.To validate the effectiveness of the new design method,two typical radio telescopes(the Green Bank Telescope(GBT)and the Large Millimeter Telescope(LMT))were selected as experimental examples.Through comparison,the theoretical calculated values of the pointing accuracy of the telescope were consistent with the measured values,with a maximum error of less than 10%.展开更多
Advancing the integration of artificial intelligence and polymer science requires high-quality,open-source,and large-scale datasets.However,existing polymer databases often suffer from data sparsity,lack of polymer-pr...Advancing the integration of artificial intelligence and polymer science requires high-quality,open-source,and large-scale datasets.However,existing polymer databases often suffer from data sparsity,lack of polymer-property labels,and limited accessibility,hindering system-atic modeling across property prediction tasks.Here,we present OpenPoly,a curated experimental polymer database derived from extensive lit-erature mining and manual validation,comprising 3985 unique polymer-property data points spanning 26 key properties.We further develop a multi-task benchmarking framework that evaluates property prediction using four encoding methods and eight representative models.Our re-sults highlight that the optimized degree-of-polymerization encoding coupled with Morgan fingerprints achieves an optimal trade-off between computational cost and accuracy.In data-scarce condition,XGBoost outperforms deep learning models on key properties such as dielectric con-stant,glass transition temperature,melting point,and mechanical strength,achieving R2 scores of 0.65-0.87.To further showcase the practical utility of the database,we propose potential polymers for two energy-relevant applications:high temperature polymer dielectrics and fuel cell membranes.By offering a consistent and accessible benchmark and database,OpenPoly paves the way for more accurate polymer-property modeling and fosters data-driven advances in polymer genome engineering.展开更多
Turbine blade is one of the critical components of aircraft engine.The performance of the engine depends on the shape and dimensions of components,but superalloy blade material cannot be easily machined.Although inves...Turbine blade is one of the critical components of aircraft engine.The performance of the engine depends on the shape and dimensions of components,but superalloy blade material cannot be easily machined.Although investment casting is an ideal process for such net-shape components,it requires an accurate determination of the casting-die profile.In this paper,a reversing design methodology for investment casting die using ProCAST is proposed.By combining the methods of simplifying grid files and quick sorting,the efficiency of sorting and matching can be largely improved.Further,the mould/die cavity anti-deformation system can be easily built.With ProCAST,the optimized die profile for investment casting can be established.展开更多
A novel method to extract conic blending feature in reverse engineering is presented. Different from the methods to recover constant and variable radius blends from unorganized points, it contains not only novel segme...A novel method to extract conic blending feature in reverse engineering is presented. Different from the methods to recover constant and variable radius blends from unorganized points, it contains not only novel segmentation and feature recognition techniques, but also bias corrected technique to capture more reliable distribution of feature parameters along the spine curve. The segmentation depending on point classification separates the points in the conic blend region from the input point cloud. The available feature parameters of the cross-sectional curves are extracted with the processes of slicing point clouds with planes, conic curve fitting, and parameters estimation and compensation, The extracted parameters and its distribution laws are refined according to statistic theory such as regression analysis and hypothesis test. The proposed method can accurately capture the original design intentions and conveniently guide the reverse modeling process. Application examples are presented to verify the high precision and stability of the proposed method.展开更多
Bistable curved shells have become a promising low-cost application in energy absorption fields owing to recentadvances in material and technology.Significant research has been conducted to improve their energy absorp...Bistable curved shells have become a promising low-cost application in energy absorption fields owing to recentadvances in material and technology.Significant research has been conducted to improve their energy absorptioneffect through forward prediction and single-objective optimization.However,these approaches may not fully explore their functional potential.In this study,we propose a multi-objective optimization framework based on theprinciple of main objective optimization that combines neural networks and genetic algorithms.The energy absorption effect and backward snapping force of the bistable curved shell are improved synchronously.Meanwhile,a reverse design algorithm is developed to generate the preset load-displacement curve,which further expandsthe application of machine learning methods in the field of multi-objective optimization.The combination ofmachine learning and multi-objective optimization is highly effective for building meta-structures with specificperformance requirements and has potential applications in solving complex optimization tasks in various fields.展开更多
PCM windows are regarded as promising translucent building envelopes due to their ability to store solar heat and enhance thermal comfort.However,limitations in thermal insulation,phase transition rate,and climate ada...PCM windows are regarded as promising translucent building envelopes due to their ability to store solar heat and enhance thermal comfort.However,limitations in thermal insulation,phase transition rate,and climate adaptability hinder their further development.Hence,a novel triple-glazed window integrated with nano-enhanced PCM,reversible design and ventilation(NPRVTW)is proposed,while its dynamic photothermal transfer model is developed.Based on simulation results for the application in Guilin and Daqing,China,the thermal comfort and energy efficiency of NPRVTW are evaluated across different seasons and climates.The multi-technology coupling mechanisms are also discussed through comparisons with four other window configurations.The influences of physical properties,phase change temperature,and thickness of NPCM,as well as ventilation volume and strategy,are analyzed.The results show that adding nanoparticles to paraffin enhances solar absorption and accelerates phase change.Exhaust air in summer aids in heat removal and PCM solidification,while intake air in winter utilizes solar energy to preheat fresh air and heat the space.The reversible design regulates the direction of discharged heat to meet seasonal thermal demands.It can be concluded that NPRVTW exhibits excellent climate adaptability.In Guilin,the energy-saving rates in summer and winter are 41.84%and 55.62%,respectively,with NPCM4,phase change temperature of 27–29℃,a thickness of 20 mm,and a ventilation rate of 0.5 m/s recommended.展开更多
Taking AutoCAD2000 as platform, an algorithm for the reconstruction ofsurface from scattered data points based on VBA is presented. With this core technology customerscan be free from traditional AutoCAD as an electro...Taking AutoCAD2000 as platform, an algorithm for the reconstruction ofsurface from scattered data points based on VBA is presented. With this core technology customerscan be free from traditional AutoCAD as an electronic board and begin to create actual presentationof real-world objects. VBA is not only a very powerful tool of development, but with very simplesyntax. Associating with those solids, objects and commands of AutoCAD 2000, VBA notably simplifiesprevious complex algorithms, graphical presentations and processing, etc. Meanwhile, it can avoidappearance of complex data structure and data format in reverse design with other modeling software.Applying VBA to reverse engineering can greatly improve modeling efficiency and facilitate surfacereconstruction.展开更多
Shot peen-forming is a more precise method of forming aircraft panels than conventional methods.The traditional method of acquiring the process parameters relies mainly on prior theoretical knowledge and trial-and-err...Shot peen-forming is a more precise method of forming aircraft panels than conventional methods.The traditional method of acquiring the process parameters relies mainly on prior theoretical knowledge and trial-and-error.Despite the finite element method’s ability to replace some experimentation,it still cannot realize the design of shot peen forming processes parameters of an aircraft panel based on a known contour.This study uses an innovative model-based deep learning approach to predict aircraft panel deformation and active design the shot peening parameters.The prediction time is less than 1 second,resulting in a significant reduction in computational time.The shot peen forming process parameters and the geometric structure characteristics of the aircraft panel are divided into independent channels to establish a high-dimensional feature map,which are used to train the deep learning model.The forming contours of the 2024-T351 high-strength aluminum alloy panel are predicted under different shot peening processes.In addition,the process parameters are designed according to the known contour of the forming process.To verify the precision of the proposed method,the designed shot peen forming process is used to manufacture a single curvature aircraft panel with a curvature radius of 3500 mm.There is good agreement between the forming contour and the theoretical design contour.The maximum deformation error is less than 1 mm and its mean error is 7.8%.The mean curvature radius error is 5.668%.The proposed method provides a new and practical reference to the precise design of the shot peen-forming process.展开更多
In order to rapidly and accurately evaluate the mechanical properties of a novel origami-inspired tube structure with multiple parameter inputs,this study developed a method of designing origami-inspired braces based ...In order to rapidly and accurately evaluate the mechanical properties of a novel origami-inspired tube structure with multiple parameter inputs,this study developed a method of designing origami-inspired braces based on machine learning models.Four geometric parameters,i.e.,cross-sectional side length,plate thickness,crease weakening coefficient,and plane angles,were used to establish a mapping relationship with five mechanical parameters,including elastic stiffness,yield load,yield displacement,ultimate load,and ultimate displacement,all of which were calculated from load-displacement curves.Firstly,forward prediction models were trained and compared for single and multiple mechanical outputs.The parameter ranges were extended and refined to improve the predicted results by introducing the intrinsic mechanical relationships.Secondly,certain reverse prediction models were established to obtain the optimized design parameters.Finally,the design method of this study was verified in finite element methods.The design and analysis framework proposed in this study can be used to promote the application of other novel multi-parameter structures.展开更多
In this study,the motion characteristics of manual stirring were analyzed to achieve the goal of realizing a highquality mechanized imitation of manual stirring for oolong tea.A test bench for collecting the motion ch...In this study,the motion characteristics of manual stirring were analyzed to achieve the goal of realizing a highquality mechanized imitation of manual stirring for oolong tea.A test bench for collecting the motion characteristics of manual stirring was designed,and the standard manual stirring motion characteristic curve was obtained.According to the requirements of the stirring motion characteristics,a variable-speed and variable-amplitude stirring mechanism was proposed,the kinematics model and reverse design model of the stirring mechanism were established,auxiliary analysis and design software were written,and the non-circular gear pitch curve and cam profile curve were obtained.A three-dimensional model of the stirring machine was established,a virtual prototype of the stirring machine was built,and the simulation experiment was completed by using the ADAMS software.A prototype of the stirring machine was developed,and the stirring experiment was conducted on the prototype.The maximum deviation of the pitch angle is 2.8772°,and the maximum deviation of the roll angle is 1.5948°according to the analysis and comparison of the actual curve data and the theoretical data curve.The experimental results showed that the simulation angle curve and the actual angle curve were consistent with the theoretical standard manual stirring motion characteristic curve,which verified the correctness of the design and modeling of the stirring mechanism.The tea was mechanically stirred by the stirring mechanism to achieve the desired stirring effect,which verified the feasibility of the stirring machine.展开更多
文摘The reverse design of solid rocket motor(SRM)propellant grain involves determining the grain geometry to closely match a predefined internal ballistic curve.While existing reverse design methods are feasible,they often face challenges such as lengthy computation times and limited accuracy.To achieve rapid and accurate matching between the targeted ballistic curve and complex grain shape,this paper proposes a novel reverse design method for SRM propellant grain based on time-series data imaging and convolutional neural network(CNN).First,a finocyl grain shape-internal ballistic curve dataset is created using parametric modeling techniques to comprehensively cover the design space.Next,the internal ballistic time-series data is encoded into three-channel images,establishing a potential relationship between the ballistic curves and their image representations.A CNN is then constructed and trained using these encoded images.Once trained,the model enables efficient inference of propellant grain dimensions from a target internal ballistic curve.This paper conducts comparative experiments across various neural network models,validating the effectiveness of the feature extraction method that transforms internal ballistic time-series data into images,as well as its generalization capability across different CNN architectures.Ignition tests were performed based on the predicted propellant grain.The results demonstrate that the relative error between the experimental internal ballistic curves and the target curves is less than 5%,confirming the validity and feasibility of the proposed reverse design methodology.
基金National Natural Science Foundation of China(No.50875243)
文摘For the purpose of obtaining satisfactory performance of the non-circular gear & crank-rocker & gear trains (NCCRG) weft insertion mechanism which was proposed in this paper, the ideal kinematic curve of this weft insertion mechanism was given, and the reverse solution models of this mechanism were established. A reverse design and simulation software was compiled based on Visual Basic 6.0 to obtain the mechanism parameters, including the pitch curves and tooth profiles of the non-circular gears. A test-bed of this mechanism was developed according to these parameters. The kinematic performance of this weft insertion mechanism was tested by high-speed video tape recorder with its corresponding video analytical software Blaster's MAS. And the test results were identical with the theoretical calculation. Compared with the conjugate cam weft insertion mechanism which is applied on TT96 rapier loom, under the condition of same weft insertion rate, the variation of acceleration of this mechanism is smaller. This novel weft insertion mechanism can meet the requirements of weft insertion on rapier looms with smooth and steady motion.
基金financially supported by the National Natural Science Foundation of China(Grant No.32171899)the Basic Research Projects of the Wenzhou Science&Technology Bureau(Grant No.N20220001).
文摘In the previous research,the seedling pick-up mechanism of the planetary gear train with incomplete eccentric circular gear and non-circular gears for vegetable plug seedlings still has two shortcomings.One is that not enough seedling pick-up depth leads to a low success ratio of seedling pick-up at high rotation speeds,the other is that the smaller seedling pushing angle results in poor seedling pushing effect.Therefore,the reverse design of the seedling pick-up mechanism based on its motion trajectory was carried out.The local trajectory of seedling pick-up and seedling pushing sections was adjusted to obtain the theoretical motion trajectory of the seedling pick-up mechanism.The cubic non-uniform B-spline curve was used to fit the adjusted trajectory.A novel seedling pick-up mechanism of the planetary gear train with non-circular gears was proposed,including three combined non-circular gears,four non-circular gears,one planetary carrier,and two seedling pick-up arms.The reverse design model of the mechanism was established.The analysis and design software of the mechanism was developed to obtain the mechanism parameters meeting design requirements.The virtual prototype of the mechanism was established and its physical prototype was manufactured.Through the virtual motion simulation and high-speed photographic kinematics bench tests of the mechanism,the kinematic model and results of reverse design of the mechanism were verified,with the kinematic performances of the mechanism prototype studied.The seedling pick-up tests of the mechanism were conducted in the laboratory.The success ratios of seedling pick-up were 94.2%,95.6% and 90.2% while the seedling pick-up efficiencies of the mechanism were 60,80 and 100 plants per minute per row,respectively.Besides,the seedling pushing effect was improved mush because of the greater seedling pushing angle.The seedling pick-up mechanism through revise design is of high value to be applied in the practical vegetable plug seedling transplanters.
基金We are grateful for the financial support from the National Natural Science Foundation of China(32071342 and 82072513)Guangdong Special Support Program(2019TQ05Y209)+2 种基金the Natural Science Foun-dation of Guangdong Province(2021A1515010431)the Science and Technology Program of Guangzhou(202102080182)Several pic-ture materials from vecteezy.com are gratefully acknowledged.
文摘As a kind of nature-derived bioactive materials, polyphenol-based hydrogels possess many unique and outstanding properties such as adhesion, toughness, and self-healing due to their specific crosslinking structures, which have been widely used in biomedical fields including wound healing, antitumor, treatment of motor system injury, digestive system disease, oculopathy, and bioelectronics. In this review, starting with the classi-fication of common polyphenol-based hydrogels, the pyramid evolution process of polyphenol-based hydrogels from crosslinking structures to derived properties and then to biomedical applications is elaborated, as well as the efficient reverse design considerations of polyphenol-based hydrogel systems are proposed. Finally, the existing problems and development prospects of these hydrogel materials are discussed. It is hoped that the unique perspective of the review can promote further innovation and breakthroughs of polyphenol-based hydrogels in the future.
基金financial support from the National Natural Science Foundation of China (51775402 and U1931139)
文摘The Qi Tai Telescope(QTT),which has a 110 m aperture,is planned to be the largest scale steerable tele-scope in the world.Ideally,the telescope’s repeated pointing accuracy error should be less than 2.5 arc seconds(arcsec);thus,the telescope structure must satisfy ultra-high precision requirements.In this pur-suit,the present research envisages a reverse-design method for the track surface to reduce the difficulty of the telescope’s design and manufacture.First,the distribution characteristics of the test data for the track error were verified using the skewness coefficient and kurtosis coefficient methods.According to the distribution characteristics,the azimuth track error was simulated by a two-scale model.The error of the long period and short amplitude was characterized as large-scale and described by a trigonometric function,while the short period and high amplitude error was characterized as small-scale and simulated by a fractal function.Based on the two-scale model,effect of the error on the pointing accuracy was deduced.Subsequently,the relationship between the root mean square(RMS)of the track error and the RMS of the pointing accuracy error of the telescope was deduced.Finally,the allowable RMS value of the track error was derived from the allowable pointing accuracy errors.To validate the effectiveness of the new design method,two typical radio telescopes(the Green Bank Telescope(GBT)and the Large Millimeter Telescope(LMT))were selected as experimental examples.Through comparison,the theoretical calculated values of the pointing accuracy of the telescope were consistent with the measured values,with a maximum error of less than 10%.
基金financially supported by the National Natural Science Foundation of China (Nos. 92372126,52373203)the Excellent Young Scientists Fund Program
文摘Advancing the integration of artificial intelligence and polymer science requires high-quality,open-source,and large-scale datasets.However,existing polymer databases often suffer from data sparsity,lack of polymer-property labels,and limited accessibility,hindering system-atic modeling across property prediction tasks.Here,we present OpenPoly,a curated experimental polymer database derived from extensive lit-erature mining and manual validation,comprising 3985 unique polymer-property data points spanning 26 key properties.We further develop a multi-task benchmarking framework that evaluates property prediction using four encoding methods and eight representative models.Our re-sults highlight that the optimized degree-of-polymerization encoding coupled with Morgan fingerprints achieves an optimal trade-off between computational cost and accuracy.In data-scarce condition,XGBoost outperforms deep learning models on key properties such as dielectric con-stant,glass transition temperature,melting point,and mechanical strength,achieving R2 scores of 0.65-0.87.To further showcase the practical utility of the database,we propose potential polymers for two energy-relevant applications:high temperature polymer dielectrics and fuel cell membranes.By offering a consistent and accessible benchmark and database,OpenPoly paves the way for more accurate polymer-property modeling and fosters data-driven advances in polymer genome engineering.
基金supported by National Key Technologies R&D Program under Grant No. 2006BAF04B02
文摘Turbine blade is one of the critical components of aircraft engine.The performance of the engine depends on the shape and dimensions of components,but superalloy blade material cannot be easily machined.Although investment casting is an ideal process for such net-shape components,it requires an accurate determination of the casting-die profile.In this paper,a reversing design methodology for investment casting die using ProCAST is proposed.By combining the methods of simplifying grid files and quick sorting,the efficiency of sorting and matching can be largely improved.Further,the mould/die cavity anti-deformation system can be easily built.With ProCAST,the optimized die profile for investment casting can be established.
基金This project is supported by General Electric Company and National Advanced Technology Project of China(No.863-511-942-018).
文摘A novel method to extract conic blending feature in reverse engineering is presented. Different from the methods to recover constant and variable radius blends from unorganized points, it contains not only novel segmentation and feature recognition techniques, but also bias corrected technique to capture more reliable distribution of feature parameters along the spine curve. The segmentation depending on point classification separates the points in the conic blend region from the input point cloud. The available feature parameters of the cross-sectional curves are extracted with the processes of slicing point clouds with planes, conic curve fitting, and parameters estimation and compensation, The extracted parameters and its distribution laws are refined according to statistic theory such as regression analysis and hypothesis test. The proposed method can accurately capture the original design intentions and conveniently guide the reverse modeling process. Application examples are presented to verify the high precision and stability of the proposed method.
基金supported by the National Natural Science Foundation of China(Grant Nos.12102143,12172151,and 12172149)National funded postdoctoral researcher program(Grant No.GZC20230962)+4 种基金Guangdong Basic and Applied Basic Research Foundation(Grant No.2024A1515010379)Natural Science Foundation of Guangzhou City(Grant Nos.202201010217,202201020539,and 2024A04J3401)Young Talent Support Project of Guangzhou Association for Science and Technology,the Fellowship of China Postdoctoral Science Foundation(Grant No.2022M711333)the Fundamental Research Funds for the Central Universities(Grant No.21623332)the High Performance Public Computing Service Platform of Jinan University.
文摘Bistable curved shells have become a promising low-cost application in energy absorption fields owing to recentadvances in material and technology.Significant research has been conducted to improve their energy absorptioneffect through forward prediction and single-objective optimization.However,these approaches may not fully explore their functional potential.In this study,we propose a multi-objective optimization framework based on theprinciple of main objective optimization that combines neural networks and genetic algorithms.The energy absorption effect and backward snapping force of the bistable curved shell are improved synchronously.Meanwhile,a reverse design algorithm is developed to generate the preset load-displacement curve,which further expandsthe application of machine learning methods in the field of multi-objective optimization.The combination ofmachine learning and multi-objective optimization is highly effective for building meta-structures with specificperformance requirements and has potential applications in solving complex optimization tasks in various fields.
基金supported by the Natural Science Foundation of Guangxi Province No.2024GXNSFAA010421the National Science Foundation of China No.52368009 and No.52078110.
文摘PCM windows are regarded as promising translucent building envelopes due to their ability to store solar heat and enhance thermal comfort.However,limitations in thermal insulation,phase transition rate,and climate adaptability hinder their further development.Hence,a novel triple-glazed window integrated with nano-enhanced PCM,reversible design and ventilation(NPRVTW)is proposed,while its dynamic photothermal transfer model is developed.Based on simulation results for the application in Guilin and Daqing,China,the thermal comfort and energy efficiency of NPRVTW are evaluated across different seasons and climates.The multi-technology coupling mechanisms are also discussed through comparisons with four other window configurations.The influences of physical properties,phase change temperature,and thickness of NPCM,as well as ventilation volume and strategy,are analyzed.The results show that adding nanoparticles to paraffin enhances solar absorption and accelerates phase change.Exhaust air in summer aids in heat removal and PCM solidification,while intake air in winter utilizes solar energy to preheat fresh air and heat the space.The reversible design regulates the direction of discharged heat to meet seasonal thermal demands.It can be concluded that NPRVTW exhibits excellent climate adaptability.In Guilin,the energy-saving rates in summer and winter are 41.84%and 55.62%,respectively,with NPCM4,phase change temperature of 27–29℃,a thickness of 20 mm,and a ventilation rate of 0.5 m/s recommended.
文摘Taking AutoCAD2000 as platform, an algorithm for the reconstruction ofsurface from scattered data points based on VBA is presented. With this core technology customerscan be free from traditional AutoCAD as an electronic board and begin to create actual presentationof real-world objects. VBA is not only a very powerful tool of development, but with very simplesyntax. Associating with those solids, objects and commands of AutoCAD 2000, VBA notably simplifiesprevious complex algorithms, graphical presentations and processing, etc. Meanwhile, it can avoidappearance of complex data structure and data format in reverse design with other modeling software.Applying VBA to reverse engineering can greatly improve modeling efficiency and facilitate surfacereconstruction.
基金supported by Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX21_0231)Jiangsu Provincial Key Research and Development Program(No.BE2021060)The authors thank the Key Projects of Scientific Research in Colleges and Universities of Anhui Provincial Department of Education(No.KJ2021A0367).
文摘Shot peen-forming is a more precise method of forming aircraft panels than conventional methods.The traditional method of acquiring the process parameters relies mainly on prior theoretical knowledge and trial-and-error.Despite the finite element method’s ability to replace some experimentation,it still cannot realize the design of shot peen forming processes parameters of an aircraft panel based on a known contour.This study uses an innovative model-based deep learning approach to predict aircraft panel deformation and active design the shot peening parameters.The prediction time is less than 1 second,resulting in a significant reduction in computational time.The shot peen forming process parameters and the geometric structure characteristics of the aircraft panel are divided into independent channels to establish a high-dimensional feature map,which are used to train the deep learning model.The forming contours of the 2024-T351 high-strength aluminum alloy panel are predicted under different shot peening processes.In addition,the process parameters are designed according to the known contour of the forming process.To verify the precision of the proposed method,the designed shot peen forming process is used to manufacture a single curvature aircraft panel with a curvature radius of 3500 mm.There is good agreement between the forming contour and the theoretical design contour.The maximum deformation error is less than 1 mm and its mean error is 7.8%.The mean curvature radius error is 5.668%.The proposed method provides a new and practical reference to the precise design of the shot peen-forming process.
基金supported by the Jiangsu Provincial Department of Science and Technology Projects(BZ2022049 and BE2023801).
文摘In order to rapidly and accurately evaluate the mechanical properties of a novel origami-inspired tube structure with multiple parameter inputs,this study developed a method of designing origami-inspired braces based on machine learning models.Four geometric parameters,i.e.,cross-sectional side length,plate thickness,crease weakening coefficient,and plane angles,were used to establish a mapping relationship with five mechanical parameters,including elastic stiffness,yield load,yield displacement,ultimate load,and ultimate displacement,all of which were calculated from load-displacement curves.Firstly,forward prediction models were trained and compared for single and multiple mechanical outputs.The parameter ranges were extended and refined to improve the predicted results by introducing the intrinsic mechanical relationships.Secondly,certain reverse prediction models were established to obtain the optimized design parameters.Finally,the design method of this study was verified in finite element methods.The design and analysis framework proposed in this study can be used to promote the application of other novel multi-parameter structures.
基金supported by the National Natural Science Foundation of China(Grant Nos.51975536 and U23A20175)the China Agriculture Research System of MOF and MARA.The authors also acknowledge American Journal Experts for their language assistance during the preparation of this article.
文摘In this study,the motion characteristics of manual stirring were analyzed to achieve the goal of realizing a highquality mechanized imitation of manual stirring for oolong tea.A test bench for collecting the motion characteristics of manual stirring was designed,and the standard manual stirring motion characteristic curve was obtained.According to the requirements of the stirring motion characteristics,a variable-speed and variable-amplitude stirring mechanism was proposed,the kinematics model and reverse design model of the stirring mechanism were established,auxiliary analysis and design software were written,and the non-circular gear pitch curve and cam profile curve were obtained.A three-dimensional model of the stirring machine was established,a virtual prototype of the stirring machine was built,and the simulation experiment was completed by using the ADAMS software.A prototype of the stirring machine was developed,and the stirring experiment was conducted on the prototype.The maximum deviation of the pitch angle is 2.8772°,and the maximum deviation of the roll angle is 1.5948°according to the analysis and comparison of the actual curve data and the theoretical data curve.The experimental results showed that the simulation angle curve and the actual angle curve were consistent with the theoretical standard manual stirring motion characteristic curve,which verified the correctness of the design and modeling of the stirring mechanism.The tea was mechanically stirred by the stirring mechanism to achieve the desired stirring effect,which verified the feasibility of the stirring machine.
