Machine learning(ML)has been increasingly adopted to solve engineering problems with performance gauged by accuracy,efficiency,and security.Notably,blockchain technology(BT)has been added to ML when security is a part...Machine learning(ML)has been increasingly adopted to solve engineering problems with performance gauged by accuracy,efficiency,and security.Notably,blockchain technology(BT)has been added to ML when security is a particular concern.Nevertheless,there is a research gap that prevailing solutions focus primarily on data security using blockchain but ignore computational security,making the traditional ML process vulnerable to off-chain risks.Therefore,the research objective is to develop a novel ML on blockchain(MLOB)framework to ensure both the data and computational process security.The central tenet is to place them both on the blockchain,execute them as blockchain smart contracts,and protect the execution records on-chain.The framework is established by developing a prototype and further calibrated using a case study of industrial inspection.It is shown that the MLOB framework,compared with existing ML and BT isolated solutions,is superior in terms of security(successfully defending against corruption on six designed attack scenario),maintaining accuracy(0.01%difference with baseline),albeit with a slightly compromised efficiency(0.231 second latency increased).The key finding is MLOB can significantly enhances the computational security of engineering computing without increasing computing power demands.This finding can alleviate concerns regarding the computational resource requirements of ML-BT integration.With proper adaption,the MLOB framework can inform various novel solutions to achieve computational security in broader engineering challenges.展开更多
Integrated computational materials engineering(ICME)is to integrate multi-scale computational simulations and key experimental methods such as macroscopic,mesoscopic,and microscopic into the whole process of Al alloys...Integrated computational materials engineering(ICME)is to integrate multi-scale computational simulations and key experimental methods such as macroscopic,mesoscopic,and microscopic into the whole process of Al alloys design and development,which enables the design and development of Al alloys to upgrade from traditional empirical to the integration of compositionprocess-structure-mechanical property,thus greatly accelerating its development speed and reducing its development cost.This study combines calculation of phase diagram(CALPHAD),Finite element calculations,first principle calculations,and microstructure characterization methods to predict and regulate the formation and structure of composite precipitates from the design of highmodulus Al alloy compositions and optimize the casting process parameters to inhibit the formation of micropore defects in the casting process,and the final tensile strength of Al alloys reaches420 MPa and Young's modulus reaches more than 88 GPa,which achieves the design goal of the high strength and modulus Al alloys,and establishes a new mode of the design and development of the strength/modulus Al alloys.展开更多
Casting technology is a fundamental and irreplaceable method in advanced manufacturing.The design and optimization of casting processes are crucial for producing high-performance,complex metal components.Transitioning...Casting technology is a fundamental and irreplaceable method in advanced manufacturing.The design and optimization of casting processes are crucial for producing high-performance,complex metal components.Transitioning from traditional process design based on"experience+experiment"to an integrated,intelligent approach is essential for achieving precise control over microstructure and properties.This paper provides a comprehensive and systematic review of intelligent casting process design and optimization for the first time.First,it explores process design methods based on casting simulation and integrated computational materials engineering(ICME).It then examines the application of machine learning(ML)in process design,highlighting its efficiency and existing challenges,along with the development of integrated intelligent design platforms.Finally,future research directions are discussed to drive further advancements and sustainable development in intelligent casting design and optimization.展开更多
This paper presents a comprehensive evaluation of Electric Spring(ES)performance through simulation experiments and polynomial regression modelling.The study pri-marily aims to assess how varying load impedance ratios...This paper presents a comprehensive evaluation of Electric Spring(ES)performance through simulation experiments and polynomial regression modelling.The study pri-marily aims to assess how varying load impedance ratios impact ES performance,develop a polynomial regression model to predict the relationship between ES parameters and the ratio of non-critical to critical load impedance,and validate the model against simulation results.Detailed simulations were performed to analyse the effects of different impedance ratios on ES behaviour.Subsequently,a polynomial regression model was formulated to accurately capture the relationship between the ES parameters and impedance ratios.The findings indicate that the polynomial regression model effectively predicts ES perfor-mance,with the predicted values closely matching the simulation results.The validation process confirms the model's accuracy and reliability,demonstrating its potential for practical applications in optimising ES performance under various impedance conditions.This study offers valuable insights into the enhancement of ES systems through precise modelling and analysis,contributing to improved stability and efficiency in power systems.展开更多
The rise of scientific computing was one of the most important advances in the S&T progress during the second half of the 20th century. Parallel with theoretical exploration and scientific experiments,scientific c...The rise of scientific computing was one of the most important advances in the S&T progress during the second half of the 20th century. Parallel with theoretical exploration and scientific experiments,scientific computing has become the 'third means' for scientific activities in the world today. The article gives a panoramic review of the subject during the past 50 years in China and lists the contributions made by Chinese scientists in this field. In addition, it reveals some key contents of related projects in the national research plan and looks into the development vista for the subject in China at the dawning years of the new century.展开更多
Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient manner.Identifying different types of brain tumors,including gliomas,meningiomas,p...Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient manner.Identifying different types of brain tumors,including gliomas,meningiomas,pituitary tumors,as well as confirming the absence of tumors,poses a significant challenge using MRI images.Current approaches predominantly rely on traditional machine learning and basic deep learning methods for image classification.These methods often rely on manual feature extraction and basic convolutional neural networks(CNNs).The limitations include inadequate accuracy,poor generalization of new data,and limited ability to manage the high variability in MRI images.Utilizing the EfficientNetB3 architecture,this study presents a groundbreaking approach in the computational engineering domain,enhancing MRI-based brain tumor classification.Our approach highlights a major advancement in employing sophisticated machine learning techniques within Computer Science and Engineering,showcasing a highly accurate framework with significant potential for healthcare technologies.The model achieves an outstanding 99%accuracy,exhibiting balanced precision,recall,and F1-scores across all tumor types,as detailed in the classification report.This successful implementation demonstrates the model’s potential as an essential tool for diagnosing and classifying brain tumors,marking a notable improvement over current methods.The integration of such advanced computational techniques in medical diagnostics can significantly enhance accuracy and efficiency,paving the way for wider application.This research highlights the revolutionary impact of deep learning technologies in improving diagnostic processes and patient outcomes in neuro-oncology.展开更多
Metal additive manufacturing(MAM)technology has experienced rapid development in recent years.As both equipment and materials progress towards increased maturity and commercialization,material metallurgy technology ba...Metal additive manufacturing(MAM)technology has experienced rapid development in recent years.As both equipment and materials progress towards increased maturity and commercialization,material metallurgy technology based on high energy sources has become a key factor influencing the future development of MAM.The calculation of phase diagrams(CALPHAD)is an essential method and tool for constructing multi-component phase diagrams by employing experimental phase diagrams and Gibbs free energy models of simple systems.By combining with the element mobility data and non-equilibrium phase transition model,it has been widely used in the analysis of traditional metal materials.The development of CALPHAD application technology for MAM is focused on the compositional design of printable materials,the reduction of metallurgical imperfections,and the control of microstructural attributes.This endeavor carries considerable theoretical and practical significance.This paper summarizes the important achievements of CALPHAD in additive manufacturing(AM)technology in recent years,including material design,process parameter optimization,microstructure evolution simulation,and properties prediction.Finally,the limitations of applying CALPHAD technology to MAM technology are discussed,along with prospective research directions.展开更多
Academician of the CAE member Youxian Sun from Zhejiang University initiated Digital Twins and Applications(ISSN 2995-2182).It is published by Zhejiang University Press and the Institution of Engineering and Technolog...Academician of the CAE member Youxian Sun from Zhejiang University initiated Digital Twins and Applications(ISSN 2995-2182).It is published by Zhejiang University Press and the Institution of Engineering and Technology and sponsored by Zhejiang Univer-sity.Digital Twins and Applications aim to provide a specialised platform for researchers,practitioners,and industry experts to publish high-quality,state-of-the-art research on digital twin technologies and their applications.展开更多
Adopting digital twin technology in the chemical industry is reshaping process optimisation,operational efficiency,and safety management.By leveraging data from sensors and control systems,the digital twins provide ac...Adopting digital twin technology in the chemical industry is reshaping process optimisation,operational efficiency,and safety management.By leveraging data from sensors and control systems,the digital twins provide actionable insights,enabling more precise control over chemical reactions,improved quality assurance,and reduced environmental impact.Additionally,the ability to simulate“what-if”scenarios accelerates the innovation cycle and supports compliance with stringent regulatory standards.This research article explores the implementation and impact of digital twins in chemical manufacturing environments.It examines how digital twins enable continuous monitoring and control by mirroring chemical processes,predicting equipment failures,and simulating complex reactions under various conditions.The study highlights the benefits of digital twins,including improved process efficiency,enhanced product quality,and reduced environmental and operational risks.The research also addresses challenges and limitations,such as data integration complexities and the need for high-fidelity models.By providing a comprehensive analysis of current applications and future prospects,this paper aims to advance the understanding of digital twins'role in driving innovation and sustainability within the chemical industry.展开更多
Artificial intelligent aided design and manufacturing have been recognized as one kind of robust data-driven and data-intensive technologies in the integrated computational material engi-neering(ICME)era.Motivated by ...Artificial intelligent aided design and manufacturing have been recognized as one kind of robust data-driven and data-intensive technologies in the integrated computational material engi-neering(ICME)era.Motivated by the dramatical developments of the services of China Railway High-speed series for more than a decade,it is essential to reveal the foundations of lifecycle man-agement of those trains under environmental conditions.Here,the smart design and manufacturing of welded Q350 steel frames of CR200J series are introduced,presenting the capability and opportu-nity of ICME in weight reduction and lifecycle management at a cost-effective approach.In order to address the required fatigue life time enduring more than 9×10^(6)km,the response of optimized frames to the static and the dynamic loads are comprehensively investigated.It is highlighted that the maximum residual stress of the optimized welded frame is reduced to 69 MPa from 477 MPa of previous existing one.Based on the measured stress and acceleration from the railways,the fatigue life of modified frame under various loading modes could fulfil the requirements of the lifecycle man-agement.Moreover,our recent developed intelligent quality control strategy of welding process mediated by machine learning is also introduced,envisioning its application in the intelligent weld-ing.展开更多
The state of art and future prospects are described for the application of the computational fluid dynamics to engineering purposes.2D and 3D simulations are presented for a flow about a pair of bridges,a flow about a...The state of art and future prospects are described for the application of the computational fluid dynamics to engineering purposes.2D and 3D simulations are presented for a flow about a pair of bridges,a flow about a cylin- der in waves,a flow about an airplane and a ship,a flow past a sphere,a two layers flow and a flow in a wall boundary layer,The choice of grid system and of turbulence modei is discussed.展开更多
Amid the digital revolution,this research explores a groundbreaking topicthe potential impact of metaverse services on the future of computing and engineering education.The transformative potential of metaverse servic...Amid the digital revolution,this research explores a groundbreaking topicthe potential impact of metaverse services on the future of computing and engineering education.The transformative potential of metaverse services in education is a beacon of the future,promising new learning modes in digital environments.This work poses two questions:Will metaverse services affect computing and engineering education learning?If so,to what extent has computing and engineering education adopted metaverse services in its curricula?To address these queries,the authors researched several metaverse activities affecting computing and engineering education.The new concepts of metaverse services,metaverse education services,and metaverse education service space are presented and analyzed.This research also discusses the influences of metaverse and services on computing and engineering education.The research showed a transformation toward metaverse service education in the evolving digital era.Academic and industry professionals must recognize the critical need to prepare students and graduates for the digital era adequately.The future is coming whereby metaverse,higher education,and services will generate a new destiny for computing and engineering education with new learning modes in digital environments.The transformative potential of metaverse services in education cannot be overstated,and the academic and industry communities must recognize and embrace this phenomenon.展开更多
The digital twins(DT)has quickly become a hot topic since it was proposed.It appears in all kinds of commercial propaganda and is widely quoted by academic circles.However,the term DT has misstatements and is misused ...The digital twins(DT)has quickly become a hot topic since it was proposed.It appears in all kinds of commercial propaganda and is widely quoted by academic circles.However,the term DT has misstatements and is misused in business and academics.This study revisits DT and defines it to be a more advanced system/product/service modeling and simulation environment that combines most modern information communication technologies(ICTs)and engineering mechanism digitization and characterized by system/product/service life cycle management,physically geometric visualization,real-time sensing and measurement of system operating conditions,predictability of system performance/safety/lifespan,and complete engineering mechanisms-based simulations.The idea of DT originates from modeling and simulation practices of engineering informatization,including virtual manufacturing(VM),model predictive control,and building information modeling(BIM).On the basis of the two-element VM model,we propose a three-element model to represent DT.DT does not have its unique technical characteristics.The existing practices of DT are extensions of the engineering informatization embracing modern ICTs.These insights clarify the origin of DT and its technical essentials.展开更多
Rotating separation flow(RSF)in hydraulic machinery is characterized by the large flow separations and complex vortical structures induced by the effects of strong rotation,large curvature and multiple wall surfaces,a...Rotating separation flow(RSF)in hydraulic machinery is characterized by the large flow separations and complex vortical structures induced by the effects of strong rotation,large curvature and multiple wall surfaces,and conducting efficient engineering computation and putting forward effective control strategy for the RSF are important topics in the inner flow theory.To meet these engineering requirements,the studies on computational method and control strategy of the RSF are conducted in this paper.In terms of the computational method,the time-scale-driven(TSD)hybrid unsteady Reynolds-averaged Navier-Stokes/large eddy simulation(URANS/LES)modelling strategy is clarified,and an adaptive TSD hybrid model is established based on the RSF characteristics in hydraulic machinery,thereby avoiding the problem of non-monotonic grid convergence and improving the robustness.Besides,a novel vortex-feature-driven idea suitable for the RSF is further developed inspired by it.In terms of the control strategy,the secondary flow generation mechanism in a rotor domain is revealed,and the relationship between natural secondary flows and blade loading distributions is grasped.On the basis of it,an active control strategy with general significance is proposed,and a general alternate loading technique(GALT)is established.Both aspects can provide generalized paradigms with expandable potential,which are of benefit to the efficient computation and effective control of the RSF in hydraulic machinery.展开更多
A novel Omega(Ω)-driven dynamic partially-averaged Navier-Stokes(PANS)model is proposed in this paper.The ratio of the modeled-to-total turbulent kinetic energies fk is dynamically adjusted by the rigid vorticity rat...A novel Omega(Ω)-driven dynamic partially-averaged Navier-Stokes(PANS)model is proposed in this paper.The ratio of the modeled-to-total turbulent kinetic energies fk is dynamically adjusted by the rigid vorticity ratio(the ratio of the rigid vorticity to the total vorticity),the key parameter of the Ω vortex identification method.Three classical flow cases with rotation and curvature are used to test the model.The results show that the turbulent viscosity is effectively adjusted by the new dynamic fk and the LES-like mode is activated,which can help the revelation of more turbulence information and improve the prediction accuracy.The new PANS model does not contain any explicit dependency on the grid size and enjoys good adaptability to the flow fields,and can be used for efficient engineering computations of the turbulent flows in the hydraulic machinery.展开更多
In recent years many long-span bridges have been or are being constructed in the world, especially in China. Wind loads and responses are the key factors for their structural design. This paper introduces some importa...In recent years many long-span bridges have been or are being constructed in the world, especially in China. Wind loads and responses are the key factors for their structural design. This paper introduces some important achievements of wind-resistant studies of the author's research team on long-span bridges. First, new concepts and identification methods of aerodynamic derivatives and aerodynamic admittances were proposed. Then mechanical and aerodynamic control strategies and methods of wind-induced vibrations of long-span bridges were the great concerned problems, and valuable achievements were presented. Especially, great efforts which have been theoretically and experimentally made on rain-wind induced vibration of cables of cable-stayed bridges were described. Finally, some new progresses in computation wind engineering were introduced, and a new method for simulating an equilibrium boundary layer was put forward as well.展开更多
文摘Machine learning(ML)has been increasingly adopted to solve engineering problems with performance gauged by accuracy,efficiency,and security.Notably,blockchain technology(BT)has been added to ML when security is a particular concern.Nevertheless,there is a research gap that prevailing solutions focus primarily on data security using blockchain but ignore computational security,making the traditional ML process vulnerable to off-chain risks.Therefore,the research objective is to develop a novel ML on blockchain(MLOB)framework to ensure both the data and computational process security.The central tenet is to place them both on the blockchain,execute them as blockchain smart contracts,and protect the execution records on-chain.The framework is established by developing a prototype and further calibrated using a case study of industrial inspection.It is shown that the MLOB framework,compared with existing ML and BT isolated solutions,is superior in terms of security(successfully defending against corruption on six designed attack scenario),maintaining accuracy(0.01%difference with baseline),albeit with a slightly compromised efficiency(0.231 second latency increased).The key finding is MLOB can significantly enhances the computational security of engineering computing without increasing computing power demands.This finding can alleviate concerns regarding the computational resource requirements of ML-BT integration.With proper adaption,the MLOB framework can inform various novel solutions to achieve computational security in broader engineering challenges.
基金supported by the National Natural Science Foundation of China(No.52073030)。
文摘Integrated computational materials engineering(ICME)is to integrate multi-scale computational simulations and key experimental methods such as macroscopic,mesoscopic,and microscopic into the whole process of Al alloys design and development,which enables the design and development of Al alloys to upgrade from traditional empirical to the integration of compositionprocess-structure-mechanical property,thus greatly accelerating its development speed and reducing its development cost.This study combines calculation of phase diagram(CALPHAD),Finite element calculations,first principle calculations,and microstructure characterization methods to predict and regulate the formation and structure of composite precipitates from the design of highmodulus Al alloy compositions and optimize the casting process parameters to inhibit the formation of micropore defects in the casting process,and the final tensile strength of Al alloys reaches420 MPa and Young's modulus reaches more than 88 GPa,which achieves the design goal of the high strength and modulus Al alloys,and establishes a new mode of the design and development of the strength/modulus Al alloys.
基金supported by the National Natural Science Foundation of China(No.52074246)the National Defense Basic Scientific Research Program of China(No.JCKY2020408B002)+1 种基金the Key R&D Program of Shanxi Province(No.202102050201011)the Shanxi Province Graduate Innovation Project(No.2021Y591).
文摘Casting technology is a fundamental and irreplaceable method in advanced manufacturing.The design and optimization of casting processes are crucial for producing high-performance,complex metal components.Transitioning from traditional process design based on"experience+experiment"to an integrated,intelligent approach is essential for achieving precise control over microstructure and properties.This paper provides a comprehensive and systematic review of intelligent casting process design and optimization for the first time.First,it explores process design methods based on casting simulation and integrated computational materials engineering(ICME).It then examines the application of machine learning(ML)in process design,highlighting its efficiency and existing challenges,along with the development of integrated intelligent design platforms.Finally,future research directions are discussed to drive further advancements and sustainable development in intelligent casting design and optimization.
文摘This paper presents a comprehensive evaluation of Electric Spring(ES)performance through simulation experiments and polynomial regression modelling.The study pri-marily aims to assess how varying load impedance ratios impact ES performance,develop a polynomial regression model to predict the relationship between ES parameters and the ratio of non-critical to critical load impedance,and validate the model against simulation results.Detailed simulations were performed to analyse the effects of different impedance ratios on ES behaviour.Subsequently,a polynomial regression model was formulated to accurately capture the relationship between the ES parameters and impedance ratios.The findings indicate that the polynomial regression model effectively predicts ES perfor-mance,with the predicted values closely matching the simulation results.The validation process confirms the model's accuracy and reliability,demonstrating its potential for practical applications in optimising ES performance under various impedance conditions.This study offers valuable insights into the enhancement of ES systems through precise modelling and analysis,contributing to improved stability and efficiency in power systems.
文摘The rise of scientific computing was one of the most important advances in the S&T progress during the second half of the 20th century. Parallel with theoretical exploration and scientific experiments,scientific computing has become the 'third means' for scientific activities in the world today. The article gives a panoramic review of the subject during the past 50 years in China and lists the contributions made by Chinese scientists in this field. In addition, it reveals some key contents of related projects in the national research plan and looks into the development vista for the subject in China at the dawning years of the new century.
基金supported by the Researchers Supporting Program at King Saud University.Researchers Supporting Project number(RSPD2024R867),King Saud University,Riyadh,Saudi Arabia.
文摘Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient manner.Identifying different types of brain tumors,including gliomas,meningiomas,pituitary tumors,as well as confirming the absence of tumors,poses a significant challenge using MRI images.Current approaches predominantly rely on traditional machine learning and basic deep learning methods for image classification.These methods often rely on manual feature extraction and basic convolutional neural networks(CNNs).The limitations include inadequate accuracy,poor generalization of new data,and limited ability to manage the high variability in MRI images.Utilizing the EfficientNetB3 architecture,this study presents a groundbreaking approach in the computational engineering domain,enhancing MRI-based brain tumor classification.Our approach highlights a major advancement in employing sophisticated machine learning techniques within Computer Science and Engineering,showcasing a highly accurate framework with significant potential for healthcare technologies.The model achieves an outstanding 99%accuracy,exhibiting balanced precision,recall,and F1-scores across all tumor types,as detailed in the classification report.This successful implementation demonstrates the model’s potential as an essential tool for diagnosing and classifying brain tumors,marking a notable improvement over current methods.The integration of such advanced computational techniques in medical diagnostics can significantly enhance accuracy and efficiency,paving the way for wider application.This research highlights the revolutionary impact of deep learning technologies in improving diagnostic processes and patient outcomes in neuro-oncology.
基金supported by the National Key Research and Development Program of China(No.2021YFB3702500)。
文摘Metal additive manufacturing(MAM)technology has experienced rapid development in recent years.As both equipment and materials progress towards increased maturity and commercialization,material metallurgy technology based on high energy sources has become a key factor influencing the future development of MAM.The calculation of phase diagrams(CALPHAD)is an essential method and tool for constructing multi-component phase diagrams by employing experimental phase diagrams and Gibbs free energy models of simple systems.By combining with the element mobility data and non-equilibrium phase transition model,it has been widely used in the analysis of traditional metal materials.The development of CALPHAD application technology for MAM is focused on the compositional design of printable materials,the reduction of metallurgical imperfections,and the control of microstructural attributes.This endeavor carries considerable theoretical and practical significance.This paper summarizes the important achievements of CALPHAD in additive manufacturing(AM)technology in recent years,including material design,process parameter optimization,microstructure evolution simulation,and properties prediction.Finally,the limitations of applying CALPHAD technology to MAM technology are discussed,along with prospective research directions.
文摘Academician of the CAE member Youxian Sun from Zhejiang University initiated Digital Twins and Applications(ISSN 2995-2182).It is published by Zhejiang University Press and the Institution of Engineering and Technology and sponsored by Zhejiang Univer-sity.Digital Twins and Applications aim to provide a specialised platform for researchers,practitioners,and industry experts to publish high-quality,state-of-the-art research on digital twin technologies and their applications.
文摘Adopting digital twin technology in the chemical industry is reshaping process optimisation,operational efficiency,and safety management.By leveraging data from sensors and control systems,the digital twins provide actionable insights,enabling more precise control over chemical reactions,improved quality assurance,and reduced environmental impact.Additionally,the ability to simulate“what-if”scenarios accelerates the innovation cycle and supports compliance with stringent regulatory standards.This research article explores the implementation and impact of digital twins in chemical manufacturing environments.It examines how digital twins enable continuous monitoring and control by mirroring chemical processes,predicting equipment failures,and simulating complex reactions under various conditions.The study highlights the benefits of digital twins,including improved process efficiency,enhanced product quality,and reduced environmental and operational risks.The research also addresses challenges and limitations,such as data integration complexities and the need for high-fidelity models.By providing a comprehensive analysis of current applications and future prospects,this paper aims to advance the understanding of digital twins'role in driving innovation and sustainability within the chemical industry.
基金supported by the National Basic Scientific Research Project of China (No.JCKY2020607B003)CRRC (No.202CDA001)
文摘Artificial intelligent aided design and manufacturing have been recognized as one kind of robust data-driven and data-intensive technologies in the integrated computational material engi-neering(ICME)era.Motivated by the dramatical developments of the services of China Railway High-speed series for more than a decade,it is essential to reveal the foundations of lifecycle man-agement of those trains under environmental conditions.Here,the smart design and manufacturing of welded Q350 steel frames of CR200J series are introduced,presenting the capability and opportu-nity of ICME in weight reduction and lifecycle management at a cost-effective approach.In order to address the required fatigue life time enduring more than 9×10^(6)km,the response of optimized frames to the static and the dynamic loads are comprehensively investigated.It is highlighted that the maximum residual stress of the optimized welded frame is reduced to 69 MPa from 477 MPa of previous existing one.Based on the measured stress and acceleration from the railways,the fatigue life of modified frame under various loading modes could fulfil the requirements of the lifecycle man-agement.Moreover,our recent developed intelligent quality control strategy of welding process mediated by machine learning is also introduced,envisioning its application in the intelligent weld-ing.
文摘The state of art and future prospects are described for the application of the computational fluid dynamics to engineering purposes.2D and 3D simulations are presented for a flow about a pair of bridges,a flow about a cylin- der in waves,a flow about an airplane and a ship,a flow past a sphere,a two layers flow and a flow in a wall boundary layer,The choice of grid system and of turbulence modei is discussed.
基金research team on metaverse education and services in Harbin Institute of Technology,and the National Science Foundation of the United States for supporting the DEAP Project(#2111435).
文摘Amid the digital revolution,this research explores a groundbreaking topicthe potential impact of metaverse services on the future of computing and engineering education.The transformative potential of metaverse services in education is a beacon of the future,promising new learning modes in digital environments.This work poses two questions:Will metaverse services affect computing and engineering education learning?If so,to what extent has computing and engineering education adopted metaverse services in its curricula?To address these queries,the authors researched several metaverse activities affecting computing and engineering education.The new concepts of metaverse services,metaverse education services,and metaverse education service space are presented and analyzed.This research also discusses the influences of metaverse and services on computing and engineering education.The research showed a transformation toward metaverse service education in the evolving digital era.Academic and industry professionals must recognize the critical need to prepare students and graduates for the digital era adequately.The future is coming whereby metaverse,higher education,and services will generate a new destiny for computing and engineering education with new learning modes in digital environments.The transformative potential of metaverse services in education cannot be overstated,and the academic and industry communities must recognize and embrace this phenomenon.
文摘The digital twins(DT)has quickly become a hot topic since it was proposed.It appears in all kinds of commercial propaganda and is widely quoted by academic circles.However,the term DT has misstatements and is misused in business and academics.This study revisits DT and defines it to be a more advanced system/product/service modeling and simulation environment that combines most modern information communication technologies(ICTs)and engineering mechanism digitization and characterized by system/product/service life cycle management,physically geometric visualization,real-time sensing and measurement of system operating conditions,predictability of system performance/safety/lifespan,and complete engineering mechanisms-based simulations.The idea of DT originates from modeling and simulation practices of engineering informatization,including virtual manufacturing(VM),model predictive control,and building information modeling(BIM).On the basis of the two-element VM model,we propose a three-element model to represent DT.DT does not have its unique technical characteristics.The existing practices of DT are extensions of the engineering informatization embracing modern ICTs.These insights clarify the origin of DT and its technical essentials.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.51836010,U22A20238 and 52209117)the China Postdoctoral Science Foundation(Grant No.2021M703516).
文摘Rotating separation flow(RSF)in hydraulic machinery is characterized by the large flow separations and complex vortical structures induced by the effects of strong rotation,large curvature and multiple wall surfaces,and conducting efficient engineering computation and putting forward effective control strategy for the RSF are important topics in the inner flow theory.To meet these engineering requirements,the studies on computational method and control strategy of the RSF are conducted in this paper.In terms of the computational method,the time-scale-driven(TSD)hybrid unsteady Reynolds-averaged Navier-Stokes/large eddy simulation(URANS/LES)modelling strategy is clarified,and an adaptive TSD hybrid model is established based on the RSF characteristics in hydraulic machinery,thereby avoiding the problem of non-monotonic grid convergence and improving the robustness.Besides,a novel vortex-feature-driven idea suitable for the RSF is further developed inspired by it.In terms of the control strategy,the secondary flow generation mechanism in a rotor domain is revealed,and the relationship between natural secondary flows and blade loading distributions is grasped.On the basis of it,an active control strategy with general significance is proposed,and a general alternate loading technique(GALT)is established.Both aspects can provide generalized paradigms with expandable potential,which are of benefit to the efficient computation and effective control of the RSF in hydraulic machinery.
基金Supported by the National Natural Science simulating the unsteady eddying motions⑴.Foundation of China(Grant Nos.51836010,51779258 and 51839001)the National Key Research and Development Program of China(Grant No.2018YFB0606103)the Nature Science Foundation of Beijing(Gmat No.3182018).
文摘A novel Omega(Ω)-driven dynamic partially-averaged Navier-Stokes(PANS)model is proposed in this paper.The ratio of the modeled-to-total turbulent kinetic energies fk is dynamically adjusted by the rigid vorticity ratio(the ratio of the rigid vorticity to the total vorticity),the key parameter of the Ω vortex identification method.Three classical flow cases with rotation and curvature are used to test the model.The results show that the turbulent viscosity is effectively adjusted by the new dynamic fk and the LES-like mode is activated,which can help the revelation of more turbulence information and improve the prediction accuracy.The new PANS model does not contain any explicit dependency on the grid size and enjoys good adaptability to the flow fields,and can be used for efficient engineering computations of the turbulent flows in the hydraulic machinery.
基金supported by the National Natural Science Foundation of China (Grant Nos. 59238161,59725818,50178049,50321803,and 50621062)
文摘In recent years many long-span bridges have been or are being constructed in the world, especially in China. Wind loads and responses are the key factors for their structural design. This paper introduces some important achievements of wind-resistant studies of the author's research team on long-span bridges. First, new concepts and identification methods of aerodynamic derivatives and aerodynamic admittances were proposed. Then mechanical and aerodynamic control strategies and methods of wind-induced vibrations of long-span bridges were the great concerned problems, and valuable achievements were presented. Especially, great efforts which have been theoretically and experimentally made on rain-wind induced vibration of cables of cable-stayed bridges were described. Finally, some new progresses in computation wind engineering were introduced, and a new method for simulating an equilibrium boundary layer was put forward as well.
