Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity ana...Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on （1） a screening method （Morris） for qualitative ranking of parameters, and （2） a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model （RSMSobol）. First, the Morris screening method was used to qualitatively identify the parameters＇ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model （RSM） were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.展开更多
In this study, a new method for conversion of solid finite element solution to beam finite element solution is developed based on the meta-modeling theory which constructs a model consistent with continuum mechanics. ...In this study, a new method for conversion of solid finite element solution to beam finite element solution is developed based on the meta-modeling theory which constructs a model consistent with continuum mechanics. The proposed method is rigorous and efficient compared to a typical conversion method which merely computes surface integration of solid element nodal stresses to obtain cross-sectional forces. The meta-modeling theory ensures the rigorousness of proposed method by defining a proper distance between beam element and solid element solutions in a function space of continuum mechanics. Results of numerical verification test that is conducted with a simple cantilever beam are used to find the proper distance function for this conversion. Time history analysis of the main tunnel structure of a real ramp tunnel is considered as a numerical example for the proposed conversion method. It is shown that cross-sectional forces are readily computed for solid element solution of the main tunnel structure when it is converted to a beam element solution using the proposed method. Further, envelopes of resultant forces which are of primary importance for the purpose of design, are developed for a given ground motion at the end.展开更多
Conventional trajectory optimization techniques have been challenged by their inability to handle threats with irregular shapes and the tendency to be sensitive to control variations of aircraft. Aiming to overcome th...Conventional trajectory optimization techniques have been challenged by their inability to handle threats with irregular shapes and the tendency to be sensitive to control variations of aircraft. Aiming to overcome these difficulties, this paper presents an alternative approach for trajectory optimization, where the problem is formulated into a parametric optimization of the maneuver variables under a tactics template framework. To reduce the size of the problem, global sensitivity analysis （GSA） is performed to identify the less-influential maneuver variables. The probability collectives （PC） algorithm, which is well-suited to discrete and discontinuous optimization, is applied to solve the trajectory optimization problem. The robustness of the trajectory is assessed through multiple sampling around the chosen values of the maneuver variables. Meta-models based on radius basis function （RBF） are created for evaluations of the means and deviations of the problem objectives and constraints. To guarantee the approximation accuracy, the meta-models are adaptively updated during optimization. The proposed approach is demonstrated on a typical airground attack mission scenario. Results reveal that the proposed approach is capable of generating robust and optimal trajectories with both accuracy and efficiency.展开更多
With increasing design demands of turbomachinery,stochastic flutter behavior has become more prominent and even appears a hazard to reliability and safety.Stochastic flutter assessment is an effective measure to quant...With increasing design demands of turbomachinery,stochastic flutter behavior has become more prominent and even appears a hazard to reliability and safety.Stochastic flutter assessment is an effective measure to quantify the failure risk and improve aeroelastic stability.However,for complex turbomachinery with multiple dynamic influencing factors(i.e.,aeroengine compressor with time-variant loads),the stochastic flutter assessment is hard to be achieved effectively,since large deviations and inefficient computing will be incurred no matter considering influencing factors at a certain instant or the whole time domain.To improve the assessing efficiency and accuracy of stochastic flutter behavior,a dynamic meta-modeling approach(termed BA-DWTR)is presented with the integration of bat algorithm(BA)and dynamic wavelet tube regression(DWTR).The stochastic flutter assessment of a typical compressor blade is considered as one case to evaluate the proposed approach with respect to condition variabilities and load fluctuations.The evaluation results reveal that the compressor blade has 0.95% probability to induce flutter failure when operating 100% rotative rate at t=170 s.The total temperature at rotor inlet and dynamic operating loads(vibrating frequency and rotative rate)are the primary sensitive parameters on flutter failure probability.Bymethod comparisons,the presented approach is validated to possess high-accuracy and highefficiency in assessing the stochastic flutter behavior for turbomachinery.展开更多
In a context where urban satellite image processing technologies are undergoing rapid evolution,this article presents an innovative and rigorous approach to satellite image classification applied to urban planning.Thi...In a context where urban satellite image processing technologies are undergoing rapid evolution,this article presents an innovative and rigorous approach to satellite image classification applied to urban planning.This research proposes an integrated methodological framework,based on the principles of model-driven engineering(MDE),to transform a generic meta-model into a meta-model specifically dedicated to urban satellite image classification.We implemented this transformation using the Atlas Transformation Language(ATL),guaranteeing a smooth and consistent transition from platform-independent model(PIM)to platform-specific model(PSM),according to the principles of model-driven architecture(MDA).The application of this IDM methodology enables advanced structuring of satellite data for targeted urban planning analyses,making it possible to classify various urban zones such as built-up,cultivated,arid and water areas.The novelty of this approach lies in the automation and standardization of the classification process,which significantly reduces the need for manual intervention,and thus improves the reliability,reproducibility and efficiency of urban data analysis.By adopting this method,decision-makers and urban planners are provided with a powerful tool for systematically and consistently analyzing and interpreting satellite images,facilitating decision-making in critical areas such as urban space management,infrastructure planning and environmental preservation.展开更多
Monitoring of the earth’s surface has been significantly improved thanks to optical remote sensing by satellites such as SPOT,Landsat and Sentinel-2,which produce vast datasets.The processing of this data,often refer...Monitoring of the earth’s surface has been significantly improved thanks to optical remote sensing by satellites such as SPOT,Landsat and Sentinel-2,which produce vast datasets.The processing of this data,often referred to as Big Data,is essential for decision-making,requiring the application of advanced algorithms to analyze changes in land cover.In the age of artificial intelligence,supervised machine learning algorithms are widely used,although their application in urban contexts remains complex.Researchers have to evaluate and tune various algorithms according to assumptions and experiments,which requires time and resources.This paper presents a meta-modeling approach for urban satellite image classification,using model-driven engineering techniques.The aim is to provide urban planners with standardized solutions for geospatial processing,promoting reusability and interoperability.Formalization includes the creation of a knowledge base and the modeling of processing chains to analyze land use.展开更多
To investigate the application of meta-model for finite element( FE) model updating of structures,the performance of two popular meta-model,i. e.,Kriging model and response surface model( RSM),were compared in detail....To investigate the application of meta-model for finite element( FE) model updating of structures,the performance of two popular meta-model,i. e.,Kriging model and response surface model( RSM),were compared in detail. Firstly,above two kinds of meta-model were introduced briefly. Secondly,some key issues of the application of meta-model to FE model updating of structures were proposed and discussed,and then some advices were presented in order to select a reasonable meta-model for the purpose of updating the FE model of structures. Finally,the procedure of FE model updating based on meta-model was implemented by updating the FE model of a truss bridge model with the measured modal parameters. The results showed that the Kriging model was more proper for FE model updating of complex structures.展开更多
In this work,a hybrid meta-model based design space differentiation（HMDSD）method is proposed for practical problems.In the proposed method,an iteratively reduced promising region is constructed using the expensive p...In this work,a hybrid meta-model based design space differentiation（HMDSD）method is proposed for practical problems.In the proposed method,an iteratively reduced promising region is constructed using the expensive points,with two different search strategies respectively applied inside and outside the promising region.Besides,the hybrid meta-model strategy applied in the search process makes it possible to solve the complex practical problems.Tested upon a serial of benchmark math functions,the HMDSD method shows great efficiency and search accuracy.On top of that,a practical lightweight design demonstrates its superior performance.展开更多
Neural networks are being used to construct meta-models in numerical simulation of structures.In addition to network structures and training algorithms,training samples also greatly affect the accuracy of neural netwo...Neural networks are being used to construct meta-models in numerical simulation of structures.In addition to network structures and training algorithms,training samples also greatly affect the accuracy of neural network models.In this paper,some existing main sampling techniques are evaluated,including techniques based on experimental design theory, random selection,and rotating sampling.First,advantages and disadvantages of each technique are reviewed.Then,seven techniques are used to generate samples for training radial neural networks models for two benchmarks:an antenna model and an aircraft model.Results show that the uniform design,in which the number of samples and mean square error network models are considered,is the best sampling technique for neural network based meta-model building.展开更多
Our research focuses on creating a meta-model for generating a web mapping application. It was difficult for non-geomatics developers to implement a webmapping application. Indeed, this type of application uses geospa...Our research focuses on creating a meta-model for generating a web mapping application. It was difficult for non-geomatics developers to implement a webmapping application. Indeed, this type of application uses geospatial data that require geomatics skills. For this reason, in order to help non-geomatics developers to set up a webmapping application, we have designed a meta-model that automatically generates a webmapping application using model-driven engineering. The created meta-model is used by non-geomatics developers to explicitly write the concrete syntax specific to the webmapping application using the xtext tool. This concrete syntax is automatically converted into source code using the xtend tool without the intervention of the non-geomatics developers.展开更多
In the current scenario of global competition and short product life cycles, customer-defined satisfaction has attracted interest in artifact design. Accordingly, intelligent decision-making through multi-objective op...In the current scenario of global competition and short product life cycles, customer-defined satisfaction has attracted interest in artifact design. Accordingly, intelligent decision-making through multi-objective optimization has been proposed as an efficient method for human-centered manufacturing. However, previous vast researches on optimization have been mainly focused on optimization theory and optimization techniques and paid little interests on the process of problem formulation itself. In this paper, therefore, the authors present a total framework for supporting multi-objective decision making. Then, the authors try to solve the formulated multi-objective optimization problem that involves both qualitative and quantitative performance measures as a general consequence from the above procedure. Taking especially quality as a qualitative measure, the authors gave a new idea to evaluate the quality quantitatively. Additionally, to facilitate the portability of the proposed method in multidisciplinary decision-making environments, the authors implement the proposal algorithm in an Excel spreadsheet and validate the effectiveness of the approach through a case study.展开更多
The second law of thermodynamics implies that any animate and inanimate systems degrade and inevitably stops functioning.It is irreversible over time that can be labeled as‘‘the degradation arrow of time".From ...The second law of thermodynamics implies that any animate and inanimate systems degrade and inevitably stops functioning.It is irreversible over time that can be labeled as‘‘the degradation arrow of time".From perspective of products’reliability design,it is essential to build appropriate models of describing the degradation arrow of time.The current modeling approaches mainly include the model-driven(having assumed forms based on cognitive experience of mankind)and data-driven(using data learning techniques without form hypothesis)approaches.In this paper,we just investigate and review the model-driven degradation approaches,hoping to provide suggestions of the model construction or selection for scholars or engineers.First,for the single mechanism,degradation law models and stochastic process models are classified as separately depicting the tendency and fluctuation of degradation.For the degradation law model,we propose the concept of meta-models as original types for various personal models.For the stochastic process model,two main types including the non-monotonic and monotonical types are presented.Then,four multi-mechanism degradation types are discussed,that are competitive degradation,multi-stage degradation,coexistence of degradation and impact,and coexistence of degradation and failure.Besides,for the multi-performance degradation,independent and coupling models are introduced.The forms,connotations,applicability and insufficiency of these models are described with a series of examples from the literature and our own experiences.The final explicit suggestions about the potential future work are provided for the development of new degradation models.展开更多
The large design freedom of variable-stiffness (VS) composite material presupposes its potential for wide engineering application. Previous research indicates that the design of VS cylindrical structures helps to incr...The large design freedom of variable-stiffness (VS) composite material presupposes its potential for wide engineering application. Previous research indicates that the design of VS cylindrical structures helps to increase the buckling load as compared to quasi-isotropic (QI) cylindrical structures. This paper focuses on the anti-buckling performance of VS cylindrical structures under combined loads and the efficient optimization design method. Two kinds of conditions, bending moment and internal pressure, and bending moment and torque are considered. Influences of the geometrical defects, ovality, on the cylinder's performances are also investigated. To increase the computational efficiency, an adaptive Kriging meta-model is proposed to approximate the structural response of the cylinders. In this improved Kriging model, a mixed updating rule is used in constructing the meta-model. A genetic algorithm (GA) is implemented in the optimization design. The optimal results show that the buckling load of VS cylinders in all cases is greatly increased as compared with a QI cylinder.展开更多
Measuring the business-IT alignment(BITA)of an organization determines its alignment level,provides directions for further improvements,and consequently promotes the organizational performances.Due to the capabilities...Measuring the business-IT alignment(BITA)of an organization determines its alignment level,provides directions for further improvements,and consequently promotes the organizational performances.Due to the capabilities of enterprise architecture(EA)in interrelating different business/IT viewpoints and elements,the development of EA is superior to support BITA measurement.Extant BITA measurement literature is sparse when it concerns EA.The literature tends to explain how EA viewpoints or models correlate with BITA,without discussing where to collect and integrate EA data.To address this gap,this paper attempts to propose a specific BITA measurement process through associating a BITA maturity model with a famous EA framework:DoD Architectural Framework 2.0(DoDAF2.0).The BITA metrics in the maturity model are connected to the meta-models and models of DoDAF2.0.An illustrative ArchiSurance case is conducted to explain the measurement process.Systematically,this paper explores the process of BITA measurement from the viewpoint of EA,which helps to collect the measurement data in an organized way and analyzes the BITA level in the phase of architecture development.展开更多
This paper presents a novel optimization technique for an efficient multi-fidelity model building approach to reduce computational costs for handling aerodynamic shape optimization based on high-fidelity simulation mo...This paper presents a novel optimization technique for an efficient multi-fidelity model building approach to reduce computational costs for handling aerodynamic shape optimization based on high-fidelity simulation models. The wing aerodynamic shape optimization problem is solved by dividing optimization into three steps—modeling 3D（high-fidelity） and 2D（lowfidelity） models, building global meta-models from prominent instead of all variables, and determining robust optimizing shape associated with tuning local meta-models. The adaptive robust design optimization aims to modify the shape optimization process. The sufficient infilling strategy—known as adaptive uniform infilling strategy—determines search space dimensions based on the last optimization results or initial point. Following this, 3D model simulations are used to tune local meta-models. Finally, the global optimization gradient-based method—Adaptive Filter Sequential Quadratic Programing（AFSQP） is utilized to search the neighborhood for a probable optimum point. The effectiveness of the proposed method is investigated by applying it, along with conventional optimization approach-based meta-models, to a Blended Wing Body（BWB） Unmanned Aerial Vehicle（UAV）. The drag coefficient is defined as the objective function, which is subjected to minimum lift coefficient bounds and stability constraints. The simulation results indicate improvement in meta-model accuracy and reduction in computational time of the method introduced in this paper.展开更多
With direct expression of individual application domain patterns and ideas,domain-specific modeling language（DSML） is more and more frequently used to build models instead of using a combination of one or more gener...With direct expression of individual application domain patterns and ideas,domain-specific modeling language（DSML） is more and more frequently used to build models instead of using a combination of one or more general constructs.Based on the profile mechanism of unified modeling language（UML） 2.2,a kind of DSML is presented to model simulation testing systems of avionic software（STSAS）.To define the syntax,semantics and notions of the DSML,the domain model of the STSAS from which we generalize the domain concepts and relationships among these concepts is given,and then,the domain model is mapped into a UML meta-model,named UML-STSAS profile.Assuming a flight control system（FCS） as system under test（SUT）,we design the relevant STSAS.The results indicate that extending UML to the simulation testing domain can effectively and precisely model STSAS.展开更多
A modified multi-objective particle swarm optimization method is proposed for obtaining Pareto-optimal solutions effectively. Different from traditional multiobjective particle swarm optimization methods, Kriging meta...A modified multi-objective particle swarm optimization method is proposed for obtaining Pareto-optimal solutions effectively. Different from traditional multiobjective particle swarm optimization methods, Kriging meta-models and the trapezoid index are introduced and integrated with the traditional one. Kriging meta-models are built to match expensive or black-box functions. By applying Kriging meta-models, function evaluation numbers are decreased and the boundary Pareto-optimal solutions are identified rapidly. For bi-objective optimization problems, the trapezoid index is calculated as the sum of the trapezoid’s area formed by the Pareto-optimal solutions and one objective axis. It can serve as a measure whether the Pareto-optimal solutions converge to the Pareto front. Illustrative examples indicate that to obtain Paretooptimal solutions, the method proposed needs fewer function evaluations than the traditional multi-objective particle swarm optimization method and the non-dominated sorting genetic algorithm II method, and both the accuracy and the computational efficiency are improved. The proposed method is also applied to the design of a deepwater composite riser example in which the structural performances are calculated by numerical analysis. The design aim was to enhance the tension strength and minimize the cost. Under the buckling constraint, the optimal trade-off of tensile strength and material volume is obtained. The results demonstrated that the proposed method can effec tively deal with multi-objective optimizations with black-box functions.展开更多
An ontology mapping approach based on set & relation theory and OCL is introduced,then an ontology mapping meta-model is established which is composed of ontology related elements,mapping related elements and defi...An ontology mapping approach based on set & relation theory and OCL is introduced,then an ontology mapping meta-model is established which is composed of ontology related elements,mapping related elements and definition rule related elements.This ontology mapping meta-model can be regarded as a unified mechanism to realize different kinds of ontology mappings.The powerful computation capability of set and relation theory and the flexible expressive capability of OCL can be used in the computation of ontology mapping meta-model to realize the unified mapping among different ontology models.Based on the mapping meta-model,a general mapping management framework is developed to provide a common mapping storage mechanism,some mapping APIs and mapping rule APIs.展开更多
The complexity of business and information systems(IS)alignment is a growing concern for researchers and practitioners alike.The extant research on alignment architecture fails to consider the human viewpoint,which ma...The complexity of business and information systems(IS)alignment is a growing concern for researchers and practitioners alike.The extant research on alignment architecture fails to consider the human viewpoint,which makes it difficult to embrace emergent complexity.This paper contributes to the extant literature in the following ways.First,we combine an enterprise architecture(EA)framework with a human viewpoint to address alignment issues in the architecture design phase;second,we describe a dynamic alignment model by developing a humancentered meta-model that explains first-and second-order changes and their effects on alignment evolution.This paper provides better support for the theoretical research and the practical application of dynamic alignment.展开更多
基金supported by the National Natural Science Foundation of China (Grant No. 41271003)the National Basic Research Program of China (Grants No. 2010CB428403 and 2010CB951103)
文摘Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on （1） a screening method （Morris） for qualitative ranking of parameters, and （2） a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model （RSMSobol）. First, the Morris screening method was used to qualitatively identify the parameters＇ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model （RSM） were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.
文摘In this study, a new method for conversion of solid finite element solution to beam finite element solution is developed based on the meta-modeling theory which constructs a model consistent with continuum mechanics. The proposed method is rigorous and efficient compared to a typical conversion method which merely computes surface integration of solid element nodal stresses to obtain cross-sectional forces. The meta-modeling theory ensures the rigorousness of proposed method by defining a proper distance between beam element and solid element solutions in a function space of continuum mechanics. Results of numerical verification test that is conducted with a simple cantilever beam are used to find the proper distance function for this conversion. Time history analysis of the main tunnel structure of a real ramp tunnel is considered as a numerical example for the proposed conversion method. It is shown that cross-sectional forces are readily computed for solid element solution of the main tunnel structure when it is converted to a beam element solution using the proposed method. Further, envelopes of resultant forces which are of primary importance for the purpose of design, are developed for a given ground motion at the end.
基金supported by Open Research Foundation of Science and Technology on Aerospace Flight Dynamics Laboratory (No. 2012afd1010)
文摘Conventional trajectory optimization techniques have been challenged by their inability to handle threats with irregular shapes and the tendency to be sensitive to control variations of aircraft. Aiming to overcome these difficulties, this paper presents an alternative approach for trajectory optimization, where the problem is formulated into a parametric optimization of the maneuver variables under a tactics template framework. To reduce the size of the problem, global sensitivity analysis （GSA） is performed to identify the less-influential maneuver variables. The probability collectives （PC） algorithm, which is well-suited to discrete and discontinuous optimization, is applied to solve the trajectory optimization problem. The robustness of the trajectory is assessed through multiple sampling around the chosen values of the maneuver variables. Meta-models based on radius basis function （RBF） are created for evaluations of the means and deviations of the problem objectives and constraints. To guarantee the approximation accuracy, the meta-models are adaptively updated during optimization. The proposed approach is demonstrated on a typical airground attack mission scenario. Results reveal that the proposed approach is capable of generating robust and optimal trajectories with both accuracy and efficiency.
基金co-supported by the National Natural Science Foundation of China(Grants 51975028 and 52105136)China Postdoctoral Science Foundation(Grant 2021M690290)the National Science and TechnologyMajor Project(Grant J2019-Ⅳ-0016-0084).
文摘With increasing design demands of turbomachinery,stochastic flutter behavior has become more prominent and even appears a hazard to reliability and safety.Stochastic flutter assessment is an effective measure to quantify the failure risk and improve aeroelastic stability.However,for complex turbomachinery with multiple dynamic influencing factors(i.e.,aeroengine compressor with time-variant loads),the stochastic flutter assessment is hard to be achieved effectively,since large deviations and inefficient computing will be incurred no matter considering influencing factors at a certain instant or the whole time domain.To improve the assessing efficiency and accuracy of stochastic flutter behavior,a dynamic meta-modeling approach(termed BA-DWTR)is presented with the integration of bat algorithm(BA)and dynamic wavelet tube regression(DWTR).The stochastic flutter assessment of a typical compressor blade is considered as one case to evaluate the proposed approach with respect to condition variabilities and load fluctuations.The evaluation results reveal that the compressor blade has 0.95% probability to induce flutter failure when operating 100% rotative rate at t=170 s.The total temperature at rotor inlet and dynamic operating loads(vibrating frequency and rotative rate)are the primary sensitive parameters on flutter failure probability.Bymethod comparisons,the presented approach is validated to possess high-accuracy and highefficiency in assessing the stochastic flutter behavior for turbomachinery.
文摘In a context where urban satellite image processing technologies are undergoing rapid evolution,this article presents an innovative and rigorous approach to satellite image classification applied to urban planning.This research proposes an integrated methodological framework,based on the principles of model-driven engineering(MDE),to transform a generic meta-model into a meta-model specifically dedicated to urban satellite image classification.We implemented this transformation using the Atlas Transformation Language(ATL),guaranteeing a smooth and consistent transition from platform-independent model(PIM)to platform-specific model(PSM),according to the principles of model-driven architecture(MDA).The application of this IDM methodology enables advanced structuring of satellite data for targeted urban planning analyses,making it possible to classify various urban zones such as built-up,cultivated,arid and water areas.The novelty of this approach lies in the automation and standardization of the classification process,which significantly reduces the need for manual intervention,and thus improves the reliability,reproducibility and efficiency of urban data analysis.By adopting this method,decision-makers and urban planners are provided with a powerful tool for systematically and consistently analyzing and interpreting satellite images,facilitating decision-making in critical areas such as urban space management,infrastructure planning and environmental preservation.
文摘Monitoring of the earth’s surface has been significantly improved thanks to optical remote sensing by satellites such as SPOT,Landsat and Sentinel-2,which produce vast datasets.The processing of this data,often referred to as Big Data,is essential for decision-making,requiring the application of advanced algorithms to analyze changes in land cover.In the age of artificial intelligence,supervised machine learning algorithms are widely used,although their application in urban contexts remains complex.Researchers have to evaluate and tune various algorithms according to assumptions and experiments,which requires time and resources.This paper presents a meta-modeling approach for urban satellite image classification,using model-driven engineering techniques.The aim is to provide urban planners with standardized solutions for geospatial processing,promoting reusability and interoperability.Formalization includes the creation of a knowledge base and the modeling of processing chains to analyze land use.
基金Sponsored by the National Key Technology Research and Development Program of China(Grant No.2011BAK02B02)
文摘To investigate the application of meta-model for finite element( FE) model updating of structures,the performance of two popular meta-model,i. e.,Kriging model and response surface model( RSM),were compared in detail. Firstly,above two kinds of meta-model were introduced briefly. Secondly,some key issues of the application of meta-model to FE model updating of structures were proposed and discussed,and then some advices were presented in order to select a reasonable meta-model for the purpose of updating the FE model of structures. Finally,the procedure of FE model updating based on meta-model was implemented by updating the FE model of a truss bridge model with the measured modal parameters. The results showed that the Kriging model was more proper for FE model updating of complex structures.
基金Project supported by the Plan for the growth of young teachers,the National Natural Science Foundation of China(No.51505138)the National 973 Program of China(No.2010CB328005)+1 种基金Outstanding Youth Foundation of NSFC(No.50625519)Program for Changjiang Scholars
文摘In this work,a hybrid meta-model based design space differentiation（HMDSD）method is proposed for practical problems.In the proposed method,an iteratively reduced promising region is constructed using the expensive points,with two different search strategies respectively applied inside and outside the promising region.Besides,the hybrid meta-model strategy applied in the search process makes it possible to solve the complex practical problems.Tested upon a serial of benchmark math functions,the HMDSD method shows great efficiency and search accuracy.On top of that,a practical lightweight design demonstrates its superior performance.
基金Specialized Research Fund for the Doctoral Program of Higher Education,China (No.20010227012)
文摘Neural networks are being used to construct meta-models in numerical simulation of structures.In addition to network structures and training algorithms,training samples also greatly affect the accuracy of neural network models.In this paper,some existing main sampling techniques are evaluated,including techniques based on experimental design theory, random selection,and rotating sampling.First,advantages and disadvantages of each technique are reviewed.Then,seven techniques are used to generate samples for training radial neural networks models for two benchmarks:an antenna model and an aircraft model.Results show that the uniform design,in which the number of samples and mean square error network models are considered,is the best sampling technique for neural network based meta-model building.
文摘Our research focuses on creating a meta-model for generating a web mapping application. It was difficult for non-geomatics developers to implement a webmapping application. Indeed, this type of application uses geospatial data that require geomatics skills. For this reason, in order to help non-geomatics developers to set up a webmapping application, we have designed a meta-model that automatically generates a webmapping application using model-driven engineering. The created meta-model is used by non-geomatics developers to explicitly write the concrete syntax specific to the webmapping application using the xtext tool. This concrete syntax is automatically converted into source code using the xtend tool without the intervention of the non-geomatics developers.
文摘In the current scenario of global competition and short product life cycles, customer-defined satisfaction has attracted interest in artifact design. Accordingly, intelligent decision-making through multi-objective optimization has been proposed as an efficient method for human-centered manufacturing. However, previous vast researches on optimization have been mainly focused on optimization theory and optimization techniques and paid little interests on the process of problem formulation itself. In this paper, therefore, the authors present a total framework for supporting multi-objective decision making. Then, the authors try to solve the formulated multi-objective optimization problem that involves both qualitative and quantitative performance measures as a general consequence from the above procedure. Taking especially quality as a qualitative measure, the authors gave a new idea to evaluate the quality quantitatively. Additionally, to facilitate the portability of the proposed method in multidisciplinary decision-making environments, the authors implement the proposal algorithm in an Excel spreadsheet and validate the effectiveness of the approach through a case study.
基金co-supported by the National Natural Science Foundation of China(Nos.51675025,and 61573043)。
文摘The second law of thermodynamics implies that any animate and inanimate systems degrade and inevitably stops functioning.It is irreversible over time that can be labeled as‘‘the degradation arrow of time".From perspective of products’reliability design,it is essential to build appropriate models of describing the degradation arrow of time.The current modeling approaches mainly include the model-driven(having assumed forms based on cognitive experience of mankind)and data-driven(using data learning techniques without form hypothesis)approaches.In this paper,we just investigate and review the model-driven degradation approaches,hoping to provide suggestions of the model construction or selection for scholars or engineers.First,for the single mechanism,degradation law models and stochastic process models are classified as separately depicting the tendency and fluctuation of degradation.For the degradation law model,we propose the concept of meta-models as original types for various personal models.For the stochastic process model,two main types including the non-monotonic and monotonical types are presented.Then,four multi-mechanism degradation types are discussed,that are competitive degradation,multi-stage degradation,coexistence of degradation and impact,and coexistence of degradation and failure.Besides,for the multi-performance degradation,independent and coupling models are introduced.The forms,connotations,applicability and insufficiency of these models are described with a series of examples from the literature and our own experiences.The final explicit suggestions about the potential future work are provided for the development of new degradation models.
基金the National NaturalScience Foundation of China (Grant 11572134)the China PostdoctoralScience Foundation (Grant 2017M612443).
文摘The large design freedom of variable-stiffness (VS) composite material presupposes its potential for wide engineering application. Previous research indicates that the design of VS cylindrical structures helps to increase the buckling load as compared to quasi-isotropic (QI) cylindrical structures. This paper focuses on the anti-buckling performance of VS cylindrical structures under combined loads and the efficient optimization design method. Two kinds of conditions, bending moment and internal pressure, and bending moment and torque are considered. Influences of the geometrical defects, ovality, on the cylinder's performances are also investigated. To increase the computational efficiency, an adaptive Kriging meta-model is proposed to approximate the structural response of the cylinders. In this improved Kriging model, a mixed updating rule is used in constructing the meta-model. A genetic algorithm (GA) is implemented in the optimization design. The optimal results show that the buckling load of VS cylinders in all cases is greatly increased as compared with a QI cylinder.
基金supported by the National Natural Science Foundation of China(71571189)the State Key Laboratory of Air Traffic Management System and Technology(SKLATM201806)
文摘Measuring the business-IT alignment(BITA)of an organization determines its alignment level,provides directions for further improvements,and consequently promotes the organizational performances.Due to the capabilities of enterprise architecture(EA)in interrelating different business/IT viewpoints and elements,the development of EA is superior to support BITA measurement.Extant BITA measurement literature is sparse when it concerns EA.The literature tends to explain how EA viewpoints or models correlate with BITA,without discussing where to collect and integrate EA data.To address this gap,this paper attempts to propose a specific BITA measurement process through associating a BITA maturity model with a famous EA framework:DoD Architectural Framework 2.0(DoDAF2.0).The BITA metrics in the maturity model are connected to the meta-models and models of DoDAF2.0.An illustrative ArchiSurance case is conducted to explain the measurement process.Systematically,this paper explores the process of BITA measurement from the viewpoint of EA,which helps to collect the measurement data in an organized way and analyzes the BITA level in the phase of architecture development.
文摘This paper presents a novel optimization technique for an efficient multi-fidelity model building approach to reduce computational costs for handling aerodynamic shape optimization based on high-fidelity simulation models. The wing aerodynamic shape optimization problem is solved by dividing optimization into three steps—modeling 3D（high-fidelity） and 2D（lowfidelity） models, building global meta-models from prominent instead of all variables, and determining robust optimizing shape associated with tuning local meta-models. The adaptive robust design optimization aims to modify the shape optimization process. The sufficient infilling strategy—known as adaptive uniform infilling strategy—determines search space dimensions based on the last optimization results or initial point. Following this, 3D model simulations are used to tune local meta-models. Finally, the global optimization gradient-based method—Adaptive Filter Sequential Quadratic Programing（AFSQP） is utilized to search the neighborhood for a probable optimum point. The effectiveness of the proposed method is investigated by applying it, along with conventional optimization approach-based meta-models, to a Blended Wing Body（BWB） Unmanned Aerial Vehicle（UAV）. The drag coefficient is defined as the objective function, which is subjected to minimum lift coefficient bounds and stability constraints. The simulation results indicate improvement in meta-model accuracy and reduction in computational time of the method introduced in this paper.
基金Aeronautical Science Foundation of China (20095551025)
文摘With direct expression of individual application domain patterns and ideas,domain-specific modeling language（DSML） is more and more frequently used to build models instead of using a combination of one or more general constructs.Based on the profile mechanism of unified modeling language（UML） 2.2,a kind of DSML is presented to model simulation testing systems of avionic software（STSAS）.To define the syntax,semantics and notions of the DSML,the domain model of the STSAS from which we generalize the domain concepts and relationships among these concepts is given,and then,the domain model is mapped into a UML meta-model,named UML-STSAS profile.Assuming a flight control system（FCS） as system under test（SUT）,we design the relevant STSAS.The results indicate that extending UML to the simulation testing domain can effectively and precisely model STSAS.
基金supported by the National Natural Science Foundation of China(Grant 11572134)
文摘A modified multi-objective particle swarm optimization method is proposed for obtaining Pareto-optimal solutions effectively. Different from traditional multiobjective particle swarm optimization methods, Kriging meta-models and the trapezoid index are introduced and integrated with the traditional one. Kriging meta-models are built to match expensive or black-box functions. By applying Kriging meta-models, function evaluation numbers are decreased and the boundary Pareto-optimal solutions are identified rapidly. For bi-objective optimization problems, the trapezoid index is calculated as the sum of the trapezoid’s area formed by the Pareto-optimal solutions and one objective axis. It can serve as a measure whether the Pareto-optimal solutions converge to the Pareto front. Illustrative examples indicate that to obtain Paretooptimal solutions, the method proposed needs fewer function evaluations than the traditional multi-objective particle swarm optimization method and the non-dominated sorting genetic algorithm II method, and both the accuracy and the computational efficiency are improved. The proposed method is also applied to the design of a deepwater composite riser example in which the structural performances are calculated by numerical analysis. The design aim was to enhance the tension strength and minimize the cost. Under the buckling constraint, the optimal trade-off of tensile strength and material volume is obtained. The results demonstrated that the proposed method can effec tively deal with multi-objective optimizations with black-box functions.
基金Sponsored by the National High Technology Research and Development Program of China(863)(Grant No.2002AA411420)National Natural Science Foundation(Grant No.60374071)
文摘An ontology mapping approach based on set & relation theory and OCL is introduced,then an ontology mapping meta-model is established which is composed of ontology related elements,mapping related elements and definition rule related elements.This ontology mapping meta-model can be regarded as a unified mechanism to realize different kinds of ontology mappings.The powerful computation capability of set and relation theory and the flexible expressive capability of OCL can be used in the computation of ontology mapping meta-model to realize the unified mapping among different ontology models.Based on the mapping meta-model,a general mapping management framework is developed to provide a common mapping storage mechanism,some mapping APIs and mapping rule APIs.
文摘The complexity of business and information systems(IS)alignment is a growing concern for researchers and practitioners alike.The extant research on alignment architecture fails to consider the human viewpoint,which makes it difficult to embrace emergent complexity.This paper contributes to the extant literature in the following ways.First,we combine an enterprise architecture(EA)framework with a human viewpoint to address alignment issues in the architecture design phase;second,we describe a dynamic alignment model by developing a humancentered meta-model that explains first-and second-order changes and their effects on alignment evolution.This paper provides better support for the theoretical research and the practical application of dynamic alignment.
