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A data-driven integrated optimization method of macroscopic topology and microscopic configuration for the graded functional cellular structures 认领 引用
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作者 Yu Guo Yijie Lu +2 位作者 Zhengwei Zhang Yanguo Zhou Hui Liu 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第2期473-495,共23页
In the topology optimization of the multiscale structure,how to ensure the connectivity between adjacent microstructures,how to control the design space of microstructures,and how to reduce the amount of calculation a... In the topology optimization of the multiscale structure,how to ensure the connectivity between adjacent microstructures,how to control the design space of microstructures,and how to reduce the amount of calculation and improve calculation efficiency are three basic challenging issues currently faced.To this end,this paper proposes a data-driven approach to achieve the integrated optimization of macroscopic topology and microscopic configuration of the graded functional cellular structures.At the macro level,a topological description function is introduced to realize the topological control of the macrostructure.At the micro level,several cutting functions are used to realize the control of the configuration and size of the microstructure.The integrated optimization design of macro and micro cellular structures can be realized.Based on the computational homogenization method and numerical integration technology,an optimization problem independent offline microstructure database is established at the microscopic scale,where the relationship between the equivalent elastic parameters,relative pseudo-density,and design variables of the microstructure is stored.Based on this offline database,the entire topology optimization process is completed only on a macro scale,which greatly reduces the amount of calculation and improves calculation efficiency.In addition,implicit geometric modeling of full-scale cellular structures can be achieved using the reconstruction technique introduced in this work,which ensures smooth connection between adjacent microstructures.Finally,numerical examples are used to verify the effectiveness of the algorithm and the superiority of gradient cellular structures compared with single-scale structures. 展开更多
关键词 Graded cellular structure Integrated optimization Data-driven Computational homogenization M-VCUT Level set method
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Data-driven methods for predicting the representative temperature of bridge cable based on limited measured data 认领 引用 被引量：2
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作者 WANG Fen DAI Gong-lian +2 位作者 HE Chang-lin GE Hao RAO Hui-ming 《Journal of Central South University》 SCIE EI CAS CSCD 2024年第9期3168-3186,共19页
Cable-stayed bridges have been widely used in high-speed railway infrastructure.The accurate determination of cable’s representative temperatures is vital during the intricate processes of design,construction,and mai... Cable-stayed bridges have been widely used in high-speed railway infrastructure.The accurate determination of cable’s representative temperatures is vital during the intricate processes of design,construction,and maintenance of cable-stayed bridges.However,the representative temperatures of stayed cables are not specified in the existing design codes.To address this issue,this study investigates the distribution of the cable temperature and determinates its representative temperature.First,an experimental investigation,spanning over a period of one year,was carried out near the bridge site to obtain the temperature data.According to the statistical analysis of the measured data,it reveals that the temperature distribution is generally uniform along the cable cross-section without significant temperature gradient.Then,based on the limited data,the Monte Carlo,the gradient boosted regression trees(GBRT),and univariate linear regression(ULR)methods are employed to predict the cable’s representative temperature throughout the service life.These methods effectively overcome the limitations of insufficient monitoring data and accurately predict the representative temperature of the cables.However,each method has its own advantages and limitations in terms of applicability and accuracy.A comprehensive evaluation of the performance of these methods is conducted,and practical recommendations are provided for their application.The proposed methods and representative temperatures provide a good basis for the operation and maintenance of in-service long-span cable-stayed bridges. 展开更多
关键词 cable-stayed bridges representative temperature gradient boosted regression trees(GBRT)method field test limited measured data
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Measurement device and method for mass and centroid of large aircraft 认领 引用 被引量：1
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作者 ZHANG Xiaolin ZHANG Yuyang +2 位作者 YANG Lifeng ZHAO Hongzhi WANG Meibao 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2025年第3期341-349,共9页
The precise acquisition of the quality characteristic parameters of large aircraft directly affects its performance characteristics.For large aircrafts such as missiles and rockets with internal fillings,traditional m... The precise acquisition of the quality characteristic parameters of large aircraft directly affects its performance characteristics.For large aircrafts such as missiles and rockets with internal fillings,traditional measurement methods involving large-angle tilting or rotation may pose safety risks.In light of the characteristics of large aircraft and in combination with existing measurement methods,we design a mass and centroid measurement method based on four-point support and small-angle tilting,and develop a set of mass and centroid testing system.This method obtains the intersection point of the gravity action line in the product coordinate system through coordinate transformation in two postures,thereby obtaining the three-dimensional centroid of the aircraft.We first elaborate on the principle of this method in detail,then introduce the composition of the equipment,and analyze the structural stress of key components.Finally,experimental verification and uncertainty analysis are carried out.Experimental verification shows that the maximum deviation of the mass measurement accuracy is less than 0.02%,the centroid measurement accuracy in the X direction is±0.15 mm,in the Y direction it is±0.21 mm,and in the Z direction it is±0.19 mm. 展开更多
关键词 large aircraft centroid measurement coordinate transformation multi-point weighing method gravity line
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Data-driven measurement performance evaluation of voltage transformers in electric railway traction power supply systems 认领 引用
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作者 Zhaoyang Li Muqi Sun +5 位作者 Jun Zhu Haoyu Luo Qi Wang Haitao Hu Zhengyou He Ke Wang 《Railway Engineering Science》 EI 2025年第2期311-323,共13页
Critical for metering and protection in electric railway traction power supply systems(TPSSs),the measurement performance of voltage transformers(VTs)must be timely and reliably monitored.This paper outlines a three-s... Critical for metering and protection in electric railway traction power supply systems(TPSSs),the measurement performance of voltage transformers(VTs)must be timely and reliably monitored.This paper outlines a three-step,RMS data only method for evaluating VTs in TPSSs.First,a kernel principal component analysis approach is used to diagnose the VT exhibiting significant measurement deviations over time,mitigating the influence of stochastic fluctuations in traction loads.Second,a back propagation neural network is employed to continuously estimate the measurement deviations of the targeted VT.Third,a trend analysis method is developed to assess the evolution of the measurement performance of VTs.Case studies conducted on field data from an operational TPSS demonstrate the effectiveness of the proposed method in detecting VTs with measurement deviations exceeding 1%relative to their original accuracy levels.Additionally,the method accurately tracks deviation trends,enabling the identification of potential early-stage faults in VTs and helping prevent significant economic losses in TPSS operations. 展开更多
关键词 Voltage transformer Traction power supply system Measurement performance Data-driven evaluation Abrupt change detection Bootstrap confidence interval
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Data-Driven Event-Triggered Control Dealing With Noisy Data 认领 引用
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作者 Xian-Ming Zhang Qing-Long Han Xiaohua Ge 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第3期543-554,共12页
This paper is concerned with event-triggered control that deals with noisy data for both discrete-time and continuoustime linear systems with unknown system matrices.First,based on a sufficiently rich finite set of no... This paper is concerned with event-triggered control that deals with noisy data for both discrete-time and continuoustime linear systems with unknown system matrices.First,based on a sufficiently rich finite set of noisy data collected in an experiment,the pair of system matrices is represented as a data-based nominal matrix plus an uncertain matrix with a bounded norm.This formulation enables classical robust control techniques to be applied to tackle the robust control problem.Second,for discretetime systems,a novel event-triggering condition is proposed,by which an event is triggered if the sum of the squares of the weighted error exceeds the square of the weighted state from the previous event.For continuous-time systems,the event-triggering condition is devised as a monotonically increasing function that starts with a negative value and triggers an event when it reaches zero.This condition can exclude the so-called Zeno behaviour due to its monotonic increase property.Third,by employing a looped functional method,several criteria are derived to co-design suitable state feedback controllers and event-triggering parameters for the systems under study.Finally,the effectiveness of the proposed method is demonstrated through a case study involving a batch reactor system. 展开更多
关键词 Data-driven control event-triggered control looped functional method noisy data
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Beam‑coupling impedance measurement and simulation of a movable collimator in BRing at HIAF 认领 引用
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作者 Guang‑Yu Zhu Jia‑Jian Ding +7 位作者 Jian‑Chuan Zhang Jun‑Xia Wu Wei‑Ping Chai Guo‑Dong Shen Zi‑Shuai Qiu Yong‑Liang Yang Jun Meng Jian‑Cheng Yang 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2026年第7期31-42,共12页
The dynamic vacuum effect is the primary constraint on beam intensity in high-intensity heavy-ion synchrotrons.The dynamic vacuum effect induced by the charge exchange beam loss significantly limits the ion intensity ... The dynamic vacuum effect is the primary constraint on beam intensity in high-intensity heavy-ion synchrotrons.The dynamic vacuum effect induced by the charge exchange beam loss significantly limits the ion intensity and beam lifetime in the booster ring(BRing)of the HIAF.The collimator is a critical and indispensable component for mitigating the dynamic vacuum effect in high-intensity heavy-ion circular accelerators.A dedicated collimation system was designed for BRing to decrease ion-induced gas desorption and suppress the dynamic vacuum effect.Nevertheless,this intercepting structure may introduce longitudinal and transverse beam-coupling impedances in BRing.In this study,comprehensive investigations were conducted to characterize the beam-coupling impedance of a movable collimator.Furthermore,we systematically describe the results of the single-and two-wire bench transmission measurements and numerical simulations.Satisfactory agreement was obtained between the numerical simulations and wire transmission bench measurements.The heat deposition power on each part of the collimator due to the longitudinal impedance was evaluated.The 24 movable collimators were processed and entered the online installation stage of the Booster Ring. 展开更多
关键词 Booster Ring(BRing) Collimator Longitudinal impedance Transverse impedance Wire transmission method Impedance bench measurement
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An Improved Method for Correction of Air Temperature Measured Using Different Radiation Shields 认领 引用
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作者 CHENG Xinghong SU Debin +6 位作者 LI Deping CHEN Lu XU Wenjing YANG Meilin LI Yongcheng YUE Zhizhong WANG Zijing 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2014年第6期1460-1468,共9页
The variation of air temperature measurement errors using two different radiation shields （DTR502B Vaisala,Finland,and HYTFZ01,Huayun Tongda Satcom,China） was studied.Datasets were collected in the field at the Daxi... The variation of air temperature measurement errors using two different radiation shields （DTR502B Vaisala,Finland,and HYTFZ01,Huayun Tongda Satcom,China） was studied.Datasets were collected in the field at the Daxing weather station in Beijing from June 2011 to May 2012.Most air temperature values obtained with these two commonly used radiation shields were lower than the reference records obtained with the new Fiber Reinforced Polymers （FRP） Stevenson screen.In most cases,the air temperature errors when using the two devices were smaller on overcast and rainy days than on sunny days; and smaller when using the imported rather than the Chinese shield.The measured errors changed sharply at sunrise and sunset,and reached maxima at noon.Their diurnal variation characteristics were,naturally,related to changes in solar radiation.The relationships between the record errors,global radiation,and wind speed were nonlinear.An improved correction method was proposed based on the approach described by Nakamura and Mahrt （2005） （NM05）,in which the impact of the solar zenith angle （SZA） on the temperature error is considered and extreme errors due to changes in SZA can be corrected effectively.Measurement errors were reduced significantly after correction by either method for both shields.The error reduction rate using the improved correction method for the Chinese and imported shields were 3.3％ and 40.4％ higher than those using the NM05 method,respectively. 展开更多
关键词 radiation shield measurement error impacts of solar zenith angle improved correction method
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Leveraging Bayesian methods for addressing multi-uncertainty in data-driven seismic liquefaction assessment 认领 引用 被引量：1
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作者 Zhihui Wang Roberto Cudmani +2 位作者 Andrés Alfonso Peña Olarte Chaozhe Zhang Pan Zhou 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2025年第4期2474-2491,共18页
When assessing seismic liquefaction potential with data-driven models,addressing the uncertainties of establishing models,interpreting cone penetration tests(CPT)data and decision threshold is crucial for avoiding bia... When assessing seismic liquefaction potential with data-driven models,addressing the uncertainties of establishing models,interpreting cone penetration tests(CPT)data and decision threshold is crucial for avoiding biased data selection,ameliorating overconfident models,and being flexible to varying practical objectives,especially when the training and testing data are not identically distributed.A workflow characterized by leveraging Bayesian methodology was proposed to address these issues.Employing a Multi-Layer Perceptron(MLP)as the foundational model,this approach was benchmarked against empirical methods and advanced algorithms for its efficacy in simplicity,accuracy,and resistance to overfitting.The analysis revealed that,while MLP models optimized via maximum a posteriori algorithm suffices for straightforward scenarios,Bayesian neural networks showed great potential for preventing overfitting.Additionally,integrating decision thresholds through various evaluative principles offers insights for challenging decisions.Two case studies demonstrate the framework's capacity for nuanced interpretation of in situ data,employing a model committee for a detailed evaluation of liquefaction potential via Monte Carlo simulations and basic statistics.Overall,the proposed step-by-step workflow for analyzing seismic liquefaction incorporates multifold testing and real-world data validation,showing improved robustness against overfitting and greater versatility in addressing practical challenges.This research contributes to the seismic liquefaction assessment field by providing a structured,adaptable methodology for accurate and reliable analysis. 展开更多
关键词 Data-driven method Bayes analysis Seismic liquefaction Uncertainty Neural network
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A data-driven PCA-RF-VIM method to identify key factors driving post-fracturing gas production of tight reservoirs 认领 引用
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作者 Yifan Zhao Xiaofan Li +5 位作者 Lei Zuo Zhongtai Hu Liangbin Dou Huagui Yu Tiantai Li Jun Lu 《Energy Geoscience》 EI CAS CSCD 2025年第2期436-450,共15页
Hydraulic fracturing technology has achieved remarkable results in improving the production of tight gas reservoirs,but its effectiveness is under the joint action of multiple factors of complexity.Traditional analysi... Hydraulic fracturing technology has achieved remarkable results in improving the production of tight gas reservoirs,but its effectiveness is under the joint action of multiple factors of complexity.Traditional analysis methods have limitations in dealing with these complex and interrelated factors,and it is difficult to fully reveal the actual contribution of each factor to the production.Machine learning-based methods explore the complex mapping relationships between large amounts of data to provide datadriven insights into the key factors driving production.In this study,a data-driven PCA-RF-VIM(Principal Component Analysis-Random Forest-Variable Importance Measures)approach of analyzing the importance of features is proposed to identify the key factors driving post-fracturing production.Four types of parameters,including log parameters,geological and reservoir physical parameters,hydraulic fracturing design parameters,and reservoir stimulation parameters,were inputted into the PCA-RF-VIM model.The model was trained using 6-fold cross-validation and grid search,and the relative importance ranking of each factor was finally obtained.In order to verify the validity of the PCA-RF-VIM model,a consolidation model that uses three other independent data-driven methods(Pearson correlation coefficient,RF feature significance analysis method,and XGboost feature significance analysis method)are applied to compare with the PCA-RF-VIM model.A comparison the two models shows that they contain almost the same parameters in the top ten,with only minor differences in one parameter.In combination with the reservoir characteristics,the reasonableness of the PCA-RF-VIM model is verified,and the importance ranking of the parameters by this method is more consistent with the reservoir characteristics of the study area.Ultimately,the ten parameters are selected as the controlling factors that have the potential to influence post-fracturing gas production,as the combined importance of these top ten parameters is 91.95%on driving natural gas production.Analyzing and obtaining these ten controlling factors provides engineers with a new insight into the reservoir selection for fracturing stimulation and fracturing parameter optimization to improve fracturing efficiency and productivity. 展开更多
关键词 Data-driven method Controlling factor Hydraulic fracturing Gas production
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A data-driven identification method for reaction rate constant and diffusion coefficient in the P2D model 认领 引用
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作者 Gaoyang Li Xiaoyu Guo +8 位作者 Yongshuai Li Jialong Huang Zhirui Wang Yizheng Ma Litao Zhu Hui Pan Feng Shao Hao Ling Yulin Min 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2025年第12期188-197,共10页
To ensure the safe operation of batteries,accurately obtaining key internal state parameters is essential.However,traditional parameter measurement methods either require opening the battery or long-term measurements,... To ensure the safe operation of batteries,accurately obtaining key internal state parameters is essential.However,traditional parameter measurement methods either require opening the battery or long-term measurements,which are impractical.Therefore,the fixed values are commonly used for these parameters in electrochemical models and have significant limitations.To overcome these limitations,this paper proposes a deep neural network(DNN)based data-driven evaluation method to determine model parameters.By coupling an improved one-dimensional isothermal pseudo-twodimensional(P2D)model with DNN,this study identified concentration-dependent parameters through detailed discharge curve analysis.The results show that the data-driven method can effectively obtain the change trend of concentration-dependent parameters through the charge and discharge curve,and the method can be extended to different battery systems in different discharge rates and aging applications.This work is expected to provide new parameter selection insights for data-driven battery prediction and monitoring models. 展开更多
关键词 Internal state parameters of batteries P2D model Parameter identification Deep neural network(DNN) Data-driven evaluation method
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A centroid measurement method based on 3D scanning 认领 引用 被引量：1
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作者 HE Xin LI Zhen 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2025年第2期186-194,共9页
The centroid coordinate serves as a critical control parameter in motion systems,including aircraft,missiles,rockets,and drones,directly influencing their motion dynamics and control performance.Traditional methods fo... The centroid coordinate serves as a critical control parameter in motion systems,including aircraft,missiles,rockets,and drones,directly influencing their motion dynamics and control performance.Traditional methods for centroid measurement often necessitate custom equipment and specialized positioning devices,leading to high costs and limited accuracy.Here,we present a centroid measurement method that integrates 3D scanning technology,enabling accurate measurement of centroid across various types of objects without the need for specialized positioning fixtures.A theoretical framework for centroid measurement was established,which combined the principle of the multi-point weighing method with 3D scanning technology.The measurement accuracy was evaluated using a designed standard component.Experimental results demonstrate that the discrepancies between the theoretical and the measured centroid of a standard component with various materials and complex shapes in the X,Y,and Z directions are 0.003 mm,0.009 mm,and 0.105 mm,respectively,yielding a spatial deviation of 0.106 mm.Qualitative verification was conducted through experimental validation of three distinct types.They confirmed the reliability of the proposed method,which allowed for accurate centroid measurements of various products without requiring positioning fixtures.This advancement significantly broadened the applicability and scope of centroid measurement devices,offering new theoretical insights and methodologies for the measurement of complex parts and systems. 展开更多
关键词 centroid measurement mass characteristic parameter 3D scanning 3D point cloud data no specialized positioning fixtures multi-point weighing method
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Dynamic quantitative deformation mapping of slip activities in NBSC superalloy using sampling moiré method 认领 引用 被引量：1
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作者 Xinyun XIE Qinghua WANG Xiaojun YAN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第1期301-312,共12页
Quantitative assessment of microscale slip activities and plastic localizations is essential for understanding the complex deformation mechanisms in crystalline materials.However,few experimental studies have been abl... Quantitative assessment of microscale slip activities and plastic localizations is essential for understanding the complex deformation mechanisms in crystalline materials.However,few experimental studies have been able to dynamically measure the deformation fields of rapidly evolving slip activities at the microscale.In this study,we used the Sampling Moire?Method(SMM)to directly measure the dynamic deformation fields of slip activities in Nickel-Based Single-Crystal(NBSC)superalloy under in-situ tensile test,and the strain and displacement fields under the evolving microplastic events with intense slip activities around the notch of the NBSC superalloy specimen were obtained for the first time.The dynamic evolution of slip bands was quantitatively characterized through detailed statistical analysis of strains and displacements under different loads.The locations of the initial appearance of slip traces were successfully predicted by the regions of plasticity localization.The results show that the deformation fields exhibit both high spatial and temporal resolutions,enabling the capture of nanometer-scale displacement fields and visualization of the dynamic fluidity of slip accumulation.This method demonstrates the superiority of the dynamic characterization of the plastic deformation field at the microscale and the promise of its application for characterizing the slip activities of various crystalline metals. 展开更多
关键词 Dynamic deformation measurement Nickel-based single-crystal superalloys Plastic deformation Samplingmoire method Slip bands evolution
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Stability evaluation of the tunnel portal slope based on improved unascertained measure method 认领 引用
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作者 ZHANG Cengceng HUANG Shibing +1 位作者 ZHENG Luobin LI Wen 《Journal of Mountain Science》 SCIE CSCD 2025年第6期2261-2275,共15页
The stability of the tunnel portal slope is crucial for ensuring safe tunnel construction.Thus,a sound stability evaluation is of significance.Given the unique geological characteristics of tunnel portal slopes,it is ... The stability of the tunnel portal slope is crucial for ensuring safe tunnel construction.Thus,a sound stability evaluation is of significance.Given the unique geological characteristics of tunnel portal slopes,it is necessary to establish a specific evaluation indicator system that differs from those used for ordinary slopes.Based on the unascertained measure method,uncertainties in the indicator are addressed by introducing the left and right half cloud asymmetric cloud model to optimize the linear membership function.The subjectivity of confidence criterion level identification is also improved by using the Euclidean distance method.Thus,a stability evaluation model for the tunnel portal slope is established based on the improved unascertained measure method.Finally,using the collected tunnel portal slope data,the results of four evaluation methods are compared with the safety factor levels.The evaluation methods include the traditional unascertained measure method,the method improved by using the left and right half cloud asymmetric cloud model,the method improved by using the Euclidean distance method,and the method improved by using both the left and right half cloud asymmetric cloud model and the Euclidean distance method.The results show that the accuracy rates of these four methods are 50%,55%,85%,and 90%,respectively.Among them,the joint improvement method has the slightest deviation,with only one level,while the other three methods had deviations of two levels.This result verifies the stability and effectiveness of the joint improvement method,providing a reference for tunnel portal slope stability evaluation. 展开更多
关键词 Tunnel portal slope Stability evaluation Improved unascertained measure method Left and right half cloud asymmetric cloud model Euclidean distance method
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Optimization of Thermoplastic Elastomer (TPE) Components for Aerospace Structures Using Computerized Data-Driven Design 认领 引用
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作者 Adwaa Mohammed Abdulmajeed Duaa Abdul Rida Musa +2 位作者 Ola Abdul Hussain Emad Kadum Njim Royal Madan 《Computers, Materials & Continua》 SCIE EI 2026年第6期766-794,共29页
A data-driven optimization framework that integrates machine learning surrogate models,finite element analysis(FEA),and a multi-objective optimization algorithm is used in this study for developing thermoplastic elast... A data-driven optimization framework that integrates machine learning surrogate models,finite element analysis(FEA),and a multi-objective optimization algorithm is used in this study for developing thermoplastic elastomer(TPE)parts for aerospace applications.By using FEA simulations and experiments,a database of input design parameters(e.g.,geometry and structural shape modifier)is generated.Afterwards,we train surrogate models(e.g.,Gaussian Process Regression,neural networks)to approximate mappings from design space to performance space.Finally,we propose Pareto-optimal TPE designs using the surrogate embedded in a multi-objective optimization loop(such as NSGA-Ⅱ or gradient-based methods).The novelty of this approach is demonstrated by employing highly simplified surrogate models,including an artificial neural network(ANN)with 10 hidden neurons trained on analytically generated synthetic data.The proposed methodology has been validated using an aerospace-related case study:a vibration-damping plate.Compared with the baseline configuration,Pareto-optimal designs identified by the proposed framework achieved a reduction in maximum deflection of 23%-28%and a reduction in von Mises stress of 18%-24%,depending on the selected trade-off solution,as the number of full FEA simulations required for optimization was reduced from 500 to 50.This framework enables faster design of TPE components for aerospace systems.Validation against high-fidelity ANSYS simulations showed a mean error of~1.18%and a maximum deviation of~2.6%. 展开更多
关键词 TPE aerospace structures surrogate modelling data-driven optimization multi-objective optimization method FEM
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Online data-driven MPC for PWA systems with unknown parameters 认领 引用
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作者 Rui Gu Aoyun Ma +2 位作者 Dewei Li Yunwen Xu Shaoying He 《Control Theory and Technology》 EI CSCD 2026年第2期307-315,共9页
A data-driven model predictive control(MPC)algorithm based on the input-mapping method is proposed for piecewise affine(PWA)systems.These systems are characterized by unknown but constant parameters and are subject to... A data-driven model predictive control(MPC)algorithm based on the input-mapping method is proposed for piecewise affine(PWA)systems.These systems are characterized by unknown but constant parameters and are subject to disturbances,as well as state and input constraints.To support the control strategy,an offline algorithm is developed to compute a non-convex robust positively invariant set that serves as the terminal set within the MPC framework tailored for PWA systems.The online MPC algorithm directly maps the future control input and predicted state to the historical input-state data associated with the corresponding state subregion.This mapping process leverages the more accurate relationships contained in the historical input-state data to enhance the prediction accuracy of future states.A state-dependent weight embedded in the cost function enables the controller to balance prediction accuracy against convergence speed,enhancing overall performance.Moreover,conditions ensuring the recursive feasibility of the optimization problem and stability of the closed-loop system are established.The effectiveness of the proposed algorithm is demonstrated through a numerical example,which highlights its ability to handle complex system dynamics and constraints while maintaining robust performance. 展开更多
关键词 Data-driven model predictive control Input-mapping method Piecewise affine systems Unknown parameters
Determination of Anisotropic Thermoelectric Properties of Bismuth Using a Tensor Inversion Method 认领 引用
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作者 Xiaohan Qin Yuanchen Shen +10 位作者 Jie Pang Jun Li Minhua Huang Yixuan Ge Chao Xin Quansheng Wu Youguo Shi Wenjie Liang Zhong-Zhen Luo Zhigang Zou Guodong Li 《Chinese Physics Letters》 SCIE EI CAS CSCD 2026年第2期300-325,共26页
Conventional methods for quantifying thermoelectric anisotropy rely on precisely aligned crystals,which are time-consuming and error-prone.To address this,we propose a tensor inversion method integrating transport mea... Conventional methods for quantifying thermoelectric anisotropy rely on precisely aligned crystals,which are time-consuming and error-prone.To address this,we propose a tensor inversion method integrating transport measurements with EBSD-derived Euler angles to determine the intrinsic tensors of as-grown bismuth crystals.This method reconstructs the full second-rank thermoelectric tensors—including electrical resistivity,thermal conductivity,and the Seebeck coefficient—by transforming transport data between the sample coordinate system and the crystal coordinate system.The inverted tensor components of pure bismuth show excellent agreement with reported principal-axis values,validating the accuracy of this method.Moreover,the reversibility of the tensor inversion approach allows for complete visualization of the directional dependence of the thermoelectric figure of merit(zT),revealing its full angular and crystallographic orientation distribution for the first time.This bidirectional framework not only provides a convenient pathway for the reconstruction of intrinsic transport tensors but also enables the prediction of orientation-dependent properties,thereby offering a robust tool for analyzing anisotropic transport behavior and guiding the optimization of thermoelectric performance. 展开更多
关键词 tensor inversion method precisely aligned crystalswhich seebeck coefficient determine intrinsic tensors thermoelectric properties transport measurements electrical resistivitythermal conductivityand anisotropy
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A new ground-motion scaling and record selection procedure for asymmetric-plan buildings using the 2DOF-modal pushover method 认领 引用
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作者 Hamid Hojaji Mohammad Sadegh Birzhandi Mohammad Mahdi Zafarani 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2026年第1期71-86,共16页
Advanced intensity measures(IMs)based on an inelastic deformation spectrum improved the evaluation of the median engineering demand parameters(EDPs)and reduced dispersion.In this regard,an optimized two-degreefreedom(... Advanced intensity measures(IMs)based on an inelastic deformation spectrum improved the evaluation of the median engineering demand parameters(EDPs)and reduced dispersion.In this regard,an optimized two-degreefreedom(2DOF)modal pushover-based scaling procedure(2DMPS)has been developed for a nonlinear dynamic analysis of asymmetric in-plan buildings.The 2DMPS procedure scales ground motions to approach close enough to a target value of the inelastic displacement of the first-mode inelastic 2DOF modal stick,extended for structures with significant contributions of higher modes.Further,4-,6-and 13-story RC SMRF buildings were selected for analyses using ground motion records scaled by the 2DMPS procedure,the modal pushover-based scaling method(MPS),and ASCE/SEI 7-16 scaling procedures.The median values of EDPs on scaled records closely matched the benchmark results.The bias in the EDP values due to the scaled records in every group regarding their median value was lower than the dispersion of the 21 unscaled records.These results generally demonstrate the accuracy and efficiency of the 2DMPS method.Additionally,the 2DOF modal stick’s inelastic response spectra are better suited for calculating seismic demands for one-way asymmetric-plan structures than the SDOF inelastic response spectra. 展开更多
关键词 intensity measure record selection asymmetric structures modal pushover method record scaling inelastic response spectra
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Multi-objective ANN-driven genetic algorithm optimization of energy efficiency measures in an NZEB multi-family house building in Greece 认领 引用
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《建筑节能（中英文）》 CAS 2026年第2期62-62,共1页
The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measu... The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%. 展开更多
关键词 energy efficiency measures gas boilerssplit units building envelope components energy efficiency economic performance artificial neural network ann driven multi objective optimization economic performance optimization ANN driven GA methods
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Sub-Pixel-Level Visual Inspection System for Dimensional Measurement of Ceramic Insulators Based on Halcon:Design and Implementation 认领 引用
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作者 Yuehua Cao Jiajie Han +1 位作者 Hanyang Zhu Ge Yuan 《Journal of Electronic Research and Application》 2026年第3期62-72,共11页
Aiming at the problems of low efficiency,poor accuracy consistency,and reliance on empirical judgment in the manual dimension inspection of ceramic insulators during the production process,a sub-pixel-level visual ins... Aiming at the problems of low efficiency,poor accuracy consistency,and reliance on empirical judgment in the manual dimension inspection of ceramic insulators during the production process,a sub-pixel-level visual inspection system based on the Halcon platform was designed.Taking the 95-porcelain insulators with a 60×60 specification as the research object,a three-layer inspection architecture of“hardware acquisition-software processing-data output”was constructed.Through key technologies such as camera calibration,distortion correction,sub-pixel contour extraction,and template matching,the automatic measurement of three core dimensions of the insulator,namely height,width,and shed distance,was achieved.The experimental results show that the detection error of this system is controlled within the range of 0.5-1.2mm,the detection success rate reaches 99.2%,the detection time per sample is 2s,and the efficiency is 40%higher than that of traditional manual inspection.It can accurately meet the dimension inspection requirements of“GB/T 772-2005 Technical Conditions for Porcelain Insulators for High-voltage Overhead Lines”.This system requires no human intervention,and the detection results are stable and reliable.It provides an efficient solution for the on-line quality control in the production process of ceramic insulators and has important engineering application value. 展开更多
关键词 Ceramic insulators Machine vision Halcon Sub-pixel detection Calibration method Dimension measurement Distortion correction PLC control Zhang Zhengyou
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Histogram method for reliable thickness measurements of graphene films using atomic force microscopy(AFM) 认领 引用 被引量：9
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作者 Yaxuan Yao Lingling Ren +1 位作者 Sitian Gao Shi Li 《Journal of Materials Science & Technology》 SCIE EI CAS CSCD 2017年第8期815-820,共6页
Atomic force microscopy（AFM） is a commonly used technique for graphene thickness measurement.However, due to surface roughness caused by graphene itself and variation introduced in AFM measurement, graphene thicknes... Atomic force microscopy（AFM） is a commonly used technique for graphene thickness measurement.However, due to surface roughness caused by graphene itself and variation introduced in AFM measurement, graphene thickness is difficult to be accurately determined by AFM. In this paper, a histogram method was used for reliable measurements of graphene thickness using AFM. The influences of various measurement parameters in AFM analysis were investigated. The experimental results indicate that significant deviation can be introduced using various order of flatten and improperly selected measurement parameters including amplitude setpoint and drive amplitude. At amplitude setpoint of 100 mV and drive amplitude of 100 m V, thickness of 1 layer（1L）, 2 layers（2L） and 4 layers（4L） graphene were measured.The height differences for 1L, 2L and 4L were 1.51 ± 0.16 nm, 1.92 ± 0.13 nm and 2.73 ± 0.10 nm, respectively. By comparing these values, thickness of single layer graphene can be accurately determined to be0.41 ± 0.09 nm. 展开更多
关键词 Graphene Thickness measurement Atomic force microscopy Histogram method
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