Advancing the integration of artificial intelligence and polymer science requires high-quality,open-source,and large-scale datasets.However,existing polymer databases often suffer from data sparsity,lack of polymer-pr...Advancing the integration of artificial intelligence and polymer science requires high-quality,open-source,and large-scale datasets.However,existing polymer databases often suffer from data sparsity,lack of polymer-property labels,and limited accessibility,hindering system-atic modeling across property prediction tasks.Here,we present OpenPoly,a curated experimental polymer database derived from extensive lit-erature mining and manual validation,comprising 3985 unique polymer-property data points spanning 26 key properties.We further develop a multi-task benchmarking framework that evaluates property prediction using four encoding methods and eight representative models.Our re-sults highlight that the optimized degree-of-polymerization encoding coupled with Morgan fingerprints achieves an optimal trade-off between computational cost and accuracy.In data-scarce condition,XGBoost outperforms deep learning models on key properties such as dielectric con-stant,glass transition temperature,melting point,and mechanical strength,achieving R2 scores of 0.65-0.87.To further showcase the practical utility of the database,we propose potential polymers for two energy-relevant applications:high temperature polymer dielectrics and fuel cell membranes.By offering a consistent and accessible benchmark and database,OpenPoly paves the way for more accurate polymer-property modeling and fosters data-driven advances in polymer genome engineering.展开更多
The purposes of this research were to 1) develop of an e-learning benchmarking model for higher education institutions;2) analyze and synthesize e-learning indicators for e-learning benchmarking model. The research wa...The purposes of this research were to 1) develop of an e-learning benchmarking model for higher education institutions;2) analyze and synthesize e-learning indicators for e-learning benchmarking model. The research was conducted using the research and development methods. The result shows that there are eight elements of e-learning benchmarking model: 1) team/staffs 2) benchmarking’s title 3) comparative companies 4) benchmarking indicators 5) data collection method 6) analysis data and results 7) report of results and 8) action plan development. Moreover, four steps of benchmarking model will be used in this research. “Plan” is the step of setting team for benchmarking title and choosing the company to collect the benchmarking while “Do” is a field study in order to analyze and collect each indicator. The step “Check” presents the data to stakeholders and set the purposes of action plan. Finally, “Act” which is the development of action plan leads to the practice or implementation which related to auditing and evaluating.展开更多
A semi-active strategy for model predictive control （MPC）, in which magneto-rheological dampers are used as an actuator, is presented for use in reducing the nonlinear seismic response of high-rise buildings. A mult...A semi-active strategy for model predictive control （MPC）, in which magneto-rheological dampers are used as an actuator, is presented for use in reducing the nonlinear seismic response of high-rise buildings. A multi-step predictive model is developed to estimate the seismic performance of high-rise buildings, taking into account of the effects of nonlinearity, time-variability, model mismatching, and disturbances and uncertainty of controlled system parameters by the predicted error feedback in the multi-step predictive model. Based on the predictive model, a Kalman-Bucy observer suitable for semi-active strategy is proposed to estimate the state vector from the acceleration and semi-active control force feedback. The main advantage of the proposed strategy is its inherent stability, simplicity, on-line real-time operation, and the ability to handle nonlinearity, uncertainty, and time-variability properties of structures. Numerical simulation of the nonlinear seismic responses of a controlled 20-story benchmark building is carried out, and the simulation results are compared to those of other control systems. The results show that the developed semi-active strategy can efficiently reduce the nonlinear seismic response of high-rise buildings.展开更多
This work illustrates the innovative results obtained by applying the recently developed the 2<sup>nd</sup>-order predictive modeling methodology called “2<sup>nd</sup>- BERRU-PM”, where the ...This work illustrates the innovative results obtained by applying the recently developed the 2<sup>nd</sup>-order predictive modeling methodology called “2<sup>nd</sup>- BERRU-PM”, where the acronym BERRU denotes “best-estimate results with reduced uncertainties” and “PM” denotes “predictive modeling.” The physical system selected for this illustrative application is a polyethylene-reflected plutonium (acronym: PERP) OECD/NEA reactor physics benchmark. This benchmark is modeled using the neutron transport Boltzmann equation (involving 21,976 uncertain parameters), the solution of which is representative of “large-scale computations.” The results obtained in this work confirm the fact that the 2<sup>nd</sup>-BERRU-PM methodology predicts best-estimate results that fall in between the corresponding computed and measured values, while reducing the predicted standard deviations of the predicted results to values smaller than either the experimentally measured or the computed values of the respective standard deviations. The obtained results also indicate that 2<sup>nd</sup>-order response sensitivities must always be included to quantify the need for including (or not) the 3<sup>rd</sup>- and/or 4<sup>th</sup>-order sensitivities. When the parameters are known with high precision, the contributions of the higher-order sensitivities diminish with increasing order, so that the inclusion of the 1<sup>st</sup>- and 2<sup>nd</sup>-order sensitivities may suffice for obtaining accurate predicted best- estimate response values and best-estimate standard deviations. On the other hand, when the parameters’ standard deviations are sufficiently large to approach (or be outside of) the radius of convergence of the multivariate Taylor-series which represents the response in the phase-space of model parameters, the contributions stemming from the 3<sup>rd</sup>- and even 4<sup>th</sup>-order sensitivities are necessary to ensure consistency between the computed and measured response. In such cases, the use of only the 1<sup>st</sup>-order sensitivities erroneously indicates that the computed results are inconsistent with the respective measured response. Ongoing research aims at extending the 2<sup>nd</sup>-BERRU-PM methodology to fourth-order, thus enabling the computation of third-order response correlations (skewness) and fourth-order response correlations (kurtosis).展开更多
The concept of seismic resilience has received significant attention from academia and industry during the last two decades. Different frameworks have been proposed for seismic resilience assessment of engineering sys...The concept of seismic resilience has received significant attention from academia and industry during the last two decades. Different frameworks have been proposed for seismic resilience assessment of engineering systems at different scales(e.g., buildings, bridges, communities, and cities). Testbeds including Centerville virtual community(CVC), Memphis testbed(MTB), and the virtual city of Turin, Italy(VC-TI) have been developed during the last decade. However, the resilience assessment results of Chinese cities still require calibration based on a unified evaluation model. Therefore, a geographic information system(GIS)-based benchmark model of a medium-sized city located in the southeastern coastal region of China was developed. The benchmark city can be used to compare existing assessment frameworks and calibrate the assessment results. The demographics, site conditions, and potential hazard exposure of the benchmark city, as well as land use and building inventory are described in this paper. Data of lifeline systems are provided, including power, transportation, water, drainage, and natural gas distribution networks, as well as the locations of hospitals, emergency shelters, and schools. Data from past earthquakes and the literature were obtained to develop seismic fragility models, consequence models, and recovery models, which can be used as basic data or calibration data in the resilience assessment process. To demonstrate the completeness of the data included in the benchmark city, a case study on the accessibility of emergency rescue after earthquakes was conducted, and the preliminary results were discussed. The ultimate goal of this benchmark city is to provide a platform for calibrating resilience assessment results and to facilitate the development of resilient cities in China.展开更多
为了在地震波激励下对大跨桥梁结构建立一套振动控制系统评价体系,比较不同控制策略的控制效果,将艾默生纪念桥(Emerson Memorial Bridge)作为斜拉桥振动控制的Benchmark模型,用以研究地震激励下斜拉桥振动控制所采取的各种控制算法和...为了在地震波激励下对大跨桥梁结构建立一套振动控制系统评价体系,比较不同控制策略的控制效果,将艾默生纪念桥(Emerson Memorial Bridge)作为斜拉桥振动控制的Benchmark模型,用以研究地震激励下斜拉桥振动控制所采取的各种控制算法和装置的有效性。系统总结十余年来各国学者在该研究中涉及到的各种传统控制算法以及智能算法,阐述了该桥被动控制、主动控制、半主动控制、混合控制的应用情况,对未来的研究趋势进行展望。以艾默生纪念桥为例,选取新型主动EMD阻尼器作为控制装置,实施基于模糊推理的智能控制。将EMD装置的速度作为模糊控制器输入,制定模糊规则,快速、有效地确定EMD装置输出电压,从而对该桥在线实时控制。数值仿真结果表明:18项控制指标接近于样本控制,尤其对基础处剪力、倾覆力矩以及桥塔处拉索的减振控制效果明显。展开更多
基金financially supported by the National Natural Science Foundation of China (Nos. 92372126,52373203)the Excellent Young Scientists Fund Program
文摘Advancing the integration of artificial intelligence and polymer science requires high-quality,open-source,and large-scale datasets.However,existing polymer databases often suffer from data sparsity,lack of polymer-property labels,and limited accessibility,hindering system-atic modeling across property prediction tasks.Here,we present OpenPoly,a curated experimental polymer database derived from extensive lit-erature mining and manual validation,comprising 3985 unique polymer-property data points spanning 26 key properties.We further develop a multi-task benchmarking framework that evaluates property prediction using four encoding methods and eight representative models.Our re-sults highlight that the optimized degree-of-polymerization encoding coupled with Morgan fingerprints achieves an optimal trade-off between computational cost and accuracy.In data-scarce condition,XGBoost outperforms deep learning models on key properties such as dielectric con-stant,glass transition temperature,melting point,and mechanical strength,achieving R2 scores of 0.65-0.87.To further showcase the practical utility of the database,we propose potential polymers for two energy-relevant applications:high temperature polymer dielectrics and fuel cell membranes.By offering a consistent and accessible benchmark and database,OpenPoly paves the way for more accurate polymer-property modeling and fosters data-driven advances in polymer genome engineering.
文摘The purposes of this research were to 1) develop of an e-learning benchmarking model for higher education institutions;2) analyze and synthesize e-learning indicators for e-learning benchmarking model. The research was conducted using the research and development methods. The result shows that there are eight elements of e-learning benchmarking model: 1) team/staffs 2) benchmarking’s title 3) comparative companies 4) benchmarking indicators 5) data collection method 6) analysis data and results 7) report of results and 8) action plan development. Moreover, four steps of benchmarking model will be used in this research. “Plan” is the step of setting team for benchmarking title and choosing the company to collect the benchmarking while “Do” is a field study in order to analyze and collect each indicator. The step “Check” presents the data to stakeholders and set the purposes of action plan. Finally, “Act” which is the development of action plan leads to the practice or implementation which related to auditing and evaluating.
基金Fujian Province Youth Foundation for InnovativResearch Under Grant No. 2006F3008Fujian ProvincEducational Special Foundation Under Grant No. JA06027
文摘A semi-active strategy for model predictive control （MPC）, in which magneto-rheological dampers are used as an actuator, is presented for use in reducing the nonlinear seismic response of high-rise buildings. A multi-step predictive model is developed to estimate the seismic performance of high-rise buildings, taking into account of the effects of nonlinearity, time-variability, model mismatching, and disturbances and uncertainty of controlled system parameters by the predicted error feedback in the multi-step predictive model. Based on the predictive model, a Kalman-Bucy observer suitable for semi-active strategy is proposed to estimate the state vector from the acceleration and semi-active control force feedback. The main advantage of the proposed strategy is its inherent stability, simplicity, on-line real-time operation, and the ability to handle nonlinearity, uncertainty, and time-variability properties of structures. Numerical simulation of the nonlinear seismic responses of a controlled 20-story benchmark building is carried out, and the simulation results are compared to those of other control systems. The results show that the developed semi-active strategy can efficiently reduce the nonlinear seismic response of high-rise buildings.
文摘This work illustrates the innovative results obtained by applying the recently developed the 2<sup>nd</sup>-order predictive modeling methodology called “2<sup>nd</sup>- BERRU-PM”, where the acronym BERRU denotes “best-estimate results with reduced uncertainties” and “PM” denotes “predictive modeling.” The physical system selected for this illustrative application is a polyethylene-reflected plutonium (acronym: PERP) OECD/NEA reactor physics benchmark. This benchmark is modeled using the neutron transport Boltzmann equation (involving 21,976 uncertain parameters), the solution of which is representative of “large-scale computations.” The results obtained in this work confirm the fact that the 2<sup>nd</sup>-BERRU-PM methodology predicts best-estimate results that fall in between the corresponding computed and measured values, while reducing the predicted standard deviations of the predicted results to values smaller than either the experimentally measured or the computed values of the respective standard deviations. The obtained results also indicate that 2<sup>nd</sup>-order response sensitivities must always be included to quantify the need for including (or not) the 3<sup>rd</sup>- and/or 4<sup>th</sup>-order sensitivities. When the parameters are known with high precision, the contributions of the higher-order sensitivities diminish with increasing order, so that the inclusion of the 1<sup>st</sup>- and 2<sup>nd</sup>-order sensitivities may suffice for obtaining accurate predicted best- estimate response values and best-estimate standard deviations. On the other hand, when the parameters’ standard deviations are sufficiently large to approach (or be outside of) the radius of convergence of the multivariate Taylor-series which represents the response in the phase-space of model parameters, the contributions stemming from the 3<sup>rd</sup>- and even 4<sup>th</sup>-order sensitivities are necessary to ensure consistency between the computed and measured response. In such cases, the use of only the 1<sup>st</sup>-order sensitivities erroneously indicates that the computed results are inconsistent with the respective measured response. Ongoing research aims at extending the 2<sup>nd</sup>-BERRU-PM methodology to fourth-order, thus enabling the computation of third-order response correlations (skewness) and fourth-order response correlations (kurtosis).
基金Scientific Research Fund of Institute of Engineering Mechanics,China Earthquake Administration under Grant Nos. 2019EEEVL0505,2019B02 and 2019A02Heilongjiang Touyan Innovation Team Program。
文摘The concept of seismic resilience has received significant attention from academia and industry during the last two decades. Different frameworks have been proposed for seismic resilience assessment of engineering systems at different scales(e.g., buildings, bridges, communities, and cities). Testbeds including Centerville virtual community(CVC), Memphis testbed(MTB), and the virtual city of Turin, Italy(VC-TI) have been developed during the last decade. However, the resilience assessment results of Chinese cities still require calibration based on a unified evaluation model. Therefore, a geographic information system(GIS)-based benchmark model of a medium-sized city located in the southeastern coastal region of China was developed. The benchmark city can be used to compare existing assessment frameworks and calibrate the assessment results. The demographics, site conditions, and potential hazard exposure of the benchmark city, as well as land use and building inventory are described in this paper. Data of lifeline systems are provided, including power, transportation, water, drainage, and natural gas distribution networks, as well as the locations of hospitals, emergency shelters, and schools. Data from past earthquakes and the literature were obtained to develop seismic fragility models, consequence models, and recovery models, which can be used as basic data or calibration data in the resilience assessment process. To demonstrate the completeness of the data included in the benchmark city, a case study on the accessibility of emergency rescue after earthquakes was conducted, and the preliminary results were discussed. The ultimate goal of this benchmark city is to provide a platform for calibrating resilience assessment results and to facilitate the development of resilient cities in China.
文摘为了在地震波激励下对大跨桥梁结构建立一套振动控制系统评价体系,比较不同控制策略的控制效果,将艾默生纪念桥(Emerson Memorial Bridge)作为斜拉桥振动控制的Benchmark模型,用以研究地震激励下斜拉桥振动控制所采取的各种控制算法和装置的有效性。系统总结十余年来各国学者在该研究中涉及到的各种传统控制算法以及智能算法,阐述了该桥被动控制、主动控制、半主动控制、混合控制的应用情况,对未来的研究趋势进行展望。以艾默生纪念桥为例,选取新型主动EMD阻尼器作为控制装置,实施基于模糊推理的智能控制。将EMD装置的速度作为模糊控制器输入,制定模糊规则,快速、有效地确定EMD装置输出电压,从而对该桥在线实时控制。数值仿真结果表明:18项控制指标接近于样本控制,尤其对基础处剪力、倾覆力矩以及桥塔处拉索的减振控制效果明显。
