Second-Order MaxEnt Predictive Modelling Methodology. III: Illustrative Application to a Reactor Physics Benchmark

This work illustrates the innovative results obtained by applying the recently developed the 2nd-order predictive modeling methodology called “2nd- 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 2nd-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 2nd-order response sensitivities must always be included to quantify the need for including (or not) the 3rd- and/or 4th-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 1st- and 2nd-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 3rd- and even 4th-order sensitivities are necessary to ensure consistency between the computed and measured response. In such cases, the use of only the 1st-order sensitivities erroneously indicates that the computed results are inconsistent with the respective measured response. Ongoing research aims at extending the 2nd-BERRU-PM methodology to fourth-order, thus enabling the computation of third-order response correlations (skewness) and fourth-order response correlations (kurtosis).

Elements and Steps of E-Learning Benchmarking Model for Higher Education Institutions

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.

Semi-active model predictive control for 3rd generation benchmark problem using smart dampers

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.

基于遗传算法的斜拉桥基准模型参数修正方法

健康监测对于斜拉桥结构全寿命的安全使用十分重要,而使用传感器采集斜拉桥数据进行健康监测存在盲区.结合Benchmark模型对桥梁结构进行监测,能够在给定状态下,比较和评价不同的健康监测方法标准,对桥梁的设计、运营以及管养等方面有重要意义.本文基于背景工程,提出用于斜拉桥结构健康监测的基准模型.首先,使用Matlab建立斜拉桥的鱼骨梁简化有限元模型,并建立斜拉桥的板壳单元精细模型,作为简化补充模型和模态矫正模型;其次,采用正交试验设计,对建模过程中的待修正参数进行斜拉桥动力特性参数的显著性分析;最后,基于遗传算法对模型参数进行修正,提出了动态自适应技术和并列选择的方法优化遗传算法结构,干涉遗传选择过程,并赋予初始种群更高的离散性,与调用GA函数的方法对模型进行修正进行比较,验证了改进后的遗传算法具有更高的计算效率,模态参数误差较小.

科技创新能促进数字新质生产力提升吗?——以数字普惠金融为调节变量

科技创新能够催生新模式、新产业、新动能,是发展与培养数字新质生产力的核心要素与强劲动力。本文选取我国2013—2022年31个省区市(未包括港澳台)面板数据对科技创新赋能数字新质生产力的影响效应、作用机制进行经验分析。研究表明:科技创新对数字新质生产力具有显著促进作用,且经过一系列稳健性检验后结果依旧成立;机制分析可知,数字普惠金融在科技创新赋能数字新质生产力提升过程中具有显著调节作用;区域异质性研究显示,科技创新对东部地区与高经济发展水平省份数字新质生产力的促进作用更强。根植于此,要完善“资源+培养+制度”科技创新体系,加快发展数字新质生产力“关键引擎”;推进数字普惠金融基础设施建设,发挥原创性颠覆性科技创新“核心效能”;构建区域协调发展新机制,夯实科技创新优势地区“辐射带动”基础,进而为数字新质生产力提升有效赋能。

中国钢铁极致能效降碳实践与基础研究

能效提升不仅是钢铁产业转型升级的内在要求,也是其实现绿色低碳高质量发展的关键驱动力。中国钢铁工业协会推进的极致能效工程,通过成熟技术快速推广应用、共性难题技术协同研发以及系列政策、法规、标准等的制定,是实现极致能效牵引钢铁极致效率的一项行业性工程。“能效达标三年行动”是落实钢铁极致能效工程的重要举措。梳理总结该举措的实践进展及实施绩效,提出数据系统是实现能效对标扶优汰劣、产能治理的基础,并以数据治理为研究目标,基于质能平衡原理,提出了能耗数据质量诊断新方法和典型工序的3层多阶理论能耗数据评价机制。最后,以烧结、高炉为例,从采集数据的边界划分、不同阶段理论能耗的计算方法确定、过程关键元素守恒的数据质量诊断、折标系数的合理选取等多个角度对数据质量和评价机制进行了梳理与讨论。利用建立的3层多阶能耗计算模型,在热量与标准煤等效折标的前提下,获得了烧结工序的理论、技术与实际极限能耗,并对影响烧结工序能耗的关键参数进行了敏感性排序,由大到小依次是漏风率、配水量、碱度、返矿率、热损失、生石灰、FeO含量、MgO含量。与此同时,还获得了高炉工序的理论与实际极限能耗,为钢铁行业的节能降碳提供了一定的理论数据支撑。

超高层建筑结构benchmark模型及其地震反应分析

参照上海中心,根据设定的性能目标设计了一个超高层建筑结构的benchmark模型用于超高层建筑结构抗震研究。该结构总高度为606.1 m,抗震设防烈度为7度,场地类别为IV类,设计分组为第一组。该结构采用巨型框架-核心筒-伸臂桁架钢-混凝土混合结构体系,8道环带桁架将结构分为9个区,环带桁架与型钢混凝土巨柱共同构成了巨型框架结构体系,并通过6道伸臂桁架与核心筒相连,共同承受水平荷载。利用PERFORM-3D软件建立了结构的非线性数值计算模型,对结构进行了弹塑性地震反应分析,验证了结构的抗震性能。计算结果表明,满足现行设计规范的该超高层结构在大震作用下具有较大的安全余量。

竖向地震作用下层间隔震结构的动力反应研究

文章针对竖向地震作用下高层结构隔震层位置变化对结构竖向动力反应的影响问题,研究5种层间隔震结构分别在3种竖向地震作用下的竖向动力反应。以国际平台的20层Benchmark钢结构模型为基准模型,利用ANSYS软件建立隔振层分别位于第1层、第3层、第5层、第7层和第9层的层间隔震结构有限元数值模型,对比分析5种层间隔震结构分别在竖向ElCentro波、竖向Taft波、竖向天津波作用下的楼层竖向位移、楼层位移角、楼层竖向加速度和基底轴力等竖向动力反应。结果表明:在竖向地震作用下,楼层竖向位移和楼层位移角控制效果较差,甚至会出现增大的现象,基底轴力具有较小的控制效果;随着隔震层位置的升高,楼层竖向加速度和基底轴力均逐渐增大,但当隔震层位于第9层时,楼层竖向加速度和基底轴力相较于隔震层位于第7层时有一定的减小。该文研究成果可用于考虑竖向地震作用的高层结构抗震设计。

斜拉桥地震响应振动控制Benchmark问题研究

文章建立了斜拉桥结构的有限元模型和振动控制Benchmark模型,采用LQG控制算法和最优控制理论,基于MATLAB环境的Simulink程序,对斜拉桥结构振动的主动控制以及Benchmark问题进行研究,给出了独塔双面索斜拉桥在随机干扰作用下振动控制的仿真结果。

地震激励下斜拉桥振动控制Benchmark模型研究

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。

PeMeBench:中文儿科医疗问答基准测试方法

大语言模型在医疗领域显现出巨大的应用潜力,如何评估其在医疗领域中的性能成为挑战。现有医疗评测基准测试多为选择题形式,难以全面和精准地评估模型在儿科医疗场景中的性能。为此,提出首个中文儿科医疗问答基准测试方法——PeMeBench。该方法基于双视角评估维度,参考来自10个儿科疾病系统的诊疗规范类书籍,将儿科医疗问答任务细分为疾病知识、治疗方案、用药剂量、疾病预防和药理作用5个儿科医疗问答子任务,构建超1万个开放式的问答题目,引入一种融合实体召回和检测语句幻觉的多粒度自动化评估方案,旨在对大语言模型在儿科基础医疗领域中的性能进行全面、准确的评估,深入剖析其潜在局限性,为提升医疗服务的智能化水平奠定坚实的基础。

A benchmark city for seismic resilience assessment

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.

图神经网络节点分类任务基准测试及分析

图神经网络(Graph Neural Network,GNN)模型由于采用端到端的模型架构,在训练过程中能够更好地将节点隐藏特征的学习和分类目标协同起来,相比图嵌入(Graph Embedding)的方法,其在节点分类等任务上得到了较大的性能提升。但是,已有图神经网络模型实验对比阶段普遍存在的数据集类型单一、样本量不足、数据集切分不规范、对比模型规模及范围有限、评价指标单一、缺乏模型训练耗时对比等问题。为此,文中选取了包括cora,citeseer,pubmed,deezer等在内的来自不同领域(引文网络、社交网络及协作网络等)的共计20种数据集,以准确率、精确率、召回率、F-score值及模型训练耗时为多维评价指标,在FastGCN,PPNP,ChebyNet,DAGNN等17种主流图神经网络模型上,进行了全面且公平的节点分类任务基准测评,进而为真实业务场景下的模型选择提供了决策参考。通过基准测试实验发现,一方面,影响模型训练速度的因素排名依次是节点属性维度、图节点规模及图边的规模;另一方面,并不存在赢者通吃的模型,即不存在在所有数据集下全都表现优异的模型,特别是在公平的基准测试配置环境下,结构简洁的模型反而比复杂的GNN模型有着更好的性能表现。

环境激励下Benchmark结构损伤识别的试验研究

针对结构健康监测中如何利用在线监测数据进行健康诊断的问题,基于时间序列分析提出了一种新的损伤识别方法。首先,获得结构健康状态的监测数据作为参考状态样本,对各数据样本建立ARMA模型并计算模型残差的方差。然后,将未知状态的监测数据作为待检状态样本,代入已建立的参考状态ARMA模型计算新的残差方差。计算发现,损伤前后两状态模型残差方差存在差异。因而,提出以残差方差之比作为损伤敏感特征,并建立基于F分布的假设检验来辨识结构的状态并预警损伤。最后,以Benchmark结构在环境激励下的试验为例,运用本文方法进行了损伤识别研究。结果表明,基于ARMA模型残差方差的损伤敏感特征可准确地区别结构的健康状态和损伤状态,具备结构在线实时损伤识别的应用价值。

数字经济对居民消费潜力的影响效应研究——基于空间杜宾数学模型的实证分析

在全球经济增长放缓的形势下,为尽快恢复经济复苏增长并推动国内大循环,加快实现国内国际双循环发展就离不开对居民有效消费需求的引导及其消费潜力的释放。近年来,以大数据、5G、人工智能为依托的经济数字化转型已深刻影响社会的各个层面,作为拉动国民经济增长重要引擎的消费领域自然也受到其深刻影响。文章基于2017—2021年全国主要99个地级市的面板数据,通过实证分析探讨数字经济发展对居民消费潜力及其各维度的作用效果和溢出效应。结果表明:(1)数字经济发展对居民消费潜力及其消费支出维度、消费收入维度和消费环境维度均有积极作用;(2)数字经济对促进居民消费潜力释放具有正向的空间溢出效应;(3)相对居民消费潜力中的收入和支出维度,数字经济对居民消费环境维度的正向空间溢出效应更加明显。

基于ANSYS软件benchmark模型耗能减振控制分析

本文系统介绍了当前国际结构振动控制的公共平台———Benchm ark模型,首次给出使用通用有限元软件ANSYS对第3阶段20层非线性钢框架抗震结构的有限元建模,结果表明,模态、无控地震反应分析结果和ASCE给出的MATLAB结果相同。利用粘滞阻尼器对此模型的耗能减振数值仿真分析的结果表明:粘滞阻尼器是一种性能很好的阻尼器,使用本文给出ANSYS的Benchm ark有限元模型来进行耗能减振控制分析是方便的、可行的。

基于智能压电摩擦阻尼器的Benchmark模型风振响应半主动控制

在改进的Pall摩擦耗能器的基础上设计了一种智能压电摩擦阻尼器,并分析了其阻尼力模型。利用设计出的智能摩擦阻尼器,采用基于经典线性最优控制理论的半主动控制策略对Benchm ark模型的风振响应控制进行了研究。结果表明:智能压电摩擦阻尼器对标准风振控制模型的半主动控制效果较为明显,相对于无控结构来说能有效降低结构的风振响应。此外,本文对基于限界Hrovat最优控制算法的半主动控制系统的参数优化进行了分析,说明了该半主动控制系统对Benchm ark模型阻尼的不确定性具有很好的鲁棒性,而对刚度的不确定性则表现出一定的敏感性。

基于Benchmark技术的汽车正面碰撞仿真建模

介绍Benchmark的工作流程;根据某车型Benchmark数据,采用有限元分析方法,建立包括车身结构、发动机和底盘结构的用于正面碰撞的整车有限元模型;根据实验结果验证模型的有效性。

Illustrative Application of the 2^nd-Order Adjoint Sensitivity Analysis Methodology to a Paradigm Linear Evolution/Transmission Model: Reaction-Rate Detector Response

This work continues the illustrative application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2nd-CASAM) to a benchmark mathematical model that can simulate the evolution and/or transmission of particles in a heterogeneous medium. The model response considered in this work is a reaction-rate detector response, which provides the average interactions of particles with the respective detector or, alternatively, the time-average of the concentration of a mixture of substances in a medium. The definition of this model response includes both uncertain boundary points of the benchmark, thereby providing both direct and indirect contributions to the response sensitivities stemming from the boundaries. The exact expressions for the 1st- and 2nd-order response sensitivities to the boundary and model parameters obtained in this work can serve as stringent benchmarks for inter-comparing the performances of all (deterministic and statistical) sensitivity analysis methods.

Illustrative Application of the 2^nd-Order Adjoint Sensitivity Analysis Methodology to a Paradigm Linear Evolution/Transmission Model: Point-Detector Response

This work illustrates the application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2nd-CASAM) to a mathematical model that can simulate the evolution and/or transmission of particles in a heterogeneous medium. The model response is the value of the model’s state function (particle concentration or particle flux) at a point in phase-space, which would simulate a pointwise measurement of the respective state function. This paradigm model admits exact closed-form expressions for all of the 1st- and 2nd-order response sensitivities to the model’s uncertain parameters and domain boundaries. These closed-form expressions can be used to verify the numerical results of production and/or commercial software, e.g., particle transport codes. Furthermore, this paradigm model comprises many uncertain parameters which have relative sensitivities of identical magnitudes. Therefore, this paradigm model could serve as a stringent benchmark for inter-comparing the performances of all deterministic and statistical sensitivity analysis methods, including the 2nd-CASAM.