A process-level hierarchical structural decomposition analysis (SDA) of energy consumption in an integrated steel plant

A hierarchical structural decomposition analysis(SDA) model has been developed based on process-level input-output(I-O) tables to analyze the drivers of energy consumption changes in an integrated steel plant during 2011-2013. By combining the principle of hierarchical decomposition into D&L method, a hierarchical decomposition model for multilevel SDA is obtained. The developed hierarchical IO-SDA model would provide consistent results and need less computation effort compared with the traditional SDA model. The decomposition results of the steel plant suggest that the technology improvement and reduced steel final demand are two major reasons for declined total energy consumption. The technical improvements of blast furnaces, basic oxygen furnaces, the power plant and the by-products utilization level have contributed mostly in reducing energy consumption. A major retrofit of ancillary process units and solving fuel substitution problem in the sinter plant and blast furnace are important for further energy saving. Besides the empirical results, this work also discussed that why and how hierarchical SDA can be applied in a process-level decomposition analysis of aggregated indicators.

APPLICATION OF DOMAIN DECOMPOSITION IN ACOUSTIC AND STRUCTURAL ACOUSTIC ANALYSIS

Conventional element based methods for modeling acoustic problems are limited to low-frequency applications due to the huge computational efforts. For high-frequency applications, probabilistic techniques, such as statistical energy analysis （SEA）, are used. For mid-frequency range, currently no adequate and mature simulation methods exist. Recently, wave based method has been developed which is based on the indirect TREFFTZ approach and has shown to be able to tackle problems in the mid-frequency range. In contrast with the element based methods, no discretization is required. A sufficient, but not necessary, condition for convergence of this method is that the acoustic problem domain is convex. Non-convex domains have to be partitioned into a number of （convex） subdomains. At the interfaces between subdomains, specific coupling conditions have to be imposed. The considered two-dimensional coupled vibro-acoustic problem illustrates the beneficial convergence rate of the proposed wave based prediction technique with high accuracy. The results show the new technique can be applied up to much higher frequencies.

Structural Decomposition Analysis on Energy Intensity Changes at Regional Level

As China's energy intensity fluctuated in recent years, it is necessary to examine whether this fluctuation happened at a regional level. This paper establishes a decomposition model by using the structural decomposition analysis (SDA) method at a regional level. Then this model is employed to empirically analyze the changes of Beijing's energy intensity. The conclusions are as follows: during 2002-2010, except petroleum, the energy intensity decreased and the changes were mostly attributed to the technology changes, while the final use variation actually increased the energy intensity; comparing different periods of 2002-2010, the decline rates of energy intensity for coal and hydropower were decreasing, resulting from the production technology being more energy-intensive than before; the energy intensity changes of petroleum firstly increased substantially and then decreased moderately.

Factor Decomposition and Regression Analysis of the Energy Related Carbon Emissions in Shandong, China: A Perspective of Industrial Structure

An in-depth study of the energy related carbon emissions has important practical significance for carbon emissions reduction and structural adjustment in Shandong Province and throughout China.Based on the perspective of industrial structure,the expanded KAYA equation to measure the energy related carbon emissions of the primary industries(Resources and Agriculture)and secondary industries(Manufacturing and Construction)and tertiary industries(Retail and Service)was utilized in Shandong Province from 2011 to 2017.The carbon emissions among industries in Shandong Province were empirically analyzed using the Logarithmic Mean Divisia Index decomposition approach.The results were follows:(1)Under the three industrial dimensions,the energy structure effect and the energy intensity effect have a restraining influence on the carbon emissions of the three industries.(2)The development level effect and the employment scale effect play a pulling role in carbon emissions.(3)From the perspective of the employment structure effect of the primary industry,there is a restraining effect on carbon emissions,while the employment structure effects of the secondary and tertiary industries play a pulling role in carbon emissions,and the employment structure effect of the tertiary industry has a greater pulling effect on carbon emissions than the secondary industry.

A SINGULAR VALUE DECOMPOSITION BASED TRUNCATION ALGORITHM IN SOLVING THE STRUCTURAL DAMAGE EQUATIONS

The structural damage identification through modal data often leads to solving a set of linear equations. Special numerical treatment is sometimes required for an accurate and stable solution owing to the ill conditioning of the equations. Based on the singular value decomposition (SVD) of the coefficient matrix, an error based truncation algorithm is proposed in this paper. By rejection of selected small singular values, the influence of noise can be reduced. A simply-supported beam is used as a simulation example to compare the results to other methods. Illustrative numerical examples demonstrate the good efficiency and stability of the algorithm in the nondestructive identification of structural damage through modal data.

Influencing mechanism of energy-related carbon emissions in Xinjiang based on the input-output and structural decomposition analysis

Analysis of carbon emission mechanism based on regional perspectives is an im- portant research method capable of achieving energy savings and emission reductions. Xin- jiang, an important Chinese energy production base, is currently going through a period of strategic opportunities for rapid development. Ensuring stable socio-economic development while achieving energy savings and meeting emission reductions targets, is the key issue currently facing the region. This paper is based on the input-output theory, and conducts a structural decomposition analysis on the factors affecting energy-related carbon emissions in Xinjiang from 1997 to 2007; this analysis employs a hybrid input-output analysis framework of ＂energy - economy - carbon emissions＂. （1） Xinjiang＇s carbon emissions from energy con- sumption increased from 20.70 million tons in 1997 to 40.34 million tons in 2007; carbon emissions growth was mainly concentrated in the production and processing of energy re- sources, the mining of mineral resources, and the processing industry. （2） The analysis of the direct effects of the influencing factors on carbon emissions showed that the change in per capita GDP, the final demand structure, the population scale, and the production structure were the important factors causing an increase in carbon emissions, while the decrease in carbon emission intensity during this period was the important influencing factor in stopping the growth of carbon emissions. This showed that while the sizes of Xinjiang＇s economy and population were growing, the economic structure had not been effectively optimized and the production technology had not been efficiently improved, resulting in a rapid growth of carbon emissions from energy consumption. （3） The analysis of the indirect effects of the influencing factors of carbon emission showed that the inter-provincial export, fixed capital formation, and the consumption by urban residents had significant influence on the changes in carbon emissions from energy consumption in Xinjiang. （4） The growth of investments in fixed assets of carbon intensive industry sectors, in addition to the growth of inter-provincial exports ofenergy resource products, makes the transfer effect of inter-provincial ＂embodied carbon＂ very significant.

A DECOMPOSITION METHOD OF STRUCTURAL DECOMPOSITION ANALYSIS

Over the past two decades, structural decomposition analysis (SDA) has developed into a major analytical tool in the field of input-output (IO) techniques, but the method was found to suffer from one or more of the following problems. The decomposition forms, which are used to measure the contribution of a specific determinant, are not unique due to the existence of a multitude of equivalent forms, irrational due to the weights of different determinants not matching, inexact due to the existence of large interaction terms.In this paper, a decomposition method is derived to overcome these deficiencies, and we prove that the result of this approach is equal to the Shapley value in cooperative games,and so some properties of the method are obtained. Beyond that, the two approaches that have been used predominantly in the literature have been proved to be the approximate solutions of the method.

Structural Decomposition Analysis to Investigate the Changes in Energy Consumption in Pakistan

The world energy demand is increasing due to rapid growth in the global economy,industrialization,and urbanization.Pakistan is also confronted with increasing energy demand on one hand and is confronted with the challenge of energy demand-supply gap on the other hand.Since energy is the major driver for growth,it becomes important to investigate the trends of energy consumption in a country and the factors that are most affecting the changes in the use of energy.This particular study aims to investigate the use of energy by all the economic sectors of Pakistan during 2000–2012.The major contribution is the first time application of structural decomposition analysi for energy usage along with using Input-Output data for the period of 2002–2012.The results show the fluctuation of the energy intensity of the sectors throughout the study period.Also,the overall effect of energy intensity is negative on energy consumption and it shows a negative contribution value of-80.90%for the study period.Furthermore,the focus on more energy-intensive products like cement,automobiles,iron,steel products and the increasing final demand of the economy contributes to the growth of energy consumption in Pakistan during 2000–2012.

Decomposition analysis applied to energy and emissions:A literature review

Decomposition analysis has been widely used to assess the determinants of energy and CO_(2)emissions in academic research and policy studies.Both the methodology and application of decomposition analysis have been largely improved in the past decades.After more than 50 years’developments,decomposition studies have become increasingly sophisticated and diversified,and tend to converge internally and integrate with other analytical approaches externally.A good understanding of the literature and state of the art is critical to identify knowledge gaps and formulate future research agenda.To this end,this study presents a literature survey for decomposition analysis applied to energy and emission issues,with a focus on the period of 2016–2021.A review for three individual decomposition techniques is first conducted,followed by a synthesis of emerging trends and features for the decomposition analysis literature as a whole.The findings are expected to direct future research in decomposition analysis.

基于结构分解分析的中国建筑业碳增长影响因素识别

建筑业是我国落实双碳目标的重点领域。为识别建筑业碳排放增长的主要影响因素,基于1997—2017年的数据,构建碳排放核算和结构分解分析模型,分析不同因素的影响效应及其随时间的变化趋势,并从能源和部门两个层面进行分解。结果显示,最终需求规模效应是拉动建筑业碳排放增长最关键的因素,碳排放强度效应一直对碳排放增长起抑制作用,但这种抑制作用随时间增长而减弱,部门关联效应在多数时候起抑制作用;在能源层面,煤炭和电力贡献最大;在部门层面,石油、煤炭及其他燃料加工业、金属冶炼和压延加工业和电力、热力的生产和供应业的影响最为显著。

基于IO-SDA法的2020~2060年中国行业CO_(2)排放预测与分析

采用IO-SDA法测算2017~2020年CO_(2)排放,后结合国内权威预测报告,利用RAS法推导2025~2060年投入产出表和各行业能源消费数据,利用IO-SDA法定量评价各驱动因素在2020~2060年对CO_(2)排放总量和各行业CO_(2)排放量变化的贡献.结果表明:2020~2060年中国行业CO_(2)排放总量呈现先增后降的趋势,2030年左右达峰,后经历平台期,2035年开始快速减排,2050年后减排速度变慢;CO_(2)排放增长的驱动因素为最终需求规模,最主要的促降因素为碳排放强度;投入产出结构和最终需求结构只在个别时期促进CO_(2)排放增长,总体上对CO_(2)减排有积极作用,但作用有限,且伴随着经济结构趋于稳定,这两者的作用逐渐削弱;CO_(2)排放总量和4项因素的变化幅度在达峰平台期、快速减排期与全面中和期3个阶段由小变大再变小;从行业角度看,电力等公共品生产和供应业、金属产品制造业、交通运输仓储和邮政业、化学工业是CO_(2)减排的主要动力.为有效实现CO_(2)减排目标,政府实施CO_(2)减排政策的过程中,应在继续充分发挥碳排放强度积极效应的同时,更加注重释放重点行业技术创新、最终需求结构优化对CO_(2)减排的积极作用.

Fused empirical mode decomposition and wavelets for locating combined damage in a truss-type structure through vibration analysis

Structural health monitoring (SHM) is a relevant topic for civil systems and involves the monitoring, data processing and interpretation to evaluate the condition of a structure, in order to detect damage. In real structures, two or more sites or types of damage can be present at the same time. It has been shown that one kind of damaged condition can interfere with the detection of another kind of damage, leading to an incorrect assessment about the structure condition. Identifying combined damage on structures still represents a challenge for condition monitoring, because the reliable identification of a combined damaged condition is a difficult task. Thus, this work presents a fusion of methodologies, where a single wavelet-packet and the empirical mode decomposition (EMD) method are combined with artificial neural networks (ANNs) for the automated and online identification-location of single or multiple-combined damage in a scaled model of a five-bay truss-type structure. Results showed that the proposed methodology is very efficient and reliable for identifying and locating the three kinds of damage, as well as their combinations. Therefore, this methodology could be applied to detection-location of damage in real truss-type structures, which would help to improve the characteristics and life span of real structures.

完全隐含能源与碳强度研究进展综述

节能减排是应对全球气候变暖的重要举措。由于不同国家和地区的经济发展水平存在明显差异,近年来能源与碳强度成为度量节能减排绩效的重要指标,受到了社会各界的广泛关注。在生产端强度控制的基础上,如何从根源上在消费端降低完全隐含能源与碳强度的研究越来越受到重视。针对消费端完全隐含能源与碳强度的研究特征与发展趋势展开综述,结果发现:(1)主要呈现出国家层面研究为主、全球层面研究显著增加、省市层面研究开始出现的特征,且国家或省市层面主要聚焦于中国;(2)相比完全隐含能源强度,现有文献更为关注完全隐含碳强度;(3)研究由不区分终端消费向细分各终端消费发展,隐含在出口中的完全隐含碳强度受到了重点讨论;(4)部分研究侧重于局部,比如深度参与到全球生产网络的部分经济部门或能源消费与碳排放在生产网络中传输的关键层级;(5)进行完全隐含碳强度变动的驱动因素的研究主要基于乘性结构分解分析模型,从时间轴和空间轴展开剖析。现有研究框架未来可以扩展到能源环境相关领域的其他指标。

Three-Dimensional Density Distribution and Seismic Activity along the Guxiang–Tongmai Segment of the Jiali Fault,Tibet

The Guxiang-Tongmai segment of the Jiali fault is situated northeast of the Namche Barwa Syntaxis in northeastern Tibet.It is one of the most active strike-slip faults near the syntaxis and plays a pivotal role in the examination of seismic activity within the eastern Himalayan Syntaxis.New study in the research region has yielded a 1:200000 gravity dataset covering an area 1500 km^(2).Using wavelet transform multiscale decomposition,scratch analysis techniques,and 3D gravity inversion methods,gravity anomalies,fault distributions,and density structures were determined across various scales.Through the integration of our new gravity data with other geophysical and geological information,our findings demonstrate substantial variations in the overall crustal density within the region,with the fault distribution closely linked to these density fluctuations.Disparities in stratigraphic density are important causes of variations in the capacity of geological formations to endure regional tectonic stress.Earthquakes are predominantly concentrated within the density transition zone and are primarily situated in regions of elevated density.The hanging wall stress within the Guxiang-Tongmai segment of the Jiali fault exhibits a notable concentration,marked by pronounced anisotropy,and is positioned within the density differential zone,which is prone to earthquakes.

A Method to Visualize the Skeleton Industrial Structure with Input-Output Analysis and Its Application in China,Japan and USA

The paper established a double filtering method (DFM) to visualize the skeleton industrial structure (SIS) of one economy and find its evolution rule. Different with the previous researches, this method is from a new view of industrial conjunctions combined by leading sectors to depict the industrial structure. It was proved that the leading sector selected by DFM must be key sector selected by Hirschman-Rasmussen method. Applied DFM to input-output tables of China, Japan and USA and MFA to Japan, and USA, the results analysis showed that DFM could overtake the two main shortcomings of minimum flow analysis (MFA), scratch SIS of each economy with its own characteristics, visualize the general evolution rules of the industrial structure with crisscrossed conjunctions among leading sectors.

Analytic algorithms for Some Models of Nonlinear Age–Structured Population Dynamics and Epidemiology

Three analytic algorithms based on Adomian decomposition, homotopy perturbation and homotopy analysis methods are proposed to solve some models of nonlinear age-structured population dynamics and epidemiology. Truncating the resulting convergent infinite series, we obtain numerical solutions of high accuracy for these models. Three numerical examples are given to illustrate the simplicity and accuracy of the methods.

基于响应面并行子空间设计的载人潜水器优化

为提高载人潜水器的设计效率和综合性能,确定了一型载人潜水器的设计参数,分析了学科与学科、学科与系统之间的关系,完成了基于多学科设计优化思想的载人潜水器学科分解,建立了载人潜水器结构设计矩阵。利用响应面模型建立了艇型与推进、结构等学科的学科分析模型,利用公式建立了其他学科及系统层分析模型。以艇重为目标函数,分别建立了基于响应面并行子空间设计和基于并行子空间优化的载人潜水器优化框架,可实现优化过程中的近似模型更新,以提高求解效率及精度。利用上述2个框架进行了优化求解,结果表明:相比初始方案,并行子空间设计并行子空间设计减重为7.822%、并行子空间优化减重为7.311%,但并行子空间设计在计算精度、求解效率和最优解获取的概率等方面更具有优势。

中国出口内涵要素结构与外贸高质量发展路径

本文借助多国投入产出模型构建了多生产要素视角下分解增加值贸易生产要素结构的单国模型。运用该模型将出口总值分解为出口中国内增加值、出口中进口国增加值和出口中第三(其他)国增加值,分别对三类出口增加值进行要素结构解析,测算出资本和三种劳动力要素对出口贸易的贡献,最后用结构分解分析法对各要素在增加值贸易中的贡献变动进行影响因素分析。结果显示:在研究期间,中国单位出口增加值中资本和高技能劳动力的贡献总体呈上升趋势,高技能劳动力扩大了各行业创造增加值的差距。在此期间,出口规模正效应影响着多数行业的三类增加值;入世后,多数制造业的三类增加值受到出口中第三(其他)国增加值变动负效应和出口中进口国增加值变动正效应的影响,2008年国际金融危机后,则转变为受出口中第三(其他)国增加值变动正效应和出口规模负效应的影响,且多数行业的三类增加值受要素质量负效应的影响减弱。在新发展阶段,中国贸易高质量发展路径的关键在于知识密集型服务业、知识密集型制造业、资本密集型服务业、公共服务业四个产业和高技能劳动力、资本两种生产要素。通过提升上述产业资本和高技能劳动力的投入数量和质量,攀升价值链路径融入国际循环,提升中国贸易增长韧性。

基于动态模态分解的输电杆塔松动检测

为了识别输电杆塔的松动状态,提出分段高阶动态模态分解(segment high-order dynamic mode decomposition,SHDMD)的检测方法。为减小振动耦合对检测的影响,利用三轴加速度和三轴角速度构造时间-空间矩阵,从中提取准确的方向振型作为松动特征,将时间-空间矩阵在时间维度上划分为若干子矩阵,对每个子矩阵进行空间维度扩展,避免DMD分解时得到错误结果,对扩展后的子矩阵进行DMD分解,得到不同时段的振动模态,利用稳定图筛选出不同时段共有的模态作为真实模态,提取与模态一一对应的方向振型。建立灰色关联检测模型,通过计算方向振型的几何特征关联度,识别当前松动状态。模拟杆塔试验与真实杆塔试验结果证明,所提方法能够很好地实现输电杆塔松动位置与松动程度的识别。