Beam string structure (BSS), which is a new kind of semi-rigid hybrid system, composed of arch, strut and string, has been developed rapidly in long-span steel structures in recent years. Based on the principle of virtual work and Updated Lagrange, the formulas of geometric nonlinear F.E.M. for spatial beam element, cable element and truss element are derived respectively in this paper. Taking the one-way BSS model of the steel roof in Guangzhou International Convention and Exhibition Center as a computational example by using both linear and nonlinear analysis method, the analytical results show that it is appropriate when adopting the straight truss element with two joints and equivalent elastic modulus to simulate the cable element with small sag. Although the linear analysis can meet the requirement of practical engineering due to its weak nonlinearity of BSS, the nonlinear method is also important to improve the precision theoretically. The conclusions obtained may be helpful for the designers in similar projects.
Based on structural finite element analysis of discrete models, a neurocomputing strategy is developed in this paper. Dynamic iterative equations are constructed in terms of neural networks of discrete models. Determination of the iterative step size, which is important for convergence, is investigated based on the positive definiteness of the finite element stiffness matrix. Consequently, a method of choosing the step size of dynamic equations is proposed and the computational formula of the best step size is derived. The analysis of the computing model shows that the solution of finite element system equations can be obtained by the method of neural network computation efficiently. The proposed method can be used for parallel computation of structural finite element in a large-scale integrated circuit (LSI).
China’s steel industry’s carbon emissions accounted for more than 60% of global carbon emissions, approximately 15% in China in 2020. China’s steel industry accounted for approximately 16% of China’s total carbon emissions in 2021. The ability to reduce the carbon dioxide emissions generated by the steel industry and protect the living environment for humans and nature has become a realistic issue for China. This paper constructs a steel consumption–carbon emission system. Research shows that by adjusting the GDP growth rate and CO2 emissions per unit of steel production, the carbon peak in the steel industry will advance to 2030 and the carbon emissions after the peak will be significantly reduced. The reduction in steel consumption in the construction and machinery sectors does not have a significant impact on carbon emissions from the steel industry, whereas the reduction in steel consumption in the transportation and infrastructure sectors has contributed to carbon reduction activities in the steel industry. When all four sectors are regulated simultaneously, it is found that the predicted carbon peaking time for the steel sector advances to 2029, fulfilling the goal of achieving carbon peaking by 2030. Carbon emissions should decrease after that point.
Based on the energy policy simulation model (EPS model) and the reality of Zhejiang Province and Inner Mongolia Autonomous Region, the carbon pricing policy scenario and the early retirement policy scenario of coal power generation units were constructed, respectively, and the policy effects simulated. The study explored whether Inner Mongolia Autonomous Region can learn from the low-carbon policies that have played a good role in Zhejiang Province in the process of achieving a carbon peak. The research found that: (1) Under the baseline scenario, both Zhejiang Province and Inner Mongolia Autonomous Region failed to achieve a carbon peak by 2030. (2) Under the scenarios of carbon pricing and early retirement of coal power generation units, the peak time of carbon in Zhejiang Province and Inner Mongolia Autonomous Region has been advanced, which shows the effectiveness of carbon pricing and early retirement of coal power generation units. (3) The above two policies have achieved good results in the overall implementation process of Zhejiang Province, but the carbon pricing policy has caused dramatic fluctuations in the power generation in Inner Mongolia Autonomous Region, and the early retirement policy of coal power units has failed to achieve the goal of reaching the peak carbon in Inner Mongolia Autonomous Region on schedule.
Background In today's society, with the sustainable development of economy, material products are rich and diverse. The production speed of products has far exceeded people's needs. Emission reduction and environmental protection have become people's new pursuit. Closed loop supply chain should consider not only product life cycle and recycling, but also economic and environmental benefits. It has become the focus of scholars all over the world. Closed loop supply chain refers to the complete supply chain cycle from procurement to final sales, including product recovery and reverse logistics supported by life cycle. It is a highly complex process. In the closed-loop supply chain, the simplest form is composed of manufacturers, retailers and recyclers. Recycler is the most critical link in the new closed-loop supply chain system, which is not available in the traditional supply chain. Therefore, this paper mainly studies the change of recyclers when exogenous variables fluctuate from the perspective of economic psychology. Research Objects and Methods Most scholars use short-term static methods when studying the uncertainty of recyclers in closed-loop supply chain. It is particularly important to analyze the uncertain factors in the closed-loop supply chain. In order to analyze this problem, this paper first improves the closed-loop supply chain model of capital flow and logistics coupling, so as to better simulate the real closed-loop supply chain. Secondly, the sensitivity analysis function of Vensim software is used to simulate the impact of exogenous variables on the inventory value and capital value of recyclers in the closed-loop supply chain model. At the same time, in order to verify the impact of recyclers' emotional stability, this study adopts the following scale. The communication anxiety scale adopts 15 questions of the Interaction Anxiety Scale (IAS) compiled by Leary, with a single dimension and a 5-level score, from 1 to 5 to “very inconsistent”. The higher the score, the greater the degree of social anxiety. The emotion regulation self-efficacy scale adopts the emotion regulation self-efficacy scale (RES) revised by Caprara. The 12 questions are divided into three dimensions: expressing positive emotions, managing depression / pain and self-efficacy of managing anger / anger, with 4 questions in each dimension. A 5-level score is adopted, from 1 to 5, which means “very inconsistent” to “very consistent”. The higher the score, the higher the degree of self-confidence in regulating their emotions. In the study, Cronbach's α The coefficient is 0.80. The aggression scale adopts the aggression scale (bpaq) compiled by Buss and Perry The scale has 29 questions and is divided into four dimensions: physical aggression, verbal aggression, anger and hostility. The higher the score, the stronger the attack. In this study, Cronbach's α The coefficient is 0.85. The depression questionnaire adopts Beck's revised depression Inventory-II (BDI-II). The questionnaire has 21 questions, with a single dimension. The higher the total score, the heavier the degree of depression. The data were obtained by spss19 0 and amos17 0 for analysis. Results the 19 exogenous variables were divided into four categories: Manufacturer related parameters, retailer related parameters, recycler related parameters and other related parameters. The sensitivity of these 19 parameters to recycler inventory and capital in closed-loop supply chain is simulated and analyzed. Through the comparative analysis of sensitivity chart, it can be seen that the manufacturer's inventory adjustment time, the retailer's safety inventory coefficient, the retailer's smoothing time, the retailer's inventory adjustment time, the collector's fixed expenditure and the collector's initial inventory value are positively correlated. And have a significant impact on collectors' inventory and emotional stability. The reason is that appropriate time adjustment helps to reduce work pressure and naturally improve job satisfaction. Conclusion in the closed-loop supply chain, the fluctuation of the same exogenous variable in the same range has a more significant impact on the recycler's inventory than on the recycler's capital. For recyclers, the decline of inventory value has a positive impact on the capital of recyclers, while the decline of capital value has a negative impact on the capital of recyclers. The impact of retailer order smoothing time on recycler inventory and capital is uncertain. Therefore, recyclers should strengthen fund management, establish insurance mechanism and prepare reserves to prevent the impact of external variable fluctuations on recyclers' funds. At the same time, in view of the uncertainty caused by exogenous variables related to manufacturers and retailers on recyclers' funds and inventory, recyclers need to deal with it through information sharing, compensation mechanism, incentive and other ways. Acknowledgements Supported by a project grant from National Natural Science Foundation of China (Grant No.71764019), the National Social Science Foundation of China (Grant No.19BGL187), the Planning Project of Philosophy and Social Science of Inner Mongolia (Grant No.2021NDB082), Inner Mongolia Natural Science Foundation (Grant No.2021MS07016 and 2020MS07020) and Research Center for Resources, Environment and Energy Development Strategic.
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