Spatial and Temporal Evolution Analysis of Industrial Green Technology Innovation Efficiency in the Yangtze River Economic Belt

As a fusion point of innovation-driven green development, green technology innovation has become an essential engine for green transformation and high-quality economic development of the Yangtze River Economic Belt. Based on the panel data of 110 cities in the Yangtze River Economic Belt from 2006 to 2020, this paper uses the super-SBM model to measure the efficiency of industrial green technology innovation. Then, the Dagum Gini coefficient and its subgroup decomposition method, kernel density estimation, and the spatial Markov chain will discuss the convergence characteristics and dynamic evolution law of industrial green technology innovation efficiency in the Yangtze River Economic Belt. The results indicate several key points. (1) On the whole, the industrial green innovation efficiency of the Yangtze River Economic Belt shows a trend of the “N” type, which increases slowly at first and then decreases and then increases, and shows a non-equilibrium feature of “east high and west low” in space. (2) The average GML index of industrial green technology innovation efficiency in the Yangtze River Economic Belt is greater than 1, and technological progress is the main driving force in promoting efficiency growth. (3) There are spatial and temporal differences in industrial green technological innovation efficiency in the Yangtze River Economic Belt. Interregional differences and hypervariable density are the primary sources of overall differences. (4) During the study period, the absolute difference in industrial green technology innovation efficiency among regions showed a trend of “expansion-reduction-expansion”, and the innovation efficiency gradually converged to a single equilibrium point. (5) The industrial green technology innovation efficiency transfer in the Yangtze River Economic Belt shows a specific spatial dependence. Accordingly, policy suggestions are put forward to further improve industrial green technological innovation in the Yangtze River Economic Belt

Experimental investigation of gusty loads on trains on a truss-girder suspension bridge

This paper was reviewed and accepted by the APCWE-IX Programme Committee for Presentation at the 9th Asia-Pacific Conference on Wind Engineering, University of Auckland, Auckland, New Zealand, held from 3-7 December 2017

Thermal response and resistance optimization of various types of point-supported glass facades

The extensive application of various types of point-supported glass facades may bring potential thermal breakage risk and impacts on indoor human beings safety. In this work, point-supported glass facades with five various types were tested under thermal loads. The present results showed that installation forms influenced significantly the first breaking time, the location of crack initiation and the final falling out area. It demonstrated that the one-point-supported glass facades had the longest time for the first crack occurrence whereas the glass eventually fell completely out of the frame. However, the six-point-supported glass facades had the shortest first breaking time, but ultimately no glass pieces fell out of the frame. To calculate the temperature variation and stress distribution of glass panel, a thermal-mechanical model was developed. In addition, an optimization simulation was further conducted using the bound optimization by quadratic approximation method to obtain a better thermal resistance performance of glass facade. This work provides significant insights on the effects of various installations upon the thermal response of glass facades and helps to understand the failure mechanism and build safer facades by the structural optimization method

A new model for accurate estimation of gas content and pressure based on Langmuir adsorption equation in Guizhou, China

In order to obtain the functional relationship of gas content and gas pressure, and to accurately calculate the two values which fitting the characteristics of coal seam, the destruction coefficient (X) and the index (ΔP) of the initial velocity of gas emission are introduced to establish the new model with higher precision based on Langmuir equation and destruction type of coal. The applicability of classic model (W-P model) and new optimization model in Guizhou mining areas are studied through the statistics of basic parameter data from 107 groups of coal-seam gas in eight mining areas. The results show that the gas content calculated by the classical model is lower than the measured value, while the gas pressure value is larger than that. The average relative error of gas content and pressure data reach 23.98% and 97.86%, respectively. The gas content and pressure data calculated by the optimization model are well fitted with the measured value. The fitting degree gradually rises with the increase of the sample size, and the average relative errors are 6.44% and 14.27%, respectively. Compared with the classical model, the average relative errors of gas content and pressure calculated by the optimization model reduce by 17.54% and 83.59%, respectively. The optimization model controls the tendency of calculated value error which significantly rises as the ΔP increases. For the coals with different destruction types, the average relative error of calculated gas content in optimization model ranges from 4.40% to 11.99%. And the average relative error of calculated pressure value ranges from 9.84% to 25.80%, both of them are far superior to that of classical model. The optimization model is more accurate for calculating the gas content and pressure in Guizhou

Transition mechanisms between selective O3 and NOx generation modes in atmospheric-pressure plasmas: decoupling specific discharge energy and gas temperature effects

Two modes of the atmospheric-pressure plasma discharge, distinguished by the dominant O3 and NOx species are studied numerically and experimentally. To investigate the mode transition mechanisms, here we develop a global chemical kinetics model for the atmospheric-pressure dielectric barrier discharge involving 63 species and 750 reactions. Validated by the experimental results, the model accurately describes the mode transition. The N, O, O2(a), and O2(b) are the essential transient intermediate species for the O3 and NOx production and loss reactions. The individual and synergistic effects of the specific discharge energy and the gas temperature on the species density and the relative contributions of the dominant reactions are quantified under the increasing discharge voltage conditions. The modeling results indicate that the gas temperature and specific discharge energy both contributed to the discharge mode transition, while the decisive factors affecting the change of the O3 and NOx density are different in the respective modes. These insights contribute to diverse plasma applications in biomedicine, agriculture, food, and other fields where selective and controlled production of O3 and NOx species is the key for the desired plasma performance.</p

Model Selection for Ecosystem Respiration Needs to Be Site Specific: Lessons from Grasslands on the Mongolian Plateau

Selecting an appropriate model for simulating ecosystem respiration is critical in modeling the carbon cycle of terrestrial ecosystems due to their magnitude and high variations in time and space. There is no consensus on the ideal model for estimating ecosystem respiration in different ecosystems. We evaluated the performances of six respiration models, including Arrhenius, logistic, Gamma, Martin, Concilio, and time series model, against measured ecosystem respiration during 2014–2018 in four grassland ecosystems on the Mongolian Plateau: shrubland, dry steppe, temperate steppe, and meadow ecosystems. Ecosystem respiration increased exponentially with soil temperature within an apparent threshold of ~19.62 °C at shrubland, ~16.05 °C at dry steppe, ~16.92 °C at temperate steppe, and ~15.03 °C at meadow. The six models explained approximately 50–80% of the variabilities of ecosystem respiration during the study period. Both soil temperature and soil moisture played considerable roles in simulating ecosystem respiration with R square, ranging from 0.5 to 0.8. The Martin model performed better than the other models, with a relatively high R square, i.e., R2 = 0.68 at shrubland, R2 = 0.57 at dry steppe, R2 = 0.74 at temperate steppe, and R2 = 0.81 at meadow. These models achieved good performance for around 50–80% of the simulations. No single model performs best for all four grassland types, while each model appears suitable for at least one type of ecosystem. Models that oil moisture include models, especially the Martin model, are more suitable for the accurate prediction of ecosystem respiration than Ts-only models for the four grassland ecosystems