Study on synergistic system of energy-absorbing yielding anti-impact supporting structure and surrounding rock

Through the improvement of supporting structure and the utilization of the interaction between surrounding rock and supporting structure, the synergistic system of energy-absorbing yielding anti-impact supporting structure and surrounding rock is established. The process of energy absorption device, energy-absorbing yielding anti-impact supporting structure and synergistic system under impact is simulated to analyze the properties of them. The following conclusions could be drawn. The deformation and yielding process under compression of energy absorption device is divided into five stages. Compared with the traditional supporting structure, the energy-absorbing yielding anti-impact supporting structure has the reaction force with lower value and smaller fluctuation range before the deformation of the energy absorption device reaches the third ascending section. The synergy between surrounding rock and supporting structure plays an important role in roadway support. Compared with the supporting structure without surrounding rock, the reaction force of the supporting structure in the synergistic system is lower, and a stationary stage is added in the early stage of the reaction force curve.

Investigation on the Microstructure Hardness for the Hot Compressed Duplex Steel

Effect of microstructure size and type on the hardness for the duplex steel were disclosed by using of optical microscope (OM), scanning electron microscope (SEM) and nanoindenter for the samples hot compressed under different temperature with reduction of 10%, 30%, 50% and 70%. OM and SEM were used to measure the average martensite lamellar width, space and indenter morphology. nanoindenter test characterized the microstructure hardness for the samples under different process. Experiment results show that martensite hardness for the sample hot compressed at 950°C has larger diversity than that of sample hot compressed at 1200°C. The martensite hardness fluctuation range for the sample compressed at 950°C is almost from about 7GPa to 12GPa, while, for the sample compressed at 1200°C, the fluctuation range is basically from about 9GPa to 12GPa. However, the average hardness for the samples hot compressed at 950°C is comparably smaller, which is related with lower quench temperature. The larger martensite hardness fluctuation is mainly related with induced ferrite formation and finer martensite lamellar width. For the ferrite phase, the hardness fluctuation range is lower.

Synergy and Correlation Optimization Analysis of Innovation System and Institutional Governance System from the Perspective of Cluster Ecosystem

Innovation and institutional governance are the key enabling factors of cluster ecosystem development. Its synergistic effects play an important role in enhancing ecosystem competitiveness. In this paper, pseudocode language is applied to cluster ecosystem cooperative model reasoning. The coordination and optimization of the innovation system and institutional governance system were studied in a biomedical cluster. Besides, Pearson algorithm was used to test the correlation degree of elements in three Chinese biomedical clusters. The results show that, in Zhangjiang and Nanchang biomedical clusters, the synergistic correlation coefficient between the innovation system and the institutional governance system fluctuates around 0.8. However, in Tonghua biomedical cluster, the synergy correlation coefficient fluctuated around -0.2. The fluctuation range between the two clusters was large. After adjusting the range of order parameters, the rank of synergy trend was Zhangjiang > Nanchang > Tonghua. Finally, further analysis shows that Zhangjiang and Nanchang biomedical clusters can achieve the optimal synergy state by adjusting innovation and institutional governance, but Tonghua cannot. Therefore, the collaboration between the innovation system and institutional governance system provides some reference for the high-quality development of the cluster ecosystem.

Responses of Macroinvertebrate Community Temporal Dissimilarity and Abundance to the Water Level Fluctuation Range in a Shallow Lake

Variations in the hydrological regime are among the anthropogenic pressures affecting biological assemblage structure in shallow freshwater lakes. We estimated the effects of the water level fluctuation range on the temporal dissimilarity of the macroinvertebrate community by sampling benthic macroinvertebrate assemblages monthly in 2017 and bimonthly in 2018. Then, we applied a boosted regression trees (BRT) model to quantitatively analyzing the relationship between macroinvertebrate abundance and microhabitat factors in different seasons. To distinguish differences in water level fluctuations at the sample site scale, we proposed a variable, namely, the percentage of water level fluctuation range (PWLFR). The results were as follows. (1) An increased water level fluctuation range would lead to more temporally heterogeneous macroinvertebrate communities. Temporal dissimilarity of macroinvertebrates increased linearly in response to increasing water level fluctuation range. (2) Species abundance presented seasonal characteristics, and the dominant factors affecting species abundance varied with the seasons. PWLFR was the dominant variable explaining macroinvertebrate abundance in summer. Macroinvertebrate abundance showed positive effects with increasing PWLFR. (3) The interaction between chlorophyll a and PWLFR in summer promoted an increase in macroinvertebrate abundance. These findings may provide a basis for the formulation of effective ecological water replenishment management decisions aimed at maintaining the stability of shallow lake ecosystems in arid and semi-arid regions.

The Equilibrium Mechanism of Interest Distribution in Farmland Transfer: Based on the Perspective of the Three-Party Game

The purpose of the paper is to study how the interests of farmland transfer be distributed among the government, contractors, and farmland transferees. The process of the paper is to analyze the evolutionary stability strategies of the government, contractors, and farmland transferees by building a three-party evolutionary game model; in order to identify the equilibrium point of the three-party evolutionary game, an example of interest distribution in a village in Anhui Province is used to analyze and simulate the three-party evolutionary game. The conclusions of the paper are as follows: the combination of a one-party subsidy, transferring farmland, and grain production is the ideal equilibrium result in the three-party game; farmland transfer rent is the a crucial factor of interest balance among the three parties; only if the farmland transfer rental price is larger than the sum of the contractor’s self-farming incomes and subsidies and lower than the grain income of the transferee can the three parties realize the equilibrium of interest distribution. The suggestions of the paper are that the government should carry out the system of “retirement allowance” and transform “subsidy” to “allowance” to protect the interests of contractors, and the government should promote farmland transfer and encourage grain production by controlling the fluctuation range of farmland transfer rent.

Error correction technique for numerical control machine tools based on the simplex method

The objective of this research is to develop a novel correction mechanism to reduce the fluctuation range of tools in numerical control (NC) machining. Error compensation is an effective method to improve the machining accuracy of a machine tool. If the difference between two adjacent compensation data is too large, the fluctuation range of the tool will increase, which will seriously affect the surface quality of the machined parts in mechanical machining. The methodology used in compensation data processing is a simplex method of linear programming. This method reduces the fluctuation range of the tool and optimizes the tool path. The important aspect of software error compensation is to modify the initial compensation data by using an iterative method, and then the corrected tool path data are converted into actual compensated NC codes by using a postprocessor, which is implemented on the compensation module to ensure a smooth running path of the tool. The generated, calibrated, and amended NC codes were immediately fed to the machine tool controller. This technique was verified by using repeated measurements. The results of the experiments demonstrate efficient compensation and significant improvement in the machining accuracy of the NC machine tool.

Nonlinear Interval Optimization of Asymmetric Damper Parameters for a Racing Car

Uncertainties in parameters can affect racing car performance. In this study, a nonlinear interval suspension damping optimization method is proposed to improve the road holding of a racing car. To evaluate the dynamic responses of racing cars under a random road input and a bump input with interval uncertain parameters, a quarter car model with a two-stage asymmetric damper is established. Then, a quadratic approximation model with second derivative terms is developed by second-order Taylor series expansion and dimension reduction to calculate the nonlinear dynamic response of the vehicle. Interval analysis of the objective function and constraints is carried out using interval arithmetic to eliminate nesting optimization and make the optimization efficient. The results show that the proposed optimization method can improve road holding performance, effectively suppress the fluctuation range of the road holding performance evaluation index, and ensure the robustness of the design scheme.

Forecast China’s monthly urban fixed asset investment based on the ARIMA model

In recent years, as China’s urbanization level has risen, China’s urban fixed asset investment has also been rising. Judging from monthly data, China’s urban fixed asset investment has shown a volatile upward trend, with an obvious 11-month cycle. And in each cycle, the fluctuation range of the investment amount is getting larger. This paper uses an ARIMA model with an additive seasonal effect to fit the monthly urban fixed asset investment sequence and predict the future investment. In the end, this paper established a fitting model for China’s urban fixed asset investment, and obtained a good forecasting effect.

LONG-TERM PREDICTION OF CASPIAN SEA LEVEL UNDER CMIP6 SCENARIOS USING ARTIFICIAL NEURAL NETWORKS

Artificial Neural Network (ANN) is employed to predict the long-term Caspian Sea level (CSL). 114-year observed CSL data (1900-2014) and the precipitation and temperature of historical and future scenarios of Coupled Model Intercomparison Phase 6 (CMIP6) are used to predict the future fluctuations of CSL (2015-2050). The values of the statistical indices in training, validating and testing periods (1900-2014) indicate the efficiency of the ANN in reconstruction of the CSL. Considering the outputs of different climate change projections (CMIP6) and excluding the human interventions, the study predicts the CSL fluctuation range of -28 m to -26m until 2050.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/Kfj-gr65TR8