Specific Energy Consumption Analysis Model and Its Application in Typical Steel Manufacturing Process

Theoretical minimum and actual specific energy consumptions （SEC） of typical manufacturing process （SMP） were studied. Firstly, a process division of a typical SMP in question was conducted with the theory of SEC analysis. Secondly, an exergy analysis model of a subsystem consisting of several parallel processes and a SEC analysis model of SMP were developed. And finally, based on the analysis models, the SEC of SMP was analyzed by means of the statistical significance. The results show that the SEC of typical SMP comprises the theoretical minimum SEC and the additional SEC derived from the irreversibility~ and the SMP has a theoretical minimum SEC of 6.74 GJ/t and an additional SEC of 19.32 GJ/t, which account for 25.88% and 74.12% of the actual SEC, respectively.

Energy consumption hierarchical analysis based on interpretative structural model for ethylene production

Interpretative structural model(ISM) can transform a multivariate problem into several sub-variable problems to analyze a complex industrial structure in a more efficient way by building a multi-level hierarchical structure model. To build an ISM of a production system, the partial correlation coefficient method is proposed to obtain the adjacency matrix, which can be transformed to ISM. According to estimation of correlation coefficient, the result can give actual variable correlations and eliminate effects of intermediate variables. Furthermore, this paper proposes an effective approach using ISM to analyze the main factors and basic mechanisms that affect the energy consumption in an ethylene production system. The case study shows that the proposed energy consumption analysis method is valid and efficient in improvement of energy efficiency in ethylene production.

Prediction of Low-Energy Building Energy Consumption Based on Genetic BP Algorithm

Combined with the energy consumption data of individual buildings in the logistics group of Yangtze University,the analysis model scheme of energy consumption of individual buildings in the university is studied by using Back Propagation(BP)neural network to solve nonlinear problems and have the ability of global approximation and generalization.By analyzing the influence of different uses,different building surfaces and different energysaving schemes on the change of building energy consumption,the grey correlation method is used to determine the main influencing factors affecting each building energy consumption,including uses,building surfaces and energy-saving schemes,which are used as the input of the model and the building energy consumption as the output of the model,so as to establish the building energy consumption analysis model based on BP neural network.However,in practical application,BP neural network has the defects of slow convergence and easy to fall into local minima.In view of this,this paper uses genetic algorithm to optimize the weight and threshold of BP neural network,completes the improvement of various building energy consumption analysis models,and realizes the qualitative analysis of building energy consumption.The model verification results show that the viscosity of the building energy consumption analysis model based on genetic algorithm improved BP neural network algorithm(GABP)in this paper is relatively high,which is more accurate than the results of the traditional BP neural network model,and the relative error of the analysis model is reduced from 11.56%to 8.13%,which proves that the GABP can be better suitable for the study of school building energy consumption analysis model,It is applied to the prediction of building energy consumption,which lays a foundation for the realization of carbon neutralization in the South expansion plan of Yangtze University.

Performance analysis of U-vertical direct-expansion ground-source heat pump

The performance of a direct-expansion ground-source heat pump（DX GSHP）system is theoretically analyzed.Compared with the conventional ground-source heat pump（GSHP）,the DX GSHP has a lower condensing temperature in the cooling mode and a higher evaporating temperature in the heating mode,and the ground heat exchanger（GHE）in the DX GSHP has a low thermal resistance.Therefore,the coefficient of performance（COP）of the DX GSHP is higher than that of the GSHP.In addition,the system performance of the DX GSHP system is higher than that of the conventional GSHP system because there are no secondary solution loops and water circulating pumps in the DX GSHP system.The experimental energy performance of the DX GSHP system is also investigated based on the actual operational data.The tested DX GSHP system is installed in Xiangtan,China.The U-vertical GHE of the DX GSHP is buried in a water well.The length and the outside nominal diameter of the GHE are 42 m and 12.7 mm,respectively.The experimental results show that the maximum（COP）and the average COP of the DX GSHP system in the heating mode are 5.95 and 4.72,respectively.

Experimental research on air film formation behavior of air cushion belt conveyor with stable load

In this paper, the air film formation behavior of air cushion belt conveyor with stable load is studied. The air cushion field is analyzed by means of theoretical derivation, numerical simulation and experimental research. An intelligent experiment platform is developed. Three dimensional pressure distribution of air film and the air film thickness distribution along the conveyor belt in the width direction are obtained. The experimental result is analyzed by comparing with theoretical calculation and numerical simulation. The numerical and theoretical results are in good agreement with those obtained from experiments. The air film formation behavior pattern of air cushion belt conveyor with stable load is presented. The optimized film thickness and pore distribution are obtained based on the comprehensive energy consumption. This study provides a basis for the optimization design of air cushion belt conveyor.