Simulation of Gas Oil Hydrotreater Heat Exchange Tube and Crystallization Prediction of NH_(4)Cl by Thermodynamic Equilibrium

The hydrotreater system heat exchanger is one of the main pieces of heat exchange equipment in petrochemical enterprises.In recent years,oil resources have shown a deterioration trend of high sulfur and high acid content,with corrosion risk being prominent in oil processing.Taking the multi-medium flow corrosion risk of the hydrotreater heat exchanger pipeline in a petrochemical enterprise as the research object,based on the parameter characteristics of corrosive NH_(3) and HCl media under a high-temperature and high-pressure environment,the ammonium salt crystallization and deposition mechanism under multi-phase flow is revealed.The thermodynamic equilibrium curve is modified based on the thermodynamic principle and fugacity coefficient variation,and the prediction model of ammonium chloride crystallization in hydrotreater heat exchanger under high temperature and high pressure is constructed according to the modification.This study uses the mixture model,the flow-thermal coupling method,and the discrete phase model method to carry out the numerical simulation of multiphase flow and the numerical prediction of particle distribution characteristics in the heat exchanger pipeline of the hydrotreater heat exchange equipment,so as to realize the quantitative prediction of the particle crystallization deposition distribution in the pipeline.The results show that with the decrease of temperature,the crystallization occurs first on both sides of the center of the tube bundle,and more crystallization occurs in the lower half of the U-shaped tube,which may seriously lead to problems such as pipe blockage and under-deposit corrosion.

The simulation of LUCC based on Logistic-CA-Markov model in Qilian Mountain area, China

The Qilian mountain area was examined for using the Logistic-CA-Markov coupling model combined with GIS spatial analyst technology to research the transformation of LUCC, driving force system and simulate future tendency of variation. Results show that： （1） Woodland area decreased by 12.55%, while grassland, cultivated land, and settlement areas increased by 0.22%, 7.92%, and 0.03%, respectively, from 1986 to 2014. During the period of 1986 to 2000, forest degradation in the middle section of the mountain area decreased by 1,501.69 km2. Vegetation cover area improved, with a net increase of grassland area of 38.12 km2 from 2000 to 2014. （2） For constructing the system driving force, the best simulation scale was 210m×210m. Based on logistic regression analysis, the contribution （weight） of composite driving forces to land use and cover change was obtained, and the weight value was more objectively compared with AHP and MCE method. （3） In the natural scenarios, it is predicted that land use and cover distribution maps of Qilian mountain area in 2028 and 2042, and the Lee-Sallee index test was adopted. Over the next 27 years （2015-2042）, farmland, woodland, grassland, settlement areas show an increasing trend, especially settlements with an obvious change of 0.56%. The area of bare land will decrease by 0.89%. Without environmental degradation, tremendous structural change of LUCC will not occur, and typical characteristic of the vertical zone of the mountain would remain. Farmland and settlement areas will increase, but only in the vicinity of Qilian and Sunan counties.

A New Paradigm for Simulating and Forecasting China's Economic Growth in the Medium and Long Term

Taking the system philosophy of human-earth relationship as the theoretical axis,and under the three-dimensional goals of economic growth,social development,and protection of the ecological environment,this paper constructs the supporting system of China’s economic development.On this basis,guided by the basic principles of system theory and system dynamics,and combined with the theories of other related disciplines,we constructed an economic geography-system dynamics(EG-SD)integrated forecasting model to simulate and quantitatively forecast China’s economic growth in the medium and long term.China’s economic growth will be affected by quantifiable and unquantifiable factors.If the main unquantifiable factors are not taken into account in the simulation and prediction of China’s economic growth in the medium and long term,the accuracy and objectivity of the prediction results will be diminished.Therefore,based on situation analysis(Strengths,Weaknesses,Opportunities,and Threats,SWOT),we combined scenario analysis with the Delphi method,and established a qualitative prediction simulation model(referred to as the S-D compound prediction model)to make up for the shortcomings associated with quantitative simulation predictions.EG-SD and S-D are organically combined to construct a simulation and prediction paradigm of China’s economic growth in the medium and long term.This paradigm not only realizes the integration of various forecasting methods and the combination of qualitative and quantitative measures,but also realizes the organic combination of unquantifiable and quantifiable elements by innovatively introducing fuzzy simulation of system dynamics,which renders the simulation and prediction results more objective and accurate.

Application of hydrological models in a snowmelt region of Aksu River Basin

This study simulated and predicted the runoff of the Aksu River Basin, a typical river basin supplied by snowmelt in an arid mountain region, with a limited data set and few hydrological and meteorological stations. Two hydrological models, the snowmelt-runoff model （SRM） and the Danish NedbФr-AfstrФmnings rainfall-runoff model （NAM）, were used to simulate daily discharge processes in the Aksu River Basin. This study used the snow-covered area from MODIS remote sensing data as the SRM input. With the help of ArcGIS software, this study successfully derived the digital drainage network and elevation zones of the basin from digital elevation data. The simulation results showed that the SRM based on MODIS data was more accurate than NAM. This demonstrates that the application of remote sensing data to hydrological snowmelt models is a feasible and effective approach to runoff simulation and prediction in arid unguaged basins where snowmelt is a major runoff factor.