Measuring and predicting soil moisture conditions for trafficability

ABSTRACT

The main cause of loss of soil structural stability is vehicle operation on unpaved wet surfaces. Unfortunately, there is a lack of continuous soil moisture data in predicting trafficable conditions. To measure changes in soil moisture conditions in real time, Percostation (Adek) sensors were installed in sandy loam Stagnosol soil at different depths. Problems with soil trafficability can be expected at the plastic limit, and the soil is unable to support vehicle operations at the liquid limit in such soils. The maximum water-holding capacity of the soil is 32%, the field capacity is 25%, the plastic limit is 22%, and the liquid limit is 30%. With rainfall of more than 10?mm d^?1, the moisture content reached the plastic limit in the upper 25?cm of soil. The average increase in the soil moisture content after more than 10?mm of rain was 1–2.5% in a time frame of 2–3 hours. After rain, the previous soil moisture level was obtained within 2 to 3 days in the vegetation period. Measurements also allowed soil water balance and evapotranspiration modelling data to predict soil moisture conditions with an accuracy of one day but failed to predict in a shorter period.     

高校引导大学生扎根林区的对策研究

对林区人力资源现状和影响大学生到林区就业的因素进行了分析,提出了高校引导大学生扎根林区的对策。     

高效液相色谱法和光度法测定苯酚的对比

分别对液相色谱法和4-氨基安替比林分光光度法,测定苯酚的精密度、检测限及准确度等,进行对比和分析.结果表明:色谱法和光度法精密度和准确度均较高,但光度法操作简便且检出限较低,费用少,建议作为酚醛胶木制品苯酚释放的定量方法.     

粗集-神经网络在农业工程项目评估中的应用

该文提出一种基于粗集-神经网络项目评估新方法，该方法应用粗糙集理论对神经网络的输入数据进行预处理,提取其中的关键成分作为网络的输入,提高了神经网络的收敛速度和逼近精度，并以中国农业水利工程项目为背景进行了实例研究，结果表明，建立的模型不仅较公平、合理，而且提高了神经网络模型的学习效率。     

可变电荷土壤对酸雨敏感度的影响因子

The sensitivity of a large number of variable charge soils to acid rain was evaluated through examining pH-H₂SO₄ input curves. Two derivative parameters, the consumption of hydrogen ions by the soil and the acidtolerant limit as defined as the quantity of sulfuric acid required to bring the soil to pH 3.5 in a 0.001mol L^-1 Ca(NO₃)₂ solution, were used. The sensitivity of variable charge soils was higher than that of constant charge soils, due to the predominance of kaolinite in clay mineralogical composition. Among these soils the sensitivity was generally of the order lateritic red soil > red soil > latosol. For a given type of soil within the same region the sensitivity was affected by parent material, due to differences in clay minerals and texture. The sensitivity of surface soil may be lower or higher than that of subsoil, depending on whether organic matter or texture plays the dominant role in determining the buffering capacity. Paddy soils consumed more acid within lower range of acid input when compared with upland soils, due to the presence of more exchangeable bases, but consumed less acid within higher acid input range, caused by the decrease in clay content.     

Effect of controllable drawbead on the formability of high strength steel box

With the application of simulation technology and orthogonal test, the effects of controllable drawbead on the formability of HSS (high strength steel) box are researched through the simulation of HSS box with 6 different drawbead shapes and 3 different drawbead trajectories. Use the limit drawing height as the evaluate indicator, it is proofed that the controllable drawbead can improve the formability of HSS by analyzing the result data that three types of controllable drawbead trajectories indicators are bigger than the immovable ones. And the 2nd trajectory, ascent—halt—descent is determined as the optimal type. The improve scales of straight drawbeads is better than the oblique drawbead, whereas the latter ones have better target. The main influence factors are obtained by range analysis. At last the reason that accounts for controllable drawbead can improve the formability is got the answer by the forming force analysis.     

The application of rough sets-neural network theory to mine ventilation system evaluation

To solve the instability problem of established sample in the neural network evaluation method for mine ventilation system, a comprehensive evaluation of the ventilation system is carried out based on rough sets and BP neural networks. Taking the ventilation system of a mine as an example, the classification quality of raw data samples are tested by using rough set data analysis system. Then, based on artificial neural network theory, a rough sets-neural network evaluation model of a mine ventilation system is established and a new rough sets-neural network evaluation method of mine ventilation system is formed. The results show that, after the model validation of data and application, its theoretical evaluation results are in line with the actual situation, and the network total error is less than 0.004. It shows that the comprehensive evaluation method based on rough sets-neural networks has a good effect in evaluating mine ventilation system in practical application.