玉米秸秆饲料除尘筛出物离散元数值模拟参数标定

为提高玉米秸秆饲料除尘过程中离散元数值模拟参数的准确度,采用物理试验与数值模拟相结合的方法对玉米秸秆饲料的筛出物进行离散元数值模拟参数标定。将物理试验测定筛出物中秸秆与尘土的接触参数作为数值模拟参数选择依据,利用Plackett-Burman试验、最陡爬坡试验和Box-Behnken试验确定对数值模拟休止角影响最显著的因素。以物理试验得到的休止角(41.668°)与标准筛除尘率(13.24%)为目标值,对显著性参数进行寻优;应用最优参数组合进行休止角与标准筛除尘率数值模拟,验证标定参数组合数值模拟精确性。结果表明:对数值模拟休止角影响显著的因素为,尘土接触模型JKR表面能、尘土-尘土恢复系数和尘土-尘土滚动摩擦因数;最优参数组合为,尘土接触模型JKR表面能9.052 J/m²、尘土-尘土恢复系数0.52、尘土-尘土滚动摩擦因数0.182。数值模拟休止角与物理试验休止角相对误差为1.26%,标准筛数值模拟除尘率与物理试验除尘率相对误差为7.93%。     

基于计算机视觉的牛脸轮廓提取算法及实现

计算机视觉技术已越来越多地应用于检测牛个体行为以给出养殖管理决策,牛脸轮廓的提取及形状分析能够进一步提高牛身份鉴别,咀嚼分析及健康状况评估的自动化程度。为实现基于计算机视觉的无接触、高精度、适用性强的肉牛养殖场环境下的牛脸轮廓提取,提出用自适应级联检测器定位牛脸位置,用统计迭代模型提取牛脸轮廓的方法。该方法采集牛脸正面图像,用级联式检测器定位出牛脸的位置,并分别采用监督式梯度下降算法(supervised descent method,SDM),局部二值算法(local binary features,LBF)和主动外观模型算法(fast active appearance model,FAAM)3种算法被用于提取牛脸轮廓。对20头肉牛共拍摄800幅牛脸正面图,随机选取训练数据720幅和测试数据80幅。结果表明,主动外观模型算法准确率最高,其轮廓提取误差为0.0184像素,适于应用在轮廓提取精度要求较高的场合,而局部二值算法的运行效率最高,在分辨率为744像素(水平)×852像素(垂直)的牛脸图像中轮廓提取时间为0.35 s,更适于应用在实时性要求较高的场合。该方法可实现养殖场中肉牛的无接触精确的面部轮廓提取,具有适用性强、成本低的特点。     

基于MCMC方法的WOFOST模型参数标定与不确定性分析

为探究作物生长模型参数的自动标定技术及其不确定性分析方法,该研究以郑州农业气象试验站为试验点,利用融入了snooker更新(snooker update)的DE-MC(differential evolution Markov chain,差分进化马尔科夫链)方法实现对WOFOST(world food studies)作物生长模型的参数标定和不确定性定量评价。snooker更新增加了DE-MC算法中候选样本的多样性,从而实现利用更少的并行链对多维参数空间进行有效采样,较适合于WOFOST模型参数众多的特性。结果表明:相比于模型默认值,采用MCMC(Markov chain Monte Carlo,马尔科夫链-蒙特卡洛)标定后的参数,叶面积指数(leaf area index,LAI)模拟精度可提高51.40%~53.07%,产量模拟精度提高8.25%~8.88%。标定参数中,SPAN、SLATB070、SLATB040、AMAXTB130和SLATB00的后验分布可近似为高斯分布,其中SPAN的不确定性最低。带入后验参数集合进行模型,LAI在三叶期至返青期之间以及拔节期至抽穗期之间模拟的不确定性较大;产量模拟的不确定性随时间不断增大,至乳熟期前后达到稳定。该方法能够实现对多参数复杂作物生长模型的参数标定和不确定性分析,对作物模型参数估计及提高模拟精度具有重要作用。     

Model Studies on Salt and Water Balances at Konanki Pilot Area, Andhra Pradesh, India

The salt and water balances at Konanki pilot area in Nagarjunasagar project right canal command in Andhra Pradesh State of India were analysed using SALTMOD. The model was calibrated by using two-year data collected in the pilot area. From the calibration, the leaching efficiencies of the root and transition zone were estimated as 65% and the out going natural sub-surface drainage was determined as 50 mm per year. The model predicts that the root zone soil water salinity will be reduced to 4, 3 and 2.5 dS/m (from an initial value of 11.5 dS/m) during the first, second and third seasons within six years after installation of the drainage system. Next, the situation prior to the installation of the drainage system was reconstructed using the model. Finally, sensitivity analyses were made to study the effects of varying drain depth, spacing and amount of irrigation water applied on root zone salinity and depth to water table. Here, the model predicted that closer than the present spacing or further deepening of the drains from the present depth of 1 m to 1.4 m will not have any better influence on the reduction of the root zone salinity than in the present situation. These simulations also suggested that by applying 80% of the present amount of irrigation water, the root zone salinity can be brought down to 5 and 4 dS/m by second and fourth years, respectively and this will in turn reduce the problem of water logging and salinity to some extent.     

基于图像配准的历史图件转绘方法

我国于20世纪80年代以前编制的林相图等大多手工绘制的、无等高线的平面图，由于图纸变形的原因，林班和小班界线等无法直接转绘到地形图上，难于充分应用。为此采用扫描——几何精校正——矢量化——GIS支持下叠合地形图的方法进行转绘。结果表明。林班和小班界线与地形图匹配效果良好。     

The simulation of phenological development in dynamic crop model: The Bayesian comparison of different methods

The main objective of our study was to use Bayesian methods to quantify the uncertainties related to phenological development of maize (Zea mays L.) under various climate conditions. For this purpose, five different phenological methods were implemented in the dynamic crop growth model, which was subsequently optimized, using the data acquired at three different locations in Slovenia. The sensitivity analysis of the crop model was performed in order to find the set of most influential physiological parameters. Subsequent Bayesian model comparison was used in order to quantify the impact of phenological method selection on the final maize yield. The results revealed the importance of using an appropriate phenological method in order to correctly estimate the duration of the growing season and yield, when used within dynamic crop model. The limitations of the phenological methods used in this study are discussed. The selection of phenological method itself did not have a significant influence on the yield estimation, except in years with high temperatures and limiting water conditions. This raises the concern that inaccurate simulation of phenological development may increase the uncertainties of impact assessment on crop yield where crop models are fed with future climate projections.     

面向夹持采收的油菜薹夹段茎秆离散元参数标定与优化

为提高离散元法对指导油菜薹有序采收装备设计与优化的准确性和可靠性,该研究以双行垄作移栽的“农大1号”双低甘蓝型油菜机械化适收期油菜薹夹段茎秆为对象,测定其本征参数、表面接触参数以及破碎力学参数,利用EDEM仿真软件Hertz-Mindlin无滑移模型和Hertz-Mindlin with bonding粘结模型建立夹段茎秆堆积仿真标定模型和破碎仿真标定模型。采用逐步调整仿真参数使仿真试验值与物理试验值逼近的方法,利用夹段茎秆堆积仿真标定模型,以休止角仿真试验值与实际物理试验值的相对误差为目标,完成夹段茎秆表面接触参数的标定与优化;利用破碎仿真标定模型,以轴向压缩和弯曲仿真试验与实际物理试验的最大轴向压缩力和最大弯曲力的相对误差为目标,利用标定后的表面接触参数完成夹段茎秆粘结参数的标定与优化。最后,利用夹段茎秆的径向压缩与剪切、内芯与表皮拉伸的破碎仿真力学试验和有序采收EDEM-Recurdyn耦合仿真试验验证标定后的表面接触参数和粘结参数。结果表明,仿真与实测试验的破碎力学参数相对误差在5% 以内,且仿真与实测的“时间-载荷”曲线变化趋势一致,低速、中速和高速档的有序采收仿真试验结果与实际物理试验结果相对误差在7.0% 以内。研究结果表明,采用离散元仿真方法研究油菜薹采收过程具有可行性,标定结果可用于指导油菜薹机械化生产。     

Transport processes for chernobyl-labelled sediments: Preliminary evidence from upland mid-wales

The nuclear accident at Chernobyl in April 1986 resulted in a significant increase in the inventory of radiocaesium retained in the soil in many regions of the United Kingdom. The deposition of ¹³⁴Cs provides a convenient tool for the examination of erosional processes in upland systems. Detailed soil sampling has been undertaken within the Plynlimon experimental catchments to establish the pattern of deposition of Chernobyl-derived radionuclides. The preliminary results of a combined radiometric and mineral magnetic approach to the study of the transport of Chernobyl-labelled sediments and their source areas on these upland catchments in mid-Wales are described.     

时域反射仪与中子仪测定土壤含水量标定试验研究

探讨了时域反射仪和中子仪测定土壤含水量的原理,并在禹城试验站对各自适宜的标定方法进行了试验。标定试验结果表明:时域反射仪和中子仪都应该用桶内标定法;时域反射仪可以不分层标定,而中子仪可以分三段标定。     

Performance evaluation and calibration of soil water content and potential sensors for agricultural soils in eastern Colorado

This study evaluated the performance of three soil water content sensors (CS616/625, Campbell Scientific, Inc., Logan, UT; TDT, Acclima, Inc., Meridian, ID; 5TE, Decagon Devices, Inc., Pullman, WA) and a soil water potential sensor (Watermark 200SS, Irrometer Company, Inc., Riverside, CA) in laboratory and field conditions. Soil water content/potential values measured by the sensors were compared with corresponding volumetric water content (θ_v, m³ m⁻³) values derived from gravimetric samples, ranging approximately from the permanent wilting point (PWP) to field capacity (FC) volumetric water contents. Under laboratory and field conditions, the factory-based calibrations of θ_v did not consistently achieve the required accuracy for any sensor in the sandy clay loam, loamy sand, and clay loam soils of eastern Colorado. Salt (calcium chloride dihydrate) added to the soils in the laboratory caused the CS616, TDT, and 5TE sensors to experience errors in their volumetric water content readings with increased bulk soil electrical conductivity (EC; dS m⁻¹). Results from field tests in sandy clay loam and loamy sand soils indicated that a linear calibration (equations provided) for the TDT, CS616 and 5TE sensors (and a logarithmic calibration for the Watermark sensors) could reduce the errors of the factory calibration of θ_v to less than 0.02 ± 0.035 m³ m⁻³. Furthermore, the performance evaluation tests confirmed that each individual sensor needed a unique calibration equation for every soil type and location in the field. In addition, the calibrated van Genuchten (1980) equation was as accurate as the calibrated logarithmic equation and can be used to convert soil water potential (kPa) to volumetric soil water content (m³ m⁻³). Finally, analysis of the θ_v field data indicated that the CS616, 5TE and Watermark sensor readings were influenced by diurnal fluctuations in soil temperature, while the TDT was not influenced. Therefore, it is recommended that the soil temperature be considered in the calibration process of the CS616, 5TE, and Watermark sensors. Further research will be aimed towards determining the need of sensor calibration for every agricultural season.