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Pack Factor Measurements for Corn in Grain Storage Bins

机译:谷物储存仓中玉米的装填系数测量

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摘要

Shelled yellow corn is commonly stored in concrete or corrugated steel bins. Granular materials compact under their own weight, primarily due to particle rearrangement, leading to an increase in bulk density and a change in volume when stored. Reliable grain pack factors are needed to estimate storage capacities and to accurately monitor grain inventories. A science-based model (WPACKING) of pack factors is available that uses the differential form of Janssen’s equation and takes into account the variation in density caused by pressure variation with height and moisture content of the grain and accounts for the effects of grain type, test weight, bin geometry, and bin material. However, this model needs to be compared to field data over a wide range of conditions to ensure robust prediction accuracy. The objective of this research was to determine the field pack factors and bin capacities for on-farm and commercial bins used to store corn in the U.S. and compare them to predictions of the WPACKING program. Bin inventory measurements were conducted in concrete bins with depths up to 31.4 m (114.8 ft) and corrugated steel bins with diameters up to 32.8 m (156Â ft). These values were also compared to the techniques used by the USDA Risk Management Agency (RMA) and the USDA Farm Service Agency, Warehouse Branch (FSA-W). The differences between predicted and reported mass were -4.54% (maximum underprediction) to +4.53% (maximum overprediction) for WPACKING, -2.69% to 4.97% for the RMA method, and -3.33% to + 5.67% for the FSA-W method. The absolute average difference was lowest for the WPACKING model (0.90%) compared to the RMA and FSA-W methods (1.61% and 1.86%, respectively). WPACKING had less than half as many prediction differences above 1% (13 out of 51 bins) as did the RMA and FSA-W methods, which had 29 out of 51 and 33 out of 51, respectively. The RMA and FSA-W methods do not take into account the variations in pack factor due to bin type and moisture content of the stored grain.
机译:带壳的黄色玉米通常存储在混凝土或波纹钢制的垃圾箱中。颗粒状材料在其自身重量下会压实,这主要是由于颗粒的重新排列,导致堆积密度的增加和储存时体积的变化。需要可靠的谷物装箱系数来估算存储容量并准确监控谷物库存。可以使用基于科学的堆积因子模型(WPACKING),该模型使用Janssen方程的微分形式,并考虑到压力随谷物高度和水分含量的变化而引起的密度变化,并考虑了谷物类型的影响,测试重量,料仓几何形状和料仓材料。但是,需要将该模型与各种条件下的现场数据进行比较,以确保可靠的预测准确性。这项研究的目的是确定用于在美国存储玉米的农场和商业垃圾箱的田间装箱系数和垃圾箱容量,并将其与WPACKING计划的预测进行比较。箱柜库存测量是在深度最大为31.4 m(114.8 ft)的混凝土箱柜和直径最大为32.8 m(156 ft)的波纹钢箱柜中进行的。这些值也与美国农业部风险管理局(RMA)和美国农业部农业服务局仓库处(FSA-W)所使用的技术进行了比较。 WPACKING的预测质量与报告质量之间的差异为-4.54%(最大预测不足)至+ 4.53%(最大过度预测),RMA方法为-2.69%至4.97%,FSA-W为-3.33%至+ 5.67%方法。与RMA和FSA-W方法相比,WPACKING模型的绝对平均差异最低(0.90%)(分别为1.61%和1.86%)。与RMA和FSA-W方法相比,WPACKING在1%以上的预测差异(51格中的13格)的比率是RMA和FSA-W方法的一半,后者分别为51格中的29格和51格中的33格。 RMA和FSA-W方法没有考虑由于存储仓的仓位类型和水分含量而导致的堆积系数变化。

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