[Objective] The aim was to improve the adhesive bonding property of wheat straw surface to prepare wheat straw particleboard of soy protein isolate （SPI） adhesive through chemical and enzyme treatments. [Method] Eva...
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[Objective] The aim was to improve the adhesive bonding property of wheat straw surface to prepare wheat straw particleboard of soy protein isolate （SPI） adhesive through chemical and enzyme treatments. [Method] Evaluation and analysis were made on wettability of wheat straws in the control group and treated groups （chemical and enzyme treatments） by means of measurement of contact angle and calculation of spreading-penetration parameters （K）. In addition, we made analysis on surface elements through X-ray photoelectron spectroscopy （XPS）. [Result] The re- sults showed that K value of straw treated with sodium hydroxide, hydrogen peroxide and lipase increased by 58.0%, 48.7% and 83.2% compared to that of control group, respectively. The XPS analysis indicated that rapid decrease of silicon content and destruction of wax layer greatly contributed to wettability improvement of wheat straw surface. [Conclusion] The chemical and lipase treatments of wheat straw provided technical support for manufacture of wheat straw particle boand.
运用RBF神经网络(Radial Basis Function Neural Network)理论,分析了大夹角V撑施工期间最大风险因素可能发生的部位,并对V撑的结构失效风险性进行了定量分析。将有限元分析结果作为神经网络训练样本数据,利用径向基神经网络建立了基本...
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运用RBF神经网络(Radial Basis Function Neural Network)理论,分析了大夹角V撑施工期间最大风险因素可能发生的部位,并对V撑的结构失效风险性进行了定量分析。将有限元分析结果作为神经网络训练样本数据,利用径向基神经网络建立了基本变量和结构响应之间的隐性映射关系,根据蒙特卡洛原理进行模拟计算,最终得出V撑施工过程中各个危险截面出现结构失效的概率预估值。通过工程实例验证表明,基于径向基神经网络所建立的施工过程风险分析方法计算效率高,具有可行性和有效性,同时为V撑施工风险决策提供了理论依据。
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