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多波曲线预应力瞬时损失的计算与试验研究 被引量:3
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作者 郭全全 李珠 +2 位作者 王远平 杨秋学 张善元 《施工技术》 CAS 北大核心 2002年第7期26-28,共3页
对万家寨引黄工程指挥调度中心中的多波曲线预应力筋的孔道摩擦损失和锚固损失进行了理论计算 ,得到了钢绞线有效预拉力沿梁长的分布 ,并对 3道预应力框架梁中的 3组钢绞线的孔道摩擦损失和锚固损失进行了全面的现场试验研究 ,现场试验... 对万家寨引黄工程指挥调度中心中的多波曲线预应力筋的孔道摩擦损失和锚固损失进行了理论计算 ,得到了钢绞线有效预拉力沿梁长的分布 ,并对 3道预应力框架梁中的 3组钢绞线的孔道摩擦损失和锚固损失进行了全面的现场试验研究 ,现场试验检验了理论计算结果的准确性 。 展开更多
关键词 无粘结预应力 多波曲线 瞬时损失 试验
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多波曲线预应力筋的预应力损失计算程序 被引量:2
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作者 陈晓宝 《建筑结构》 CSCD 北大核心 1995年第12期33-36,共4页
根据多波曲线预应力筋的特点,本文介绍了计算预应力筋损失的计算程序.它能适用于由多段任意形状曲线组成的预应力情况,且能提供预应力筋全长任意一点的预应力损失.
关键词 预应力混凝土 预应力筋 多波曲线 程序计算
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多波曲线预应力在大跨度现浇框架梁中的应用
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作者 孟松合 张再兴 《施工技术》 CAS 北大核心 2002年第7期29-30,共2页
关键词 多波曲线 预应力 大跨度 框架
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The Interaction of Oblique Flexural Gravity Waves With a Small Bottom Deformation on a Porous Ocean-Bed: Green's Function Approach 被引量:2
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作者 Smrutiranjan Mohapatra 《Journal of Marine Science and Application》 CSCD 2016年第2期112-122,共11页
The interaction of oblique incident water waves with a small bottom deformation on a porous ocean-bed is examined analytically here within the framework of linear water wave theory. The upper surface of the ocean is a... The interaction of oblique incident water waves with a small bottom deformation on a porous ocean-bed is examined analytically here within the framework of linear water wave theory. The upper surface of the ocean is assumed to be covered by an infinitely extended thin uniform elastic plate, while the lower surface is bounded by a porous bottom surface having a small deformation. By employing a simplified perturbation analysis, involving a small parameter c^(〈〈l ), which measures the smallness of the deformation, the governing Boundary Value Problem (BVP) is reduced to a simpler BVP for the first-order correction of the potential function. This BVP is solved using a method based on Green's integral theorem with the introduction of suitable Green's function to obtain the first-order potential, and this potential function is then utilized to calculate the first-order reflection and transmission coefficients in terms of integrals involving the shape function c(x) representing the bottom deformation. Consideration of a patch of sinusoidal ripples shows that when the quotient of twice the component of the incident field wave number propagating just below the elastic plate and the ripple wave number approaches one, the theory predicts a resonant interaction between the bed and the surface below the elastic plate. Again, for small angles of incidence, the reflected wave energy is more as compared to the other angles of incidence. It is also observed that the reflected wave energy is somewhat sensitive to the changes in the flexural rigidity of the elastic plate, the porosity of the bed and the ripple wave numbers. The main advantage of the present study is that the results for the values of reflection and transmission coefficients obtained are found to satisfy the energy-balance relation almost accurately. 展开更多
关键词 oblique incident waves bottom deformation porous bed elastic plate Green's function reflection coefficient transmission coefficient energy identity
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Methods of data processing in multi-wavelength thermometry
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作者 孙晓刚 赵巍 +1 位作者 原桂彬 戴景民 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2006年第4期421-426,共6页
Three kinds of methods for processing the data of the multi-wavelength pyrometer are presented in this paper and are named curve auto-search method, curve auto-regression method and neural network method. Tbe experime... Three kinds of methods for processing the data of the multi-wavelength pyrometer are presented in this paper and are named curve auto-search method, curve auto-regression method and neural network method. Tbe experimental results indicate that the calculated temperature and the spectral emissivity compared with the true target temperature and spectral emissivity have significant deviation using the curve auto-search and the curve auto-regression methods. However, the calculated temperature and the spectral emissivity with higher accuracy can be obtained using the neural network method. 展开更多
关键词 multi-wavelengtb thermometry curve auto-search method curve auto-regression method neural network
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