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Adaptive inverse analysis (AIA) applied and verified on various fiber reinforced concrete composites

机译:自适应逆分析(AIA)在各种纤维增强混凝土复合材料中的应用和验证

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During the past decades several inverse approaches have been developed to identify the stress-crack opening (sigma - w) by means of indirect test methods, such as the notched three point bending-, wedge splitting-, and round panel testing. The aim is to establish reliable constitutive models for the tensile behavior of fiber reinforced concrete materials, suitable for structural design. Within this context, the adaptive inverse analysis (AIA) was recently developed to facilitate a fully general and automatized inverse analysis scheme, which is applicable in conjunction with analytical or finite element simulation of the experimental response. This paper presents a new formulation of the adaptive refinement criterion of the AIA method. The paper demonstrates that the refinement criterion of the nonlinear least square curve fitting process, is significantly improved by coupling the model error to the crack mouth opening and the crack opening displacement relationship (w(cmod) - w(cod)). This enables an adaptive refinement of the sigma - w model in the line segment with maximum model error, which entails significant improvement of the numerical efficiency of the AIA method without any loss of robustness. The improved method is applied on various fiber reinforced concrete composites and the results are benchmarked with the inverse analysis method suggested by the Japanese Concrete Institute (Method of test for fracture energy of concrete by use of notched beam, Japanese Concrete Institute Standard, Tokyo, 2003) and recently adopted in ISO 19044 (Test methods for fibre-reinforced cementitious composites-load-displacement curve using notched specimen, 2015). The benchmarking demonstrates that the AIA method, in contradiction to the JCI/ISO method, facilitates direct determination of the tensile strength and operational multi-linear sigma - w models.
机译:在过去的几十年中,已经开发出了几种通过间接测试方法来识别应力裂纹开口(sigma-w)的反向方法,例如带缺口的三点弯曲,楔形劈裂和圆板测试。目的是建立适用于结构设计的纤维增强混凝土材料抗拉性能的可靠本构模型。在此背景下,最近开发了自适应逆分析(AIA)以促进完全通用和自动化的逆分析方案,该方案可与实验响应的分析或有限元模拟结合使用。本文提出了AIA方法的自适应细化准则的新表述。本文证明,通过将模型误差与裂纹口张开度和裂纹张开位移关系(w(cmod)-w(cod))耦合,可以大大改善非线性最小二乘曲线拟合过程的细化准则。这使得能够以最大的模型误差对线段中的sigma-w模型进行自适应细化,从而极大地提高了AIA方法的数值效率,而不会损失任何鲁棒性。改进的方法应用于各种纤维增强的混凝土复合材料,结果以日本混凝土协会提出的反分析方法为基准(采用缺口梁的混凝土断裂能测试方法,日本混凝土协会标准,东京,2003年) ),最近在ISO 19044(采用缺口试样的纤维增强水泥基复合材料的试验方法-载荷-位移曲线的测试方法,2015)中采用。基准测试表明,与JCI / ISO方法相反,AIA方法有助于直接确定拉伸强度和可操作的多线性sigma-w模型。

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