Finite element model updating using base excitation response function

Finite element model updating is an effective way to build accurate analytical models for structures. Most of the available updating methods employ information from modal testing. However, in astronautics engineering, information provided by vibration table testing is more valuable than those from modal testing. Therefore, it is necessary to study updating methods which can adopt information from vibration table testing. This paper presents the study on such issue. The base excitation response function is analyzed with the assumption that the vibration table gives the structure a single direction motion excitation. Model updating method which adopts the response function is then proposed. In the numerical simulation, several case studies are constructed for a truss structure with small or significant modeling errors respectively. Data selection, which has great influence on the success of updating, is carefully studied. A novel adaptive data selection approach is suggested. Simulation results show that model updating converge with good accuracy when the adaptive data selection approach is used

Automatic Nonlinear Subspace Identification Using Clustering Judgment Based on Similarity Filtering

Accurately determining system order plays a vital role in system identification directly related to the accuracy of identification results, especially for nonlinear system identification. Due to the need for human subjective judgment, the traditional sequence determination method easily causes uncertainty in the results; and the phenomenon of the virtual mode or omission occurs. An automatic nonlinear subspace identification method is proposed to address the aforementioned problems. When the eigenvalue decomposition of the constructed Hankel matrix is performed, the calculation range of the modal order of the system is estimated. The similarity coefficient and distance function are introduced to cluster the identified modal results, the poles of the false modes are removed to obtain the cluster stabilization diagram, and the best order of the system is received. Then, the modal parameters and nonlinear coefficients are obtained. Simulation examples are carried out to verify the effectiveness and robustness of the proposed method. An experimental study is carried out on a multilayer building with nonlinear characteristics. Compared with the traditional stabilization graph, the accuracy of the automatic order determination proposed in this paper is proven

Finite element model updating using base excitation response function

Finite element model updating is an effective way to build accurate analytical models for structures. Most of the available updating methods employ information from modal testing. However, in astronautics engineering, information provided by vibration table testing is more valuable than those from modal testing. Therefore, it is necessary to study updating methods which can adopt information from vibration table testing. This paper presents the study on such issue. The base excitation response function is analyzed with the assumption that the vibration table gives the structure a single direction motion excitation. Model updating method which adopts the response function is then proposed. In the numerical simulation, several case studies are constructed for a truss structure with small or significant modeling errors respectively. Data selection, which has great influence on the success of updating, is carefully studied. A novel adaptive data selection approach is suggested. Simulation results show that model updating converge with good accuracy when the adaptive data selection approach is used

Thermal cracking of gas oil in a helical coil reactor

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Winning Small Retailers’ Trust: A Suppliers’ Perspective

Trust is one of the key elements in long-term relationship retention (Morgan & Hunt, 1994; Barnes, 1997; Gwinner, Dwayne & Bitner, 1998; Reynolds & Arnold, 2000), which has been paid much attention to by both academics and practitioners. Trust is not only important for businesses to retain their customers; it is also crucial for suppliers to maintain good relationship with their retailers (Ganesan, 1994). Hence, how to create retailers’ trust has been studied excessively in business to business (B to B) context. Many studies focus on suppliers’ performance because retailers’ trust is rooted in suppliers’ high level of performance. Since businesses are commercial entities who hunt for economic outcomes and high level of performance is a sign of competence (Kim et al., 2004). However, performance is the ultimate goal of businesses, which would be influenced a lot by environmental factors of the market; how retailers decide whether to trust their suppliers should be more complicated, rather than consider the performance solely. Till now, the question that how retailers, especially those small retailers, judge from their suppliers’ performance, as well as other relevant factors to decide the overall trust over their suppliers has been insufficiently studied (Corsten & Kumar, 2005). Based on a review of the literature, our study proposes that small retailers would have a whole process of reasoning in deciding whether to trust their suppliers. Besides suppliers’ performance, they would take environmental factors, as well as some other factors, such as suppliers’ opportunism and market intelligence, into consideration to make an overall judgment. This study will contribute to understand the reasons that can generate small retailers’ trust; it will provide great implications for suppliers’ relationship marketing in practice