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This paper aims to develop a method for evaluating the failure probability and global sensitivity of multiple failure modes based on convex-probability hybrid uncertainty.

The uncertainty information of the input variable is considered as convex-probability hybrid uncertainty. Moment-independent variable global sensitivity index based on the system failure probability is proposed to quantify the effect of the input variable on the system failure probability. Two-mode sensitivity indices are adopted to characterize the effect of each failure mode on the system failure probability. The method based on active learning Kriging (ALK) model with a truncated candidate regions (TCR) is adopted to evaluate the systems failure probability, as well as sensitivity index and this method is termed as ALK-TCR.

The results of five examples demonstrate the effectiveness of the sensitivity index and the efficiency of the ALK-TCR method in solving the problem of multiple failure modes based on the convex-probability hybrid uncertainty.

Convex-probability hybrid uncertainty is considered on system reliability analysis. Moment-independent variable sensitivity index based on the system failure probability is proposed. Mode sensitivity indices are extended to hybrid uncertain reliability model. An effective global sensitivity analysis approach is developed for the multiple failure modes based on convex-probability hybrid uncertainty.

This study considers a Lagrange direct way of modal assurance criterion (MAC) values of an undamped system. The mentioned method for the sensitivity analysis of the MAC of a sliding machine working table is more close to the exact solution and time efficient. The paper aims to discuss these issues.

Using the Lagrange multipliers to compute the first and second-order sensitivity analysis of MAC values.

Because of the Lagrange multiplier without considering the number of design parameters, one only needs to perform the calculation once. Compared with the indirect way, the direct way is more effective when the number of design parameters is greater than one. This calculation procedure is simple and accurate, which can be popularized and used.

Engineering structure often requires only some structure design, and most of the sub-structure design variables are not related to each other. In this case, this way is better and more efficient. The direct way can be applied to the dynamic optimization design of large structures, the frequency and the mode sensitivity analysis in the process of model modification.

Utilizing through-the-thickness pin reinforcement in metal-to-composite joints can significantly increase the joint mechanical properties, enabling the introduction to a whole new field of applications in joining technology. However, with the rise of advanced pin manufacturing techniques – such as additive layer manufacturing, little research has been performed on the pin shape optimization and its behavior. The paper aims to discuss this issue.

In this study, a numerical shape optimization algorithm is used to produce optimized pin shapes for several initial pin dimension parameters, having as objective to achieve a more uniform stress distribution along the surface of the pin, enhancing the pin strength and joint integrity.

Results showed that pin shape is a crucial factor in the mechanical response of the pin. In Mode I, the presence of an undercut feature on the pin head can increase the ultimate load of the pin by +250 percent, while in Mode II, the base diameter is the dominant feature in the joint ultimate strength.

With these results, the paper aims to utilize commercial available numerical software to explore optimization capabilities in joints strength. These optimization capabilities show that it could be used for the enhancement of metal-to-composite joints response.

Condition monitoring (CM) of structures is important from safety consideration. Damage detection techniques, using inverse dynamic approaches, are important tools to improve the mathematical models for monitoring the condition of structure. Uncertainties in the measured data might lead to unreliable identification of damage in structural system. Experimental validation is crucial for establishing its practical applicability. The measurement of dynamic responses at all degrees of freedom (DOFs) of a structure is also not feasible in practice. In addition the effect of these uncertainties and constraint of limited measurement are required to be studied based on experimental validation. This paper aims to discuss these issues.

Proposed numerical model based on measured natural frequencies and mode shapes is found suitable for CM of framed structures in the framework of finite element model with limited dynamic responses. The structural properties, namely, axial rigidity and bending rigidity are identified at the element level in the updated models of the system. Damage at the element level is identified by comparing the identified structural parameters of the updated model of the system with those of the undamaged state. Proposed numerical model is suitable for practical problem, as it is able to identify the structural parameters with limited modal data of first few modes, measured at selected DOFs.

The model is able to identify the structural damage with greater accuracy from the noisy dynamic responses even if the extent of damage is small. Experimental studies, on simple cantilever beams, establish the potential of the proposed methods for its practical implementation.

The greater random noise will lead to unreliable identification of structural parameters as observed. Thus, filtering of noise technique may be required to be adopted prior to consideration of the measured data in the proposed identification approach.

Requirement of higher modal data seems to be difficult in case of real life practical problem. Thus, simulation technique like condensation or SEREP technique may be adopted.

Structural health monitoring of infrastructural system is significantly important. CM of those structures from global response with limited measured data seems to be an effective tool to ensure safety and durability of structures.

The modal testing and subsequent extraction of modal data have been carried out at the authors’ laboratory. The numerical code based on inverse dynamic approach has been developed independently with original contribution.

Presents a model for strategic selection of processes for benchmarking. The process selection methodology, which incorporates Saaty′s Analytical Hierarchy Process, starts with situation analysis, is followed by the differentiation of target customer wants, and concludes with the prioritization of the value chain processes to be benchmarked. The proposed methodology was implemented in a manufacturing setting. Sensitivity analysis was carried out to test the robustness of the results. The feedback from the managers who participated in the selection process confirmed the utility of this approach.

The purpose of this paper is to present a model for a comprehensive and integrated approach to managing interface conflict from the early stages of a dam construction project.

A case study methodology is adopted. Following comprehensive literature review, qualitative data were gathered from case studies through interviews conducted on the Middle Marsyangdi Hydroelectric Project (MMHEP) dam project in Nepal. Causal loop diagrams on the typical evolution of key indicators of interface conflict were then developed and a simulate‐able model of interface conflict was derived using system dynamic modeling technique. The model was then simulated to derive viable policies for future management of dam construction projects in developing countries.

The study reveals that interface conflicts at the construction stage of projects are caused mainly by lack of effective Environmental Impact Assessment, public participation and mutual consultation, on timely basis and accurate information from the early stages of projects. The system dynamic model is able to replicate general behavior of evolution of interface conflict in a dam construction project. Furthermore, the study explored three viable policies to avoid and minimize interface conflict in the construction stage of a dam project. The policies were tested and demonstrated to be useful in improving the value of projects to stakeholders. It is demonstrated that a combination of policies is better than adopting a single policy to stakeholder management.

The paper demonstrates the utility of system dynamics as a modeling tool for understanding the dynamics of conflicts on dam construction projects. The model should be helpful to policy makers on large projects, especially those likely to be subject to social and environmental conflict. Policies derived from the model have the potential of being used to assess and take proactive measures to manage conflicts effectively and efficiently from early in a project's life.

A critical step in all benchmarking methodologies is “to determine what to benchmark.” Although benchmarking methodologies have been noted in the literature, the need has arisen for the development of structured approaches to determine priority improvement needs. The purpose of this paper is to provide a framework for determining improvement needs in higher education benchmarking.

The paper makes use of the analytic hierarchy process to develop a framework. The application of the framework is demonstrated through a case study.

The framework discussed in this paper is consensus-based, allows different viewpoints to be integrated, and promotes input to and ownership of the decision making process and its outcomes. The feedback of the participants confirmed the usefulness of the approach.

The previous research has established that determining improvement needs in benchmarking was mostly unsystematic and ad hoc based. And failures in precisely determining improvement needs can result in a lack of alignment between processes to be benchmarked and strategic priorities of higher education institutions (HEIs). The developed framework can help determine priority improvement needs aligned with the strategic priorities of the HEI.

Since continual improvement is an essential element of all quality initiatives, the framework provides a starting point for benchmarking as well as other improvement initiatives such as total quality management.

The use of corporate simulation models has grown dramatically over the past decade. A survey of 300 major US companies taken in 1974 indicated that nearly two‐thirds of the respondents were already using corporate models, and that over two‐thirds of the remainder were either developing or planning to develop a model. A more recent study in the UK estimates that some 40% to 50% of the “Times 1000” companies now have models of one form or another.