136 research outputs found

    Detecting Structural Defects Using Novel Smart Sensory and Sensor-less Approaches

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    Monitoring the mechanical integrity of critical structures is extremely important, as mechanical defects can potentially have adverse impacts on their safe operability throughout their service life. Structural defects can be detected by using active structural health monitoring (SHM) approaches, in which a given structure is excited with harmonic mechanical waves generated by actuators. The response of the structure is then collected using sensor(s) and is analyzed for possible defects, with various active SHM approaches available for analyzing the response of a structure to single- or multi-frequency harmonic excitations. In order to identify the appropriate excitation frequency, however, the majority of such methods require a priori knowledge of the characteristics of the defects under consideration. This makes the whole enterprise of detecting structural defects logically circular, as there is usually limited a priori information about the characteristics and the locations of defects that are yet to be detected. Furthermore, the majority of SHM techniques rely on sensors for response collection, with the very same sensors also prone to structural damage. The Surface Response to Excitation (SuRE) method is a broadband frequency method that has high sensitivity to different types of defects, but it requires a baseline. In this study, initially, theoretical justification was provided for the validity of the SuRE method and it was implemented for detection of internal and external defects in pipes. Then, the Comprehensive Heterodyne Effect Based Inspection (CHEBI) method was developed based on the SuRE method to eliminate the need for any baseline. Unlike traditional approaches, the CHEBI method requires no a priori knowledge of defect characteristics for the selection of the excitation frequency. In addition, the proposed heterodyne effect-based approach constitutes the very first sensor-less smart monitoring technique, in which the emergence of mechanical defect(s) triggers an audible alarm in the structure with the defect. Finally, a novel compact phased array (CPA) method was developed for locating defects using only three transducers. The CPA approach provides an image of most probable defected areas in the structure in three steps. The techniques developed in this study were used to detect and/or locate different types of mechanical damages in structures with various geometries

    Non-Contact Quantification of Longitudinal and Circumferential Defects in Pipes using the Surface Response to Excitation (SuRE) Method

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    Rapid screening and monitoring of hollow cylindrical structures using active guided-waves based structural health monitoring (SHM) techniques are important in chemical, petro-chemical, oil and gas industries. Successful implementation of the majority of these techniques in the SHM of pipes depends on the identification of the appropriate guided-waves modes and their frequencies for each application. The highly dispersive nature of the guided-waves and presence of multi modes at each frequency makes the mode selection and the interpretation of signals a challenging task. The surface response to excitation (SuRE) method was developed to detect the defects and loading condition changes on plates with minimum dependence on the excitation of particular modes at certain frequencies. In the present study, the SuRE method is proposed for quantification of longitudinal and circumferential defects, with varying severities, as common examples of axisymmetric and nonaxisymmetric defects in pipes. The results indicate that the SuRE method can be used effectively for damage quantification in hollow cylinders

    Conceptual Framework for Managing Uncertainty in a Collaborative Agri-Food Supply Chain Context

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    [EN] Agri-food supply chains are subjected to many sources of uncertainty. If these uncertainties are not managed properly, they can have a negative impact on the agri-food supply chain (AFSC) performance, its customers, and the environment. In this sense, collaboration is proposed as a possible solution to reduce it. For that, a conceptual framework (CF) for managing uncertainty in a collaborative context is proposed. In this context, this paper seeks to answer the following research questions: What are the existing uncertainty sources in the AFSCs? Can collaboration be used to reduce the uncertainty of AFSCs? Which elements can integrate a CF for managing uncertainty in a collaborative AFSC? The CF proposal is applied to the weather source of uncertainty in order to show its applicability.The first author acknowledges the partial support of the Program of Formation of University Professors of the Spanish Ministry of Education, Culture, and Sport (FPU15/03595). The other authors acknowledge the partial support of the Project 691249, RUC-APS: Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems, funded by the EU under its funding scheme H2020-MSCA-RISE-2015.Esteso-Álvarez, A.; Alemany Díaz, MDM.; Ortiz Bas, Á. (2017). Conceptual Framework for Managing Uncertainty in a Collaborative Agri-Food Supply Chain Context. IFIP Advances in Information and Communication Technology. 506:715-724. https://doi.org/10.1007/978-3-319-65151-4_64S715724506Taylor, D.H., Fearne, A.: Towards a framework for improvement in the management of demand in agri-food supply chains. Supply Chain Manag. Int. J. 11, 379–384 (2006)Matopoulos, A., Vlachopoulou, M., Manthou, V., Manos, B.: A conceptual framework for supply chain collaboration: empirical evidence from the agri-food industry. Supply Chain Manag. Int. 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    Developing lean and responsive supply chains : a robust model for alternative risk mitigation strategies in supply chain designs

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    This paper investigates how organization should design their supply chains (SCs) and use risk mitigation strategies to meet different performance objectives. To do this, we develop two mixed integer nonlinear (MINL) lean and responsive models for a four-tier SC to understand these four strategies: i) holding back-up emergency stocks at the DCs, ii) holding back-up emergency stock for transshipment to all DCs at a strategic DC (for risk pooling in the SC), iii) reserving excess capacity in the facilities, and iv) using other facilities in the SC’s network to back-up the primary facilities. A new method for designing the network is developed which works based on the definition of path to cover all possible disturbances. To solve the two proposed MINL models, a linear regression approximation is suggested to linearize the models; this technique works based on a piecewise linear transformation. The efficiency of the solution technique is tested for two prevalent distribution functions. We then explore how these models operate using empirical data from an automotive SC. This enables us to develop a more comprehensive risk mitigation framework than previous studies and show how it can be used to determine the optimal SC design and risk mitigation strategies given the uncertainties faced by practitioners and the performance objectives they wish to meet

    Toward community standards and software for whole-cell modeling

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    Whole-cell (WC) modeling is a promising tool for biological research, bioengineering, and medicine. However, substantial work remains to create accurate, comprehensive models of complex cells. Methods: We organized the 2015 Whole-Cell Modeling Summer School to teach WC modeling and evaluate the need for new WC modeling standards and software by recoding a recently published WC model in SBML. Results: Our analysis revealed several challenges to representing WC models using the current standards. Conclusion: We, therefore, propose several new WC modeling standards, software, and databases. Significance:We anticipate that these new standards and software will enable more comprehensive models

    Microgeographical, inter-individual, and intra-individual variation in the flower characters of Iberian pear Pyrus bourgaeana (Rosaceae)

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    Flower characteristics have been traditionally considered relatively constant within species. However, there are an increasing number of examples of variation in flower characteristics. In this study, we examined the variation in attracting and rewarding flower characters at several ecological levels in a metapopulation of Pyrus bourgaeana in the Doñana area (SW Spain). We answered the following questions: what are the variances of morphological and nectar characters of flowers? How important are intra-individual and inter-individual variance in flower characters? Are there microgeographical differences in flower characters? And if so, are they consistent between years? In 2008 and 2009, we sampled flowers of 72 trees from five localities. For six flower morphological and two nectar characteristics, we calculated coefficients of variation (CV). The partitioning of total variation among-localities, among-individuals, and within-individuals was estimated. To analyze differences among localities and their consistency between years, we conducted generalized linear mixed models. The CVs of nectar characters were always higher than those of morphological characters. As expected, inter-individual variation was the main source of variation of flower morphology, but nectar characters had significant variation at both intra- and inter-individual levels. For most floral traits, there were no differences among localities. Our study documents that variation is a scale-dependent phenomenon and that it is essential to consider intra- and inter-individual variance when investigating the causes and consequences of variation. It also shows that single year studies of floral characters should be viewed with caution
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