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<div class="section abstract"><div class="htmlview paragraph">Executable Digital Twins (xDT) are starting a revolution in the industry, where high fidelity simulation models extend their usage from the design and validation phases to in-operation and service phase. Two critical technology blocks in this revolution are Model Order Reduction and Smart Virtual Sensing. The former allows the high-fidelity models to be represented in compact forms and the latter allows to extend the limits of physical sensors and provide full field data combining simulation models and test data in a real-time estimator framework.</div><div class="htmlview paragraph">The smart virtual sensing technology leverages a state-of-the-art Kalman filtering approach to combine the simulation and physical testing. This allows to virtually measure locations that are not accessible with physical sensors due to e.g. physical constrains or high temperatures. In case of large sensors setups, the instrumentation time, and hence the cost, can be greatly reduced by using a combination of physical and smart virtual sensors. Moreover, the estimation is performed in a non-deterministic framework in order to compensate for the modelling inaccuracies and measurement uncertainties.</div><div class="htmlview paragraph">Throughout this paper, the smart virtual sensing technology is initially described and successively applied to virtually measure the stress hotspot locations of the anchorage of a truck axle to prevent its early failure. In this application, the morphology of the components does not allow the placement of any physical sensor at the stress hotspots due to the lack of physical space. In order to provide reliable virtual measurements, an xDT is first authored in Simcenter™ 3D using the Smart Virtual Sensing technology and it is successively imported in Simcenter Testlab™ to directly link the physical sensors to the xDT. This allows to quickly estimate the virtual measurements and process the results.</div></div>

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Purpose Although organizations have more data than ever at their disposal, actually deriving meaningful insights and actions from them is easier said than done. In this concern, the main objective of this study is to identify trends and research opportunities regarding data management within new product development (NPD) and collaborative engineering. Design/methodology/approach Bibliometric and systemic analyses have been carried out using the methodological procedure ProKnow-C, which provides a structured framework for the literature review. A bibliographic portfolio (BP) was consolidated with 33 papers that represent the state of art in the subject. Findings Most recent researches within the BP indicate new trends and paradigm shifts in this area of research, tackling subjects such as the internet of things, cloud computing, big data analytics and digital twin. Research gaps include the lack of data automation and the absence of a common architecture for systems integration. However, from a general perspective of the BP, the management of experimental data is suggested as a research opportunity for future works. Although many studies have tackled data and collaboration based on computer-aided technologies environments, no study examined the management of the measured data collected during the verification and validation stages of a product. Originality/value This work provides a fresh and relevant source of authors, journals and studies for researchers and practitioners interested in the domain of data management applied to NPD and collaborative engineering.

Abstract:The main objective of this paper is to analyse the vertical loads effects applied on the pavement, considering the variation of tire pressure, from a truck's front suspension. For the measurements, a durability test track located in Brazil has been used. The tire pressure was increased by 10 psi from 90 psi to 130 psi with a constant load of 6 t on the front suspension, the maximum allowed load for front axle according to Brazilian legislation. By applying relative damage concept, it is possible to conclude that the variation on the tire pressure will not affect significantly the load applied on the pavement. However, it is recommended to repeat the same methodology in order to analyse the influence on the variation of the other quarter car model variants.