The Externally Bonded Reinforcement (EBR) of timber structures with Carbon Fiber Reinforced Polymers (CFRP) is a solution that has been increasing. Like CFRP strengthened concrete structures, it is known that the premature debonding of the CFRP also occurs on timber structures. To study other alternative solutions to the EBR technique, the Near Surface Mounted (NSM) and six other situations with an additional anchorage were considered. A total of 33 single-lap shear tests were carried out. The experimentally obtained load-slip responses, the strains developed in the CFRP strips or the local bond-slip relationships are all reported and discussed. Compared to the EBR technique, the efficiency of each anchorage system and/or bonding technique is also analysed. The current preliminary results suggest that using two superposed metallic L-shape profiles or embedding the CFRP strip into the timber substrate are the best anchorage systems for the reinforcement of a timber structure with CFRP strips. The NSM technique has also led to high load capacities of the CFRP-to-timber interface. © 2020 Elsevier Ltd

Computational limit analysis methods invariably lead to the need to solve a mathematical programming problem. The alternating direction method of multipliers (ADMM) is one versatile and robust technique to solve non-linear convex optimization problems that has recently found applications in a wide range of fields. Its solution scheme, based on an operator splitting algorithm, is not only easy to implement but also suitable to efficiently solve large-scale variational problems. Starting from the ADMM framework, we derive a strict upper bound finite element formulation using a two-(primal)-field approximation, one for the velocity field and the other for the plastic strain rate field. Next, following a similar approach, we develop a novel strict lower bound formulation. Here, the two-(primal)-field model is based on a redundant approximation of the stress field. Duality principles are then explored in order to unify these two formulations.The effectiveness of this approach is demonstrated on test problems and, to conclude, some considerations are made about the performance results.

Journal of Analytical Atomic Spectrometry (2020), 35, 2920-2927, doi:10.1039/D0JA00307G

Abstract Photonic front-coatings with self-cleaning properties are presented as means to enhance the efficiency and outdoor performance of thin-film solar cells, via optical enhancement while simultaneously minimizing soiling-related losses. This is achieved by structuring parylene-C transparent encapsulants using a low-cost and highly-scalable colloidal-lithography methodology. As a result, superhydrophobic surfaces with broadband light-trapping properties are developed. The optimized parylene coatings show remarkably high water contact angles of up to 165.6° and extremely low adhesion, allowing effective surface self-cleaning. The controlled nano/micro-structuring of the surface features also generates strong anti-reflection and light scattering effects, corroborated by numeric electromagnetic modeling, which lead to pronounced photocurrent enhancement along the UV?vis?IR range. The impact of these photonic-structured encapsulants is demonstrated on nanocrystalline silicon solar cells, that show short-circuit current density gains of up to 23.6%, relative to planar reference cells. Furthermore, the improvement of the devices' angular response enables an enhancement of up to 35.2% in the average daily power generation.

Green and lean are manufacturing management paradigms that identify new opportunities to improve the business to be more competitive. The purpose of this research is to contribute for the understanding of how to address green–lean approaches in a supply chain. The objective is to provide basic mechanisms to implement an organization’s supplychain based on an integrated green and lean approach. To attain this objective, some relevant initiatives for a green and lean transformation were considered first. Second, a multiple case study was conducted in the automotive industry to test qualitatively the several integrated green and lean initiatives and see how they are being implemented in the real world. Based on the literature review and the case study, an oriented-tool is suggested, which involves a roadmap to achieve a green–lean supply-chain transformation. The proposed roadmap can serve as the basis for further research in green and lean supply chain management, providing insights into the implementation of a green–lean approach.

https://docentes.fct.unl.pt/lblm/files/bioelectrochem-2019-127-76.pdf

https://docentes.fct.unl.pt/lblm/files/bioelectrochem-2019-125-8.pdf

https://docentes.fct.unl.pt/lblm/files/sensorsactbchem-2019-285-445.pdf

We report on measurements of the Kβ diagram, valence-to-core (VtC), and hypersatellite X-ray spectra induced in metallic Cr by photon single and double K-shell ionization. The experiment was carried out at the Stanford Synchrotron Radiation Lightsource using the seven-crystal Johann-type hard X-ray spectrometer of the beamline 6-2. For the Kβ diagram and VtC transitions, the present study confirms the line shape features observed in previous works, whereas the K h β hypersatellite transition was found to exhibit a complex spectral line shape and a characteristic low-energy shoulder. The energy shift of the hypersatellite relative to the parent diagram line was deduced from the measurements and compared with the result of extensive multiconfiguration Dirac–Fock (MCDF) calculations. A very good agreement between experiment and theory was found. The MCDF calculations were also used to compute the theoretical line shape of the hypersatellite. A satisfactory agreement was obtained between the overall shapes of the experimental and theoretical spectra, but deviations were observed on the low- and high-energy flanks of the hypersatellite line. The discrepancies were explained by chemical effects, which were not considered in the MCDF calculations performed for isolated atoms.

Our world is facing substantial economic and social challenges due to an increasing pace of technological developments. The introduction of the Internet of Things (IoT) is ushering in a fourth industrial revolution. The vision of Industry 4.0 describes a whole new approach to business operations, and especially the production industries which is characterized by a new level of socio-technical interaction. Emphasizing the importance of intangibles management, organizations have become increasingly focused on the Intellectual Capital (IC) as the main source of value creation. From a strategic point of view, IC is linked to the ability to create and apply the potential of an organizations knowledge based capabilities, and is commonly categorized into three main components: human, structural and relational capital. The industry 4.0 is changing the way we create value which requires from organizations and individuals a rethinking of what is expected or desired from the internet-connected devices. As a phenomenon of interactions and complementarities, IC can offer a possible pathway for reconfiguring business models. The contribution of this work is mainly conceptual. The aim of this paper is to explore what has been researched so far about the importance of industry 4.0 with impact in organizational value creation and how the theory of intellectual capital can help to leverage its benefits. To achieve this objective, a comprehensive review of journal articles, conference papers, books and international reports was performed

Purpose: The purpose of this study intends to make a characterization of a shop floor management (SFM) system in the context of smart manufacturing, through smart technologies and digital shop floor (DSF) features. Design/methodology/approach: To attain the paper objective, a mixed method methodology was used. In the first stage, a theoretical background was carried out, to provide a comprehensive understanding on SFM system in a smart manufacturing perspective. Next, a case study within a survey was developed. The case study was introduced to characterize a SFM system, while the survey was made to understand the level of influence of smart manufacturing technologies and of DSF features on SFM. In total, 17 experts responded to the survey. Findings: Data analytics is the smart manufacturing technology that influences more the SFM system and its components and the cyber security technology does not influence it at all. The problem solving (PS) is the SFM component more influenced by the smart manufacturing technologies. Also, the use of real-time digital visualization tools is considered the most influential DSF feature for the SFM components and the data security protocols is the least influential one. The four SFM components more influenced by the DSF features are key performance indicator tracking, PS, work standardization and continuous improvement. Research limitations/implications: The study was applied in one multinational company from the automotive sector. Originality/value: To the best of the authors’ knowledge, this work is one of the first to try to characterize the SFM system on smart manufacturing considering smart technologies and DSF features.