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This research addresses the diverse characteristics of existing railway steel bridges in China, including variations in construction age, design standards, structural types, manufacturing processes, materials and service conditions. It also focuses on prominent defects and challenges related to heavy transportation conditions, particularly low live haul reserves and severe fatigue problems.

The study encompasses three key aspects: (1) Adaptability assessment: It begins with assessing the suitability of existing railway steel bridges for heavy-haul operations through comprehensive analyses, experiments and engineering applications. (2) Strengthening: To combat frequent crack defects in the vertical stiffener end structure of girder webs, fatigue performance tests and reinforcement scheme experiments were conducted. These experiments included the development of a hot-spot stress S-N curve for this structure, validating the effectiveness of methods like crack stop holes, ultrasonic hammering and flange angle steel. (3) Service life extension: Research on the cruciform welded joint structure (non-fusion transfer type) focused on fatigue performance over the long life cycle. This led to the establishment of a fatigue S-N curve, enhancing Chinese design codes.

The research achieved several significant outcomes: (1) Successful implementation of strengthening and retrofitting measures on a 64-m single-span double-track railway steel truss girder on an existing heavy-duty line. (2) Post-reinforcement, a substantial 26% to 32% reduction in live haul stress on bridge members was achieved. (3) The strengthening and retrofitting efforts met design expectations, enabling the bridge to accommodate vehicles with a 30-ton axle haul on the railway line.

This research systematically tackles challenges and defects associated with Chinese existing railway steel bridges, providing valuable insights into adaptability assessment, strengthening techniques and service life extension methods. Furthermore, the development of fatigue S-N curves and the successful implementation of bridge enhancements have practical implications for improving the resilience and operational capacity of railway steel bridges in China.

Many additively manufactured parts suffer from reduced interlayer strength. This anisotropy is necessarily tied to the orientation during manufacture. When individual features on a part have conflicting optimal orientations, the part is unavoidably compromised. This paper aims to demonstrate a strategy in which conflicting features can be functionally separated into “co-parts” which are individually aligned in an optimal orientation, selectively reinforced with continuous fiber, printed simultaneously and, finally, assembled into a composite part with substantially improved performance.

Several candidate parts were selected for co-part decomposition. They were printed as standard fused filament fabrication plastic parts, parts reinforced with continuous fiber in one plane and co-part assemblies both with and without continuous fiber reinforcement (CFR). All parts were loaded until failure. Additionally, parts representative of common suboptimally oriented features (“unit tests”) were similarly printed and tested.

CFR delivered substantial improvement over unreinforced plastic-only parts in both standard parts and co-part assemblies, as expected. Reinforced parts held up to 2.5x the ultimate load of equivalent plastic-only parts. The co-part strategy delivered even greater improvement, particularly when also reinforced with continuous fiber. Plastic-only co-part assemblies held up to 3.2x the ultimate load of equivalent plastic only parts. Continuous fiber reinforced co-part assemblies held up to 6.4x the ultimate load of equivalent plastic-only parts. Additionally, the thought process behind general co-part design is explored and a vision of simulation-driven automated co-part implementation is discussed.

This technique is a novel way to overcome one of the most common challenges preventing the functional use of additively manufactured parts. It delivers compelling performance with continuous carbon fiber reinforcement in 3D printed parts. Further study could extend the technique to any anisotropic manufacturing method, additive or otherwise.

This study was intended to ensure learner-centred pedagogy in an open and distance learning environment by applying scaffolding and positive reinforcement techniques.

This study critically analysed the context and current instructional practice of Bangladesh Open University (BOU) via document analysis and literature review. The conceptual framework of this study was adapted from the ADDIE model, i.e. the analysis, design, development, implementation and evaluation model.

The study explored that the instructional practice of BOU was dominated by teacher-centred pedagogy. Hence, to ensure learner-centred pedagogy, the researchers developed three model lesson plans. These lesson plans infused the theoretical directives of scaffolding and positive reinforcement as well as several assessment tasks which can assess the learners’ lower-order and higher-order thinking skills. The researchers also presented possible challenges for the sound implementation of these model lesson plans and suggested pragmatic solutions accordingly.

This study recommended that the combined application of scaffolding and positive reinforcement would effectively ensure learner-centred pedagogy.

This paper aims to provide an overview of the current manufacturing methods for three-dimensional textile preforms while providing experimental data on the emerging techniques of combining yarn interlocking with yarn interlooping.

The paper describes the key textile technologies used for composite manufacture: braiding, weaving and knitting. The various textile preforming methods are suited to different applications; their capabilities and end performance characteristics are analysed.

Such preforms are used in composites in a wide range of industries, from aerospace to medical and automotive to civil engineering. The paper highlights how the use of knitting technology for preform manufacture has gained wider acceptance due to its flexibility in design and shaping capabilities. The tensile properties of glass fibre knit structures containing inlay yarns interlocked between knitted loops are given, highlighting the importance of reinforcement yarns.

The future trends of reinforcement yarns in knitted structures for improved tensile properties are discussed, with initial experimental data.

The purpose of this paper is to develop a method suitable for the design of reinforced concrete columns subjected to a standard fire.

The Zone Method – a ’simplified calculation method” included in Eurocode 2 – has been developed by Hertz as a manual calculation scheme for the check of fire resistance of concrete sections. The basic idea is to disregard the thermal strains and to calculate the resistance of a cross-section by reducing the concrete cross-section by a “damaged zone”. It is assumed that all fibers can reach their ultimate, temperature dependent strength. Therefore, it is a plastic concept; the information on the state of strain is lost. The calculation of curvatures and deflections is thus only possible by making further assumptions. Extensions of the zone method toward a general calculation method, suitable for the implementation in commercial design software and using the temperature dependent stress–strain curves of the Advanced Calculation Method, have been developed in Germany. The extension by Cyllok and Achenbach is presented in detail. The necessary assumptions of the Zone Method are reviewed, and an improved proposal for the consideration of the reinforcement in this extended Zone Method is presented.

The principles and assumptions of the Zone Method proposed by Hertz can be validated.

An extension of the Zone Method suitable for the implementation in design software is proposed.

This paper aims to investigate how the extant literature on sustainable supply chain management (SSCM) empirically explores the perspective of emerging economy suppliers operating in global supply chains (GSCs). It thereby explains the role of emerging economy suppliers in determining the success of SSCM.

A systematic literature review of 41 empirical papers (published between 2007 and 2021) was conducted, involving both descriptive and thematic analyses.

The findings demonstrate that emerging economy suppliers have a key role in SSCM, given their use of positive feedback loops to proactively create remedies to surpass barriers using their collaboration mechanisms, and exploit authentic sustainability outcomes as reinforcements to drive further sustainability initiatives. The authors also demonstrate that suppliers are particularly focused on the cultural and institutional dimensions of sustainability. Finally, the authors provide an explanatory analytical framework to reduce the institutional distance between buyers and their global suppliers.

This review identifies avenues for future research on the role of emerging economy suppliers in SSCM.

Recognising remedies to surpass barriers and reinforcements to drive new actions can aid SSCM in GSCs and improve understanding between buyers and suppliers.

The valorisation of cultural and institutional issues can lead to more responsible supplier interactions and improved sustainability outcomes in emerging economies.

This review only analyses the viewpoint of emerging economy suppliers, whereas prior SSCM reviews have focused on the buyer perspective. Thus, the authors reduce supplier invisibility and institutional distance between GSC participants.

This study aims to propose an enhanced eco-driving strategy based on reinforcement learning (RL) to alleviate the mileage anxiety of electric vehicles (EVs) in the connected environment.

In this paper, an enhanced eco-driving control strategy based on an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed for connected EVs. The EEDC-HRL simultaneously controls longitudinal velocity and lateral lane-changing maneuvers to achieve more potential eco-driving. Moreover, this study redesigns an all-purpose and efficient-training reward function with the aim to achieve energy-saving on the premise of ensuring other driving performance.

To illustrate the performance for the EEDC-HRL, the controlled EV was trained and tested in various traffic flow states. The experimental results demonstrate that the proposed technique can effectively improve energy efficiency, without sacrificing travel efficiency, comfort, safety and lane-changing performance in different traffic flow states.

In light of the aforementioned discussion, the contributions of this paper are two-fold. An enhanced eco-driving strategy based an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed to jointly optimize longitudinal velocity and lateral lane-changing for connected EVs. A full-scale reward function consisting of multiple sub-rewards with a safety control constraint is redesigned to achieve eco-driving while ensuring other driving performance.

In the construction industry, an under researched area of study is how main contractor (MC) sub-contract design responsibilities to sub-contractor (SC). This lack of knowledge is particularly serious in the context of delivery methods such as design and construct where design responsibilities are pushed down the supply chain. In this study, it is aimed to explore which level of design responsibility MCs sub-contract to SCs, for what reasons, and what the impact of sub-contracting decisions is on projects.

A qualitative in-depth multiple case study was conducted. Six sub-contracting cases were examined in two civil engineering projects. In each project, the MCs sub-contracted pre-fabricated beams, reinforcement and railing to SCs. Data collection included document analysis and interviews. A within-case and cross-case analysis was conducted to examine emerging empirical patterns. These patterns were used to elaborate theory and develop propositions.

MCs sub-contracted design responsibilities to SCs as suggested by literature. However, despite that sub-contracting was in keeping with literature, several problems were reported in the cases where MCs involved SCs no earlier than in the construction stage. This is not to be expected according to theory.

This study adds value to the sub-contracting field as it provides new insights in relationships between the level of design responsibilities sub-contracted and the impact of that on projects. The study also revealed new factors such as building information modelling (BIM) interoperability that should get more attention in sub-contracting.

This study aims to introduce a deep neural network (DNN) to estimate the effective thermal conductivity of the flat heat pipe with spreading thermal resistance.

A total of 2,160 computational fluid dynamics simulation cases over up to 2,000 W/mK are conducted to regress big data and predict a wider range of effective thermal conductivity up to 10,000 W/mK. The deep neural networking is trained with reinforcement learning from 10–12 steps minimizing errors in each step. Another 8,640 CFD cases are used to validate.

Experimental, simulational and theoretical approaches are used to validate the DNN estimation for the same independent variables. The results from the two approaches show a good agreement with each other. In addition, the DNN method required less time when compared to the CFD.

The DNN method opens a new way to secure data while predicting in a wide range without experiments or simulations. If these technologies can be applied to thermal and materials engineering, they will be the key to solve thermal obstacles that many longing to overcome.

This study aims to focus on a reinforcement supplier’s efforts to diffuse solutions, more or less innovative, in the construction sector to gain understanding of what facilitates and complicates innovation diffusion from a supplier perspective.

The interpretative research presented builds on 28 semi-structured interviews with the supplier and its customers and document studies. The research emphasizes dynamics in the diffusion process and rests on the assumption that the innovation content, innovation context and the innovation process interacts in the diffusion process.

The findings and the contribution from the study provide significant details concerning how the dimensions interact and how the diffusion process may unfold over time, but also that different solutions interact to push diffusion forward.

The study relates to one supplier’s work and the interplay implies uniqueness in different cases. Studies in other contexts could, therefore, also be suitable to develop findings and their transferability.

The study provides understanding for suppliers diffusing innovations in construction on how to act.

A major contribution from the study is that it puts emphasis on how the diffusion process proceeds in interaction with its content and context and problematizes this dimension. Furthermore, the importance of nuancing sub-contexts to display decisive factors in the diffusion process is emphasized.