Hydrogen has a key role to play in decarbonising industry and other sectors of society. It is important to develop low-carbon hydrogen production technologies that are cost-effective and energy-efficient. Sorption-enhanced steam methane reforming (SE-SMR) is a developing low-carbon (blue) hydrogen production process, which enables combined hydrogen production and carbon capture. Despite a number of key benefits, the process is yet to be fully realised in terms of efficiency. In this work, a sorption-enhanced steam methane reforming process has been intensified via exergy analysis. Assessing the exergy efficiency of these processes is key to ensuring the effective deployment of low-carbon hydrogen production technologies. An exergy analysis was performed on an SE-SMR process and was then subsequently used to incorporate process improvements, developing a process that has, theoretically, an extremely high CO2 capture rate of nearly 100 %, whilst simultaneously demonstrating a high exergy efficiency (77.58 %), showcasing the potential of blue hydrogen as an effective tool to ensure decarbonisation, in an energy-efficient manner.

For some time, both practitioners and scholars have been arguing that coaching should play a stronger and more central role to achieve successful business outcomes. However, when looking to inspire leaders to gain competence in the skills of coaching, ill-founded assumptions are made. Including, but not limited to, the very definition of leadership and the very nature of coaching when embedded into leadership (termed in this chapter, leaders-who-coach). The research described in this chapter looks into these practices to proffer 15 dimensions of leaders-who-coach, drawing on multiple sources which seek to ameliorate the shortfalls of previous research in this area. Finally, the chapter includes a discussion on the less than perfect nature of the approach taken due to the philosophical misalignments between the described realities of leadership and coaching and the ontological and epistemological challenges of research. The primary aim of this chapter is to respond to the growing organizational calls for more leaders to have the skills of coaching.

ABSTRACT What happens to newly built resilience capabilities when the pandemic is over? Using the concept of exaptation, we investigate how supply chain organizations have repurposed supply chain resilience capabilities post-pandemic. In particular, we examine the degree of ambidexterity capabilities to identify the exaptation potential from the newly acquired supply chain resilience capabilities during a disruptive event. In this paper, we (1) adopt a framework that depicts four types of different exaptation potential for supply resilience based on the management constructs of exploitation and exploration capabilities and (2) use the results from a related survey among 447 supply chain managers in Australia to subsequently analyse the exaptation potentials post COVID-19. The integration of the exaptation potential into supply chain literature opens a new chapter on how resilience capabilities are utilized, and we found that the majority of supply chains are able to simultaneously pursue and develop exploitative and exploratory capabilities.

A stochastic modelling framework is developed to predict the flexural properties of high-strength sheet moulding compounds made of randomly oriented ultra-thin carbon fibre-reinforced thermoplastic prepreg tapes. The model enables reliable designs using ultra-thin randomly oriented strands with less testing, leading to potential applications in automotive primary structures. The stochastic model is based on a Monte Carlo simulation. The flexural modulus is predicted using classical laminate theory, while the flexural strength is predicted by following a Weibull distribution. Fibre discontinuities are considered through stress concentrations introduced by tape overlaps. The results are validated against new 3-point bending and previously reported 4-point bending experimental results. A scaling effect on strength and scatter is predicted, and its implications for structural applications are also discussed.

Analytical modelling is an effective approach to obtaining a gear dynamic response or vibration pattern for health monitoring and useful life prediction. Many researchers have modelled this response with various fault conditions commonly observed in gears. The outcome of such models provides a good idea about the changes in the dynamic response available between different gear health states. Hence, a catalogue of the responses is currently available, which ought to aid predictions of the health of actual gears by their vibration patterns. However, these analytical models are limited in providing solutions to useful life prediction. This may be because a majority of these models used single fault conditions for modelling and are not valid to predict the remaining life of gears undergoing more than one fault condition. Existing reviews related to gear faults and dynamic modelling can provide an overview of fault modes, methods for modelling and health prediction. However, these reviews are unable to provide the critical similarities and differences in the single-fault dynamic models to ascertain the possibility of developing models under combined fault modes. In this paper, existing analytical models of spur gears are reviewed with their associated challenges to predict the gear health state. Recommendations for establishing more realistic models are made especially in the context of modelling combined faults and their possible impact on gear dynamic response and health prediction.

Continuous monitoring of structural health is essential for the timely detection of damage and avoidance of structural failure. Guided-wave ultrasonic testing (GWUT) assesses structural damages by correlating its sensitive features with the damage parameter of interest. However, few or no studies have been performed on the detection and influence of debris-filled damage on GWUT under environmental conditions. This paper used the pitch–catch technique of GWUT, signal cross-correlation, statistical root mean square (RMS) and root mean square deviation (RMSD) to study the combined influence of varying debris-filled damage percentages and temperatures on damage detection. Through experimental result analysis, a predictive model with an R2 of about 78% and RMSE values of about 7.5×10−5 was established. When validated, the model proved effective, with a comparable relative error of less than 10%.

Our current planetary crisis moves the need for effective ecosystem restoration centerstage and compels us to explore unusual options. We here propose exploring combinatorial approaches to restoration practices: management practices are drawn at random and combined from a locally relevant pool of possible management interventions, thus creating an experimental gradient in the number of interventions. This will move the current degree of interventions to higher dimensionality, opening new opportunities for unlocking unknown synergistic effects. In this concept, regional restoration hubs play an important role as guardians of locally relevant information and sites of experimental exploration. Data collected from such studies could feed into a global database, which could be used to learn about general principles of combined restoration practices, helping to refine future experiments. Such combinatorial approaches to exploring restoration intervention options may be our best hope yet to achieve decisive progress in ecological restoration at the timescale needed to mitigate and reverse the most severe losses.

Few layers Black phosphorus (BP) and phosphorene are two-dimensional (2D) materials renowned for their adjustable bandgaps, high carrier mobility, and anisotropic conductivity, which make them highly promising for applications in the visible and infrared spectrum. The incorporation of these materials into polymer matrices has led to significant advancements in material science, resulting in nanocomposites with enhanced mechanical, electrical, and optical properties. This article provides a thorough analysis of BP/phosphorene polymer nanocomposites, including synthesis techniques (such as exfoliation methods) and manufacturing approaches. Advanced characterisation techniques are utilised to assess the structure, morphology, and properties of these composites. The article highlights the potential applications of these materials in energy storage (e.g., high-capacity batteries), flexible electronics (e.g., bendable displays), environmental sensing, and emerging biomedical fields such as targeted drug delivery. Furthermore, the article discusses potential solutions to tackle the challenges associated with the scalable, cost-effective production and ambient stability of BP/phosphorene, leveraging recent advancements in engineering research. The conclusion outlines future research directions, emphasising the importance of addressing persistent challenges through technological breakthroughs and exploring potential avenues for further advancement.

A new approach for output feedback L1 adaptive control based on a proportional adaptation law is presented. The effectiveness of this design is assessed in simulation and validated through real-time testing on an airfoil pitch control wind tunnel experimental rig. Experimental evaluation of the robustness of the controllers, assessed by introducing various disturbances into the control signals, shows that the adaptive control has a better performance compared to PID control, particularly in scenarios with reduced control effectiveness and time-varying disturbances. The experimental results demonstrate the efficacy of the proposed method in practical applications.