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A post-deposition in situ passivation strategy using a multi-functional molecular agent is reported with enhanced colloidal dispersibility of an environmentally-friendly AgBiS2 nanocrystal ink, achieving a PCE over 10% in a solar cell.

This paper assesses the capacity of Whitehouse, Jamaica to adapt to climate change. A community-based vulnerability assessment was conducted that employed semi-structured interviews with community members within or related to the tourism, fisheries and agricultural sectors. The results were analysed using the Local Adaptive Capacity (LAC) framework, which characterises adaptive capacity based on five elements: asset base; institutions and entitlements; knowledge and information; innovation; and flexible forward-looking decision-making and governance. This paper contributes to the literature in three ways. First, it argues that many elements of the LAC framework correspond with an evolutionary perspective on adaptive capacity. Second, it offers an in-depth case study of the capacity of Whitehouse to adapt to climate change. Third, it offers a critical assessment of whether the LAC framework fully captures the important elements of adaptive capacity.

This paper presents the application of a probabilistic multi-stability assessment of a modified two-area system under the presence of low and high uncertainty sources. The stability of the network is assessed under four stability regimes: frequency, small-signal rotor angle, large-signal rotor angle, and long-term voltage. The probabilistic assessment is carried out using Monte Carlo simulation. Two cases considering low and high uncertainty are investigated. The obtained results are presented in the form of parallel coordinate plots so that the interaction between multiple stability regimes can be more easily understood. It is observed that the poor response of small-signal rotor angle stability generally corresponds to poor response of other stability types in low uncertainty case. However, once the level of uncertainty increases and more sources of uncertainty exist, this relationship is significantly changed.

Three modules are integrated into the built-in OpenFOAM rhoCentralFoam solver towards accurate and efficient modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures within the OpenFOAM 10.0 framework. The first module is the mixture-averaged diffusion model. The second module is the built-in OpenFOAM Lagrangian solver coupled with optimised droplet drag coefficient and convective heat transfer coefficient sub-models. The last module is a sparse stiff chemistry solver based on dynamic adaptive hybrid integration (AHI-S). The optimised droplet sub-models are first verified in correct implementation for subsequent simulations in this work. They show good accuracy against experimental and analytical data in the modelling of ammonia droplet acceleration and cooling in the flowing and/or low-temperature air. The accuracy and efficiency gains related to the mixture-averaged diffusion model and the AHI-S chemistry solver are examined by simulating 1-D detonation propagation in ammonia droplet-free/laden ammonia-oxygen mixtures. Numerical results of detonation propagation speed, gaseous temperature, density, and species distributions around the induction zone show good agreement with experimental data and analytical solutions. Compared to the built-in OpenFOAM diffusion model, the mixture-averaged diffusion model provides different numerical predictions of pulsating instabilities in detonation propagation. It shows better accuracy in depicting the detonation structure within the droplet-free section attributed to improved multi-component diffusion modelling. Compared to the built-in OpenFOAM solver EulerImplicit (backward Euler), the AHI-S chemistry solver reduces the computational cost by around 50%. It achieves satisfactory accuracy in calculating detonation propagation speed within the droplet-free section with the optimal efficiency when the safety factor, β, equals 0.5.

The aim of this study is to define strategies to increase green nuclear energy investments. Within this context, a model is suggested that includes two different stages. Firstly, the consensus-based fuzzy preferences are determined for these investments. For this purpose, four different TRIZ-based strategies are identified, which have an influence on the effectiveness of these projects. Furthermore, in the second stage, the significance weights of these strategies are calculated by considering the spherical fuzzy DEMATEL approach. The findings indicate that dynamicity is the most appropriate TRIZ strategy for the effectiveness of green nuclear energy investments. In addition, the prior action is another significant strategy that should also be considered in these projects. It is obvious that sufficient technological infrastructure is very important for the performance of green nuclear power plants and there is a rapid development of this technology. Because of this situation, these nuclear power plants should be designed effectively so that they can be adoptable to any changes in the technology. In this scope, qualified personnel should be employed, and communication between departments should be effective and of high quality. With the help of these issues, technological changes can be adopted more easily.

Digitalization trends in building management increasingly emphasize the creation of Digital Twins (DTs) for building management but often neglect how occupants interact with these technologies. This paper aims to explore the functionalities of building management systems based on occupant interactions with DTs. To achieve this, occupant preferences are investigated through a questionnaire survey conducted with 106 respondents from two case studies. The survey investigated participants’ interest in using DTs for various building management tasks, their familiarity with DTs and their demographic factors. Analysis results revealed that occupant’s interest in DTs is not significantly influenced by their prior knowledge or gender. Instead, providing access to DTs increased their interest in areas beyond their job roles, particularly in aspects related to comfort and environmental management. Younger participants showed a heightened interest in using DTs for environmental and energy management issues. The study also suggests that promoting occupant interaction with DTs can enhance productivity and satisfaction. This paper underscores the need for additional research to integrate smart technologies into building management with a focus on occupant involvement. It highlights the potential of DTs to improve real-time monitoring and support sustainability initiatives and thus, offers a more inclusive and effective alternative to traditional management tools. This work was supported by the Association Nationale de la Recherche et de la Technologie (ANRT) under the Grant CIFRE 2017/1782. Peer Reviewed

AbstractThis study investigates the potential recognition and engagement of the natural environment as an important factor in strategic investment decisions by accommodation suppliers in a small island context. The investigation, based on empirical data from two Thai islands, Koh Tao and Koh Phi Phi, contributes to the debate if the environment, by focusing on climate change, can be identified as a primary stakeholder for accommodation suppliers. The findings show that strategic investment decisions are influenced by impacts commonly associated with climate change, although a conscious recognition of climate change as a strategic stakeholder or important factor in strategic investment decisions could not be confirmed. Conversely, the element of unconsciousness in the process of recognising climate change in investment decisions sparks questions regarding the degree to which the recognition of business stakeholders requires being a conscious process and if the focus on investments could be another element for stakeholder identification frameworks for businesses.

Threats to engine integrity and life from deposition of environmental particulates that can reach the turbine cooling systems (i.e. <10 micron) have become increasing important within the aero-engine industry, with an increase of flight paths crossing sandy, tropical storm-infested, or polluted airspaces. This has led to studies in the turbomachinery community investigating environmental particulate deposition, largely applying the Discrete Random Walk (DRW) model in CFD simulations of air paths. However, this model was conceived to model droplet dispersion in bulk flow regimes, and therefore has fundamental limitations for deposition studies. One significant limitation is an insensitivity to particle size in the turbulent deposition size regime, where deposition is strongly linked to particle size. This is highlighted within this study through comparisons to published experimental data. Progress made within the wider particulate deposition community has recently led to the development and application of the Continuous Random Walk (CRW) model. This new model provides significantly improved predictions of particle deposition seen experimentally in comparison to the DRW for low temperature pipe flow experiments. However, the CRW model is not without its difficulties. This paper highlights the sensitivities within the CRW model and actions taken to alleviate them where possible. For validation of the model at gas turbine conditions, it should be assessed at engine-representative conditions. These include high-temperature and swirling flows, with thermophoretic and wall-roughness effects. Thermophoresis is a particle force experienced in the negative direction of the temperature gradient, and can strongly effect deposition efficiency from certain flows. Previous validation of the model has centred on low temperatures and pipe flow conditions. Presented here is the validation process which is currently being undertaken to assess the model at gas turbine-relevant conditions. Discussion centres on the underlying principles of the model, how to apply this model appropriately to gas turbine flows and initial assessment for flows seen in secondary air systems. Verification of model assumptions is undertaken, including demonstrating that the effect of boundary layer modelling of anisotropic turbulence is shown to be Reynolds-independent. The integration time step for numerical solution of the non-dimensional Langevin equation is redefined, showing improvement against existing definitions for the available low temperature pipe flow data. The grid dependence of particle deposition in numerical simulations is presented and shown to be more significant for particle conditions in the diffusional deposition regime. Finally, the model is applied to an engine-representative geometry to demonstrate the improvement in sensitivity to particle size that the CRW offers over the DRW for wall-bounded flows.