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Measuring progress in a new energy technology deployment: The case of small modular reactors
Get PDFSmall modular reactors (SMRs) are increasingly recognised as a promising solution to address the global energy trilemma of security, affordability, and sustainability. However, despite their potential, SMRs face systemic challenges that hinder their progression from conceptual designs to full commercial deployment. While existing literature identifies critical barriers individually, such as policy, regulation, financing, and supply chain development, integrated frameworks for assessing systemic progress remain scarce. This study addresses this gap by developing a novel, structured framework for evaluating the readiness of SMR deployment. Drawing on document analysis and 25 semi-structured expert interviews, a thematic analysis guided by abductive reasoning was conducted to identify the critical threshold criteria for the deployment of SMRs. A framework was then developed and operationalised across five core areas: policy support, licensing and regulatory readiness, financial viability, supply chain availability, and commercial readiness. The resulting framework offers policymakers, investors, and developers a practical tool for identifying bottlenecks, measuring systemic progress, and accelerating SMR deployment
Shifting skies: A cross-country investigation of evolution of public perception toward urban air mobility through Twitter (X) discourse
Get PDFUrban air mobility (UAM) is increasingly being recognised as a promising response to the challenges of rapid urban expansion and its negative externalities. While technological advancements in vertical take-off and landing (VTOL) aircraft have accelerated development in this space, the widespread adoption of UAM services hinges on societal acceptance driven by public perceptions. Understanding these perceptions, especially their variation across regions and over time, is critical for developing policies to maximise their adoption rate. This study leverages a large-scale and long-term Twitter dataset to discern the spatio-temporal evolution of public perceptions towards UAM. To this end, we employed a combination of machine learning (ML) and a large language model (LLM) for performing sentiment classification. Subsequently, sentiment polarities are integrated with time series analysis, indicating the prevalence of positive perception for most of the last decade, while detecting the effect of various real-world events. In terms of spatial K-means clustering results, it reveals four clusters of countries with distinct characteristics. For example, people in countries like the USA and Australia are observed to be highly opinionated towards UAM, while public discourse in Germany and India is more neutral. Finally, dynamic topic modelling coupled with an LLM-based representation uncovers underlying themes of public discourse. Topic model findings underline three major global themes: (1) industry innovation and testing, (2) unmanned aviation systems, and (3) mobility benefits. Furthermore, we identified in some cases that local themes driven by specific incidents have a more substantial effect in shaping the preferences than the generic global ones. The paper hence contributes to the literature by providing the first global-level dynamic spatio-temporal assessment of future UAM services. The insights are expected to offer valuable policy guidance for policymakers, regulators, and industry stakeholders aiming to improve the public acceptance of UAM technologies and consequently the uptake
Speeding up sequential Markov chain Monte Carlo methods in the context of large volumes of data from distributed sensor networks
No full textAdvances in digital sensors, digital data storage, and communications have resulted in systems being capable of accumulating large collections of data. In light of dealing with the challenges that large volumes of data present, this work proposes solutions to inference and filtering problems within the Bayesian framework. Two novel sequential Markov chain Monte Carlo (SMCMC) frameworks are proposed for nonlinear and non-Gaussian state space models, able to deal with large volumes of data (or observations). These are SMCMC frameworks relying on two key ideas: (1) a divide-and-conquer type approach computing local filtering distributions, each using a subset of the data, and (2) subsampling the large data and utilizing a smaller subset for filtering and inference. Simulation results highlight the large computational savings that can reach 90% by the proposed algorithms when compared with a state-of-the-art SMCMC approach
Shakedown limit analysis for heavy-haul railway tracks
Get PDFThe lower-bound shakedown theorem provides a useful framework for evaluating the long-term stability of structures subjected to cyclic loading by defining both the shakedown limit and critical depth. However, its application in freight railway engineering remains relatively limited. To overcome this gap, shakedown theory has been integrated into the design of heavy-haul railway trackbed systems, enabling assessment of substructure stability under repeated loading. The stress distributions along the longitudinal and transverse axes of the sub-ballast surface, induced by a four-axle loading pattern, were quantified and validated through Gaussian curve fitting. Additionally, a methodology based on the Mohr–Coulomb yield criterion was developed to estimate the shakedown limit of the subgrade, employing the corresponding shakedown axle load as the primary evaluation index. Parametric analyses examined the effects of three key design parameters: the internal friction angle of the sub-ballast, the elastic modulus of the engineered subgrade, and the thickness ratio between the sub-ballast and engineered subgrade. Findings consistently showed that increases in these parameters lead to higher shakedown axle loads. Among them, the internal friction angle of the sub-ballast has the most pronounced influence, whereas the thickness ratio plays a relatively minor role. For example, elevating the internal friction angle from 25° to 40° produces a significant 47.5% rise in the shakedown axle load, highlighting its pivotal contribution to enhancing the substructure's resilience against cyclic loads
Balancing comfort and efficiency: Optimal deceleration rates at crosswalks and intersections in automated driving
Get PDFUnderstanding passenger comfort in automated vehicles (AVs) is critical for advancing highly automated driving systems. This test track study was conducted with 41 participants who are accustomed to European driving norms. It examined how deceleration rates and environmental factors influence passenger perceptions in two scenarios: crosswalks and blind intersections. The participants were driven by a real AV, which braked using deceleration rates of −1.5 m/s2, −2.5 m/s2, and −3.5 m/s2. Additionally, the visibility time of an approaching pedestrian was manipulated in the crosswalk scenario, while the presence or absence of an approaching vehicle was varied in the intersection scenario. The results show that passengers generally prefer lower to medium deceleration (−1.5 m/s2, −2.5 m/s2) rates but accept higher rates (−3.5 m/s2) when a pedestrian becomes visible more unexpectedly. In the intersection scenario, comfort ratings were less influenced by the presence of an approaching vehicle than by the deceleration rate, with lower and medium deceleration rates being favoured. These findings are valuable for the development of AVs. The study suggests that tailoring AV deceleration to specific traffic scenarios can improve passenger comfort. It can help AV developers to define driving styles that passengers perceive as comfortable and safe, without compromising efficiency
The impact of N-back-induced mental workload and time budget on takeover performance
Get PDFMental Workload (MWL) refers to the specification of information processing capacity used for maintaining task performance. Some studies find no effects of high MWL on the timing and quality of takeovers, whilst others have found increases in crash risk and delayed response times. The effect of time budget – the time between event onset and an impending crash − is much clearer; drivers react faster when time budgets are smaller. However, no study has investigated whether the effects of a pure MWL interact with the effects of time budget during critical takeovers from a hands-off Level 2 (L2) driving system. A Bayesian multilevel modelling approach was used to quantify the direction, size, and uncertainty of the effects that MWL and time budget have on driver performance. Drivers (N = 37) used a hands-off L2 driving system: once while completing a pure MWL task (2-back) and another while monitoring the road. Rear-end conflicts were generated via lead vehicles decelerating with short (TTC = 3 s) or long (TTC = 5 s) time budgets. 2-back-induced MWL had no consistent or substantial impact on the timing or quality of takeovers. Conversely, drivers were faster to respond but more erratic in their post-takeover lateral control following events with smaller time budgets. We discuss the reasons for the absence of effects from the 2-back-induced MWL on takeover performance. One suggestion is that rear-end scenarios elicit automatised behaviours that do not rely upon cognitive control and thus remained unaffected by MWL. Conversely, scenarios that require cognitive control (e.g., lane change manoeuvres or hazard perception tasks) may be more susceptible to the detrimental effects of MWL during transitions of control
A Self-Levelling railway sleeper concept and its large-scale testing
Get PDFRailway track transition zones present engineering challenges due to their abrupt change in stiffness between structural elements such as embankments, bridges and tunnels affecting track geometry parameters. Although a variety of stiffness-based remedial measures have been widely applied, their implementation can be constrained by high capital cost, operational disruption, and the complexities associated with modifying the substructure. As a result, interventions in practice commonly focus on controlling permanent deformations and differential settlement, particularly related to the development of hanging sleepers. Thus, this study investigates the use of modular self-levelling sleepers (SLS) as a solution. To do so, two concept SLS systems are designed and developed: one employing a granular mechanism (SLS-G), and the other based on a horizontally acting wedge mechanism (SLS-HW). Both variants use the polymeric sleepers and are designed for compatibility with conventional ballasted track systems. Experimental laboratory testing is undertaken, and it is found that the SLS prototypes were able to restore the sleeper-ballast contact for voids up to 40 mm depth, while stress measurements at the interface indicated improved load distribution under the rails. The findings support the proof-of-concept that self-levelling sleepers have the potential to be a modular, low-disruption solution for mitigating track geometry degradation and reducing maintenance requirements at transition zones
New models of implantation: towards a whole better than the sum of parts
Get PDFRecent advances in the development of stem-cell-based embryo models and endometrial assembloids have fuelled understanding of their respective biology. However, a faithful combined approach is required to truly advance our understanding of implantation processes. This mini-review considers the most recent developments in producing reliable in vitro models of the human endometrium and human embryo, and the next steps required to combine their respective potential. While the fundamental biology of implantation is the primary driver of in vitro model development, the combined effort of embryo and endometrial models to generate new models of implantation provides the opportunity to manipulate either compartment to further understand the aetiologies of reproductive dysfunction. Through combining both systems, their efforts are symbiotic, each extending the relevance and utility of their counterpart to generate a whole greater than the sum of its parts
Collaborating With Early Career Researchers to Enhance the Future of Scholarly Publication:A Guide for Publishers
Get PDFThe scholarly publishing system is adapting to many changes, including open access and open data mandates, artificial intelligence, and other new technologies. Members of the research and publishing communities are working to establish a more equitable, fair, and rigorous system that serves researchers' evolving needs. Early career researchers (ECRs) are drivers of change, and publishers may wonder why and how they should involve ECRs in shaping the future of scholarly publishing. We held a virtual unconference to explore this issue with publishers and ECRs who were working to improve publishing. Some participants sought to improve peer reviewer or editor performance, whereas others sought to improve the publishing system itself through iterative or transformative change. Strategies for collaborating with ECRs to shape the future of scholarly publishing included peer review programmes, editorial programmes, ECR-led journals, ECR boards and committee representatives, and other ECR-initiated activities. ECRs particularly wanted to see three things improved: (1) Sharing research outputs other than publications, (2) addressing technological limitations to create systems that meet the research community's needs and facilitate knowledge advancement, and (3) fostering diversity, equity, inclusion, and accessibility. We offer tips for publishers on how to collaborate with ECRs to enhance scholarly publishing, appeal to and learn from younger researchers, and better meet researchers' needs
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