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Influence of one-dimensional material flow on mechanical properties and fiber orientation distribution of thin-ply carbon fiber reinforced thermoplastics sheet molding compounds
Get PDFThe molding flow of carbon fiber reinforced thermoplastic sheet molding compounds (CFRTP-SMC) is complex and requires a comprehensive understanding of underlying processes. This study investigates the material behavior during compression molding processes, focusing on the influence of the ratio of initial material charge area over mold area (charge ratio) on mechanical properties. The results highlight the CFRTP-SMC material's excellent flowability and moldability and confirm that the mechanical properties and internal morphology change with charge ratios. In addition, a correlation between mechanical properties and internal morphology is established through quantitative analysis of fiber orientation distributions using X-ray computed tomography. This comprehensive investigation not only sheds light on the molding ‘behavior of CFRTP-SMCs, but also underscores the importance of material charge ratios in influencing the mechanical properties. This study also provides a case study for validating numerical process models.This work was supported by Japan Science and Technology Agency's SPRING Program (JPMJSP2108). The work was also partially funded by the Royal Society (IEC\R3\213017) and Japan Society for the Promotion of Science (JPJSBP 120225702).Composites Communication
Data in support of: PTFE layer formation during brush electroplating of nickel
No full textThis research has been funded jointly by Cranfield University and SIFCO Applied Surface Concepts under an Industrial Doctorate Scheme. The authors would like to acknowledge the work of Danijela Milosevic from SIFCO ASC on the salt spray testing. J.E. thanks the Spain Ministry of Science and Innovation for financially supporting the projects TED2021 132752B-I00, and PID2021-1287270B-I00
Eco-driving control for connected plug-in hybrid electric vehicles in urban scenarios with enhanced lane change engagement
Get PDFEco-driving control techniques have shown significant potential in reducing energy consumption in urban scenarios. The presence of slow-moving vehicles typically disrupts ecological velocity planning, leading to an increase in energy consumption. To solve it, this study proposes a hierarchical eco-driving control strategy, that integrates speed optimization and lane change decision-making in urban scenarios, to not only ensure traffic efficiency, but also save the energy consumption. Firstly, a data-driven energy model is leveraged in the upper level to estimate the energy consumption of candidate lanes and generate ecological lane change decisions. Then, in the lower level, the preceding vehicles and traffic lights are considered to plan an ecological velocity profile via deep reinforcement learning algorithm after transitions to the target driving lane, thereby enhancing the fuel economy and travel efficiency. A virtual driving environment model is established to verify the proposed method through numerous simulation cases. The results indicate that the proposed method effectively reduces energy consumption while maintaining favorable travel efficiency, compared with conventional benchmarks. Furthermore, the notable improvements are observed particularly in free traffic conditions.National Natural Science Foundation of ChinaEnerg
Water extraction in aero gas turbines for contrail mitigation
Get PDFWater vapour and particles in aero engine exhaust can give rise to condensation trails (contrails) in the wake of aircrafts, and recent studies suggest that persistent contrails and contrail cirrus account for circa 50% of the total aviation-derived radiative forcing (RF). The Schmidt-Appleman criterion is widely used to qualitatively predict the formation of contrails. The criterion indicates that the formation of contrails is affected by both aero engine exhaust and ambient air conditions and can therefore provide the theoretical basis to devise contrail mitigation strategies and further allows quantitative assessment of these strategies. This work focuses on water extraction from the aircraft engine exhaust for contrail mitigation. The fuel water emission index (EIh2o) is one of the key factors that determines whether persistent contrails form or not. It indicates the amount of water produced for every kg of fuel burnt. Research has indicated that water extraction from the exhaust of the aero engine has been considered for Nitrogen oxides (NOx) reduction, but not for contrail mitigation. Assuming that water extraction is indeed possible, the emphasis of this work will therefore be on understanding how much water is needed to be extracted for contrail mitigation depending on the altitude and the relative humidity (RH), with the aim to carry out a meaningful study on the mitigation of persistent contrails and contrail cirrus to enable a fast and considerable reduction in aviation-derived RF.The Aeronautical Journa
Subjective measures on task complexity using touchscreens in flight operations
Get PDFhttps://ergonomics.org.uk/events-calendar/ehf2024.htmlThe following preliminary study uses subjective measures of situational awareness, workload, and system usability to assess the effect of touchscreen flight deck displays in simple and complex flying environments during a simulated flight task. Eighteen participants were evaluated whilst flying a simulated aircraft, conducting both simple and complex flight operations. Results showed that situational awareness improved, and perceived workload was maintained, when task complexity was increased during touchscreen interaction on the flight deck. This was likely driven by touchscreens providing increased attentional supply. This improves the flight deck human-machine interface (HMI) from a pilot-centred perspective by improving access to task-relevant information. There was no significant change in levels of touchscreen usability as flight task complexity increased, once again ratifying the use of touchscreens in assisting cognitive function in some task types. The application and limitations of these findings is discussed.Ergonomics & Human Factors 202
Formula-E multi-car race strategy development—a novel approach using reinforcement learning
Get PDFElectric motorsport such as Formula E is becoming more and more popular in recent years. Race strategy in such races can be very complex involving resource management, e.g. energy and thermal management, but more importantly multi-car interactions which could be both collaborative and competitive. Reinforcement Learning has been implemented in the literature for such electric racing strategy development but only accounts for one single car. In this paper, we proposed a new architecture iRaXL to implement reinforcement learning for such complex strategy development featuring hybrid action space, multi-car interactions, and non-zero-sum gaming. The iRaXL proves to be able to develop different strategies for individual competitors and also team-based objectives. In a bigger scope, this framework can be used to solve more generic problems with hybrid features such as zero/non-zero-sum games, discretized/continuous action space, and competition/collaboration interactions.IEEE Transactions on Intelligent Transportation System
Towards a distributed digital twin framework for predictive maintenance in Industrial Internet of Things (IIoT)
Get PDFThis study uses a wind turbine case study as a subdomain of Industrial Internet of Things (IIoT) to showcase an architecture for implementing a distributed digital twin in which all important aspects of a predictive maintenance solution in a DT use a fog computing paradigm, and the typical predictive maintenance DT is improved to offer better asset utilization and management through real-time condition monitoring, predictive analytics, and health management of selected components of wind turbines in a wind farm. Digital twin (DT) is a technology that sits at the intersection of Internet of Things, Cloud Computing, and Software Engineering to provide a suitable tool for replicating physical objects in the digital space. This can facilitate the implementation of asset management in manufacturing systems through predictive maintenance solutions leveraged by machine learning (ML). With DTs, a solution architecture can easily use data and software to implement asset management solutions such as condition monitoring and predictive maintenance using acquired sensor data from physical objects and computing capabilities in the digital space. While DT offers a good solution, it is an emerging technology that could be improved with better standards, architectural framework, and implementation methodologies. Researchers in both academia and industry have showcased DT implementations with different levels of success. However, DTs remain limited in standards and architectures that offer efficient predictive maintenance solutions with real-time sensor data and intelligent DT capabilities. An appropriate feedback mechanism is also needed to improve asset management operations.Sensor
Enabling the uptake of circular water solutions
Get PDFThis study advances the discourse on the transition from a linear to a circular water paradigm, within which water is reused and resources such as nutrients and energy can be recovered. The research provides an empirical evidence from demonstrative cases, identifying the technological, economic, socio-cultural, and regulatory factors that facilitate or impede the broader adoption of circular solutions in the water sector. It proposes an integrated system approach, which encompasses a comprehensive set of enabling instruments, including (a) the demonstration of the sustainability of circular water technologies at a system level, thereby providing a robust proof of concept; (b) a shift from a conventional financial cost-benefit approach to a business model predicated on circular value chains, underscoring the economic feasibility of these solutions; (c) the enhancement of social acceptance through active stakeholder engagement, thereby fostering a supportive community for these transformative changes; and (d) the adaptation of the regulatory framework to incentivise circular water solutions, such as the establishment of dedicated end-of-waste criteria to facilitate market access for recovered resources. The study concludes that a concerted effort is required to reconceptualise our water systems as circular systems, and to legitimise the role of circular water within our society and economy.Water Polic
Toward quieter and more efficient supersonic flight: multi-objective optimization of a Bell-Shaped Lift Distribution wing SSBJ
Get PDFThe optimization for low drag and boom of a new promising supersonic aircraft concept is presented in this paper. The Bell-Shaped Lift Distribution wing concept by Prandtl has been explored by the authors to design and optimize a supersonic business jet. This historical concept, known to be a theoretical solution for minimum induced drag wing, has been applied to redesign the SENECA E-19 Supersonic business jet wing. After having demonstrated that a bell span loading operates as intended in the supersonic regime, the configuration so designed has been optimized for low drag and boom by varying fuselage and tail design parameters. In addition, different combinations of engine positions have been also investigated within the optimization loop. The NSGA-II genetic algorithm has been chosen to carry out the multi- objective optimization. Low-to-medium fidelity numerical methods have been implemented to obtain the aerodynamic solution, while in-house multi-level of fidelity tool based on well-known methods has been used to perform sonic boom assessment. Take-off airframe noise assessment has been also performed on the final configuration resulting from optimization. The final configuration shows 6 % increase in aerodynamic efficiency and 7 % in boom with respect to the baseline.AIAA SCITECH 2024 Foru
Hybrid energy system integration and management for solar energy: a review
Get PDFThe conventional grid is increasingly integrating renewable energy sources like solar energy to lower carbon emissions and other greenhouse gases. While energy management systems support grid integration by balancing power supply with demand, they are usually either predictive or real-time and therefore unable to utilise the full array of supply and demand responses, limiting grid integration of renewable energy sources. This limitation is overcome by an integrated energy management system. This review examines various concepts related to the integrated energy management system such as the power system configurations it operates in, and the types of supply and demand side responses. These concepts and approaches are particularly relevant for power systems that rely heavily on solar energy and have constraints on energy supply and costs. Building on from there, a comprehensive overview of current research and progress regarding the development of integrated energy management system frameworks, that have both predictive and real-time energy management capabilities, is provided. The potential benefits of an energy management system that integrates solar power forecasting, demand-side management, and supply-side management are explored. Furthermore, design considerations are proposed for creating solar energy forecasting models. The findings from this review have the potential to inform ongoing studies on the design and implementation of integrated energy management system, and their effect on power systems.Energy Conversion and Management: