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Critical comparison of potential machine learning methods for lightning thermal damage assessment of composite laminates
Get PDFThe present study assesses the potential of using machine learning (ML) methods to predict the extent of lightning thermal damage in fiber-reinforced composite laminates using three supervised machine learning (SML) algorithms: (1) linear regression (LR), (2) decision tree (DT)-based, and (3) MLP models. These models were based on the 10 most significant factors that influence the severity of lightning damage, including three current waveform parameters, four material configurations, and three orthogonal electrical conductivities of each composite. All models demonstrated good performance with coefficient of determination (R2) values between 0.84 ~ 0.96. The multilayer perceptron (MLP) regression model trained with the lightning matrix damage dataset showed the most promising results (R2 > 0.94). Additional hyperparameter optimization was performed to improve the prediction performance of the baseline MLP model. The hyperparameter optimization (Adam optimizer, tanh activation function, and three hidden layers with 234 neurons) slightly improved the performance of the baseline MLP model by ~0.02, but achieved faster convergence. This result suggests that the baseline MLP model trained with the lightning matrix damage dataset is sufficiently accurate and robust. This paper highlights that ML-informed regression models can serve as an efficient first pass-estimator of lightning matrix damage in composite laminates, potentially reducing the amount of extremely time-consuming and expensive laboratory-scale lightning tests or streamlining the development of complex lightning damage models for future design.Advanced Composite Material
An empirical torsional spring model for the inclined crack in a 3D-printed acrylonitrile butadiene styrene (ABS) cantilever beam
Get PDFThis paper presents an empirical torsional spring model for the inclined crack on a 3D-printed ABS cantilever beam. The work outlined deals mainly with our previous research about an improved torsional spring model (Khan-He model), which can represent the deep vertical (90°) crack in the structure. This study used an experimental approach to investigate the relationships between the crack angle and torsional spring stiffness. ABS cantilever beams with different crack depths (1, 1.3 and 1.6 mm) and angles (30, 45, 60, 75 and 90°) were manufactured by fused deposition modelling (FDM). The impact tests were performed to obtain the dynamic response of cracked beams. The equivalent spring stiffness was calculated based on the specimen’s fundamental frequency. The results suggested that an increased crack incline angle yielded higher fundamental frequency and vibration amplitude, representing higher spring stiffness. The authors then developed an empirical spring stiffness model for inclined cracks based on the test data. These results extended the Khan-He model’s application from vertical to inclined crack prediction in FDM ABS structures.Polymer
Quantification of students’ active learning in design, build, and test engineering modules
Get PDFThe focus in this paper is to address the primary research question ‘How can instructors leverage assessment tools in design, build, and test modules to quantify students’ active learning well enough to improve modules for future students?’ In the engineering module, Product Design Group Project (PDGP), the primary goal is to enable students to internalize five principles of engineering design (POED), wherein each assignment students are tasked with writing learning statements (LS). LS captures how much students internalize the target POED and formulate an understanding of how to apply this knowledge moving forward. Each academic year in the PDGP module, at a university in north-west England, around 780 LS are consented by module students. In this paper, a flexible text mining framework is used to process LS and analyse students’ learning and improve the delivery of design, build, and test engineering modules, such as the PDGP.Developing Academic Practic
Microstructure and mechanical properties of Inconel 718 and Inconel 625 produced through the wire + arc additive manufacturing process
Get PDFScience and Technology Organization - Meeting Proceedings - Applied Vehicle TechnologyIn developing the wire + arc additive manufacturing (WAAM) process for heat and creep resistant alloys, structures were built from nickel-based superalloys Inconel 718 (IN718) and Inconel 625 (IN625). In this paper, wall structures were deposited in both superalloys, using a plasma transferred arc process. The microstructure was analysed optically and under SEM; both alloys revealed typical dendritic structure with long columnar grains, with little variation between the alloys. The findings suggest that the structures included significant segregation of alloying elements, with potential intermetallic phases e.g. Laves phases and δ-phases also found across the alloys, which showed significantly more segregation of Nb and Mo at the grain boundaries and inter-dendritic regions. The alloys also underwent room temperature mechanical testing, in addition to this IN625 specimens were tested after a solutionising and ageing treatment. Hardness measurements indicated that in general the WAAM process has the effect of increasing material hardness by approximately 10 %, when compared to wrought alloy in a solutionised state. In IN625 the heat-treated specimens showed an increase in hardness of around 6 %, when compared with its as-deposited condition. Elongation in IN625 showed much greater values. Overall, IN718 showed a greater strength with less elongation than IN625. A comparison between both alloys and their stated maximum UTS and YS values from literature revealed that WAAM built IN718 and IN625 in its as-deposited condition can achieve just over half the maximum achievable UTS, with no post-process treatment. The heat-treatment process tested in IN625 marginally reduced the gap in UTS performance by 3.5 %.NATO Workshop STO-MP-AVT-356: Research Symposium on Physics of Failure for Military Platform Critical Subsystem
Set-based design space exploration to investigate the effect of energy storage durability on the energy management strategy of a hybrid-electric aircraft
Get PDFTo investigate the key enabling technologies for hybrid-electric regional aircraft, several assumptions about the maturity and required level of technology are necessary. Within the EU-funded project FutPrint50, a decision-making framework based on Set-Based Design principles is being developed to address these uncertainties arising from operational requirements and technological feasibility levels. The methodology has been applied to study the effects of the energy storage durability and technology level on the energy management strategies of a regional hybrid-electric aircraft. Results highlight the key role of battery energy density on the durability of the battery pack and the viability of the hybrid-electric aircraft concept. Additionally, the trade-off between zero-day environmental compatibility and battery lifetime is identified alongside its causing mechanism. Optimal energy management strategies are suggested in light of this new information. Finally, statistical data of cell energy density is used to estimate the most probable year of feasibility of hybrid-electric propulsion for regional aircraft.European Union funding: 875551AIAA SciTech Forum 202
Assessing preferences for cultural ecosystem services in the English countryside using Q methodology
Get PDFCultural Ecosystem Services (CES) are difficult to assess due to the subjective and diverse way in which they are experienced. This can make it difficult to apply CES research to enhance human experience of nature. This study applies Q methodology to group people according to their preferences for CES. The Q methodology survey was carried out with 47 local residents and tourists in Wiltshire, in South West England. Four groups of respondents were identified drawing value from nature through: (1) spiritual benefits and mental well-being (Group 1—Inspired by nature); (2) nature and biodiversity conservation (Group 1—Conserving nature); (3) cultural heritage in multifunctional landscapes (Group 3—Countryside mix); and (4) opportunities for outdoor activities (Group 4—Outdoor pursuits). All four groups stated that benefits from nature were enhanced by actually visiting the countryside, through a better understanding of nature itself, and through a range of sensory experiences. They particularly identified relaxation opportunities as a very important CES benefit. These findings, and the demonstrated use of the Q methodology, could support local planning and landscape management in order to provide accessible and functional landscapes that can provide a range of different CES benefits to people.Natural Environment Research Council (NERC): NE/J014710/1
European Union fundingLan
Low-cost multi-object positioning system with optical sensor fusion
Get PDFIndoor position estimation of any moving objects with the aid of integration of multiple sensors such as optical, radio, and ultrasonic is an ongoing field of research. Although, commercial companies like VICON and OptiTrack provides the higher precision indoor positioning by using custom design optical sensors, but not every teaching or research institute can afford them because of the cost metric. To overcome this problem, an affordable low-cost solution for object tracking using multiple low-cost cameras is provided in this paper. The object tracking system introduced in this paper uses cameras to track active markers such as LEDs and estimate the coordinates of these LEDs with less than 0.15 meters of error in all the axes. The VICON camera system setup is used to opt ground truth measurements which later utilized for error estimation of the low-cost object tracking system.AIAA SciTech Forum 202
Towards a risk ranking for improved management of discharges of fats, oils, and greases (FOGs) from food outlets
Get PDFThe understanding of fats, oils, and greases (FOGs) pathways in commercial kitchens is relatively poor. In this contribution, we extend our understanding of how FOG is perceived and managed by those working within food service establishments (FSEs). A questionnaire (n = 107) exposes awareness of and experiences with FOG and characterises two important behaviours: kitchen appliance cleaning regimes and waste management practices. Findings demonstrate that awareness of issues caused by FOG in sewer networks is independent of job role or position and that a majority of respondents (74%) are acquainted with the impacts of poor FOG management. Application of a risk ranking approach revealed a low risk of emissions from waste frying oils and exposed behaviours which can serve to reduce FOG emission potential including pre-rinsing of plates and cleaning of fryers and extraction hoods. Critically, 69% of FSEs had no means of managing their FOG emissions. We conclude that sampled FSEs were generally unaware of the relative contribution of FOG sources, thereby limiting their ability to respond to the behavioural and technological options available for minimising its impact. The risk ranking developed in this paper could be used to suggest efforts to reduce and mitigate FOG emissions from FSEs.Engineering and Physical Sciences Research Council (EPSRC): EP/L15412/1.
ACO Technologies plc.; Thames Water Utilities LtdH2Open Journa
Digital twin-enabled automated anomaly detection and bottleneck identification in complex manufacturing systems using a multi-agent approach
Get PDFDigital twin (DT) models are increasingly being used to improve the performance of complex manufacturing systems. In this context, DTs automatically enabling anomaly detection, such as increase in orders, and bottleneck identification, such as shortage of products, can significantly enhance decision-making to mitigate the consequences of the identified bottlenecks. The existing literature has mainly focused on implementing top-down approaches for analysing the bottlenecks without considering the emergent behaviour of micro-level agents, including inventory levels and human resources, and their impact on the macro-level system’s performance. In order to handle the aforementioned challenges, this paper extends the current literature by proposing a novel DT integrated in a multi-agent cyber physical system (CPS) for detecting anomalies in sensor data, while identifying and removing bottlenecks that emerge during the operation of complex manufacturing systems. An extended 5 C CPS architecture, using multi-agent approach, is implemented to allow DT integration. The agent-based simulation technique enables capturing the probabilistic variability, and aggregate parallelism and dynamism of parallel dynamic interactions within the DT-CPS. A new single agent at the exo-level of the multi-level agent-based modelling structure, called the ‘monitoring agent’, is introduced in this research. The agent detects anomalies and identify bottlenecks through communicating with other agents in different levels automatically. The DT-CPS provides feedback automatically to the physical space to remove and mitigate the identified bottlenecks. The proposed DT based multi-agent CPS has been tested successfully on a real case study in a cryogenic warehouse shop-floor from the cell and gene therapy industry. The performance of the studied cryogenic warehouse is continuously measured using real-time sensor data. The analyses of the results show that the proposed DT-CPS improves the utilisation rates of human resources, on average, by 30% supporting decision making and control in complex manufacturing systems.Innovate UK: 104515.
Engineering and Physical Sciences Research Council (EPSRC): EP/R032718/1Journal of Manufacturing System
Using Inert Crystalline Materials as a Simulation for Energetic Materials
No full textResearchers are aware that different crystal structures result in different materials properties. The understanding of a materials crystal structure is significant for materials development in multiple industries, from munitions to pharmaceuticals. The energetic material, HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) is a commonly used energetic material and is found as a by-product in some manufacturing processes for RDX. HMX exists in multiple polymorphs and also exhibits a phenomenon known as crystal twinning. Experimentation of the co-crystallisation of paracetamol and seven other isomers and analogues yielded initial results that shows similar crystalline properties between paracetamol and HMX. Making paracetamol and ideal starting point for the development of the experimental techniques required to grown single crystal HMX. Eight isomers of paracetamol and 26 combinations within 3 different ratios have been identified as a starting point for looking into co-crystallisation, the process of two or more entities aggregating together in a crystal structure with no covalent bonding, with optical microscopy, Powder Xray Diffraction and Differential Scanning Calorimetry being employed as methods of analysis of the resulting crystals. Research into the co-crystallisation of paracetamol and the various isomers and polymorphs has yielded initial results that indicate that some co-crystallisation has occurred.AW