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Item Open Access 2D linear friction weld modelling of a Ti-6Al-4V T-joint(Technological Educational Institute of Eastern Macedonia and Thrace, 2015) Lee, Lucie Alexandra; McAndrew, Anthony; Buhr, Clement; Beamish, K. A.; Colegrove, Paul A.Most examples of linear friction weld process models have focused on joining two identically shaped workpieces. This article reports on the development of a 2D model, using the DEFORM finite element package, to investigate the joining of a rectangular Ti-6Al-4V workpiece to a plate of the same material. The work focuses on how this geometry affects the material flow, thermal fields and interface contaminant removal. The results showed that the material flow and thermal fields were not even across the two workpieces. This resulted in more material expulsion being required to remove the interface contaminants from the weld line when compared to joining two identically shaped workpieces. The model also showed that the flash curves away from the weld due to the rectangular upstand "burrowing" into the base plate.Understanding these critical relationships between the geometry and process outputs is crucial for further industrial implementation of the LFW process.Item Open Access A 4D-trajectory planning method based on hybrid optimization strategy for demand and capacity balancing(IEEE, 2021-11-15) Chen, Yutong; Xu, Yan; Hu, Minghua; Huang, Fei; Nie, QiTo effectively solve the Demand and Capacity Balancing (DCB) in future Trajectory-Based Operation (TBO) scenarios, this article first proposes a pre-tactical-and-tactical integrated Four-Dimensional Trajectory (4DT) planning framework. The framework decomposes large-scale 4DT planning into two stages, namely, the General 4DT (G4DT) planning in the pre-tactical stage and the Special 4DT (S4DT) planning in the tactical stage. A Hybrid Optimization Strategy (HOS) based planning method is designed for G4DT planning. In this method, the sequential decision architecture based on time window, heuristic strategy (greedy strategy) and optimization algorithm are combined to realize the fast trajectory planning of large-scale flights. In the optimization model based on continuous time, the nonlinear model is transformed into a linear model by constructing the flight conflict correlation matrix, which greatly improves the solving speed of the model. Real flight schedule data for French and Spanish airspace were used to verify the effectiveness and efficiency of the HOS method. This method is compared with Computer-Assisted Slot Allocation (CASA). The results show that the proposed method can effectively reduce the flight delay time and improve the flight on-time rate. Due to its fast operation speed, the proposed method has great potential to dynamically update the planning results according to the real-time air space operation status in actual operation.Item Open Access Abrupt fault detection and isolation for gas turbine components based on a 1D convolutional neural network using time series data(AIAA, 2020-08-17) Zhao, Junjie; Li, YiguangThe FDI step identifies the presence of a fault, its level, type, and possible location. Gas turbine gas-path fault detection and isolation can improve the availability and economy of gas turbine components. Data-driven FDI methods are studied in this paper. Some notable gas turbine FDI challenges include: insensitivity to operating conditions, robust separation of faults, noisy sensor readings and missing data, reliable fault detection in time-varying conditions, and the influence of performance gradual deterioration. For conventional ML methods, the problem with handling time series data is its volume and the associated computational complexity; therefore, the available information must be appropriately compressed via the transformation of high-dimensional data into a low-dimensional feature space with minimal loss of class separability. In order to improve the detection and isolation sensitivity, this paper develops a method for FDI based on CNNs. Work in this paper includes: (1) Defining the problem and assembling a dataset. (2) Preparing data for training, validation and test: data generation, feature engineering, data pre-processing, data formatting. (3) Building up the model. (4) Training and validating the model (evaluation protocol). (5) Optimizing: a. deciding the model size. b. regularizing the model by getting more training data, reducing the capacity of the network, adding weight regularization or adding dropout. c. tuning hyperparameters. (6) Evaluation.Item Open Access An accelerometer based-feedback technique for improving dynamic performance of a machine tool(European Society for Precision Engineering and Nanotechnology, 2016-06-30) Abir, Jonathan; Morantz, Paul; Longo, Stefano; Shore, PaulA novel concept for improving machine dynamic performance was developed and realised, a virtual metrology frame, for a small size CNC machine with flexible frame. Its implementation in a simplified linear motion system shows a reduction in the magnitude of the first resonance in the plant frequency response function by 12 dB. Realising the concept required developing a real -time accelerometer-based measurement technique. It shows a low sensor noise σ=30 nm with optimal phase delay of <70 μs.Item Open Access Achieving rotorcraft noise and emissions reduction for 'Clean Sky' - The measurement of success(2015-12-31) Smith, Chrissy; Pachidis, Vassilios; Castillo Pardo, Alejandro; Gires, Ezanee; Stevens, Jos; Thevenot, Laurent; d'Ippolito, RobertoThis paper describes the work done and strong interaction between Cranfield University as member of the Technology Evaluator (TE) team , Green Rotorcraft (GRC) Integrated Technology Demonstrator (ITD) and Sustainable and Green Engine (SAGE) ITD of the Clean Sky Joint Technology Initiative (JTI). The aim of Clean Sky is to develop and integrate new and innovative technologies that will hel p meeting the emission and noise reduction targets set by the Advisory Council for Aviation Research and Innovation in Europe (ACARE) for aircraft of next generation. The GRC and SAGE ITDs are responsible for developing new helicopter airframe and engine t echnologies respectively, whilst the TE has the distinctive role of assessing the environmental impact of these technologies at single flight (mission), airport and Air Transport System levels (ATS). Cranfield University as a member of the TE is responsibl e for the mission trajectory definition and for conducting the environmental performance assessments . The assessments reported herein have been performed by using a GRC - developed multi - disciplinary simulation framework called PhoeniX (Platform Hosting Oper ational and Environmental Investigations for Rotorcraft) that comprises various computational modules. These modules include a rotorcraft performance code (EUROPA), an engine performance and emissions simulation tool (GSP) and a noise prediction code (HELE NA). PhoeniX can predict the performance of a helicopter along a prescribed 4D trajectory offering a complete helicopter mission analysis. In the context of the TE assessments reported herein, three helicopter classes are examined, namely a Twin Engine Lig ht (TEL) configuration, for Emergency Medical Service (EMS) and Police missions, and a Single Engine Light (SEL) configuration for Passenger/Transport missions, and a Twin Engine Heavy (TEH) configuration for Oil & Gas missions. The different technologies assessed reflect three simulation points which are the ‘Baseline’ Year 2000 technology, ‘Reference’ Y2020 technology, without Clean Sky benefits, and finally the ‘Conceptual’, reflecting Y2020 technology with Clean Sky benefits. The results of this study i llustrate the potential that incorporated technologies possess in terms of improving performance and gas emission metrics such as fuel burn, CO2, NOx as well as the noise footprint on the ground.Item Open Access Adaptive control with neural networks-based disturbance observer for a spherical UAV(Elsevier, 2016-10-03) Matassini, T.; Shin, Hyo-Sang; Tsourdos, Antonios; Innocenti, M.This paper develops a control scheme for a Spherical Unmanned Aerial Vehicle (UAV) which can be used in complex scenarios where traditional navigation and communications systems would not succeed. The proposed scheme is based on the nonlinear control theory combined with Adaptive Neural-Networks Disturbance Observer (NN-DOB) and controls the attitude and altitude of the UAV in presence of model uncertainties and external disturbances. The NN-DOB can effectively estimate the uncertainties without the knowledge of their bounds and the control system stability is proven using Lyapunov’s stability theorems. Numerical simulation results demonstrate the validity of the proposed method on the UAV under model uncertainties and external disturbances.Item Open Access Adaptive detection tracking system for autonomous UAV maritime patrolling(IEEE, 2020-08-06) Panico, Alessandro; Zanotti Fragonara, Luca; Al-Rubaye, SabaNowadays, Unmanned Aerial Vehicles (UAVs) are considered reliable systems, suitable for several autonomous applications, especially for target detection and tracking. Although significant developments were achieved in object detection systems over the last decades using the deep learning technique known as Convolutional Neural Networks (CNN), there are still research gaps in this area. In this paper, we present a new object detection-tracking algorithm that can be used on low power consuming processing boards. In particular, we analysed a specific application scenario in which a UAV patrols coastlines and autonomously classifies different kind of marine objects. Current state of the art solutions propose centralised architectures or flying systems with human in the loop, making the whole system poorly efficient and not scalable. On the contrary, applying a Deep Learning detection system that runs on commercial Graphics Processing Units (GPUs) makes UAVs potentially more efficient than humans (especially for dull tasks like coastline patrolling) and the whole system becomes easily scalable because each UAV can fly independently and the Ground Control Station does not represent a bottleneck. To deal with this task, a database consisting of more than 115000 images was created to train and test several CNN architectures. Furthermore, an adaptive detection-tracking algorithm was introduced to make the whole system faster by optimizing the balancing between detecting new objects and tracking existing targets. The proposed solution is based on the measure of the tracking confidence and the frame similarity, by means of the Structural SIMilarity (SSIM) index, computed both globally and locally. Finally, the developed algorithms were tested on a realistic scenario by means of a UAV test-bed.Item Open Access Adaptive mesh refinement techniques for high-order finite-volume WENO schemes(European Congress on Computational Methods in Applied Sciences and Engineering, 2016-06-30) Srinivasan, Harshavardhana; Tsoutsanis, PanagiotisThis paper demonstrates the capabilities of Adaptive Mesh Refinement Techniques (AMR) on 2D hybrid unstructured meshes, for high order finite volume WENO methods. The AMR technique developed is a conformal adapting unstructured hybrid quadrilaterals and triangles (quads & tris) technique for resolving sharp flow features in accurate manner for steady-state and time dependent flow problems. In this method, the mesh can be refined or coarsened which depends on an error estimator, making decision at the parent level whilst maintaining a conformal mesh, the unstructured hybrid mesh refinement is done hierarchically.When a numerical method can work on a fixed conformal mesh this can be applied to do dynamic mesh adaptation. Two Refinement strategies have been devised both following a H-P refinement technique, which can be applied for providing better resolution to strong gradient dominated problems. The AMR algorithm has been tested on cylindrical explosion test and forward facing step problems.Item Open Access Addressing imminent impactors threat from distant retrograde orbits (DRO)(International Astronautical Federation (IAF), 2022-09-22) Martinez Mata, Alfonso; Perozzi, Ettore; Ceccaroni, MartaPlanetary Defence is gaining momentum after the launching toward the Didymos binary system of NASA DART, the first asteroid deflection mission, foreseeing also the deployment of ASI’s LICIAcube. Moreover, the ESA Hera spacecraft, which will contribute to assessing the DART impact momentum transfer, is in full realization phase. After the well established US planetary defence activities, the European Union has recently included the NEO hazard in its own Space Programme in order to extend and complement the ESA initiatives i.e. the establishment of NEO Coordination centre at ESRIN and the realization of the wide-field high-sensitivity Flyeye telescope. Both NASA and ESA also plan to improve the efficiency of their observational networks by launching space mission devoted to NEO observations from space. Finally, the ever-growing NEO discovery rate moves toward increasingly smaller objects passing close to our planet, thus posing new challenges in performing follow- up observations for determining their orbital and physical properties. Within this framework, addressing the so called ”imminent impactors” threat, posed by objects in the 10-40 m range in route of collision with the Earth (the Tunguska-class objects), has become a key issue for planetary defence. Deflection capabilities are useless if a celestial body large enough to produce significant damage can sneak up on the Earth undetected, as could asteroids hiding by the Sun, lurking in the well-known blind spot that ground-based observations can never peer into. In this respect the advantages of placing a telescope on a stable Distant Retrograde Obit (DRO) around the Earth when compared with other orbital configurations have already been proven, and they are now well established in the literature. In this work the feasibility of a mission scenario foreseeing a constellation of four spacecraft in DRO is invesitgated in detail, comparing several target orbits and different transfer strategies, including lunar swing-bys. The more efficient orbital configurations in terms of accessibility and detection capabilities are investigated and validated using case studies of historic asteroid undetected close encounters. Results prove that a DRO constellation would be able to detect and refine the trajectory of a Tunguska-size object with a warning time exceeding the requirement set for natural disasters. The possibility of contributing to the physical characterization of an imminent impactor is also discussed, which is essential for building up an efficient rapid response system for civil protection purposes.Item Open Access Addressing the challenges of implementation of high-order finite volume schemes for atmospheric dynamics of unstructured meshes(European Congress on Computational Methods in Applied Sciences and Engineering, 2016-06-30) Tsoutsanis, Panagiotis; Drikakis, DimitrisThe solution of the non-hydrostatic compressible Euler equations using Weighted Essentially Non-Oscillatory (WENO) schemes in two and three-dimensional unstructured meshes, is presented. Their key characteristics are their simplicity; accuracy; robustness; non-oscillatory properties; versatility in handling any type of grid topology; computational and parallel efficiency. Their defining characteristic is a non-linear combination of a series of high-order reconstruction polynomials arising from a series of reconstruction stencils. In the present study an explicit TVD Runge-Kutta 3rd -order method is employed due to its lower computational resources requirement compared to implicit type time advancement methods. The WENO schemes (up to 5th -order) are applied to the two dimensional and three dimensional test cases: a 2D rising.Item Open Access Advancing fault diagnosis in aircraft landing gear: an innovative two-tier machine learning approach with intelligent sensor data management(AIAA, 2024-01-04) Kadripathi, K. N.; Ignatyev, Dmitry; Tsourdos, Antonios; Perrusquía, AdolfoRevolutionizing aircraft safety, this study unveils a pioneering two-tier machine learning model specifically designed for advanced fault diagnosis in aircraft landing gear systems. Addressing the critical gap in traditional diagnostic methods, our approach deftly navigates the challenges of sensor data anomalies, ensuring robust and accurate real-time health assessments. This innovation not only promises to enhance the reliability and safety of aviation but also sets a new benchmark in the application of intelligent machine-learning solutions in high-stakes environments. Our method is adept at identifying and compensating for data anomalies caused by faulty or uncalibrated sensors, ensuring uninterrupted health assessment. The model employs a simulation-based dataset reflecting complex hydraulic failures to train robust machine learning classifiers for fault detection. The primary tier focuses on fault classification, whereas the secondary tier corrects sensor data irregularities, leveraging redundant sensor inputs to bolster diagnostic precision. Such integration markedly improves classification accuracy, with empirical evidence showing an increase from 95.88% to 98.76% post-imputation. Our findings also underscore the importance of specific sensors—particularly temperature and pump speed—in evaluating the health of landing gear, advocating for their prioritized usage in monitoring systems. This approach promises to revolutionize maintenance protocols, reduce operational costs, and significantly enhance the safety measures within the aviation industry, promoting a more resilient and data-informed safety infrastructure.Item Open Access Adversarial proximal policy optimisation for robust reinforcement learning(AIAA, 2024-01-04) Ince, Bilkan; Shin, Hyo-Sang; Tsourdos, AntoniosRobust reinforcement learning (RL) aims to develop algorithms that can effectively handle uncertainties and disturbances in the environment. Model-free methods play a crucial role in addressing these challenges by directly learning optimal policies without relying on a pre-existing model of the environment. This abstract provides an overview of model-free methods in robust RL, highlighting their key features, advantages, and recent advancements. Firstly, we discuss the fundamental concepts of RL and its challenges in uncertain environments. We then delve into model-free methods, which operate by interacting with the environment and collecting data to learn an optimal policy. These methods typically utilize value-based or policy-based approaches to estimate the optimal action-value function or the policy directly, respectively. To enhance robustness, model-free methods often incorporate techniques such as exploration-exploitation strategies, experience replay, and reward shaping. Exploration-exploitation strategies facilitate the exploration of uncertain regions of the environment, enabling the discovery of more robust policies. Experience replay helps improve sample efficiency by reusing past experiences, allowing the agent to learn from a diverse set of situations. Reward shaping techniques provide additional guidance to the RL agent, enabling it to focus on relevant features of the environment and mitigate potential uncertainties. In this paper, a robust reinforcement learning methodology is adapted utilising a novel Adversarial Proximal Policy Optimisation (A-PPO) method integrating an Adaptive KL penalty PPO. Comparison is made with DQN, DDQN and a conventional PPO algorithm.Item Open Access Aerodynamic analysis of Saab 340B aircraft with data fusion implementation(AIAA, 2024-01-04) Sahin, Kadir; Gomec, Fazil; Millidere, Murat; Whidborne, JamesThis paper conducts an aerodynamic analysis of the Saab 340B passenger aircraft, employing AVL and as numerical methods and DATCOM as a collection of engineering methods and empirical data that provide a set of aerodynamic coefficients for assessment. The investigation is focused on examining the longitudinal aerodynamic behavior of aircraft, specifically considering the impacts of flaps and elevators at varying angles of attack. The outcomes from the clean configuration are compared with the results obtained from computational fluid dynamics studies found in existing literature. While the results may not precisely match, they capture the general trends in the behavior of the aircraft. This aligns with the expected outcomes from preliminary methods like AVL and DATCOM. Data fusion techniques are strategically employed to integrate insights from these diverse sources, enhancing the overall accuracy and reliability of the aerodynamic assessment. The research aims to provide a comprehensive understanding of the clean configuration's aerodynamic performance, contributing significantly to the advancement of aviation technology.Item Open Access Aerodynamic interference for aero-engine installations(AIAA, 2016-01-02) Stankowski, Tomasz P.; MacManus, David G.; Sheaf, Christopher T.; Grech, NicholasItem Open Access Aerodynamic optimisation of civil aero-engine nacelles by dimensionality reduction and multi-fidelity techniques(Unknown, 2022-03-30) Tejero, Fernando; MacManus, David G.; Hueso Rebassa, Josep; Sanchez Moreno, Francisco; Goulos, Ioannis; Sheaf, Christopher T.Aerodynamic shape optimisation is complex due to the high dimensionality of the problem, the associated nonlinearity and its large computational cost. These three aspects have an impact on the overall time of the design process. To overcome these challenges, this paper develops a method for transonic aerodynamic design with dimensionality reduction and multi-fidelity techniques. It is used for the optimisation of an installed civil ultra-high bypass ratio aero-engine nacelle. As such, the effects of airframe-engine integration are considered during the optimisation routine. The active subspace method is applied to reduce the dimensionality of the problem from 32 to 2 design variables with a database compiled with Euler CFD calculations. In the reduced dimensional space, a co-Kriging model is built to combine Euler lower-fidelity and RANS higher-fidelity CFD evaluations. Relative to a baseline aero-engine nacelle derived from an isolated optimisation process, the proposed method yielded a non-axisymmetric nacelle configuration with an increment in net vehicle force of 0.65% of the nominal standard net thrust. This work demonstrates that the developed methodology enables the optimisation of complex aerodynamic problems.Item Open Access Aerodynamic optimization of the exhaust system of an aft-mounted boundary layer ingestion propulsor(2022-03-28) Matesanz García, Jesús; Piovesan, Tommaso; MacManus, David G.Novel aircraft propulsion configurations require a greater integration of the propulsive system with the airframe. As a consequence of the closer integration of the propulsive system, higher levels of flow distortion at the fan face are expected. This distortion will propagate through the fan and penalize the system performance. This will also modify the exhaust design requirements. Hence, the aerodynamic design of the exhaust system becomes crucial to reduce the penalties of the distortion on the system performance. This work defines a methodology for the optimization of exhaust systems for novel embedded propulsive systems. As the case study a 2D axisymmetric aft mounted annular boundary layer ingestion (BLI) propulsor is used. An automated CFD approach is applied with a parametric definition of the design space. A throughflow body force model for the fan is implemented and validated for 2D axisymmetric and 3D flows. A multi-objetive optimization based on evolutionary algorithms is used for the exhaust design. A maximum benefit of approximately 0.32% on the total aircraft required thrust was observed by the application of compact exhaust designs. Furthermore, for the embedded system, is observed that the design of the compact exhaust and the nacelle afterbody have a considerable impact on the aerodynamic performance. To the author’s knowledge, this is the first detailed optimization of an exhaust system on an annular aft-mounted BLI propulsor.Item Open Access Aerodynamic performance investigation through different chemistry modelling approaches for space re-entry vehicles using the DSMC method(Unconfirmed, 2022-04-22) Farah, Elias; Teschner, Tom-RobinHigh-speed flows with Mach numbers well above the hypersonic regime pose significant modelling com-plexities due to increased levels of thermal energy, which in turn result in a variety of chemical reactionsthat become dominant and thus have to be accurately modelled. Within Computational Fluid Dynamics(CFD), the Direct Simulation Monte Carlo (DSMC) method is commonly chosen here as it has shownsuperior performance over traditional Navier-Stokes-based solvers due to a breakdown in the continuumhypothesis. Space re-entering vehicles are commonly exposed to high Mach numbers when entering intoearth’s atmosphere and low density so that the mean free path of particles is comparable to the lengthof the vehicle itself. Thus, these types of applications require challenging modelling approaches which isthe subject of this study. We use the open-source CFD solver OpenFOAM in this study, which comesprebuilt with the dsmcFoam solver. This implementation of the DSMC method lacks, however, the abilityto model chemical reactions and thus is not equipped to predict aerodynamic coefficients for high-speedflows. Recently, the dsmcFoam+ solver has been proposed [1] and implemented into OpenFOAM whichfeatures, among other things, the ability to model chemical reactions through the Quantum-Kinetic (QK)model. The aim of this study, then, is threefold; 1) Validate the new dsmcFoam+ solver against availablereference data from the literature and compare it to the default dsmcFoam solver, highlighting the im-portance of chemical modelling, 2) Publish all simulation and setup files through an online repository tofacilitate an easy case setup for researchers wishing to evaluate or adopt the new dsmcFoam+ solver, 3)Provide documentation for the new dsmcFoam+ solver in the context of OpenFOAM where there is littledocumentation available. We investigate the flow of a re-entry vehicle with a freestream Mach number of25.6 at different angle of attacks and find that the chemical modelling approach taken has a significantinfluence over the aerodynamic coefficients which are up to 24% apart. Similar results are obtained forthe heat transfer coefficient, which shows differences of up to 28%. Based on our findings, we advocatethat the dsmcFoam+ solver should be used for aero-thermodynamic calculations as its ability to predictchemical reactions and thus changes in the flow field will significantly affect the overall solution accuracycompared to a non-reacting modelling approach.Item Open Access Aerodynamics of a compact nacelle at take-off conditions(IEEE, 2023-06-08) Swarthout, Avery E.; MacManus, David G.; Tejero, Fernando; Matesanz García, Jesús; Goulos, Ioannis; Boscagli, Luca; Sheaf, Christopher T.Next generation ultra-high bypass ratio turbofans may have larger fan diameters than the previous generation of aircraft engines. This will potentially increase the nacelle diameter and may incur penalties to the weight and drag of the powerplant. To offset these penalties, a more compact nacelle may be used. Compact nacelles may be more sensitive to boundary layer separation at the end-of-runway conditions, particularly at an off-design windmilling operating point. Additionally, the flow separation on the external cowl surface is likely to be influenced by the integration between the powerplant, pylon and airframe. The publicly available NASA high lift common research model (HL-CRM) with take-off flap and slat settings was modified to accommodate an ultra-high bypass ratio powerplant. The powerplant has an intake, separate jet exhaust, external cowl and pylon. Boundary layer separation on the external cowl of the compact powerplant is assessed at end-of-runway rated take-off and take-off windmilling scenarios. Additionally, the lift curve and Cp distributions of the high lift common research model (HL-CRM) are compared for rated take-off and take-off windmilling engine mass flows. Overall, the nacelle boundary layer separates from the nacelle highlight at windmilling conditions when the engine mass flow is relatively low. The mechanism of separation at windmilling conditions is diffusion driven and is initiated on the nacelle aft-body. The pylon has a small impact on the overall mechanism of separation. However, the wing and high-lift devices of the HL-CRM introduce local separation on the external cowl. The HL-CRM wing with the installed powerplant stalls at a similar angle (αa/c = 16°) to the HL-CRM with the through flow nacelle available in the open literature. Compared with the nominal take-off condition, the maximum lift coefficient of the HL-CRM airframe was reduced by about 2% under windmilling engine mass flows.Item Open Access Aerodynamics of aero-engine installation(AIAA, 2016-01-02) Stankowski, Tomasz P.; MacManus, David G.; Sheaf, Christopher T.; Grech, NicholasSmall internal combustion engines, particularly those ranging in power from 1 kW to 10 kW, propel many remotely piloted aircraft (RPA) platforms that play an increasingly significant role in the Department of Defense. Efficiency of these engines is low compared to conventional scale engines and thermal losses are a significant contributor to total energy loss. Existing thermal energy loss models are based on data from much larger engines. Whether these loss models scale to the engine size class of interest, however, has yet to be established. The Small Engine Research Bench (SERB) was used to measure crank angle resolved gas temperature inside the combustion chamber of a small internal combustion engine (ICE). A 55 cc, two stroke, spark-ignition ICE was selected for this study. The engine was modified for optical analysis using sapphire rods 1.6 mm in diameter on opposite sides of the combustion chamber. The engine modification was found to have no measurable impact on indicated mean effective pressure or heat rejection through the cylinder. FTIR absorption thermometry was used to collect mid-infrared absorption spectra. The FTIR was allowed to scan continuously while simultaneously recording the scanning mirror position and crank angle associated with each data point, then data was re-sorted by crank angle. Measured spectra were compared with lines generated using CDSD-4000 and HITEMP line list databases. The line of best fit corresponded to the mean gas temperature through the combustion chamber. In this way temperature was determined as a function of crank angle for three operating conditions: 4,300, 6,000, and 7,500 revolutions per minute, all at wide open throttle. High cycle-to-cycle variation in the regions of combustion and gas exchange degraded temperature measurements at the affected crank angles. Future research will attempt to improve signal to noise in these measurements.Item Open Access Aeroelastic scaling for flexible high aspect ratio wings(AIAA, 2019-12-31) Yusuf, Sezsy; Pontillo, Alessandro; Weber, Simone; Hayes, David; Lone, MudassirThis paper provides an overview of the work conducted as part of the Cranfield BEAmReduction and Dynamic Scaling (BeaRDS ) programme, which aims to develop a methodologyfor designing, manufacturing and testing of a dynamically scaled High Aspect Ratio (HAR)Wing inside Cranfield 8’x6’ wind tunnel. The aim of this paper is to develop a methodologythat adopts scaling laws to allow experimental testing of a conceptual flexible-wing planformas part of the design process. Based on the Buckinghamπtheorem, a set of scaling lawsare determined that enable the relationship between a full-scale and sub-scale model. Thedynamically sub-scaled model is manufactured as a combination of spar, skin, and addedmass representing the stiffness, aerodynamic profile, and aeroelastic behaviour respectively.The spar was manufactured as a cross-sectional shape using Aluminium material, while theskin was manufactured using PolyJet technology. Compromises due to the manufacturingprocess are outlined and lessons learned during the development of the sub-scaled model arehighlighted.