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Item Open Access A Benchtop Flight Control Demonstrator - Data and Code(Cranfield University, 2019-09-10 09:28) Duran, Joris; Whidborne, James; Pontillo, Alessandro; alejandro Carrizales rodriguez, MartinCodes and data for "A benchtop flight control demonstrator" J R Duran, J F Whidborne, M Carrizales Rodriguez, A Pontillo International Journal of Mechanical Engineering Education Published online July 27, 2019 doi: 10.1177/0306419019852688CodesFlight-Desk-Control-Demonstrator-master.zip - GUI on a computer programmed in JAVA - PID Controller for ArduinoExperimental Results- Test open loop.xls- Test P.xls- Test PID.xlsFluent CFD Fileswindtunnel.casWindtunnel.jouWindtunnel_refine.meshdatJavaFoil filescriptJaveFoilMicrosoft Excel Windtunnel design worksheetWind Tunnel Design V2.xlsmCATIA CAD filesCAD-CATIA.zipMSc DissertationDuran JR. Flight Desk Control Demonstrator. MSc dissertation, Cranfield University, Bedfordshire, U.K., 2018. Available at: http://dspace.lib.cranfield.ac.uk/handle/1826/14154Item Open Access 'A Holistic Cabin Conceptualisation Approach (HCCA) framework'(Cranfield University, 2023-11-01 09:50) Kirensky, Roman; Lawson, Craig; Orson, BenThe presented toolset defines the stakeholders involved in aircraft passenger cabin interior development projects, and their pursued design drivers. - Stakeholder Definition sheet presents all types of organisations involved in the design of aircraft cabin interiors, disregarding of the involvement extent. - Stakeholder Analysis sheet contains the pairwise comparison matrices for all stakeholders along the influence and interest axes, and the resulting plot. - Cabin Design Drivers sheet contains the definition of drivers pursued by the cabin interior projects. These are defined as a multi-level structure including: -- Top-level profitability-based design drivers, -- Their constituent factors representing the design considerations and themes, and -- Bottom-level design criteria representing the detailed product specifications, requirements, features, qualities, performance targets etc. - Design Factor Weights present a set of pairwise comparison matrices for deriving the relative importance weights at the factor and driver levels. - R Input sheet contains R code template to use with R Studio software to retrieve Eigenvector values. - Design Factors Map sheet contains factor applicability mapping to represent stakeholder concern and interaction points on a cabin interior project. - Cabin Product Breakdown sheet presents the composition of state-of-the-art cabin interiors by listing out the components it may have. The presented list is an all-encompassing version and does not represent the product line of any specific cabin manufacturer or equipment supplier. The presented sheets may be used as information source, or be amended to reflect the needs of their specific project. Amendments may be performed in the white cells of the pairwise comparison matrices on Stakeholder Analysis and Design Factor Weights; and applicability indicators in Design Factors Map and Cabin Product Breakdown sheets.Item Open Access A tutorial on the Loewner-based system identification and structural health monitoring approach for mechanical systems.(Cranfield University, 2023-04-19 09:14) Dessena, GabrieleThe tutorial should be considered complementary material for the article "A Loewner-based system identification and structural health monitoring approach for mechanical systems" (DOI: 10.1155/2023/1891062). The tutorial illustrates, via a simple example, the capability of the Loewner Framework for System Identification and Structural Health Monitoring. The second goal of this tutorial is to make available a Loewner Framework program for MATLAB to the public based on the published work. Please cite [1-5] when using this software for your work or research, Thank you. This tutorial is linked to the following article: G. Dessena, M. Civera, L. Zanotti Fragonara, D. I. Ignatyev, J. F. Whidborne, A Loewner-based system identification and structural health monitoring approach for mechanical systems, Structural Control and Health Monitoring, Vol. 2023 (2023). (DOI: 10.1155/2023/1891062) The repository entry contains five files: 1. data_9dof.mat: the data for the tutorial model; 2. LF_id.m: the script for the LF-based System Identification; 3. loewner.m: the Loewner Matrix function; 4. LF_tutorial.mlx: the LF tutorial in MATLAB live mode 5. LF_tutorial.pdf: the LF tutorial in pdf. The program was created in MATLAB 2020a, compatibility with earlier or later versions is not guaranteed. References [1] G. Dessena, M. Civera, L. Zanotti Fragonara, D. I. Ignatyev, J. F. Whidborne, A Loewner-based system identification and structural health monitoring approach for mechanical systems, Structural Control and Health Monitoring, Vol. 2023 (2023). (DOI: 10.1155/2023/1891062) [2] G. Dessena, A Loewner-based system identification and structural health monitoring approach for mechanical systems, CORD repository (2021) (DOI: 10.17862/cranfield.rd.16636279) [3] A. J. Mayo, A. C. Antoulas, A framework for the solution of the generalized realization problem, Linear Algebra and its Applications 425, pp. 634–662 (2007). (DOI:10.1016/j.laa.2007.03.008) [4] S. Lefteriu, A. C. Antoulas, A New Approach to Modeling Multiport Systems From Frequency-Domain Data, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Vol. 29, No. 1, pp. 14–27 (2010). (DOI: 10.1109/TCAD.2009.2034500) [5] S. Lefteriu, A. C. Ionita, A. C. Antoulas, Modeling Systems Based on Noisy Frequency and Time Domain Measurements, Lecture Notes in Control and Information Sciences, vol. 398/2010, 365-368 (2010). (DOI: 10.1007/978-3-540-93918-4_33)Item Open Access Air jet flow control on pitching aerofoils(Cranfield University, 2019-07-08 09:09) Prince, Simon; Green, Richard; Khodaglian, VahikExperimental data on the effect of steady and pulsed air jet vortex generator blowing on a RAE9645 aerofoil section in dynamic stall.Item Open Access Airport Operation Frequency Analysis(Cranfield University, 2023-08-21 09:28) Hin Pang, ChiThis spreadsheet is the airport operation frequency analysis performed using data from EuroControl Onesky.Item Open Access Assessment of Turbulence Models for Transonic / Supersonic Smooth Surface Separation(Cranfield University, 2021-06-21 13:14) Prince, Simon; González caballero, Roberto; Di Pasquale, DavideA systematic comparison of the principle modern turbulence prediction methods for the solution of the Navier-Stokes equations for the calculation of high speed flows about slender forebodies at low to moderate angle of attack is presented. This class of flow involves smooth surface turbulent boundary layer separation resulting in steady symmetric leeside vortices, and also the formation of embedded shock waves from the displacement effect of the large vortices in supersonic flow. As such this flow is both complex and highly sensitive to the state of the boundary layers on the body. This study revealed that the method which most consistently provides accurate predictions of the overall forces and moments on the body, the most accurate distribution of surface pressure and can most accurately resolve the flow features, including leeside vortices and embedded shock wave features, is the Solution Adaptive Simulation method. Detached Eddy Simulation and the Reynold Stress Model, which would be expected to provide superior accuracy over the RANS based linear eddy viscosity models, on the whole, failed to provide better predictions. In fact, the k-omega Realizable and k-omega SST turbulence models provided data which was almost as consistently accurate as the Solution Adaptive Simulation method. The standard k-omega turbulence model appears to be completely unsuitable for the computation of this class of high speed flow problem, and this may be associated with the poor initial / default prescription of the value of omega at the far-field boundary.Item Open Access ASTRA_TOOLBOXES(Cranfield University, 2023-01-03 15:27) Andrea, BellomeASTRA_TOOLBOXES Author: Andrea Bellome Supervisors: Joan-Pau Sánchez Cuartielles, Leonard Felicetti, Stephen Kemble This project contains the following toolboxes: - AUTOMATE: AUTOmatic Multiple-gravity Assist with Tisserand Exploration - ASTRA: Automatic Swing-By TRAjectories - DYNAMIS: DYnamic programming for Asteroid MISsions Each toolbox comes with its own sub-folder. In each sub-folder, main .m scripts are included that represent test cases to use the toolboxes. Each script should be self-explanatory and easy to use. These are described briefly here. 1) st1_AUTOMATE This folder contains AUTOMATE toolbox. This is usefult to construct MGA sequences based upon Tisserand criterion. Both Solar System planets, Jovian and Saturn moons are available. In the case of moons' tour, single-objective dynamic programming (SODP) is used to find the optimal path. 2) st2_ASTRA This folder contains ASTRA toolbox. This can be used to optimize MGA sequences using either single-objective or multi-objective dynamic programming (SODP and MODP, respectively). 3) st3_DYNAMIS This folder contains DYNAMIS toolbox. This is useful to optimize MGA trajectory options that pass-by many asteroids using dynamic programming. Both single-objective and multi-objective dynamic programming are available (SODP and MODP, respectively).Item Open Access Astronaut Playscapes - Table Football in space - a crazy idea … or a sensible contribution to keeping astronauts functioning in complex space systems?(Cranfield University, 2021-11-23 18:26) Cullen, David; Goument, LauraPoster summarising the status of the Astronaut Playscapes concept as of November 2021Item Open Access Blended wing body design and analysis(Cranfield University, 2024-05-23 12:45) Chan, Joseph; Sun, Yicheng; Smith, HowardData collected from different simulations and analyses calculated using GENUSItem Open Access British Airways Analysed Flight Data(Cranfield University, 2023-08-21 09:26) Hin Pang, ChiThese files are generated by the Analysis Python Program. They contain information for calculating taxi energy in each flight file.Item Open Access British Airways Analysis Output Files(Cranfield University, 2023-08-21 09:26) Hin Pang, ChiThese files are the CSV and word files generated by the "Taxi Time and Energy Analysis Python Program" automatically. It concludes the taxi time and taxi energy found by the program under different models of aircraft.Item Open Access British Airways File Lists(Cranfield University, 2023-08-21 09:25) Hin Pang, ChiThese files are the inputs of files to the "Taxi Time and Energy Analysis Python Program". They should be filled in by users with the flight data that needs to be analysed and be placed in the same folder as the Python Program. The particular column of "File Name" should contain the exact file name of flight data csv file. Otherwise, the "Taxi Time and Energy Analysis Python Program" would not be able to locate the flight file and perform analysis.Item Open Access British Airways Plots(Cranfield University, 2023-08-21 09:28) Hin Pang, ChiThese plots are generated by the Plot Python Program by users. They include important findings from the research project.Item Open Access British Airways Raw Flight Data(Cranfield University, 2023-08-21 09:26) Hin Pang, ChiThese files are extracted from FlightRadar24 which contains information to be extracted with the Analysis Python Program. They should be placed in the same folder as the Python Program to ensure the analysis can be done. Please do not share the files without having consent from FlightRadar24.Item Open Access Case studies for alternative fuels in different aircraft configurations(Cranfield University, 2024-05-24 13:09) Chan, Joseph; Sun, Yicheng; Howard,PeterResults of three case studies for different aircraft configurations, tube-and-wing, high aspect ratio wing and blended wing body, using different alternative fuels, kerosene based jet fuel, biofuel, ammonia, liquefied natural gas and liquid hydrogen.Item Open Access Civil Transport Aircraft Evolvability Data(Cranfield University, 2018-10-15 13:44) Van Heerden, Stevan; Guenov, Marin; Molina-Cristobal, ArturoThis is an appendix to the paper `Evolvability and Design Reuse in Civil Jet Transport Aircraft', by A.S.J. van Heerden, Marin D. Guenov, and Arturo Molina-Cristobal. It contains data that was used to create the plots and figures in Sections 6, 7, and 8 of the paper.Item Open Access Code and data supporting 'A Comprehensive Analysis of Machine Learning and Deep Learning Models for Identifying Pilots' Mental States from Imbalanced Physiological Data'(Cranfield University, 2023-09-18 16:40) Alreshidi, Ibrahim; Moulitsas, Irene; Jenkins, Karl; Yadav, SatendraData: This folder contains: - A dataset called combined_df4, which contains the power spectral density features after employing SMOTE. - A dataset called combined_df5, which contains the power spectral density features after employing SMOTE and cosine similarity. Source code: This folder contains: - A jupyter notebook called AdaBoost.ipynb which was used to generate the results for the AdaBoost algorithm. - A jupyter notebook called CNN.ipynb which was used to generate the results for the CNN algorithm. - A jupyter notebook called CNN+LSTM.ipynb which was used to generate the results for the CNN+LSTMalgorithm. - A jupyter notebook called LSTM.ipynb which was used to generate the results for the LSTMalgorithm. - A jupyter notebook called FNN.ipynb which was used to generate the results for the FNN algorithm. - A jupyter notebook called Random_Forest.ipynb which was used to generate the results for the Random Forest algorithm. - A jupyter notebook called XGBoost.ipynb which was used to generate the results for the XGBoost algorithm.Item Open Access Code and Data: Multimodal Approach for Pilot Mental State Detection Based on EEG(Cranfield University, 2023-08-23 15:04) Alreshidi, Ibrahim; Moulitsas, Irene; Jenkins, KarlData: This folder contains: A dataset called Crews_equalized_dataset_epo.fif which was used to obtain the results presented in the journal paper. It is the preprocessed EEG dataset used to predict four mental states, Channelised Attention, Diverted Attention, Startle/Surprise, and Baseline. A dataset called Example_raw.fif which was used to obtain Figure 6 of the journal paper. Source code: This folder contains a jupyter notebook called python_code.ipynb which implements the proposed EEG preprocessing pipeline and all the algorithms presented and validated in the journal paper. Output: This folder contains: A figure called Confusion Matrices.jpg which shows results from the Random Forest classifier in (A), Extremely Randomized Trees in (B), Gradient Tree Boosting in (C), AdaBoost in (D), and Voting in (E). Figures called Figure 6A.jpg and Figure 6B.jpg which show the EEG signals before applying the preprocessing pipeline, and after applying the preprocessing pipeline, respectively. A text file called ML models evaluation.txt which contains the results produced by all algorithms presented and validated in the journal paper. A figure called The preprocessed EEG signals.jpg which shows the EEG signals, upon completion of our preprocessing pipeline, fed into the machine learning models for training and testing purposes.Item Open Access CODE_MRF.zip(Cranfield University, 2023-10-11 09:00) Silva, Paulo; Tsoutsanis, Panagiotissource codeItem Open Access Conceptual and preliminary design methods for use on conventional and blended wing body airliners(Cranfield University, 2019-02-19 11:40) Smith, Howard; Fielding, JohnTranscript of John Fielding and Howard Smith's 1999 lecture to Court, Cranfield University.