Data Management Plan for Project "Steady-State Off-Design Performance of a Double Spool Turbofan Engine Using SIMULINK"

Data management plan (DMP) Steady-State Off-Design Performance of a Double Spool Turbofan Engine Using SIMULINK ICFD12-EG-5044 2 ICFD12-EG-5044 DMP version 2.0 Version Effective date Description of document/changes 1.0 08/11/2025 First version of the DMP – created for the start of the project 2.0 21/11/2025 Update the contributors, Storage and backup Level of distribution This DMP is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). It is publicly available under 10.5281/zenodo.17703176 ICFD12-EG-5044 DMP version 2.0 3 Project details Project Coordinator Principal Investigator Bassam Elsayed Saleh Abrisha, [email protected], TU Wien, ROR: ror.org/04d836q62, Principal Investigator Contact person (responsible for data management and DMP) Bassam Elsayed Saleh Abrisha, [email protected], TU Wien, ROR: ror.org/04d836q62 Contributors Ahmed Farouk AbdelGawad, ORCID: 0000-0002-2480-8229, Zagazig University, Supervisor Mohammed Gobran, ORCID: 0000-0003-2320-1449, Cairo University Faculty of Engineering, Supervisor Start date 2014-10-31 End date 2017-12-31 Funder Not Applicable Funding programme, grant number Not Applicable Internal project number Not Applicable List of acronyms DMP data management plan RDM research data management NASA National Aeronautics And Space Administration … … … … … … … … … … 4 ICFD12-EG-5044 DMP version 2.0 Content INHALTSVERZEICHNIS INTRODUCTION 5 Science Europe practical guide, FAIR data 5 Relevant Policies and Guidelines 5 1. DATA DESCRIPTION 6 1a Lists of datasets that will be reused or produced 6 1b Data generation and reuse 6 2. DOCUMENTATION AND DATA QUALITY 7 2a Data organisation, metadata and documentation 7 2b Data quality control 7 3. STORAGE AND BACKUP DURING RESEARCH PROCESS 8 3a Storage and backup facilities 8 3b Data security and protection of sensitive data 8 4. LEGAL AND ETHICAL REQUIREMENTS 8 4a Personal data 8 4b Intellectual property rights and ownership 8 4c Ethical issues 8 5. DATA SHARING AND LONG-TERM PRESERVATION 9 5a Data publication and access conditions 9 5b Long-term preservation and deletion of data 9 6. RDM RESPONSIBILITIES AND RESOURCES 10 6a RDM-roles and responsibilities 10 6b Resources 10 ICFD12-EG-5044 DMP version 2.0 5 Introduction Science Europe practical guide, FAIR data A DMP is a structured document that keeps record of what research data is created and what happens to that data during and after a project. It helps with planning the research process and defining responsibilities in a research project involving several researchers or institutions. For writing this DMP, we followed the recommendations of Science Europe as they reflect the guidelines agreed upon by the major funders in Europe. To make our data FAIR, they generally will be treated according to the following criteria:  We will make our data findable, by uploading it to a data repository that provides a persistent identifier and adding relevant metadata.  We will make our data accessible by providing open access to data, wherever possible. In cases, where open access is not possible, we will provide meaningful metadata plus contact information for access requests.  We will make our data interoperable by providing and describing data in a way that is common within our domain by using the same file formats, schemas and vocabularies. We will provide good documentation for all our datasets.  We will make our data reusable by adding metadata and comprehensive Readme files to all published datasets. The descriptions include details on the methodology used, analytical and procedural information. In case of publication, licenses for code and data will always be assigned and clearly marked. Relevant Policies and Guidelines  European Commission’s document on Ethics and Data Protection: https://ec.europa.eu/info/funding-tenders/opportunities/docs/20212027/horizon/guidance/ethics-and-data-protection_he_en.pdf 6 ICFD12-EG-5044 DMP version 2.0 1. Data description 1a Lists of datasets that will be reused or produced Produced datasets dataset ID title type format estimated volume contains sensitive data P1 Experiment Results Data Structured text csv 100 - 1000 MB no Description for "Experiment Results Data": After conducting the experiment according to the software capability, the experiment results are exported in two configurations, the first which is this data set are the results tables for variation of fan and compressor parameters like pressure ratio and efficiency with the specific thrust or specific fuel consumption. The second configuration is plotting these data as figures and plots. Reused datasets dataset ID title source rights (e.g. license) contains sensitive data R1 Fan and compressor maps NASA TN-D-6653 no R2 International Standard Atmosphere ISA MATLAB/SIMULINK software under license of Mathworks no Description for "Fan and compressor maps": 1st Data set extracted from NASA repository (NASA TN -D-6553) by Laurence H. Fishbach and Robert W, Koenig “A Program for calculating design and off design performance of two and three spool turbofans with as many as three nozzle”,1972 Description for "International Standard Atmosphere ISA": 2nd Data Set extracted from International Standard Atmosphere "ISA" in Matlab/Simulink data library for the international standard atmosphere conditions (temperature and pressure) varied with the altitude. 1b Data generation and reuse Methods and software used for data generation and reuse The research data consists of both reused and newly generated datasets. The reused dataset (for example, Fan and Axial Compressor maps) were obtained from external NASA engine performance data and manipulated through design conditions then imported into SIMULINK® for further usage and ICFD12-EG-5044 DMP version 2.0 7 analysis. The produced dataset (tables_final_18-7-2016.xlsx / datatables.csv) was generated from SIMULINK® simulations of the double-spool turbofan engine under off-design operating conditions. Data processing and organization were performed using MATLAB and Microsoft Excel to extract relevant performance parameters, create tables, and ensure machine-actionable formats suitable for further analysis. 2. Documentation and data quality 2a Data organisation, metadata and documentation The data will be structured according to the project’s directory convention, including folders for input data, model files, simulation results, and analysis outputs. Filenames will follow a consistent naming pattern with timestamps and descriptive identifiers. Version control is maintained through GitHub to ensure that all updates to the Simulink model and related scripts are automatically tracked. Each dataset version is linked to the corresponding simulation run, enabling full traceability of results. Metadata accompanying the project will provide essential descriptive information to allow the identification, understanding, and potential reuse of the data. Each dataset will include basic administrative details such as the project title, authors name, institutional affiliation (TU Wien), and date of data creation. Reference to the associated conference paper will also be included to link the data with its scientific context. Technical metadata will describe the software environment used to generate the results, including MATLAB/Simulink version numbers and any relevant toolboxes. The main file types (.slx, .mat, .m, .csv, and .png) will be identified, along with short explanations of key variables, for example thrust [N] and mass flow rate [kg/s]. While most parameter information is embedded in the Simulink model, additional notes are provided in a short readme file to clarify input assumptions and the operating conditions used in each simulation run. Structural metadata will briefly describe the directory organization of the preserved folder, distinguishing between input data, model files, and generated results. File names include timestamps to reflect versioning, methodological metadata describe the turbofan configuration, solver type, and main modeling assumptions however, documentation of all intermediate processing steps is limited. To support discoverability, a short abstract and relevant keywords (e.g., turbofan engine, off-design, Simulink, gas turbine performance) will be attached to the dataset. Future extensions may include richer metadata standards and persistent identifiers (e.g., DOI) to improve long-term reusability and citation. This will help others to identify, discover and reuse our data. Additionally, we will provide common metadata such as title, description or keywords when publishing data in open access repositories. In such a case, we will follow the default template provided by the repository, such as Data Cite Metadata or Dublin Core. A far as possible, we will use controlled vocabularies for our data to allow inter-disciplinary interoperability and machine-actionability. All documentation is stored together with the model and datasets in the project’s GitHub repository. Each update to the Simulink model, input files, and analysis scripts includes commit messages describing the purpose of changes. A concise readme file outlines the folder structure, simulation procedure, and software requirements to reproduce the results. Users with MATLAB/Simulink can reuse the data by following the provided instructions. Future updates may add structured metadata templates and workflow descriptions to further support reproducibility. 2b Data quality control The following data quality checks will be done: Consistency and quality were ensured by comparing simulation outputs with published reference results, either visually (side-by-side plots) or by extracting reference data for overlay plots. All model updates were tracked using GitHub version control to maintain traceability of changes.. 8 ICFD12-EG-5044 DMP version 2.0 3. Storage and backup during research process 3a Storage and backup facilities For the duration of the project, storage and backup of data will be ensured by Bassam Elsayed Saleh Abrisha (acting as the person responsible for data management and DMP) in cooperation with the system operator. The data will be stored on the servers of TU Wien. P1 (Experiment Results Data), R1 (Fan and compressor maps), R2 (International Standard Atmosphere ISA) will be stored on TU servers like reposiTUm or TUgitLab which is an application for managing repositories based on Git provided and managed by Campus IT. Our institute’s administrators will manage GitLab groups, assign project permissions, and appoint external project partners as additional GitLab users. This service is highly available and scalable on the Kubernetes platform. 3b Data security and protection of sensitive data We pay strict attention to compliance with the relevant institutional and national data protection policies listed in the introduction of this document. At this stage, it is not foreseen to process any sensitive data in the project. If this changes, advice will be sought from the data protection specialist at TU Wien, and the DMP will be updated. Access to data during research: dataset ID selected project members all other project members the public P1 reading only reading only reading only R1 reading only reading only reading only R2 reading only reading only reading only 4. Legal and ethical requirements 4a Personal data At this stage, it is not foreseen to process any personal data in the project. If this changes, advice will be sought from the data protection specialist at TU Wien, and the DMP will be updated. 4b Intellectual property rights and rights of use The following individual(s) hold rights and control access to the project data: Me, the main investigator and the supervisors 4c Ethical issues No particular ethical issue is foreseen with the data to be used or produced by the project. This section will be updated if issues arise. ICFD12-EG-5044 DMP version 2.0 9 5. Data sharing and long-term preservation 5a Data publication and access conditions As far as possible, obtained datasets will be published in repositories. Details on access conditions, reuse licenses, reasons for restrictions, etc. are collected in the table below. dataset ID access conditions estimated publication date location for publication (repository) PID license P1 Open 2018-01-08 TU Wien Research Data DOI CC-BY-4.0 Repository description: TU Wien Research Data is an institutional repository of TU Wien to enable storing, sharing and publishing of digital objects, in particular research data. It facilitates the funders' requirements for open access to research data and the FAIR principles by making research output findable, accessible, interoperable, and reusable. A DOI is assigned to each dataset published in TU Wien Research Data. This service is developed by the TU Wien Center for Research Data Management and hosted by TU.it. https://researchdata.tuwien.at/ Methods or software needed to access and use data: The NASA TN-D6653 scaled data and the simulation results are provided as CSV files and can be accessed with standard spreadsheet software or programming environments, while the ISA inlet conditions are part of the Simulink model and require MATLAB/Simulink to be reused. 5b Long-term preservation and deletion of data dataset ID location for long-term storage minimum retention period (≥ 10 years) foreseeable research uses and/or users P1 TU Wien Research Data 10 years The target audience for these datasets includes aerospace engineers and researchers, academic instructors and students, and developers of simulation or modeling tools.