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BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20260323T090000
DTEND;TZID=Europe/Stockholm:20260327T170000
DTSTAMP:20260506T103741
CREATED:20251204T180050Z
LAST-MODIFIED:20260312T085322Z
UID:4739-1774256400-1774630800@sarc.center
SUMMARY:Conceptual Aircraft Design Course
DESCRIPTION:[vc_row type=”in_container” full_screen_row_position=”middle” column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” scene_position=”center” text_color=”dark” text_align=”left” row_border_radius=”none” row_border_radius_applies=”bg” row_position_desktop=”default” row_position_tablet=”inherit” row_position_phone=”inherit” overflow=”visible” overlay_strength=”0.3″ gradient_direction=”left_to_right” shape_divider_position=”bottom” bg_image_animation=”none”][vc_column column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” flex_gap_desktop=”10px” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”none” column_link_target=”_self” column_position=”default” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1/1″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][divider line_type=”No Line”][vc_column_text css=”” text_direction=”default”]A 5-Day Conceptual Aircraft Design Course in collaboration with The German Aerospace Center (DLR) and TU Braunschweig.  March 23-27\, 2026. \nVenue\nThe course is hold in ZAL Tech Center:\nHein-Saß-Weg 22\n21129 Hamburg\, Germany \nThe lecture room is at DLR\, MBSE Lab (Room A-4-130) \, 4th floor in the A-Wing. \nTutors\nIngo Staack (TUB)\nBjörn Nagel (DLR)\nPetter Krus (LiU)\nMikael Stenfelt (Saab)\nSvjetlana Stekovic (LiU) \nProgramme\n\n\n\n\n\n\n\n\n\n\n\n\n9:00h-10:30 h\n11:00h-12:30h\n12:30-13:30h\n13:30h-15:30h\n16:00h-17:30h\n\n\n\nMonday\nTravel to Hamburg (or L00)\nWelcome lunch buffet\nWelcome\, Introduction to Aircraft Design (L01)\nTechnical Visit ZAL Tech Center\n\n\nTuesday\nLecture Fundamentals of Aircraft Design (L02)\nLecture FAD (L03)\nLunch (buffet or canteen)\nHands-on exercise (LAB1) & Recap/Task\nInvited Talk: Airbus Future Projects Office (FPO)\n\n\n\nWednesday\nLecture FAD (L04)\nLecture FAD (L05)\nLunch (buffet or canteen)\nTalk: Digital Engineering Methods for Aircraft Design at DLR\nHands-on exercise (LAB2) & Recap/Task\nTodo: Evening Activity\n\n\nThursday\nVisit Airbus Factory incl. Final Assembly Line A320 (9:40-11:40)\nLunch (buffet or canteen)\nLecture FAD (L06)\nLecture FAD (L07)\nTalk: Green Aircraft Design Examples from DLR\n\n\n\nFriday\nHands-on exercise (LAB3) & Recap/Task & Follow-Up\nTravel back to Sweden / Lunch individually on the way\n\n\n\n\nDetailed schedule\n\n\n\nCourse code\nTopic\nResponsible person(s)\nContent/Keywords; Course structure & learning outcomes\n\n\nL00\nArrival & Registration\nLeonie\, Björn\, Ingo\nArrival on Sunday evening or Monday morning; Registration; Informal meet and greet; Start with lunch buffet\n\n\nL01\nIntroduction to the Course & Aicraft Concept Design (ACD) at a glance\nIngo: ACD foundations\nBjörn: Digital engineering\nPetter: Systems engineering\nOverview of Aircraft Design Process (Ingo); Requirements definition; Aircraft sizing fundamentals; Importance of normalization (dimensionless coefficients);\nReferences areas & parametar selection (Petter); Parameterisation principles; Data-driven methods (regression\, AI) in early design phases\n\n\nL02\nCrash-Course: The Complete Aircraft Design Loop\nIngo\, Björn\nWalkthrough of one full conceptual aircraft design cycle (Ingo);\nInterdependencies between disciplines (Björn); Trade-offs and iteration logic (Björn);\n“On‑the‑fly” treatment of aerodynamics\, structures\, performance and sizing (Ingo\, Björn)\n\n\nL03\nFundamentals of Lift and Drag\nIngo\nDrag: Aerodynamic forces; Induced drag & parasite drag;\nLift: Lift generation; Lift curve slope; Wing geometry effects; Laminar vs. turbulent flow; Drag polars; Connection to performance & sizing\n\n\nLAB1\nStatistical analysis & Mission calculation\nLinking Research Topics to Aircraft Concept Design\nBjörn\, Ingo\, Petter\nBasic statistical methods for design; Mission definition & mission fuel calculation; Performance constraints; How to connect individual research topics to the aircraft design workflow; Data extraction & analysis for conceptual design\n\n\nL04\nWing Design\, Weight Estimation & Structural Engineering (incl. Loads & Stability)\nIngo\, Mikael\, Svjetlana\nWing planform geometry (Ingo); High-lift systems (Ingo); Structural integration (Mikael): Initial structural layouts; Weight estimation methods; Center of Gravity (CG) CG and CG-travel (Ingo); Stability and control introduction (Ingo\, Mikael); Loads cases and aero-structural interactions (Mikael); Materials & structural performance (Svjetlana)\n\n\nL05\nMission analysis\, Performance Evaluation & Propulsion Fundamentals\nIngo\, Mikael\nMission calculation (Ingo); Performance constraints\, sizing diagram (Ingo); Climb/Cruise/loiter performance (Ingo); Propulsion system types & selection criteria (Mikael); Propulsion efficiency; Coupling between propulsion and aerodynamic/mission requirements (Mikael)\n\n\nLAB2\nDrag build-up methods & Digital tools\n(OpenVSP\, CPACS & TIGL)\nBjörn\, Ingo\,Petter\nManual drag build‑up; Component drag estimation; Using OpenVSP (import/export workflow); Introduction to CPACS framework; Geometry visualisation with TiGL‑Viewer; Comparison of manual vs. automated methods\n\n\nL06\nFull aircraft configuration from A to Z\nIngo\, Mikael\nFuselage design & sizing (Ingo); Empennage design & tail sizing (Ingo)\, Engine/propulsion systemintegration (Mikael); Landing gear setups & integration (Ingo);\nSpecial mission influences (e.g.\, SAR\, maritime patrol\, research aircraft); Operational considerations & CG management (Ingo)\n\n\nL07\nSystems Engineering: “The devil is in the details”\nPetter\, Ingo\, Mikael\, Björn\, Svjetlana\nAircraft systems overview (electric\, pneumatic\, hydraulic) (Ingo); System integration challenges (Petter\, Mikael); Safety and reliability requirements (Ingo); Material-system interactions (Svjetlana)\nFuture system trends: new system designs and opportunities (Björn)\n\n\nLAB3\nGroup formation & Task definition for collaborative projects [examination]\nBjörn\, Ingo\, Petter\nFormation of project teams; Definition of project scope; Choosing between e.g. AI‑based individual scripts or collaborative concept design tasks; Development of preliminary project plan; Expectations for the examination submission\n\n\n\nFollow-up activities\n\n\n\n\n\n\n\n\nFollow-up 1\nca. 1 Month after Course\nOnline Catch-up and evt. Specialisation (on Request) (ca. 1h30)\nBjörn\, Ingo\, Petter\n\n\nFollow-up 2\nca. 3 Months after Course\nOnsite Catch-up (e.g. within the SARC annual meeting) to finalize task or collaborative project/paper (ca. 0.5..1.0 day)\nBjörn\, Ingo\, Petter\n\n\n\n[/vc_column_text][/vc_column][/vc_row]
URL:https://sarc.center/event/conceptual-aircraft-design-course-2026/
LOCATION:DLR Hamburg\, Hamburg\, Germany
CATEGORIES:Course
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20260310T130000
DTEND;TZID=Europe/Stockholm:20260505T170000
DTSTAMP:20260506T103741
CREATED:20251204T144406Z
LAST-MODIFIED:20260226T170403Z
UID:4728-1773147600-1778000400@sarc.center
SUMMARY:Engineering Systems Design Analytics and AI\, 6.0 ECTS
DESCRIPTION:[vc_row type=”in_container” full_screen_row_position=”middle” column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” scene_position=”center” text_color=”dark” text_align=”left” row_border_radius=”none” row_border_radius_applies=”bg” row_position_desktop=”default” row_position_tablet=”inherit” row_position_phone=”inherit” overflow=”visible” overlay_strength=”0.3″ gradient_direction=”left_to_right” shape_divider_position=”bottom” bg_image_animation=”none”][vc_column column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” flex_gap_desktop=”10px” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”none” column_link_target=”_self” column_position=”default” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1/1″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][vc_column_text css=”” text_direction=”default”]\n\n\n\n\n\n\n\nCREDITS\n\n6.0 (ECTS) credits\n\n\n\nCOURSE LEVEL\n\nPost graduate level (Science Master\, and PhD students)\n\n\n\nEXAMINER\n\nPetter Krus\, Linköping University (LiU)\n\n\n\nCONTACT\n\nPetter Krus\, Linköping University (LiU)\npetter.krus@liu.se\n\n\n\nTARGET GROUP\n\nPhD student interested in model-based system engineering and design analytics and the application of artificial intelligence.\n\n\n\nPREREQUISITES\n\nBasic background in engineering. Some experience in Python is advantageous but not required.\n\n\n\nAIM\n\n\nThe course aims to provide doctoral students with advanced analytical methods for evaluation and design of complex engineering systems. Emphasis is placed on statistical modelling\, machine learning\, sensitivity analysis\, functional modelling\, system complexity\, and information-theoretic measures. The course prepares participants to critically and productively integrate modern machine learning techniques and large language models into engineering research and industrial development projects.\n\n\n\n\nLEARNING OUTCOMES\n\nAfter successful completion of the course\, the student shall be able to:\nApply functional modelling\, decomposition\, and systematic methods for engineering system concept generation.\nDevelop data-driven models capturing relationships between system requirements and component or system characteristics.\nPerform sensitivity and robustness analyses and interpret system coupling effects.\nEstimate and analyse system complexity\, including computational complexity aspects.\nUse Generative AI tools to generate\, evaluate\, and refine analysis-oriented software code for system design\, modelling\, and design analytics\, with critical assessment of correctness and applicability.\n\n\n\nCONTENTS\n\n\nDesign analytics (8 hours)\n• Axiomatic design\n• Sensitivity analysis\n• Robustness\n• Functional correlation\n\nMachine learning and design space generation (8 hours)\n• Introduction to machine learning in design contexts\n• Multiple regression analysis\n• Principal component analysis (PCA) using singular value decomposition (SVD)\n• Neural networks\n• Design space representation and parametrization\n\nSystem structures and modelling (4 hours)\n• Use of large language models (LLMs) for analysis\, modelling\, and simulation\n• Requirement and functional modelling (UML/SysML)\n• Dependency structure matrices\n• System concept generation supported by LLMs\n\nInformation entropy in engineering design (4 hours)\n• Shannon’s information theory\n• Information entropy as a measure of system complexity\n• Design space quantification\n• Axiomatic design and complexity\n• System optimisation and information entropy\n\nThroughout the course\, large language models are treated as design-support and analysis tools\, with emphasis on critical evaluation\, validation\, and integration into engineering workflows.\n\n\n\n\nTEACHING AND LEARNING ACTIVITIES\n\nThe course is delivered online and consists of lectures\, supervised exercises\, project work\, and an examination presentation meeting. Each scheduled teaching occasion typically includes approximately two hours of lectures and two hours of supervised exercises.\nThe main project is conducted individually or in small groups and is closely aligned with each participant’s doctoral research topic.\n\n\n\nLITERATURE\n\n\nCourse compendium and selected scientific journal and conference papers.\n\n\n\n\nEXAMINATION\n\nThe primary examination component is a written project report. The report shall demonstrate the application of course methods to a well-defined engineering system problem relevant to the student’s doctoral research.\nAdditional compulsory assignments\, including oral presentations\, are included during the course.\nGrading scale: Pass / Fail.\n\n\n\nCOURSE OFFERING\n\nThe course is offered as an online doctoral-level course. It is normally scheduled to start in March and run over two months. Exact dates and times are announced well in advance.\n\n\n\nSCHEDULE\n\nMarch 10. 13-17 (CET). Design analytics I\, Axiomatic design\, Machine learning in design.\nMarch 17. 13-17 (CET). Design analytics II. Sensitivity Analysis\, Robustness and functional correlation.\nMarch 31. 13-17 (CET). Machine learning and design space generation I: Subsystem modelling. Regression analysis and Principal Component Analysis\nApril 7. 13-17 (CET). Machine learning and design space generation II. Principal Component Analysis and Neural Networks. System structures and modelling\nApril 14. 13-17 (CET). Invited talks (TBD).\nApril 21. 13-17 (CET). Information entropy in Design and Optimization.\nMay 5. 13-17 (CET). Project presentation.\nSchedule is preliminary and may be subject to change.\n\n\n\nDownload course syllabus here. \nRegisteration\nDeadline: March 3\, 2026 \nRegistration is closed now! [/vc_column_text][/vc_column][/vc_row]
URL:https://sarc.center/event/engineering-systems-design-analytics-and-ai/
LOCATION:Online
CATEGORIES:Course
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20240918T130000
DTEND;TZID=Europe/Stockholm:20241030T170000
DTSTAMP:20260506T103741
CREATED:20240807T083451Z
LAST-MODIFIED:20240816T093030Z
UID:4488-1726664400-1730307600@sarc.center
SUMMARY:Engineering Systems Design Analytics and AI\, 6.0 ECTS
DESCRIPTION:  \n\n\n\n\n\n\n\nCREDITS\n\n6.0 (ECTS) credits\n\n\n\nEXAMINER\n\nPetter Krus\, Linköping University (LiU)\n\n\n\nCONTACT\n\nPetter Krus\, Linköping University (LiU)\npetter.krus@liu.se\n\n\n\nTARGET GROUP\n\nPhD student interested in model-based system engineering and design analytics and the application of artificial intelligence.\n\n\n\nPREREQUISITES\n\nBasic background in engineering. Some experience in Python is advantageous but not required.\n\n\n\nAIM\n\nThe course aims to equip students with analytical tools for evaluating complex systems\, focusing on statistical modelling\, machine learning\, sensitivity analysis\, and computational complexity. It should prepare the participants to take on the transformation implied by the rise and democratization of machine learning and large language models and the ability to use these methods in industrial projects.\n\n\n\nLEARNING OUTCOMES\n\nAfter the course\, the student shall demonstrate skill and ability in:\n– Generate models based on statistical data regarding relations between different requirements and system/component characteristics.\n– Produce sensitivity analysis of a system and be able to draw conclusions regarding robustness and the degree of coupling.\n– Estimate system complexity and make analysis of computational complexity.\n– Be able to generate extensive programming using Generative AI.\n\n\n\nCONTENTS\n\nDesign analytics (8h):\n– Axiomatic design.\n– Sensitivity analysis.\n– Robustness.\n– Functional correlation.\nMachine learning and design space generation (8h):\n– Introduction to Machine Learning in design.\n– Multiple regression analysis.\n– Principal component analysis (PCA) using Singular value decomposition (SVD).\n– Neural networks.\n– Design space and parametrization.\nSystem structures and modelling (4h):\n– The use of Large Language Models (LLMs) for analysis and modeling and simulation.\n– Requirement and Functional modeling (UML/SysML).\n– Dependency structure matrix.\n– System Concept Generation using LLM.\nInformation entropy in design (4h):\n– Shannon’s Information Theory.\n– Information entropy as a measure for system complexity.\n– Design space quantification.\n– Axiomatic Design and Complexity.\n– System Optimization and Information Entropy.\n\n\n\nORGANISATION\n\nLectures\, projects\, and a one-day examination presentation meeting. The project will be a collaborative project using LLMs to generate analysis codes (tentatively) in Python that reflect the content of the course and apply it to an example related to the individual student’s research projects.\nFor each occasion there will be about 2h lectures and 2h of supervised exercises.\nThere will one half day examination presentation meeting.\n\n\n\nLITERATURE\n\nCourse Compendium + Scientific papers\n\n\n\nEXAMINATION\n\nThe main examination task is a written project report that can be aligned towards the PhD students’ research. The grade is passed/not passed.\n\n\n\nSCHEDULE\n\n– Sept 18. 13-17 (CET). Design analytics I\, Axiomatic design\, Machine learning in design\n– Sept 25. 13-17 (CET). Design analytics II. Sensitivity Analysis\, Robustness and functional correlation.\n– Oct. 2. 13-17 (CET). Machine learning and design space generation I: Subsystem modelling. Regression analysis and Principal Component Analysis.\n– Oct. 9. 13-17 (CET). Machine learning and design space generation II. Principal Component Analysis and Neural Networks. System structures and modelling.\n– Oct. 16. 13-17 (CET). Information entropy in Design and Optimization.\n– Oct 30 13-17 (CET). Project presentation.Schedule is preliminary and may be subject to change.\n\n\n\nRegisteration\nRegistration is closed now!
URL:https://sarc.center/event/engineering-systems-design-analytics-and-ai-6-0-ects/
CATEGORIES:Course
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20240425T130000
DTEND;TZID=Europe/Stockholm:20240618T170000
DTSTAMP:20260506T103741
CREATED:20240329T122228Z
LAST-MODIFIED:20240408T093841Z
UID:4406-1714050000-1718730000@sarc.center
SUMMARY:PhD Course in System Modelling and Simulation\, 7.5 ECTS
DESCRIPTION:This course is about the simulation of complex technical systems. It covers the range from detailed equations to integration of multiple software for simulation. The course is based around the transmission line modelling (bi-directional delay lines) paradigm for partitioning of models\, with application mainly in the Hopsan simulation package\, and for co-simulation. However\, it also includes more general topics applicable to simulation in general. \nCourse objective\nAfter the course the participants should: \n\nHave a broad orientation of simulation methods and tools.\nBe able to use methods and tools for simulation and co-simulation.\nBe able to develop system models.\nBe able to develop component models at an equation level for system simulation.\nBe able to match the level of detail with what is needed for a specific task.\nUse simulation models for optimization.\nBeing prepared to use Large Language Models\, LLMs for modelling.\n\nCourse content\n\nIntroduction and Basic Concepts of System Simulation\n\nCourse overview\nIntroduction to the Hopsan simulation package and relation to other simulation tools\n\n\nTransmission Line Modelling\n\nSimulation in the frequency domain\nFrequency dependent friction.\n\nHydraulic and Electrical systems.\n\n\nThe Unit Transmission Line Element\n\n\nNumerical Methods\n\nAccuracy and stability analysis and characteristics of different methods\nDifferential Algebraic Equations\nAlgebraic solvers\, Newton-Raphson\nVariable time step\nEvent free systems\n\n\nEquation Based Modelling\n\nObject Oriented Modelling\nModelica\n\n\nConnectivity\n\nCo-simulation (e.g.\, Matlab/Simulink)\nSimulation with FMI\n\n\nComponent modelling\n\nHopsan built-in editor and Mathematica/Compgen\nHydraulic components\nElectrical components\nGas/pneumatic components\nMechanical components\n\nEuler-Lagrange equation\nFriction\, multi-body systems\, 2D-mechanics\n\n\nDiscrete event systems\nUsing LLM for modelling and simulation\n\n\nSimulation based optimization.\n\nOptimization methods\nObjective function formulation\nParametrization\nOptimizer performance\nMacro functionality\n\n\n\nLiterature\n\nLecture Notes\nSelected research publications\nDissertations from IEI/Flumes.\n\nExamination\nThe course is examined through a project that is defined together with the examiner which is then executed and then presented at the end of the course. \nInstructors\n\nPetter Krus\, petter.krus@liu.se\nRobert Braun\, robert.braun@liu.se\n\nRegistration\nPlease register here! \nPreliminary Schedule\n\n\n\nDate\nTopic\n\n\nApril 25\n13-17 CET\nIntroduction and Basic Concepts of System Simulation (PK\, RB) \nTransmission line dynamics (PK) \n\nSimulation in the frequency domain\nFrequency dependent friction\n\nElectrical Systems\n\n\nMay 7\n13-17 CET\nNumerical methods (PK\, RB)\n\n\nMay 8\n13-17 CET\nEquation based languages. (RB)\n\n\nMay 15\n13-17 CET\nComponent Modelling (PK\, RB)\n\n\nMay 16\n13-17 CET\nComponent Modelling (PK)\n\n\nMay 21\n13-17 CET\nSpare\n\n\nJune 12\n13-17 CET\nCo-simulation (RB)\n\n\nJune 13\n13-17 CET\nSimulation based optimization (RB)\n\n\nTBD Sept\nExamination (PK; RB)
URL:https://sarc.center/event/course-in-system-modelling-and-simulation-7-5-ects/
CATEGORIES:Course
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20230921T130000
DTEND;TZID=Europe/Stockholm:20231018T170000
DTSTAMP:20260506T103741
CREATED:20230718T104934Z
LAST-MODIFIED:20230919T073851Z
UID:4228-1695301200-1697648400@sarc.center
SUMMARY:PhD course in Engineering Systems Design Analytics and AI
DESCRIPTION:CREDITS\n6.0 credits\n\n\nEXAMINER\nPetter Krus\, Linköping University (LiU)\n\n\nCONTACT\npetter.krus@liu.se\n\n\nREGISTRATION\nPlease register here.\n\n\nTARGET GROUP\nPhD student interested in model-based system engineering and design analytics and the application of artificial intelligence.\n\n\nPREREQUISITES\nBasic background in engineering. Some experience in Python isadvantageous but not required.\n\n\nAIM\nThe course aims to equip students with analytical tools for evaluating complex systems\, focusing on statistical modelling\, machine learning\, sensitivity analysis\, and computational complexity. It should prepare the participants to take on the transformation implied by the rise and democratization of machine learning and large language models and the ability to use these methods in industrial projects.\n\n\nLEARNING OUTCOMES\nAfter the course\, the student shall demonstrate skill and ability in: \n\nGenerate models based on statistical data regarding relations between different system/component characteristics.\nProduce sensitivity analysis of a system and be able to draw conclusions regarding robustness and the degree of coupling.\nEstimate system complexity and make analysis of computational complexity.\n Be able to generate extensive programming using Generative AI.\n\n\n\n\nCONTENTS\n\n\nDesign analytics (8 hours)\n\nAxiomatic design.\nSensitivity analysis.\nRobustness.\nFunctional correlation.\n\n\nMachine learning and design space generation (8 hours)\n\nIntroduction to Machine Learning in design.\nMultiple regression analysis.\nPrincipal component analysis (PCA) using Singular value decomposition (SVD).\nNeural networks.\nDesign space and parametrization.\n\n\nSystem structures and modelling (4 hours)\n\nThe use of Large Language Models (LLMs) for analysis and modeling.\nRequirement and Functional modeling (UML/SysML).\nDependency structure matrix.\nConnectivity graphs.\n\n\nInformation entropy in design (4 hours)\n\nShannon’s Information Theory.\nInformation entropy as a measure for system complexity.\nDesign space quantification.\nAxiomatic Design and Complexity.\nInformation Entropy in Optimization.\n\n\n\n\n\n\nORGANISATION\nLectures\, projects\, and a one-day examination presentation meeting. The project will be a collaborative project using LLMs to generate analysis codes (tentatively) in Python that reflect the content of the course and apply it to an example related to the individual students research projects.\n\n\nLITERATURE\nCourse Compendium + Scientific papers\n\n\nEXAMINATION\nThe main examination task is a written project report that can be aligned towards the PhD students’ research.\nThe grade is passed/not passed.\n\n\nDETAILED SCHEDULE\n\n\nSept 21. 13-17: Design analytics I\, Axiomatic design\, Machine learning in design\nSept 22. 13-17: Design analytics II. Sensitivity Analysis\, Robustness and functional correlation\nOct. 2. 13-17: Machine learning and design space generation I: Subsystem modelling. Regression analysis and Principal component analysis\nOct. 10. 13-17: Machine learning and design space generation II. Subsystem modelling. Singular Value Decomposition and Neural Networks.\nOct. 11. 13-17: System structures and modelling\nOct 18 13-17: Information entropy in Design\nOct 23 13-17: Project presentation.
URL:https://sarc.center/event/phd-course-in-engineering-systems-design-analytics-and-ai/
CATEGORIES:Course
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BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20230828T150000
DTEND;TZID=Europe/Stockholm:20231027T170000
DTSTAMP:20260506T103741
CREATED:20230731T110926Z
LAST-MODIFIED:20231018T101231Z
UID:4244-1693234800-1698426000@sarc.center
SUMMARY:PhD course in Data-driven Methods in Engineering
DESCRIPTION:CREDITS\n7.5 credits\n\n\nEXAMINER\nRicardo Vinuesa\, KTH Royal Institute of Technology\n\n\nCONTACT\nrvinuesa@mech.kth.se\n\n\nRegistration\nPlease register here.\n\n\nTARGET GROUP\nPhD students\n\n\nPREREQUISITES\nA good understanding of standard topics in engineering mathematical analysis will be very helpful. In particular\, a strong background in linear algebra\, differential equations\, and optimization will be beneficial. Since hands-on data-driven modeling will invariably require some coding\, familiarity with Matlab\, Python or other similar languages/platforms will be helpful.\n\n\nAIM\nThe course is aimed at methods for analyzing complex systems and models.The course should equip students with the ability to use different methods in industrial projects.\n\n\nLEARNING OUTCOMES\nAfter taking the course the students should be able to: \n\nUnderstand the meaning and significance of mathematical operations required to process\, represent\, and approximate data.\nUnderstand the objectives\, advantages\, and disadvantages of various data-driven model- ing techniques.\nLearn how to load and manipulate large datasets in Matlab and/or Python.\nDevelop the required skills to apply various data-driven algorithms to potentially large and complex datasets\nInterpret the results of modeling algorithms to build an enhanced understanding of a given dataset.\nInterpret and understand the physics of the underlying system that the data comes from.\nBe able to assess the implications of the developed data-driven solutions for sutainable development.\n\n\n\n\nCONTENTS\n\n\nDimensionality Reduction (Part I):\n\nThis section introduces tools for finding low-dimensional representations of high-dimensional data\, which allows for data to be efficiently stored\, transferred\, and analyzed.\n\n\nMachine Learning and Data Analysis (Part II):\n\nThis section will give a relatively brief tour through aspects of data analysis\, from classical curve fitting to neural networks and deep learning\, building on the material introduced in Part I.\n\n\nDynamics\, Control and Reduced-Order Models (Part III):\n\nIn this section\, we assume that the data that we are studying comes from some underlying physical laws (in the context of dynamical systems\, solid mechanics\, fluid mechanics\, etc.)\, which can be learned/approxi- mated from data\, or from some combination of data and physics.\n\n\nFinal Project (Part IV):\n\nThe students will apply the techniques developed in this course (or extensions thereof) to a dataset/problem of their own choosing.\n\n\n\n\n\n\nCOURSE EVALUATION\nThere are three parts contributing to the course grade: \n\nHomework (2 hp). These will be solved individually and submitted for evaluation. The student will have two opportunities to implement the teacher’s feedback and obtain a passing grade.\nFinal exam (2 hp). The exam will last 3 hours and will contain both theoretical and practical aspects discussed in the course.\nProject (3.5 hp). The students will propose research projects in groups of around 4. These projects will be developed throughout the semester with the input of the teachers. The evaluation will be based on a final report and presentation.\n\nThe final grade will be Pass/Fail\, and in order to pass the course the student needs to pass the three parts.\n\n\nLITERATURE\nData-driven Science and Engineering: Brunton and Kutz. Cambridge University Press. The book is not required to follow the course.\n\n\nEXAMINATION\nThe main examination task is a written project report that can be aligned towards the PhD students’ research.The grade is passed/not passed.\n\n\nDETAILED SCHEDULE\nThe course consists of 15 theory lectures\, 6 practical lectures\, 1 presentation session and 1 final exam.\nFor schedule see the course webpage:\nhttps://www.kth.se/student/kurser/kurs/FSM3001
URL:https://sarc.center/event/phd-course-in-data-driven-methods-in-engineering/
CATEGORIES:Course
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20230327T090000
DTEND;TZID=Europe/Stockholm:20230331T170000
DTSTAMP:20260506T103741
CREATED:20230205T142058Z
LAST-MODIFIED:20231018T101438Z
UID:4042-1679907600-1680282000@sarc.center
SUMMARY:Advanced aeordynamics course
DESCRIPTION: \n\n\n\nWelcome to a course on advanced aerodynamics. This course is given in collaboration with Cranfield University.  \n\n\n\nDates and place\n\n\n\nThe course is given from March 27 to March 31\, 2023\, and is held in person at the Cranfield University\, UK. \n\n\n\nCosts\n\n\n\nThe registration fee is £1500. SARC provides scholarship to 10 PhD students\, covering their registration fees. In case number of the scholarship applicants exceed 10\, selection will be made by the SARC management. \n\n\n\nRationale/Aim\n\n\n\nTo introduce the techniques and tools for modelling\, simulating and analysing realistic computational fluid dynamic problems for industrial scale applications with practical hands on experience of commercial software packages used in industry. \n\n\n\nLecturers\n\n\n\nProf. Karl Jenkins\, Prof. Martin Skote\,  Dr. Laszlo Konozsy\, Dr. Panagiotis Tsoutsanis\, Dr. Tom Teschner\, Dr. Istvan Tamas Josza. \n\n\n\nSyllabus\n\n\n\n\n\n\n\nModule Intended Learning Outcomes\nOn successful completion of this module a student should be able to:  1.     Have a comprehensive understanding of the Computational Fluid Dynamic Process.2.     Understand the governing equations for fluid flows and how to solve them computationally.3.     Appreciate the wide range of applications using computational fluid dynamics.4.     Undertake pre-processing\, processing and post processing techniques using a commercial code for physical fluid flow problems.5.     Enable to evaluate parallel simulations using high performance computing\n\n\nSyllabus/Indicative content\nIntroduction to Computational Fluid Dynamics  ·       Governing equations·       The Computational Engineering Fluid Process·       Fluid Simulation and visualisation techniques·       Turbulence and turbulence modelling techniques·       High performance computing·       Practical session\n\n\n\n\n\n\n\nSchedule\n\n\n\n\n\n\n\nDay\nMonday\nTuesday\nWednesday\nThursday\nFriday\n\n\nDate\n March 27\n March 28\n March 29     \n March 30\n March 31\n\n\nTime\n \n \n \n \n \n\n\n09:00-10:00\nGoverning Equations   \nNumerical Methods         \nModelling Low Speed Flows  \nValidation and Verification   \nHigh Performance Computing  for CFD  \n\n\n10:00-10:10\nBreak\nBreak\nBreak\nBreak\nBreak\n\n\n10:10-11:00\nGoverning Equations   \nNumerical Methods        \nModelling Low Speed Flows  \nTurbulence      \nHigh Performance Computing  for CFD  \n\n\n11:00-11:10\nBreak\nBreak\nBreak\nBreak\nBreak\n\n\n11:10-13:10\nGrid Generation   \nVisualisation and Post-Processing        \nModelling High Speed Flows       \nTurbulence Modelling  \nCase Studies  \n\n\n13.10 – 14:00\nLunch\nLunch\nLunch\nLunch\nLunch\n\n\n14:00-15:30\nGrid Generation Labs           \nLab: FLUENT  \nLab: FLUENT  \nLab: FLUENT \nDiscussions & individual problems   \n\n\n15:30-15:45\nBreak\nBreak\nBreak\nBreak\nBreak\n\n\n15:45-16:15\nGrid Generation Labs            \nLab: FLUENT  \nLab: FLUENT  \nLab: FLUENT  \nLab: FLUENT  \n\n\n16:15-16:30\nBreak\nBreak\nBreak\nBreak\nBreak\n\n\n16:15-17:00\nGrid Generation Labs  \nLab: FLUENT  \nLab: FLUENT  \nLab: FLUENT  \nLab: FLUENT \n\n\n\n\n\n\n\nRegistration\n\n\n\nRegister here.
URL:https://sarc.center/event/advanced-aeordynamics-course/
CATEGORIES:Course
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BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20230224T090000
DTEND;TZID=Europe/Stockholm:20230331T120000
DTSTAMP:20260506T103741
CREATED:20230201T232751Z
LAST-MODIFIED:20230206T104152Z
UID:4003-1677229200-1680264000@sarc.center
SUMMARY:Turbine design for clean power and propulsion
DESCRIPTION:PhD Course\, 7.5 higher education credits\nWelcome to an online course on turbomachinery. \nAudience\nEngineers concerned with environmental aspects\, efficient energy production\, less polluting transportation. Researchers aiming to be trained in aerothermal development of turbomachinery. Engineering students interested in pursuing a career in the energy sector\, aircraft propulsion\, turbomachinery. \nCourse description\nThis course is composed of five parts. In the first section the fundamental relationships are explained through several modules comprising: the development of non-dimensional analysis\, velocity triangles\, efficiency and the degree of reaction\, and radial equilibrium. At the end of this section the learner acquired the tools to perform mono-dimensional design of a turbomachinery as well as the meridional analysis. In the second section we present the experimental and computational tools available to assess the aerothermal performance of turbomachinery. The third section is focused on axial turbines\, which includes consecutive modules on all possible architectures\, blade design\, secondary flows\, trailing edge flows\, tip flows\, unsteady flows\, forced response and noise. The fourth section is concerned with compressors\, axial and radial\, their performance and design. The last section focuses on the new areas of research as well as the future use of turbomachinery for power and propulsion. \nCourse learning objectives\nBy the end of the course\, you should be able to: \n\nDesign a turbomachine\, assess their aerodynamic performance & and convective heat transfer\nCharacterize the unsteady behavior of the turbomachinery\nCommunicate final developed design to a panel of experts in the field\nDevelop a critical analysis to optimize future turbomachinery concepts based on physical principles\nOutline future research programs to address aerothermal challenges\n\nPrerequisites\n\nFundamentals of thermodynamics\nFundamentals of fluid mechanics\n\nLecturer\nProfessor Guillermo Paniagua\, Purdue University\, USA\nFulbright scholarship for the Distinguished chair in Alternative Energy at Chalmers University of Technology\,\nCourse schedule\n \nRegistration\nRegister here.
URL:https://sarc.center/event/turbine-design-for-clean-power-and-propulsion/
LOCATION:Online
CATEGORIES:Course
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BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20221004T080000
DTEND;TZID=Europe/Stockholm:20230228T170000
DTSTAMP:20260506T103741
CREATED:20220828T161401Z
LAST-MODIFIED:20221114T154349Z
UID:3774-1664870400-1677603600@sarc.center
SUMMARY:PhD Course on Product Innovation for Aerospace Applications
DESCRIPTION:PhD Course (2022)\, 7.5 HEC (7.5 higher education credits) & Industrial participants in the aerospace industry (diploma course).\nWelcome to a PhD and practitioners course where product development methods and product innovations for aerospace applications will be explored\, in terms of scientific research in the field\, combined with practical examples. Aerospace applications currently in use will be studied along the course\, as well as future visionary aerospace innovation solutions. Participants can develop their own product ideas along the course. \nContent\nCourse reading includes literature in the field of product development and innovation\, both in general (any industry\, but with focus on engineering)\, and specifically for advances in aerospace industry. As an illustrative learning example will each participant select one aerospace industry company to study closer. The primary course objective is to provide a theoretical reference base for conducting research in product development for aerospace applications. A secondary objective is to introduce participants to carry out research and innovation activities in aerospace industry\, including engineering and innovation management perspectives. \nSchedule\, Course Organization\, and Registration\nThe course starts online 4 October 2022\, and contains both online seminars\, workshops and study visits in Linköping and Kiruna: Space Innovation Forum (Oct22)\, MODPROD (Feb23) and “Rymdforum” (Mar23). \nThe course is given by SwedishAerospaceResearchCenter (SARC) and the #SpaceTechGradSchool\, in close collaboration with Aerospace Cluster Sweden (ACS) and Innovair. \nPlease see the complete course description / the course syllabus (pdf) for more details. Registration can be performed via a form on kunskapsförmedlingen.se (link\, registration already close). \nResponsible teacher: Anna Öhrvall Rönnbäck (LTU)
URL:https://sarc.center/event/phd-course-on-product-innovation-for-aerospace-applications/
LOCATION:Luleå Tekniska Universitet Space Campus Kiruna\, LTU Space Campus Kiruna\, Kiruna\, 98192\, Sweden
CATEGORIES:Course
ATTACH;FMTTYPE=image/jpeg:https://sarc.center/wp-content/uploads/2022/08/image001-aircraft-northernlight.jpg
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20211108
DTEND;VALUE=DATE:20211214
DTSTAMP:20260506T103741
CREATED:20210701T083021Z
LAST-MODIFIED:20231018T102123Z
UID:2402-1636329600-1639439999@sarc.center
SUMMARY:PhD/industry course: Engineering Design Optimization (EngDesOpt)
DESCRIPTION:PhD Course (2021)\, 7.5 HEC (7.5 higher education credits) Industrial participants in the aerospace industry (diploma course) \nDuration\nNovember 8th-9th and 22th-23th; December 13th \nSee the detailed schedule in the course syllabus (PDF). \nContent\n\nEngineering Design and Optimization- How can optimization support the design process?\nOptimization methods – from traditional gradient based methods to non-gradient methods such as the Complex method\, Genetic Algorithms and Particle Swarm Optimization.\nMulti-objective optimization – How to handle problems with several conflicting objectives.\nHandling of constraints via penalty functions.\nSurrogate Models – How to use Design of Experiments and Surrogate Models to reduce the optimization time.\nPost-optimization analysis – How to choose a solution from a large pool of optimal solutions.\nApplication examples where modelling\, simulation and optimization are used to solve real world industrial problems.\n\nPlease find the complete course description with more details\, registration and the detailed schedule in the course syllabus (PDF).
URL:https://sarc.center/event/phd-industry-course-engineering-design-optimization-engdesopt/
LOCATION:Linköping University\, A-hus\, room ACAS\, Linköping\, Östergötland\, 58183\, Sweden
CATEGORIES:Course
ORGANIZER;CN="Swedish Aeronautical Research Center":MAILTO:info@sarc.center
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20210420T123000
DTEND;TZID=Europe/Stockholm:20210420T163000
DTSTAMP:20260506T103741
CREATED:20210315T123015Z
LAST-MODIFIED:20231018T102050Z
UID:2137-1618921800-1618936200@sarc.center
SUMMARY:PhD/industry course: Sustainability for Aerospace Applications
DESCRIPTION:PhD Course (2021)\, 4 HEC (4 higher education credits) Industrial participants in the aerospace industry (diploma course) \nDuration\nApril 20-May 31\, 2021. Subscription no later than April 16\, 2021 at \nFor details and registration visit\nhttps://kunskapsformedlingen.se/en/courses/sustainability-for-aerospace-applications/ \nContent\nThe course gives an overview of United Nations Development Program’s (UNDP’s) Sustainable Development Goals (SDGs)\, and tools to assess and develop towards increased sustainability for aerospace applications research and development and innovation (R&D\, R&I) projects. It consists of: \n\nLectures (online) on sustainability and eco-design\, by academic researchers and representatives from aerospace companies to cover current progress (state-of-art and state-of-practice).\nIndividual assignment\, based on the UNDP SDG assessment tool: https://sdgimpactassessmenttool.org/\n\nWorkshops (online\, with break-out sessions) to discuss the individual assessment\, and innovative and creative workshop to investigate further improvements. \nTarget group\nPhD candidates and postdocs conducting research in the Swedish Aerospace Research Center (SARC) and the Graduate School of Space Technology\, and aerospace engineers\, active in research & development and research & innovation (R&D/R&I) projects. \nCourse objectives\nThe objective of this course is to increase awareness about sustainability issues in the participant’s own and other participants’ ongoing R&D/R&I projects\, and to improve the participant’s ability to address these issues in their own work. \nBy raising sustainability issues in the participant’s current\nproject\, and by reflecting upon them in groups with other\ncourse participants\, teachers and guest lecturers\, the course objective is that the participant achieves deeper insights about sustainability aspects\, in order to improve management of and communication about sustainability issues in the current project\, the research work\, and\, especially for industrial participants\, in their organizations. \nOn completion of the course\, the participant should be able to demonstrate (in a short text and in a presentation of the PhD research project) the ability to make relevant sustainability statements about the own research (R&D/R&I) project and be able to discuss the project in relation to UNDP’s 2030 sustainability goals.
URL:https://sarc.center/event/phd-industry-course-sustainability-for-aerospace-applications/
CATEGORIES:Course
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20200127T081500
DTEND;TZID=Europe/Stockholm:20200131T150000
DTSTAMP:20260506T103741
CREATED:20191031T155114Z
LAST-MODIFIED:20231018T102010Z
UID:1322-1580112900-1580482800@sarc.center
SUMMARY:PhD course in Aerospace Actuators
DESCRIPTION:CREDITS\n\n5.0 credits\n\n\n\n\nLECTURER\n\nJean-Charles Maré\, \nProfessor at the National Institute of Applied Sciences (INSA)\, and researcher at the Clément Ader Institute in Toulouse\, France.\n\n\n\n\nEXAMINER\n\nPETTER KRUS\, LINKÖPING UNIVERSITY (LIU) \npetter.krus@liu.se\n\n\n\n\nCONTACT\n\nINGO STAACK\, LINKÖPING UNIVERSITY (LIU) \ningo.staack@liu.se \nARDESHIR HANIFI\, KTH \nhanifi@kth.se\n\n\n\n\nTARGET GROUP\n\nPhD students interest in on-board aircraft systems.\nSeniors within aeronautics dealing with flight control\, on-board systems and actuator design..\n\n\n\n\nPREREQUISITES\n\nBasic background in engineering. Experiences in Matlab/Simulink is advantageous but not required.\n\n\n\n\nAIM\n\nThe course is aimed to actuator technology for aerospace applications. E.g. actuator for actuation for primary and secondary control surfaces\, landing gears and other miscellaneous functions.\n\n\n\n\nLEARNING OUTCOMES\n\nAfter the course\, the student shall demonstrate skill and ability in: \n\nUnderstanding of the different actuator concepts.\nModeling and simulation of different actuators.\n\n\n\n\n\n\n\nCONTENTS\n\n\n\nActuation in aerospace\, 3h\nArchitecting safety critical fluid power transmission systems\, 6h\n\nCase study: comparative analysis of BA609 and V22 pylon conversion actuators\n\n\nTowards more/all electric actuation in aerospace. 8h\n\nSignal-by-Wire / Power-by-Wire\, architectures\, principle of operation\, and specific challenges of electric drives\n\n\nProcess and best practices for lumped parameters modelling and simulation. 3h\nModelling and simulation of electromechanical actuators\, 6h\n\nIncluding power electronics\, motor\, mechanical transmission\, with fault injection and illustration on AMESim and Matlab Simulink)\n\n\n\n\n\n\n\n ORGANISATION\n\nLectures\, assignments.\n\n\n\nLITERATURE\n\nTBD\n\n\n\nEXAMINATION\n\nThe main examination task is assignments. \nThe grade is passed/not passed.\n\n\n\nORGANISATION\n\nLectures\, exercises and assignment.\n\n\n\nSCHEDULE\n\nThe course is given as a block course. The schedule is \n\nMonday Jan 27             8:15-15:00   6h\nTuesday Jan 28            8:15-15:00   6h\nWednesday Jan 29        8:15-15:00   6h\nThursday Jan 30           8:15-15:00   6h\nFriday Jan 31               8:15-15:00   6h\nProject presentation TBD\n\n\n\n\n\n  \nCourse info
URL:https://sarc.center/event/phd-course-in-aerospace-actuators/
LOCATION:Linköping University\, A-hus\, room ACAS\, Linköping\, Östergötland\, 58183\, Sweden
CATEGORIES:Course
ORGANIZER;CN="Swedish Aeronautical Research Center":MAILTO:info@sarc.center
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20190317
DTEND;VALUE=DATE:20190324
DTSTAMP:20260506T103741
CREATED:20190611T074905Z
LAST-MODIFIED:20231018T102212Z
UID:1100-1552780800-1553385599@sarc.center
SUMMARY:SARC.Academy Short Summer School on Conceptual Aircraft Design\, March 17-23\, 2019\, Florianópolis\, Brazil
DESCRIPTION:Welcome to the first SARC.Academy short summer school (S4) in collaboration with SC2C.Aero at Florianópolis\, Santa Caterina\, Brazil.Welcome to the first SARC.Academy short summer school (S4) in collaboration with SC2C.Aero at Florianópolis\, Santa Caterina\, Brazil. \n \nCourse Program\n\n\n\nDay\nTime\n                                 Program\n\n\nSunday\, 17th\n17:00 – 18:00\nSARC presentation (Dan Henningson)SARC.Academy information (Ingo Staack)SARC-SC2C.Aero Collaboration & Opportunities (Petter Krus & Victor De Negri)\n\n\n19:00 – 21:00\nReception\n\n\n \n \n\n\nMonday – Friday\nCourse lectures (see own lecture plan below)\n\n\nThursday\, 22th\n19:00 – 22:00\nDinner\n\n\nFriday\, 22th\n15:00 – 18:00\nVisit of the Federal University of Santa Catarina and CERTI Foundation including the laboratories at UFSC and CERTI\n\n\n \n\n\nSaturday\, 23t (Swedish participants only)\n10:00-11:30\nFuture Collaboration and Research Planning: open discussion Session lead by Prof. Petter Krus and the SARC.research team.Take this opportunity to find like-minded researcher/manoeuvre students to broaden your research and expertise horizon!\n\n\n11:30 – 12:30\nPresentation and WP planning of the SARC collaborative PhD project (Tomas Grönstedt)\n\n\n14:00 – 18:30\nSocial Event by endorsement:\n  \nExcursion by bus through local beaches ORMarine cruise on the Florianopolis bay \n\n\n\n\nCourse Outline\n\n\n\nLecture\nTopic\n\n\n1\nINTRODUCTION:Overview of the design process\, requirements definition\, end products of design.\n\n\n2\nQUICK DESIGN & SIZING TECHNIQUES:Methods to quickly determine aircraft weight and size required to meet mission requirements\, rapid aero/weights/propulsion methods\, design trade studies.\n\n\n3\nWING/TAIL GEOMETRY SELECTION:Selection of wing geometry and tail arrangement.\n\n\n4\nTHRUST-TO-WEIGHT AND WING LOADING\, INITIAL SIZING:manoeuvre selection of wing loading and thrust-to-weight (or horsepower-to-weight) ratio to satisfy requirements such as stall speed\, climb rate\, and manoeuvrability. Refined estimation of takeoff weight and determination of fuselage\, wing\, and tail sizes.\n\n\n5\nCONFIGURATION LAYOUT AND LOFT:Design layout of a credible aircraft configuration arrangement including external geometry\, conic lofting\, flat-wrap development\, smoothness verification\, cross-section definition\, and internal layout. Design layout of wings and tails including airfoil interpolation\, trapezoidal and non-trapezoidal geometries\, wing location guidelines.\n\n\n6\nAERO & STRUCTURES CONSIDERATIONS: Design guidance and rules-of-thumb for creation of configuration layouts with good aerodynamics and structural arrangement.\n\n\n7\nSPECIAL CONSIDERATIONS:\n  \nDesign impacts of observability (radar\, IR\, visual\, and aural)\, vulnerability\, producibility\, and maintainability. \n\n\n\n8\nSYSTEMS INTEGRATION:Design integration of landing gear\, hydraulics\, electrics\, pneumatics\, and avionics.\n\n\n9\nPAYLOAD\, PASSENGERS\, & CREW:Design layout of the crew station\, passenger compartment\, cargo bays\, and weapons integration.\n\n\n10\nPROPULSION INTEGRATION:Jet engine integration including engine selection\, engine scaling\, engine location considerations\, inlet geometry and location\, and nozzle geometry. Propeller engine integration including engine selection and location\, cowling\, and propeller sizing. Aircraft fuel system considerations.\n\n\n11\nAERODYNAMIC ANALYSIS:Methods for estimating the aerodynamic lift and drag from low subsonic through supersonic speeds\, including the component drag build-up method\, the leading edge suction method\, and the Sears-Haack wave drag method. Introduction to Computational Fluid Dynamics (CFD).\n\n\n12\nSTABILITY AND CONTROL ANALYSIS:Methods for determining if the design satisfies essential stability and control requirements including trim\, nosewheel liftoff\, static stability\, departure susceptibility\, and spin recovery.\n\n\n13\nPROPULSION ANALYSIS:Methods for calculation of the installed net propulsive force for jet or propeller-driven aircraft\, including installation corrections\, inlet drag\, nozzle drag\, and propeller thrust.\n\n\n14\n  \n  \n\nLOADS\, STRUCTURES AND WEIGHTS:Aircraft loads\, aerospace materials and properties. Introduction to the Finite Element Method (FEM).  Estimation of aircraft weights and mass moments using statistical models and corrections for advanced materials.\n\n\n15\nPERFORMANCE ANALYSIS:\n  \nPerformance analysis methods for level flight\, climb\, glide\, takeoff\, landing\, and maneuver. Energy manoeuvrability methods for combat analysis and minimum time/fuel to climb. Fighter measures of merit including agility and post-stall maneuver. \n\n\n\n16\nTRADE STUDIES AND COST ANALYSIS:\n  \nRefined sizing techniques and discussion of industry methods. Sizing matrix and carpet plot optimization techniques\, along with Multidisciplinary Optimization (MDO) methods. Use of performance constraint curves to determine the optimal aircraft. Life Cycle Cost analysis using statistical and operational data.  Airline economic analysis \n\n\n\n17\nCOMPUTER-AIDED CONCEPTUAL DESIGN:Use of CAD in the conceptual design environment\, tools for facilitating initial design layout and design iteration. Demonstration of conceptual design CAD and integrated analysis and optimization including MDO methods (RDSwin-Pro).\n\n\n18\nVTOL\, HELICOPTER\, AND DERIVATIVE AIRCRAFT DESIGN:Overview of jet VSTOL design and analysis including concepts and integration issues.  Helicopter aerodynamics\, performance\, controls\, design\, and sizing techniques. Design considerations for the development of derivatives of existing aircraft\, including performance\, weight\, and cost estimation.\n\n\n19\nINNOVATIVE DESIGN CONCEPTS:\n  \nOverview of innovative design concepts including Canard\, Flying Wing\, Joined-Wing\, Blended Wing Body\, Unmanned Aircraft (UAV)\, Asymmetric\, and others. \n\n\n\n20\nDESIGN EXAMPLES:Review of prior lessons by a step-by-step design examples from initial requirements and first sketch to completed configuration layout and optimization\n\n\n\nAbout the Instructor -Daniel P. Raymer\, Ph.D.\nThe 2010 recipient of the AIAA Aircraft Design Award\, Dr Daniel Raymer is a recognized expert in the areas of Aerospace Vehicle Design and Configuration Layout\, Computer-aided Design Methodologies and Design Education. An AIAA Fellow and recipient of the AIAA Summerfield Book award\, he was named Rockwell Engineer of the Year for his pioneering work in aircraft computer-aided conceptual design. Dr. Raymer is the author of the best-selling textbook “Aircraft Design: A Conceptual Approach” and the mass-market books “Dan Raymer’s Simplified Aircraft Design for Homebuilders” and “Living in the Future: The Education and Adventures of an Advanced Aircraft Designer.” He regularly teaches his popular five-day Aircraft Conceptual Design Short Course\, a two-day Advanced Aircraft Design Short Course\, a three-day Short Course in Aircraft Design Management\, Requirements Definition\, and System Engineering\, and a course in Unmanned Air Vehicle (UAV) Design. \n Dr. Raymer is President of the design and consulting company\, Conceptual Research Corporation\, and conducts design studies and consulting for NASA\, the USAF Research Lab (WPAFB)\, DARPA\, Composite Engineering Inc.\, and others. He is a regular Forum Speaker at the EAA AirVenture (Oshkosh). His previous positions include Director-Advanced Design with Lockheed\, Director-Future Missions at the Aerojet Propulsion Research Institute\, and Project Manager-Engineering at Rockwell North American Aviation. He was Head of Air Vehicle Design for X-31 during the conceptual design phases\, and was intimately involved in the actual configuration definition. He also consulted with both RAND and CNA during the JAST/JSF concept development phase. \nDr Raymer received B.S. and M.S. engineering degrees in Astronautics and Aeronautics from Purdue\, an MBA from the University of Southern California\, and a Doctorate of Engineering (PhD) from the Swedish Royal Institute of Technology (KTH) in the field of Aircraft Multidisciplinary Design Optimization. He is a recipient of the Purdue University Outstanding Aerospace Engineer Award given to “honour those alumni who have distinguished themselves in the aerospace industry”.
URL:https://sarc.center/event/sarc-academy-short-summer-school-2019/
LOCATION:Florianopolis\, Brazil\, Florianopolis\, Santa Caterina\, Brazil
CATEGORIES:Course
ATTACH;FMTTYPE=image/jpeg:https://sarc.center/wp-content/uploads/2019/06/raymer_course_deNegri.jpg
ORGANIZER;CN="Swedish Aeronautical Research Center":MAILTO:info@sarc.center
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