1Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxMultidisciplinary System Design Optimization (MSDO)IntroductionLecture 1Prof. Olivier de Weck Prof. Karen Willcox2Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxIntroductionsOlivier de Weck, Ph.D. – LecturerAssociate Professor Karen Willcox, Ph.D. – LecturerAssociate ProfessorAnas Alfaris, Ph.D. – Assistant LecturerResearch ScientistDouglas Allaire, Ph.D – Assistant LecturerPostdoctoral AssociateAndrew March – Teaching AssistantGraduate StudentKaushik Sinha – Teaching AssistantGraduate Student3Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxToday’s Topics• Course Rationale• Role of MSDO in Systems Engineering • Learning Objectives• Pedagogy and Course Administration• A historical perspective on MDO• MSDO Framework introduction4Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxCourse RationaleComputational Design and Concurrent Engineering (CE) are becoming an increasingly important part of the Product Development Process (PDP) in IndustryCourtesy of Cambridge Seven Associates, Inc..Used with permission.5Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxA collection of subsystems?=Fuselage GroupControls GroupHydraulics GroupElectrical GroupPower Plant GroupLoft GroupProduction Engineering Group Equipment GroupAerodynamics GroupStress GroupImage by MIT OpenCourseWare.?6Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxSequential –vs- Concurrent DesignAspect Ratio ARWingMinimumStructuralWeightWminC1(t/o length)C2(rate of climb)C3(flutter)AR*010203DJ dueTo sequentialdesignP increasing(e.g. range)7Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxRole of MSDO in Engineering SystemsGoal: Create advanced and complex engineering systems that must be competitive not only in terms of performance, but also in terms of life-cycle value.Need: A rigorous, quantitative multidisciplinary design methodology that can work hand-in-hand with the intuitive non-quantitative and creative side of the design process.This class presents the current state-of-the-artin concurrent, multidisciplinary design optimization (MDO)8Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxProduct Development ProcessBeginningof Lifecycle- Mission- Requirements- ConstraintsCustomerStakeholderUserArchitectDesignerSystem EngineerConceiveDesignImplement“process information”“turninformationto matter”SRRPDRCDRiterateiterateThe Environment: technological, economic, political, social, natureThe EnterpriseThe Systemcreativityarchitectingtrade studiesmodeling simulationexperimentsdesign techniquesoptimization (MDO)virtualrealManufacturingassemblyintegrationchoosecreate9Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxExample 1: Nexus Spacecraft-60 -40 -20 0 20 40 60-60-40-200204060Centroid X [mm]Centroid Y [mm]Centroid Jitter on Focal Plane [RSS LOS]T=5 sec14.97 mm 1 pixelRequirement: Jz,2=5 mmGoal: Find a “balanced” system design, where the flexiblestructure, the optics and the control systems work together toachieve a desired pointing performance (RSS LOS), given various constraintsNASA Nexus Spacecraft ConceptImage by MIT OpenCourseWare.10Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxExample 2: BWB AircraftAircraft Comparison ofBWB & A3XX-50RApprox. 480 passengers eachApprox. 8,700 nm range eachMaximumTakeoffWeightBWBA3XX-50R18%BWBA3XX-50R19%TotalSea-LevelStatic Thrust19%BWBA3XX-50ROperatorsEmptyWeightFuelBurnper Seat32%BWBA3XX-50RBoeing Blended Wing Body ConceptGoal: Find a design for a family of blended wing aircraft that will combine aerodynamics, structures, propulsion and controls such that a competitive system emerges - as measured by a set of metrics that matter to the operator.Image of Boeing Blended Wing Body Concept removed due to copyright restrictions.11Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxCourse ObjectivesThe course will …• Enhance MIT’s offerings in the area of simulation and optimization of multidisciplinary systems during the conceive and design phases • develop and codify a normative (prescriptive) approach to multidisciplinary modeling and quantitative assessment of new or existing system/product designs• engage both faculty and graduate students in the emerging research field of MDO, while anchoring the CDIO principles in the graduate curriculum12Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxLearning Objectives (I)The students will (1) learn how MSDO can support the product development process of complex, multidisciplinary engineered systems(2) learn how to rationalize and quantify a system architecture or product design problem by selecting appropriate objective functions, design variables, parameters and constraints(3) subdivide a complex system into smaller disciplinary models, manage their interfaces and reintegrate them into an overall system model13Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxLearning Objectives (II)(4) be able to use various optimization techniques such as sequential quadratic programming, simulated annealing or genetic algorithms and select the ones most suitable to the problem at hand(5) perform a critical evaluation and interpretation of simulation and optimization results, including sensitivity analysis and exploration of performance, cost and risk tradeoffs(6) be familiar with the basic concepts of multi-objective optimization, including the conditions for optimality and the computation of the Pareto front14Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxLearning Objectives (III)(7) understand the concept of design for value and be familiar with ways to quantitatively assess the expected lifecycle cost of a new system or product(8) sharpen their presentation skills, acquire critical reasoning with respect to the validity and fidelity of their MSDO models and experience the advantages and challenges of teamworkHow to achieve these learning objectives ?15Massachusetts Institute of Technology - Prof. de Weck and Prof. WillcoxMSDO PedagogyGuestLecturesReadingsMIT Intranet(unavailable)Class ProjectAssignmentsA1-A5e.g. “Industry/Govt.”e.g. “SensitivityAnalysis”e.g. “GA Aircraft”e.g. Design ofExperiments (DOE)LecturesLabse.g. “Principles ofOptimal