Summary
T42 Developing MDO framework for aircraft design optimization M818In this task an MDO framework for aircraft design optimization will be developed by TUBS and SOTON The framework is based on the aircraft design tool SUAVE which is under development by the Stanford University and TU Braunschweig The models developed in T41 will be integrated with SUAVE energy network A crosscheck with the aircraft designs from T22 an T32 is necessary to identify differences between SUAVE and TU Delft Aircraft Initiator designs The nonintrusive univariate reduced quadrature URQ method will be used to propagate the uncertainties through the analysis disciplines of SUAVE The design credibility will be formulated based on the probability of the technologies to be realised in a similar way to the reliability constraint The SUAVE design framework will be connected to the open source Surrogate Model Toolbox SMT from the University of Michigan Using the SMT computationally inexpensive models will be generated to be used for credibility based optimization T43 Credibilitybased MDO M1824The framework developed in T42 will be used for credibilitybased optimization of the reference aircraft initially designed in T32 The optimization will be performed by TUBS and SOTON to fine tune the design variables including the aircraft geometry as well as energy network Only continuous design variables such as wing geometry or battery energy density will be considered The optimization will be performed to eg minimize the total energy consumption of the aircraft subject to constraints on TLAR Besides a constraint on credibility will be defined Different values for minimum credibility will be used for optimization Both gradient based and gradient free optimization algorithms will be used The optimization will start with a gradient free such as Genetic Algorithms to find a good starting point for gradient based optimization such as Sequential Quadratic Programming Then the gradient based method will be executed to fine tune the optimum design The optimizations will be executed on the Phoenix computer cluster of TU Braunschweig T44 Assessment of the optimization results M2127The outcomes of the MDO in T43 will be used to investigate the potentials of the target technologies in realizing hybrid electric aircraft The KPIs defined in T23 together with the credibility criteria resulted from MDO in T43 will be used to identify the critical points the switching points for technologies for different categories of hybrid electric aircraft Critical points are considered hierarchically starting from the highest system level down to cross over points that can occur in the drive topology design Therefore analysis of significant system changes with regard to machine cooling behaviour material selection and topology variants implementation of superconductivity gear coupled high speed drives are identified and assessed Assessment will be performed by both SOTON TUD and TUBS A workshop with AB as well as other invitees from industries and academia will be arranged to discuss the final resultsResponsible SOTON contribution TUD and TUBS
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