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Institute
BTU
Due to their high complexity, aero engine development
is a time-consuming and cost-intensive process. Therefore,
pre-developed proven aerodynamic and geometric
compressor information is often used as starting point and
transferred to new compressor designs. In the present paper,
a new approach for aerodynamic cloning of an already
existing compressor flow to a new compressor geometry by
use of a streamline curvature based Throughflow solver is
presented. Parameterized compressor quantities are
automatically modified with the help of optimization
strategies, and the resulting compressor aerodynamics are
compared to a reference design in each iteration step. The
target is to minimize the discrepancy between reference
design and new design regarding essential flow parameters
like de Haller number, Mach number etc., and thereby to
reproduce the aerodynamic image of the reference design.
Thus, already collected experience from existing compressor
flow fields can be used to reduce costs for developing as well
as testing of new compressor configurations. Conducted
investigations show a notable acceleration of the design
process in comparison to former strategies starting from
scratch while achieving an acceptable compliance of
aerodynamic parameters.
The present paper compares four different optimization
strategies for decoupled optimization in the context of
preliminary core engine design for aero engines. An
optimization with the AAO (All-At-Once) approach is
performed as a baseline and compared against the
performance and results of three cascaded optimization
strategies: CO (Collaborative Optimization), BLISS 2000
(Bi-Level Integrated System Synthesis) and ISOC (Interface
Segmentation Optimization Concept). The optimization
problem is based on a thermodynamic core engine model
representing an industrial application example. The results
are assessed with respect to typical requirements for
multidisciplinary core engine design. The impact of the used
optimization strategy on the performance of the optimization
concept is investigated and discussed.
Compressor Blade Design for Stationary Gas Turbines Using Dimension Reduced Surrogate Modeling
(2017)
Deterministic optimization is used in all fields of engineering, especially in early design processes based on digital prototypes and simulation. A major disadvantage of deterministic optimization is the unknown robustness of the found solution against uncertainties of system parameters. Therefore, the Robust Design Optimization (RDO) concept as combination of Robustness Analysis (RA) and deterministic optimization was developed. In this paper, such an approach is applied to the optimization of a suspension for passenger cars w.r.t. typical driving maneuvers. The suspension behavior has to be robust against uncertainties without defining strict limits or safety margins. The coupled multi-objective RDO procedure will find a Pareto-front w.r.t. mean value and variance of chosen objectives. As a result, a specific compromise regarding system robustness and mean performance may be chosen from this Pareto-set. To overcome the vast amount of CPU-time, required for expensive direct function evaluations, an adaptive response surface method (aRSM) is integrated. The overall process then consists of an inner loop involving a multi-objective evolutionary algorithm based on response surfaces and an outer loop, where metamodeling is performed on a set of support points. This set is initialized in the first iteration step and updated afterwards by picking promising designs from the Pareto-fronts of the surrogate model, which are then evaluated exactly.
Transfer Matrix Method for the Determination of the Free Vobration of Two Eastically Coupled Beams
(2013)
Contradictory Integer Objective Approaches for Mixed-variables Evolutionary Optimization Problems
(2014)
System Integration as Key for Improving and Speeding up the Preliminary Design Phase of Aero Engines
(2013)
A design change from bladed disk to blisk leads to stronger endurance limits. The paper deals with aerofoil adaption of a blisk within a multi-criterion optimisation loop. Blisks are more sensitive to external excitation since mechanical damping is very low. Thus stronger limits have to be applied which are hard to be fulfilled and hence it requires the use of numerical optimisation. Combination of 2D CFD and FEM in a common optimisation loop to re-design a given blisk. Determination of relevant features for improving blisk endurance. Modern process integration and multi-criterion optimisation tools in combination with today's increased computational power allow to perform mulitphysics design even in the case of complex industrial design tasks.