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BTU
The paper shows a methodology for designing a complex system in a collaborative design environment by sharing information on autonomous subsystems and coupling parameters. Collaborative design is a current issue in aviation industry where intellectual property rights of individual companies prohibit a common evaluation model. State of the art approaches based on nested local optimisation loops are not sufficient if time-consuming component analyses are involved. A new approach for collaborative design is developed where the overall optimisation of a complex system is split into subsystem optimisation problems. Coupling parameters are treated as local design variables and only optimal coupling parameters are exchanged regularly. Application to a test example shows a huge time reduction and improved probability for finding the global optimum. Advantages are also demonstrated for an industrial design task.
Simulation studies on an active all-wheel-steering car show that disturbance of vehicle parameters have high influence on lateral car dynamics. This motivates the need of robust design against such parameter uncertainties. A specific parametrisation is established combining deterministic, velocity dependent steering control parameters with partly uncertain, velocity independent vehicle parameters for simultaneous use in a numerical optimisation process. Model-based objectives are formulated and summarized in a multi-objective optimisation problem where especially the lateral steady state behaviour is improved by an adaption strategy based on measurable uncertainties. The normally distributed uncertainties are generated by optimal Latin hypercube sampling and a response surface based strategy helps to cut down time consuming model evaluations which offers the possibility to use a genetic optimisation algorithm. Optimisation results are discussed in different criterion spaces and the achieved improvements confirm the validity of the proposed procedure.
Untersuchung des Geräuschverhaltens von Kraftfahrzeug-Schwingungsdämpfern und Elastomerlagern
(2017)
Abstract Automated structural design optimization should take into acc
ount risk of failure which depends on eigenmodes, since eigenmode shap
es determine failure risk by their characteristic stress concentration
pattern, as well as by their specific interaction with excitations. T
hus, such a process needs to be able to identify eigenmodes with low e
rror rate. This is a rather challenging task, because eigenmodes depen
d on the geometry of the structure which is changing during the design
process, and on boundary conditions which are not clearly defined due
to uncertainties in the assembly and running conditions. The present
investigation aims to find a proper classification method for eigenmod
es of compressor airfoils. Specific data normalization and data depend
ent initialization of a neural network using principle-component direc
tions as initial weight vectors have led to the development of a class
ification and decision procedure enabling automatic assignment of prop
er uncertainty bands to eigenfrequencies of a specific eigenmode shape
. Application to compressor airfoils of a stationary gas-turbine with
hammer-foot and dove-tail roots demonstrates the high performance of t
he proposed procedure.
Verbesserte Vorauslegung des Kerntriebwerks mithilfe eines kaskadierten Optimierungsprozesses
(2018)
Vortex-induced Vibration Analysis of a composite Riser System Based on the Transfer Matrix Method
(2018)
The international standard ISO 6336-3 defines a calculation method for the tooth root capacity of standard gears with basic rack profile according to ISO 53. However, the results of this method may become too optimistic for non-standard gears with custom root fillets, large pressure angles or asymmetric teeth, since the effect of general mean stresses on the local tooth root strength are neglected. Therefore, a more generic calculation method is suggested, which considers the mean stress influence by utilizing the Haigh diagram. Both approaches are then used as basis of root fillet shape optimizations. A comparison of results demonstrates significant differences in the safety assessment and the resulting root geometry.
Currently, prediction of crack initiation by corrosion pits is only possible by assuming regular geometrical shapes, such as semi-spheres or semi-ellipsoids. Moreover, typical fatigue life diagrams associate the crack initiation life with geometrical features, such as pit depth or aspect ratio, often leading to unsatisfactory correlations due to high pit shape variability and data scatter. In the context of blade-disc fixation in aero engine turbines, this limitation translates into highly conservative life estimations. Therefore, a new crack initiation predictor is formulated based on experimental testing and numerical analysis of 28 artificial corrosion pits. A low-cycle fatigue test campaign is conducted using three-point bending test specimens to simulate maximum takeoff operation conditions of the aero engine and the associated loading of the blade root designed as firtree. An artificial pit is located at the critical point of each test specimen, respectively. The prediction criterion is based on finite element analysis and is formulated as the lowest plastic strain of a plastic region with a certain volume in the corrosion pit. This reference volume is varied until an optimum correlation with experimental crack initiation life is obtained. The criterion shows a superior correlation with crack initiation life compared to pure geometrical parameters such as pit depth.
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.