Aircraft Configuration Design Using a Multidisciplinary Optimization Approach

2004 ◽  
Author(s):  
C.S. Rao ◽  
H.M. Tsai ◽  
T Ray
Keyword(s):  
Multidisciplinary Optimization ◽  
Configuration Design ◽  
Optimization Approach

A MultiDisciplinary Optimization Approach for Sizing Vertical Lift Aircraft

2021 ◽  
Author(s):  
Ananth Sridharan ◽  
Bharath Govindarajan
Keyword(s):  
Optimal Solution ◽  
Multidisciplinary Optimization ◽  
Shape Design ◽  
Optimization Approach ◽  
Optimization Strategy ◽  
Clock Time ◽  
Element Analysis ◽  
Analysis And Design ◽  
Design Variables ◽  
Vertical Lift

This paper presents an approach to reframe the sizing problem for vertical-lift unmanned aerial vehicles (UAVs) as an optimization problem and obtains a weight-optimal solution with up to two orders of magnitude of savings in wall clock time. Because sizing is performed with higher fidelity models and design variables from several disciplines, the Simultaneous Analysis aNd Design (SAND) approach from fixed-wing multidisciplinary optimization literature is adapted for the UAV sizing task. Governing equations and disciplinary design variables that are usually self-contained within disciplines (airframe tube sizes, trim variables, and trim equations) are migrated to the sizing optimizer and added as design variables and (in)equality constraints. For sizing consistency, the iterative weight convergence loop is replaced by a coupling variable and associated equality consistency constraint for the sizing optimizer. Cruise airspeed is also added as a design variable and driven by the sizing optimizer. The methodology is demonstrated for sizing a package delivery vehicle (a lift-augment quadrotor biplane tailsitter) with up to 39 design variables and 201 constraints. Gradient-based optimizations were initiated from different starting points; without blade shape design in sizing, all processes converged to the same minimum, indicating that the design space is convex for the chosen bounds, constraints, and objective function. Several optimization schemes were investigated by moving combinations of relevant disciplines (airframe sizing with finite element analysis, vehicle trim, and blade aerodynamic shape design) to the sizing optimizer. The biggest advantage of the SAND strategy is its scope for parallelization, and the inherent ability to drive the design away from regions where disciplinary analyses (e.g., trim) cannot find a solution, obviating the need for ad hoc penalty functions. Even in serial mode, the SAND optimization strategy yields results in the shortest wall clock time compared to all other approaches.

Optimization of Coupled System Components Using Approximations of Interface Quantities

2017 ◽  
Author(s):  
Michael Lockan ◽  
Dieter Bestle ◽  
Christian Janke ◽  
Marcus Meyer
Keyword(s):  
System Analysis ◽  
Complete System ◽  
Coupled System ◽  
System Optimization ◽  
Multidisciplinary Optimization ◽  
Collaborative Optimization ◽  
Optimal System ◽  
Design Parameters ◽  
Optimization Approach ◽  
Interface Parameters

Optimization of complex systems like jet engines is a process where discipline experts from several departments or even different companies have to work together. Thus, a complete system analysis code usually does not exist preventing an overall system optimization. Therefore, the system is typically split into components, and interface parameters between components are decided and fixed in early design stages based on low-fidelity information. Finally the components are optimized separately according to these fixed settings which, however, may prohibit an overall optimal system behavior even if sophisticated subsystem optimization is performed. Consequently, interface parameters should be varied in an overall coupled system optimization process and adapted to subsystem needs. This may be supported by utilizing collaborative optimization strategies. Basically there are two types of such optimization approaches: global strategies with nested optimization loops and local subsystem optimization strategies supported by sensitivity-based approximations of other subsystems. The multidisciplinary optimization approach presented here combines the benefits of both strategies: efficient global optimization and approximations of subsystem quantities without the need of sensitivity information. It starts with an initial design of experiments for each component by varying all input parameters and evaluating the associated outputs. Due to the fact that these quantities consist of shared design parameters and outputs of other components, not all of the used input parameter combinations are feasible for the coupled system. In order to enforce consistency for the entire system, the interface regions are characterized by feasibility criteria acting as approximated constraints for further component optimizations. Beside that an approximation of the overall system objective is provided to all components to drive component design towards an overall optimal system performance. The developed approach is demonstrated by an application to a jet engine turbine consisting of a high and low pressure part where the goal is to maximize the overall turbine efficiency. On the one hand the turbine is optimized with the proposed approach by splitting it into two coupled components; on the other hand the turbine is optimized as a complete system. It turns out that the proposed approach yields equally good results in much shorter time than overall optimization.

STS Forebody Material Selection Method Using Integrated Aerothermodynamic Optimization Approach

2012 ◽  
Vol 488-489 ◽  
pp. 1103-1108 ◽  
Author(s):  
Ali Sarosh ◽  
Dong Yun-Feng ◽  
Dimitar Kamarinchev
Keyword(s):  
Material Selection ◽  
Ceramic Matrix Composites ◽  
Selection Method ◽  
Multidisciplinary Optimization ◽  
Optimization Approach ◽  
Mass Model ◽  
External Compression ◽  
Inlet System ◽  
Space Applications ◽  
Selection Of

Ceramic matrix composites have been recommended for space applications. Accordingly, in this paper, a material selection method for the forebody of a space transportation system is demonstrated. The methodology is based on mass-model coupled aerothermodynamic design of a highly-integrated forebody-inlet system that uses the multidisciplinary optimization capability of the TIPSO (Two-steps Improved PSO) algorithm. The design optimization and hence material parameters are evolved using the newly developed SHWAMIDOF-FI tool. This paper focuses on validating the selection of carbon composite material by optimizing the configuration parameters for integrating a cone-derived forebody into planar wedge surfaces and an inlet-isolator assembly, so as to form a mixed internal-external compression system. Surface temperature, thermal conductivity, tensile strength and emissivity are used as primary parameters for selection of a forebody material. The optimization results validate that a carbon fibre reinforced carbon and silicon carbide (C/C-SiC) dual matrix composite is best suited for the application

A Multidisciplinary Design Optimization Approach to Relating Affordability and Performance in a Conceptual Submarine Design

2010 ◽  
Vol 26 (04) ◽  
pp. 273-289 ◽  
Author(s):  
N. Vlahopoulos ◽  
C. G. Hart
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Geometric Model ◽  
Multidisciplinary Optimization ◽  
System Level ◽  
Multidisciplinary Design ◽  
Manufacturing Cost ◽  
Optimization Approach ◽  
And Performance ◽  
The Impact

A multidisciplinary design optimization (MDO) framework is used for a conceptual submarine design study. Four discipline-level performances—internal deck area, powering, maneuvering, and structural analysis—are optimized simultaneously. The four discipline-level optimizations are driven by a system level optimization that minimizes the manufacturing cost while at the same time coordinates the exchange of information and the interaction among the discipline-level optimizations. Thus, the interaction among individual optimizations is captured along with the impact of the physical characteristics of the design on the manufacturing cost. A geometric model for the internal deck area of a submarine is created, and resistance, structural design, and maneuvering models are adapted from theoretical information available in the literature. These models are employed as simulation drivers in the discipline-level optimizations. Commercial cost-estimating software is leveraged to create a sophisticated, automated affordability model for the fabrication of a submarine pressure hull at the system level. First, each one of the four discipline optimizations and also the cost-related top level optimization are performed independently. As expected, five different design configurations result, one from each analysis. These results represent the "best" solution from each individual discipline optimization, and they are used as reference for comparison with the MDO solution. The deck area, resistance, structural, maneuvering, and affordability models are then synthesized into a multidisciplinary optimization statement reflecting a conceptual submarine design problem. The results from this coordinated MDO capture the interaction among disciplines and demonstrate the value that the MDO system offers in consolidating the results to a single design that improves the discipline-level objective functions while at the same time produces the highest possible improvement at the system level.

The Analysis and Optimization Design of Thermal-Electrical Coupling System with Consideration of Numerical Noises

2016 ◽  
Vol 13 (10) ◽  
pp. 6906-6915
Author(s):  
Zhuo Zhang ◽  
Fei Yu ◽  
Bo Xu ◽  
Shipeng Du ◽  
Qiuying Wang
Keyword(s):  
Optimization Design ◽  
Electrical Coupling ◽  
Likelihood Estimation ◽  
Multidisciplinary Optimization ◽  
Penalty Function Method ◽  
Optimization Approach ◽  
Analysis And Design ◽  
Simultaneous Analysis And Design ◽  
Optimization Function ◽  
Set Up

The optimization function for designing is usually not smooth or discontinuous due to numerical noises, which makes the multidisciplinary decoupling and optimization design more difficult. An global multidisciplinary optimization approach with consideration of numerical noises is proposed in this paper. First, the decoupling problem is transferred into optimization in line with the idea of Simultaneous Analysis and Design (SAND). Kriging models are introduced as surrogate models in order to filter the numerical noises, then the location of new samples is determined with the method of Maximum Likelihood Estimation (MLE), in order to reduce repetitive times of decoupling analysis. Second, the multidisciplinary optimization model of coupling systems is set up using the penalty function method. Finally, the proposed model and method is verified through a typical thermalelectrical coupling example.

scholarly journals An Integrated Design and Optimization Approach for Radial Inflow Turbines—Part I: Automated Preliminary Design

2018 ◽  
Vol 8 (11) ◽  
pp. 2038 ◽  
Author(s):  
Qing-Hua Deng ◽  
Shuai Shao ◽  
Lei Fu ◽  
Hai-Feng Luan ◽  
Zhen-Ping Feng
Keyword(s):  
Three Dimensional ◽  
Integrated Design ◽  
Multidisciplinary Optimization ◽  
Flow Coefficient ◽  
Design Stage ◽  
Optimization Approach ◽  
Preliminary Design ◽  
Design And Optimization ◽  
Preliminary Design Stage ◽  
Radial Inflow Turbine

An integrated design and optimization approach was developed for radial inflow turbines, which consists of two modules, an automated preliminary design module, and a flexible three-dimensional multidisciplinary optimization module. In this paper, the first module about the automated preliminary design approach was presented in detail and validated by the experimental data. The approach employs a genetic algorithm to explore the design space defined by the loading coefficient, flow coefficient, and rotational speed. The aim is to obtain the best design scheme with high aerodynamic performance under specified constraints and to reduce the dependency on human experiences when designing a radial inflow turbine. The validation results show that the present approach is able to get the optimal design and alleviate the dependence on the designer’s expertise under specified constraints at the preliminary design stage. Furthermore, the optimization results indicate that using the present optimization approach the total-to-static efficiency of the optimized T-100 radial inflow turbine can be increased by 1.0% under design condition and the rotor weight can be decreased by 0.35 kg (26.7%) as compared with that of the original case.

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