This paper reviews the use of computational flow simulation for aircraft design. While computational simulation has already yielded great benefits, its impact continues to be restricted by computational and human costs. The requirements of the design process are examined in detail. In current practice there are bottlenecks in geometry modelling, data handling and mesh generation. To exploit computational simulation more effectively there is also a need to combine it with automatic optimization procedures. A case study is presented of a recent industrial experience with optimization. Finally it is suggested that developments in information technology now offer the opportunity to produce an integrated numerical design environment, and to re-engineer the design process.

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Re-Engineering the Design Process Through Computation

Geometry modeling and grid generation (GMGG) have played, and will continue to play, an important role in computational aerosciences. During the last two decades, tremendous progress has occurred in GMGG; however, GMGG is still the biggest bottleneck to routine applications for complicated computational fluid dynamics and computational structures mechanics models for analysis, design, and optimization. We are still far from incorporating GMGG tools in a design and optimization environment for complicated configurations. It is still a challenging task to parameterize an existing model in today's computer-aided design systems, and the models created are not always good enough for automatic grid generation tools. Despite many advances in grid generation, the process is still the most labor-intensive and time-consuming part of the computational aerosciences for analysis, design, and optimization. In an ideal design environment, a design engineer would use a parametric model to evaluate alternative designs effortlessly and optimize an existing design for a new set of design objectives and constraints. For this ideal environment to be realized, the GMGG tools must have the following characteristics: 1) be automated, 2) provide consistent geometry across all disciplines, 3) be parametric, 4) provide sensitivity derivatives, and 5) fit in the product development cycle times. This paper reviews the status of GMGG for analysis, design, and optimization processes, and it focuses on some emerging ideas that will advance the GMGG toward the ideal design environment.

Status and Future of Geometry Modeling and Grid Generation for Design and Optimization

http://aero-comlab.stanford.edu/Papers/jameson_applied_numerical_math_1993.pdf

Computational algorithms for aerodynamic analysis and design

Re-engineering the design process through computation

The use of hot-wire anemometry for obtaining fluctuating data in transonic flows has been evaluated From hot-wire heat loss correlations based on previous transonic data, the sensitivity coefficients for velocity, density, and total temperature fluctuations have been calculated for a wide range of test conditions and sensor parameters For sensor Reynolds numbers greater than 20 and high sensor overheat ratios, the velocity sensitivity remains independent of Mach number and equal to the density sensitivity These conclusions were verified by comparisons of predicted sensitivities with those from recent direct calibrations in transonic flows Based on these results, techniques are presented to obtain meaningful measurements of fluctuating velocity, density, and Reynolds shear stress using hot-wire and hot-film anemometers Examples of these measurements are presented for two transonic boundary layers

/pdf/hot-wire-anemometry-in-transonic-flow-4uskxlzn4i.pdf

Hot wire anemometry in transonic flow

It is pointed out that in other fields of computational physics, such as ballistics, celestial mechanics, and neutronics, computations have already displaced experiments as the principal means of obtaining dynamic simulations. In the case of aerodynamic investigations, the complexity of the computational work involved in solving the Navier-Stokes equations is the reason that such investigations rely currently mainly on wind-tunnel testing. However, because of inherent limitations of the wind-tunnel approach and economic considerations, it appears that at some time in the future aerodynamic studies will chiefly rely on computational flow data provided by the computer. Taking into account projected development trends, it is estimated that computers with the required capabilities for a solution of the complete viscous, time-dependent Navier-Stokes equations will be available in the mid-1980s.

D. R. Chapman

Papers

Computers vs. wind tunnels for aerodynamic flow simulations