طراحی آیرودینامیک بهبود یافته از پردازش در توربوماشین ها بوسیله بهینه سازی عددی
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|10416||2003||11 صفحه PDF||سفارش دهید|
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله تقریباً شامل 5000 کلمه می باشد.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
- تولید محتوا با مقالات ISI برای سایت یا وبلاگ شما
- تولید محتوا با مقالات ISI برای کتاب شما
- تولید محتوا با مقالات ISI برای نشریه یا رسانه شما
پیشنهاد می کنیم کیفیت محتوای سایت خود را با استفاده از منابع علمی، افزایش دهید.
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Aerospace Science and Technology, Volume 7, Issue 4, June 2003, Pages 277–287
The aerodynamic optimization of a transonic compressor is reported in this paper. The Q3D Navier–Stokes solver COLIBRI is coupled to a gradient-based method (CONMIN) and to a genetic algorithm (GADO). The suction side of a 2D blade is optimized by using both optimization methods with a significant efficiency improvement. In 3D, the performance improvement is obtained by modifying the suction surface of a transonic compressor with a Bézier surface and by using the CANARI solver coupled to the gradient method (CONMIN).
Engine manufacturers are steadily asking for higher performance in terms of efficiency, pressure ratio or mass flow of the different components of the engine (rows, stages, . . .). This will leads to the use of CFD in an intensive way for turbomachinery blade design  but this higher performance must be achieved within shorter design cycles and at lower cost. Traditionally, CFD has been used in an analysis mode for cut-and-try approaches to design, with eventually a large scattering of the results. The recent progress of the CFD code performance (reduced CPU time, better accuracy, improved reliability) enable to reduce the design time by coupling CFD codes with optimization tools. This can be applied both in Q3D and 3D, with various optimization and blade deformation techniques.This paper describes the performance improvement of a transonic compressor blade computed both with a Q3D and a 3D approach. All CFD calculations are carried out with a Navier–Stokes solver. The goal of the optimization is to achieve maximum efficiency at a given operating point (pressure ratio, mass flow). In the Q3D approach, a gradient-based method is used for a first optimization and is compared to the optimization result obtained with a genetic algorithm. The suction side of the blade is modified by applying a deformation function defined by a Bézier curve which control points are positioned by the design variables. The overall efficiency is increased by more than two points in both cases. Moreover, the optimized blading shows a significant improvement of performance both at the design and at off-design points. In the 3D approach, the gradientbased method is used. The suction side of the blade is modified by applying a deformation function defined by a Bézier surface. The efficiency improvement is greater than one point after only three optimization cycles.
نتیجه گیری انگلیسی
An optimization of a transonic compressor blade is performed with a Q3D Navier–Stokes solver by modifying the suction side of this blade with a deformation function defined by a Bézier curve. The operating point is maintained constant by applying both geometrical and optimization constraints. The application of both a gradient and a genetic algorithm has shown very close results. The efficiency improvement is about 2.4 points at the operating point and the off design performances show a good behavior of the optimized blading. The same principle is extended to a 3D blade. The Navier–Stokes code CANARI is coupled to a gradient method and the blade is modified by applying a deformation function defined by a Bézier surface. The optimization, carried out with account of the tip clearance, improves the efficiency by more than 1 point with only small variations of the operating point. The fully 3D aerodynamic optimization presented here shows that such a process can be included in a design cycle, as new blading can be defined in about 10 CPU hours. The next step concerns the introduction of additional geometrical constraints, and the opening to multidisciplinary approach such as mechanics and thermal transfers in the optimization process.