In the domain of fluid dynamics, the problem of shape optimization is relevant because is essential to increase lift and reduce drag forces on a body immersed in a fluid. The current state of the art in this aspect consists of two variants: (1) evolution from an initial guess, using optimization to achieve a very specific effect, (2) creation and genetic breeding of random individuals. These approaches achieve optimal shapes and evidence of response under parameter variation. Their disadvantages are the need of an approximated solution and / or the trial-and-error generation of individuals. In response to this situation, this manuscript presents a method which uses Fluid Mechanics indicators (e.g. streamline curvature, pressure difference, zero velocity neighborhoods) to directly drive the evolution of the individual (in this case a wing profile). This pragmatic strategy mimics what an artisan (knowledgeable in a specific technical domain) effects to improve the shape. Our approach is not general, and it is not fully automated. However, it shows to efficiently reach wing profiles with the desired performance. Our approach shows the advantage of application domain-specific rules to drive the optimization, in contrast with generic administration of the evolution.
In the context of measurements in the boundary layer, the problem of estimating the skinfriction velocity is relevant because this velocity is proportional to the drag force and therefore is related to the energy wasted by friction in vehicles such as planes, cars, ships, etc. The existing literature is scarce when presenting an overview of the methods appropriate for the estimation in the scenario: (a) flat plate flow, (b) air incompressible regime, (c) outdoor conditions, (d) turbulent flow. As a response to such shortcomings, this manuscript presents an overview of the methods: (1) hot-wire anemometry, (2) hotfilm anemometry and (3) particle image velocimetry (PIV), in the aforementioned scenario. This manuscript reviews the diverse components that these methods require and contrasts the skin-friction velocity measurements stemming from them. Our results show a consistent estimation of the skin-friction velocity with the three methods. Future work is required in assessing the influence of wall proximity on hot-wire measurements and the influence of different Reynolds regimes on the skin-friction velocity estimations. Future work is required in the aspects of comparing the direct measurement of the skinfriction velocity with the hot-wire probe very close to the wall and the assessment of the accuracy of the techniques at different Reynolds numbers.
Fitting of analytic forms to point or triangle sets is central to computer-aided design, manufacturing, reverse engineering, dimensional control, etc. The existing approaches for this fitting assume an input of statistically strong point or triangle sets. In contrast, this manuscript reports the design (and industrial application) of fitting algorithms whose inputs are specifically poor triangular meshes. The analytic forms currently addressed are planes, cones, cylinders and spheres. Our algorithm also extracts the support submesh responsible for the analytic primitive. We implement spatial hashing and boundary representation for a preprocessing sequence. When the submesh supporting the analytic form holds strict C0-continuity at its border, submesh extraction is independent of fitting, and our algorithm is a real-time one. Otherwise, segmentation and fitting are codependent and our algorithm, albeit correct in the analytic form identification, cannot perform in real-time.
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