b'Aerospace | Engineer InnovationMinimizing the aerodynamic impact of water bottlesAnalyzing the impact of water bottle placement on aerodynamics was required in order to discover a design that made the Madone the fastest bike under real-world conditions. The addition of down tube and seat tube water bottles impacts drag by creating additional pressure and disrupting airflow on the tube surfaces. To minimize these unfavorable drag impacts, HEEDS was used to explore optimal water bottle locations to minimize overall frame drag. In the starting CAD model, water bottles were mounted on the down tube and seat tube at arbitrary points on a prototype frame. Each bottles original location was marked with respect to the center of the500 Accumulated force vs. postionbottom bracketthe component that450connects the crankset (chainset) to the bicycle and allows the crankset to rotate400freely. HEEDS then iterated over new350Drag (grams)designs (new bottle positions),300progressively adjusting the iteration input values according to the prior drag250responses. After 140 iterations, the final200result showed a 5.5 percent reduction in150overall drag. In this study, the aggregate result showed the preference to place100the seat tube bottle as low as possible50toward the bottom bracket, while -0.4 -0.2 0 0.2 0.4 0.6 0.8 1keeping its influence minimal on theBike position (m)down tube. The seat tube is an important area for determining overallFigure 4: Impact of water bottles on surface pressure and surface flow (top) and accumulated drag force versus bike position (bottom).bike drag and affects the bikes yawing ability, so keeping this tube as exposed as possible would minimize the draginformation about a design than the penalty. limited number of iterations possible with sequential, manually executed The most important benefit of HEEDS,analysis runs, Trek engineers say their Treks engineers say, is what they call anconclusions tend to be more objective ensemble-based analysis, wherein trendsand data-driven than before. for achieving the objective become apparent once sufficient data arePreviously, when carrying out produced via design space exploration.optimization manuallywith CFD and This uncovers previously unknownFEA but without HEEDSengineers correlations among design variables andwould typically analyze 30 to 50 different performance attributes, as well asdesign iterations for a given problem. deepening engineers insight intoNow, HEEDS makes it easy and practical already known phenomena. Beyondto carry out 500 to 1,000 iterations in the furthering their understanding of thesame time or even less. This, in turn, underlying physics of their designs, itcreated a new challenge: substantially also inspires them to look at problemsgreater demand for computational from multiple viewpointsindeed, theresources. Trek turned to cloud software sometimes discovers solutionscomputing, taking advantage of the that engineers hadnt thought of, asavailability of HEEDS on ScaleX, the occurred in the water-bottle placementcloud simulation and HPC platform from study. Because automated design spaceRescale. Trek benchmarked a typical exploration reveals much moreSimcenter STAR-CCM+ case involving a 31'