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Chouinard last won the day on July 23 2020

Chouinard had the most liked content!


  • Location
  • Home Mountain/Resort?
  • Occupation?
    Professional Engineer
  • Current Boards in your Quiver
    Thirst Superconductor
    Thirst SF [Mini-Conductor]
    Burton Speed - dormant
    Donek Razor 170 - softboot
    Burton M6 - retired
  • Current Boots Used?
    Deeluxe T700
    Burton DriverX
  • Current bindings and set-up?
    F2 Intec Titanium
    F2 Intec TitanFlex
    Gecko Plates
    Flow NXT AT [Soft}
  • Snowboarding since
  • Hardbooting since

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  1. Hi:Rise Varial foil Med-w/65cm mast TECH SPECS * Chord: 226mm * Projected area: 116,508.2 mm² * Wingspan: 685.4mm * AR: 4.0 * Volume: 1,621,983 mm³ .
  2. Sent money to purchase the kit but never received it. Change of plans. Purchased a "like new" foil from a surf shop in Fla. Going to mount it on and old windsurfer and practice behind the pontoon boat before committing to a shorter board and wing. If the foil doesn't hit me in the head as I ramp up the learning curve I'll be carving on a foil before summers end!
  3. Coming from a windsurfing perspective using a seat harness I’m wondering how the overhead wing affects your unsupported lower back?
  4. @Pat Donnelly https://www.clearwaterfoils.com/
  5. Not necessarily. There are two guys that ride Whitefish with a bottomless pit of boards that are uniquely qualified to do this. Make the results public for all our talented board builders Donek, Coiler, Thirst, etc. and the race would be on.
  6. A DOE is a planned set of tests on the response variable(s) (KPOVs) with one or more inputs (factors) (PIVs) each at two or more settings (levels) which will: •Determine if any factor or combination of factors is significant •Define prediction equations •Allow efficient optimization •Direct activity to rapid process improvements •Create significant events for analysis •Learning the most from as few runs as possible; efficiency is the objective of DOE •Identifying which factors affect mean, variation, both or none •Screening a large number of factors down to the vital few •Modeling the process with a prediction equation •Optimizing the factor levels for desired response •Validating the results through confirmation The only thing missing here is the bong. this
  7. If you want to understand the interaction then you may consider doing something like this if you have access to a large diverse quiver of boards. Rider perception - Start with a screening DOE: 1) Make a list of the critical input/output characteristics such as: Dampness, edge hold, ease of turn initiation, flex index, side cut, chamber, etc. Some metrics will be rider perceived, some will be geometric as-built and some will have to be measured using a repeatable test method. Use at least 10 measurement bins. 2) Record the geometric as-builts dimensions and measurables. 3) Make a survey form and take a diverse quiver of boards out and using the same rider/setup/condition/technique make several runs and rate the characteristics from 1 to 10. Now change the rider setup to the riders optimized settings for that board based on past experience and rate the characteristics again. Repeat the trials for different surface conditions representing everything from powder to glare ice. 1) Bin all the metrics into at most three levels. 2) Use Minitab or other and generate a DOE for each separate output characteristic using all the input characteristics. 3) Crunch the data. The analysis with statistically shake out any significant interactions and the primary inputs for each output separately. You will also generate a prediction equation that will allow you to identify the optimize input metric values. 4) Now take the separate results and select the board that is a blend of all the optimal inputs [closely matches the individual prediction equations] and verify the results. Board Design - all purpose board [for a condition specific board ignore data collected under non-specific conditions]: Identify the design elements that control the significant inputs identified in the screening DOE and use a DOE again but this time look at the input levels of the design elements both geometrical and mechanically. Hand off the results to the board builder for a prototype. Ride the board and validate the design. Start with a rider perception, translate it to numbers, optimize the numbers, translate it back to a rider perception with a prototype.
  8. I think I'll quote myself. If you've got a lot of time on your hands due to government lockdowns maybe you could suspend a board at the ends of it's effective length using rotating sleeves to relieve friction, load the board on the two binding locations with 5, 15 and 25 weights [each location] and use a dial indicator to measure board deflections at 1" increments see what the data tells you about flex under different loads.
  9. And a powder hound to boot!
  10. A singular “flex” value is a coarse measurement. There’s magic in how the “flex coefficient” changes as the board shape changes.
  11. 2gr (3.5lL) from a sienna van is lighter than stock turbo with an aluminum block, zero lag and zero heat issues from over boosting. With revised ecu calibration, ported intake, tuned headers & exhaust he has about $14,000 total into the build including the car and it pulls like 5.0L. Your thinking of a Honda engine used for dragging, a lot more work. This was literally a plug and play. Me thinks I might build a newer convertible version.
  12. 92MR2 - 2GR Spent more time on this than my board this season...for a number of reasons including poor conditions.
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