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Quantitative FBDs. Just like in units 1 & 2, our models (x-t, v-t, a-t graphs) didn’t really mean a whole lot if they couldn’t have predictive power
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Quantitative FBDs • Just like in units 1 & 2, our models (x-t, v-t, a-t graphs) didn’t really mean a whole lot if they couldn’t have predictive power • Because predictive power requires actual numbers (how fast something will be going, how far something has traveled) we need to make sure our FBD models have predictive power as well With 1-D forces, it’s fairly easy • With 2-D forces, we have to do a bit more work to calculate the forces involved • Involves basic trigonometry Fn (R, C) 5 kg cat sitting motionless on rug 50 N 50 N Fg = 5 kg x 10 m/s2 Fg = 50 N Fn = 50 N (must balance Fg) Fg (E, C)
First, a little intro to basic trig. • Sine, Cosine, and Tangent • 3 main functions in trig • Usually shortened as sin, cos, and tan SOH CAH TOA • To calculate sin, cos, and tan • Divide the length of one side by another side……but you must know which sides!
Find the hypotenuse and the length of the side adjacent (next to) the angle given
Let’s apply what we have just learned to a more physics-based question: • An 10 kg object sits motionless on an incline due to friction 300
The 2000 kg elephant is standing motionless on the ramp due to friction. • What is the normal force that the ramp is pushing up on the elephant with? What is the force of friction that prevents the elephant from sliding down?