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gtnhenbr [62]
3 years ago
13

Many vehicles have indicator lights telling you when your

Engineering
1 answer:
Lisa [10]3 years ago
6 0

Answer:

Many vehicles have indicator lights telling you when your <em>Tires</em><em> </em><em>are</em><em> </em><em>underinflated</em><em>.</em>

Explanation:

Hope it helps you..

Your welcome in advance..

(ㆁωㆁ)

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Select the correct answer.
boyakko [2]
I think the answer is b
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3 years ago
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What is the magnitude of the maximum stress that exists at the tip of an internal crack having a radius of curvature of 1.9 × 10
Fiesta28 [93]

Answer:

Recall the formula for the maximum stress, σₐ = 2σ₀ *√ (α/ρₓ)

where

σ₀ = tensile stress = 140 MPa = 1.40x 10⁸Pa

α = crack length = 3.8 × 10–2 mm = 3.8 x 10⁻⁵m

ρₓ = radius of curvature = 1.9 × 10⁻⁴mm = 1.9 × 10⁻⁷m

Substituting these values into the formula, we can calculate the max stress as

 ====== 2 x 1.40x 10⁸ x √(3.8 x 10⁻⁵/1.9 × 10⁻⁷)

σₐ  = 24.4MPa

6 0
3 years ago
Limited time only for christmas give yourself free 100 points YES YES muhahahahhaha
Setler79 [48]
Answer:

Thank you so much and may god bless you.
6 0
2 years ago
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In this problem set, you will implement multidimensional scaling (MDS) from scratch. You may use standard matrix/vector librarie
EleoNora [17]

Features of Multidimensional scaling(MDS) from scratch is described below.

Explanation:

Multidimensional scaling (MDS) is a way to reduce the dimensionality of data to visualize it.  We basically want to project our (likely highly dimensional) data into a lower dimensional space and preserve the distances between points.  

If we have some highly complex data that we project into some lower N dimensions, we will assign each point from our data a coordinate in this lower dimensional space, and the idea is that these N dimensional coordinates are ordered based on their ability to capture variance in the data.  Since we can only visualize things in 2D, this is why it is common to assess your MDS based on plotting the first and second dimension of the output.  

If you look at the output of an MDS algorithm, which will be points in 2D or 3D space, the distances represent similarity. So very close points = very similar, and points farther away from one another = less similar.

Working of MDS

The input to the MDS algorithm is our proximity matrix.  There are  two kinds of classical MDS that we could use:  Classical (metric) MDS is for data that has metric properties, like actual distances from a map or calculated from a vector .Nonmetric MDS is for more ordinal data (such as human-provided similarity ratings) for which we can say a 1 is more similar than a 2, but there is no defined (metric) distance between the values of 1 and 2.

Uses

Multidimensional scaling (MDS) is a means of visualizing the level of similarity of individual cases of a dataset. MDS is used to translate "information about the pairwise 'distances' among a set of n objects or individuals" into a configuration of n points mapped into an abstract Cartesian space.

8 0
3 years ago
A circuit contains a resistor, an inductor, and a capacitor. When an AC voltage is applied across the circuit, the impedance of
katen-ka-za [31]

Answer:

The impedance of  the circuit depends on the angular frequency of the voltage source.

Explanation:

  • In a electric circuit, the magnitude of  the impedance, is given by the following expression:

       Z = \sqrt{R^{2} + (Xl-Xc)^{2} (1)

        where R = Resistance

                   Xl = Inductive reactance = ω*L

                   Xc = Capacitive Reactance = 1/ωC

        and  ω = angular frequency of the voltage source.

  • So, it can be seen that the impedance depends on the value of the constants R,L and C, and on the angular frequency ω.

3 0
3 years ago
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