Answer:
1.3cm
Explanation:
the arrow is 3 lines past the 1 so it is 1.3cm
Answer:
a. 4
b. 1 m
Explanation:
According to the question, the data is as follows
The Density of water at 20 degrees celcius is 1000 kg/m^3
Viscosity is 0.001kg/m/.s
Velocity V = 25 cm/s
V = 0.25 m/s
Now
a. The creeping motion is
As we know that
Reynold Number = (Density of water × V × d) ÷ (Viscosity)
1 = (1,000 × 0.25 × d) ÷ 0.0001
d = (1 × 0.001) ÷ (1,000 × 0.25)
= 4E - 06^m
= 4
b. Now the sphere diameter is
Reynold Number = (Density of water × V × d) ÷ (Viscosity)
250,000 = (1,000 × 0.25 × d) ÷ 0.0001
d = (250,000 × 0.001) ÷ (1,000 × 0.25)
= 1 m
Answer:
a) Please see attached copy below
b) 0.39KJ
c) 20.9‰
Explanation:
The three process of an air-standard cycle are described.
Assumptions
1. The air-standard assumptions are applicable.
2. Kinetic and potential energy negligible.
3. Air in an ideal gas with a constant specific heats.
Properties:
The properties of air are gotten from the steam table.
b) T₁=290K ⇒ u₁=206.91 kj/kg, h₁=290.16 kj/kg.
P₂V₂/T₂=P₁V₁/T₁⇒ T₂=P₂T₁/P₁ = 380/95(290K)= 1160K
T₃=T₂(P₃/P₂)⁽k₋1⁾/k =(1160K)(95/380)⁽⁰°⁴/₁.₄⁾ =780.6K
Qin=m(u₂₋u₁)=mCv(T₂-T₁)
=0.003kg×(0.718kj/kg.k)(1160-290)K= 1.87KJ
Qout=m(h₃₋h₁)=mCp(T₃₋T₁)
=0.003KG×(1.005kj/kg.k(780.6-290)K= 1.48KJ
Wnet, out= Qin-Qout = (1.87-1.48)KJ =0.39KJ
c)ηth= Wnet/W₍in₎ =0.39KJ/1.87KJ = 20.9‰
Since this traffic flow has a jam density of 122 veh/km, the maximum flow is equal to 3,599 veh/hr.
<u>Given the following data:</u>
- Jam density = 122 veh/km.
<h3>How to calculate the
maximum flow.</h3>
According to Greenshield Model, maximum flow is given by this formula:

<u>Where:</u>
is the free flow speed.
is the Jam density.
In order to calculate the free flow speed, we would use this formula:

Substituting the parameters into the model, we have:

Max flow = 3,599 veh/hr.
Read more on traffic flow here: brainly.com/question/15236911
Historical data is examined for patterns that are then used to make predictions is one of the analysis methods that describe neural computing
What is neural computing?
A neural network is an artificial intelligence technique that instructs computers to analyze data in a manner modeled after the human brain. It is a kind of artificial intelligence technique known as deep learning that makes use of interconnected neurons or nodes in a layered structure to mimic the human brain.
Historical data is nothing but the existing network data which is stored for the predicting in future
In the context of neural networks, the word "pattern" refers to a collection of activations over a group of units (neurons).
Hence to conclude neural netwoks almost describes the patterns
To know more on neural networks follow this link
brainly.com/question/27371893
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