1D Heat Transfer Analytical Wall

In summary, the engineer finds that the time scale for the temperature within the wall to respond to the outside heat transfer is much longer than the time scale for the thermal inertia of the wall to respond to the outside heat transfer. Therefore, they conclude that it is valid to use a lumped parameter model for the slab, with the temperature profile within the slab treated as uniform.
  • #1
kartini99
1
0
TL;DR Summary
Problem finding the correct temperature value for unexposed heat by using separation variables.
Hello everyone,

I'm trying to solve the transient heat transfer problem within the ID wall.
The material is steel, and it is isotropic.
The properties are given below :
L = 5 mm
qin = 0
Tinf = 100 deg C
Tini = 20 deg C
rho = 7850 kg/m3
cp = 460 W/Kg.K
k = 45.8 W/m.K
h = 20 W/m^2.K
alpha = k / rho*cp
t = 360 second
Fo = alpha * t / (L**2)

By using the attached formulation, I got the root of the function lambda is 0.03303492.
However, I increased the time, and the temperature in the unexposed wall was reduced. and when I change the time to 1 (one), the value shows almost like the T imposed, which is 100. Kind of the opposite way, Kindly any body help me with that. I also attached the script below

Python:
from scipy.optimize import fsolve
import numpy as np

def xtanxmbi(x, Bi):
    # tan = np.tan(x*np.pi/180)
    # return np.arctan(tan)*Bi-x
    # return (1/np.tan(x))*Bi-x
    return (np.cos(x)/np.sin(x))*Bi-x

# W = 1
# H = 0.1
L = 2.5 / 1000
qin = 0
Tinf = 100
Tini = 20
rhocp = 7850 * 460
k = 45.8
h = 20
alpha = k / rhocp
t = 360
Fo = alpha * t / (L**2)
print(f"The Fo is = {Fo}")
N = 6
n = 6
Bi = h * L / k
theta = np.zeros((n, N))
x0 = np.arange(n) * np.pi + 0.3
ans = fsolve(xtanxmbi, x0=x0, args=(Bi), full_output=True)
if ans[2] != 1:
    print("error solving roots of transcendental equation")
roots = ans[0]
Bi5 = Bi
print(f"Bi = {Bi5} , {roots}")

for i in np.arange(n):
    An = 2* np.sin(roots[I]) / (roots[I]+np.sin(roots[I])*np.cos(roots[I]))
    print(f"An = {An}")
    x = 1
    theta[I] = An * np.exp((-roots[I] ** 2 )* Fo) * np.cos(roots[I] * x)
    print(f"value of theta = {theta}")
    print(type(theta))
# Cn_0 = 4.0 * np.sin(roots[0]) / (2.0 * roots[0] + np.sin(2.0 * roots[0]))
# print(f"value of Cn is ={Cn_0}")
# theta_0 = Cn_0 * np.exp(-roots[0] ** 2 * Fo) * np.cos(roots[0] * x)
# print(f"value of theta is ={theta_0}")
sum_theta = theta[0, 0]
# print(sum_theta)

T = Tini + (Tinf - Tini) * sum_theta
print(f"value T={T}")
[/I][/I][/I][/I][/I][/I][/I]
 

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  • #2
Please provide a diagram.
 
  • #3
The units of Cp are incorrect
 
  • #4
As an engineer, my approach to this is entirely different, and I actually get a simple accurate answer. Looking at the time scale for flattening of the temperature within the wall ##L^2/\alpha##, I conclude that this time scale is only a few seconds, compared to the time scale for the thermal inertia of the wall to respond to the outside heat transfer ##\tau = \rho C_p L/h##, which is on the order of 900 sec. So it is valid to use an lumped parameter model for the slab, with the temperature profile within the slab treated as uniform. For this description, the temperature is a function only of time, given by $$T=100-(100-20)e^{-t/\tau}$$At 360 seconds, this gives a temperature of about 46 C.
 

FAQ: 1D Heat Transfer Analytical Wall

What is 1D heat transfer in the context of an analytical wall?

1D heat transfer refers to the transfer of heat through a wall in one dimension, typically along the thickness of the wall. This simplification assumes that heat flows in a straight line from one side of the wall to the other, ignoring any variations in the other two dimensions. This approach is useful for analyzing thermal performance in a straightforward and manageable way.

How is the temperature distribution across a 1D wall determined?

The temperature distribution across a 1D wall can be determined using Fourier's law of heat conduction. By solving the heat equation, which is a partial differential equation, one can find the temperature profile as a function of the position within the wall. For steady-state conditions, this often simplifies to a linear temperature gradient if the thermal conductivity is constant.

What assumptions are made in 1D heat transfer analysis?

Several assumptions are typically made in 1D heat transfer analysis: (1) Heat transfer is unidirectional, (2) The material properties (thermal conductivity, density, specific heat) are homogeneous and isotropic, (3) Steady-state conditions are assumed unless otherwise specified, and (4) There is no internal heat generation within the wall.

What are the boundary conditions used in 1D heat transfer problems?

Boundary conditions for 1D heat transfer problems can include specified temperatures at the surfaces (Dirichlet conditions), specified heat fluxes or insulated surfaces (Neumann conditions), or convective heat transfer with an external fluid (Robin conditions). These conditions are essential for solving the heat equation and obtaining a unique solution.

How does thermal conductivity affect heat transfer through a 1D wall?

Thermal conductivity is a measure of a material's ability to conduct heat. In a 1D heat transfer scenario, higher thermal conductivity means that heat will transfer more efficiently through the wall, leading to a smaller temperature gradient. Conversely, lower thermal conductivity will result in a larger temperature gradient for the same amount of heat transfer.

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