<jupyter_start><jupyter_text>**Heat-Exchanger Estimation Algorithm**<jupyter_code># Created by: <NAME>
# Details:    
# Date: 
#Variable Declaration
N = 1000
T = 100
dt = T/N

#Noise Intensity
a1 = 0.00015
a2 = 0.0001
a3 = 0.0001
a4 = 0.0001

#Inputs and Outputs
fc   = float(input('Enter Input Flowrate of Cold Stream bet.n 0.002 to 0.00555 kg/s: '))
fh   = float(input('Enter Input Flowrate of Hot Stream bet.n 0.009 to 0.02 kg/s: '))
Tcin = int(input('Enter Input Temperature of Cold Stream bet.n 280 to 305 K: '))
Thin = int(input('Enter Input Temperature of Hot Stream bet.n 345 to 360 K: '))
h    = int(input('Enter Heat Transfer Coefficient: '))
Ac   = float(input('Enter Cross-sectional Area of Cold Stream: '))
Ah   = float(input('Enter Cross-sectional Area Hot Stream: '))
mc   = float(input('Enter mass Cold Stream: '))
mh   = float(input('Enter mass Hot Stream: '))
Cpc  = float(input('Specific Heat of Cold Stream: '))
Cph  = float(input('Specific Heat of Hot Stream: '))
r    = int(input('Noise Coefficient: '))
#Initialization
import array as arr
x1 = []
x2 = []
x1.append(298)
x2.append(353)
for i in range(0,10):
  x1.append(x1[i] + 5)
x1<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.14261603375527426, 'fraction_numerical': 0.06582278481012659, 'mean_word_length': 4.294642857142857, 'pattern_counts': {'":': 0, '<': 6, '<?xml version=': 0, '>': 6, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '518669', 'license': 'MIT', 'n_tokens_mistral': 496, 'n_tokens_neox': 430, 'n_words': 136, 'path': 'heatExchanger.ipynb', 'repo_name': 'Shnagarsheth/HeatExchangerEstimationAlgorithm', 'size': '1197'}