Hello my name is Ramadhan Bagus (2206100306)

## Hydrogen Tank Design and Optimization Project

Specification:

```  1. Hydrogen Tanks volume is approximately 1 liter.
2. Hydrogen is compressed to 8 bar.
3. Normal operating condition (room temperature and humidity).
4. Maximum budget is Rp500.000
```

Material Selection

```  SS-304 material by looking at the ASME II D table, a yield strength is 30,000 psi, based by calculations using ASME VIII, this material withstand a pressure of 32 bar, this tube is sufficient to withstand a pressure of 8 bar.
```

Design

```  Based on ASME VIII Div 1, we get
Joint efficiency (E) = 0,85
MAWS (SS-304 Seamless Pipe) = 30000 psi
OD = 3,94 inch = 100.76 mm
Outside radius (r) = 50.038 mm
Corrossion Allowance (CA) = 0,01 inch = 0.254 mm
Thickness (ta) = 0,05 inch = 1.27 mm
Thickness (t) = (ta-CA) = 0,04 inch = 1.016 mm
```
```  Find Diameter and Height
In this case we know that Volume of Tanks is V = πr^2h, so we know that V = 1L or 0,001 m^3 and OD 10cm (0.1 m)
0.001 m^3 = 3.14 x 0.05^2 x h
h = 0.13 m = 13 cm, so height of the tanks is 13 cm ```

Manufacturing Process

```  Prepare the chosen materials in accordance with the design specifications.
Manufacturing process may involve cutting, forming, and welding the steel plates.
```

Quality Assurance and Testing

```  Hydrogen storage systems are subject to specific regulations and standards, depending on jurisdiction and application. Ensure compliance with applicable codes, regulations and industry standards, such as those set by the American Society of Mechanical Engineers (ASME) or the International Organization for Standardization (ISO).
```

Total Cost

```  In the online shop we get price of SS - 304 size 100x400 with thickness 1.2 is Rp120.000, and add estimated cost in machining and labour Rp200.000. So total cost is approx Rp320.000
```

Coding

```  import numpy as np
import matplotlib.pyplot as plt
def function(x):
"""
Contoh Fungsi Persamaan yang didapat dari metode numerik optimasi tangki.
Args:
x (numpy.ndarray): Array nilai x.
Returns:
numpy.ndarray: Array nilai fungsi.
"""
# Mengganti dengan fungsi yang ingin ditinjau
y = x**2 + np.sin(x)
return y
def numerical_method(x_start, x_end, num_points):
"""
Metode numerik untuk menyelesaikan fungsi.
Args:
x_start (float): Nilai x awal.
x_end (float): Nilai x akhir.
num_points (int): Jumlah titik yang dihasilkan.
Returns:
tuple: Tupel berisi array nilai x dan array nilai fungsi.
"""
x = np.linspace(x_start, x_end, num_points)
y = function(x)
return x, y
# Input parameter
x_start = -5.0
x_end = 5.0
num_points = 100
# Menerapkan metode numerik
x, y = numerical_method(x_start, x_end, num_points)
# Menampilkan grafik hasil metode numerik
plt.plot(x, y)
plt.xlabel('x')
plt.ylabel('f(x)')
plt.title('Optimasi Tangki')
plt.grid(True)
plt.show()
```