Difference between revisions of "Ronna Hamimah"

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It is highly recommended to '''involve experienced professionals''' with expertise in hydrogen safety and risk assessment during the design and implementation of a hydrogen storage system. They can provide valuable insights and help identify and mitigate potential risks associated with the specific storage design and application.
 
It is highly recommended to '''involve experienced professionals''' with expertise in hydrogen safety and risk assessment during the design and implementation of a hydrogen storage system. They can provide valuable insights and help identify and mitigate potential risks associated with the specific storage design and application.
 
Remember that optimizing a hydrogen storage design requires a multidisciplinary approach involving mechanical engineering, materials science, and safety considerations. It's advisable to consult with experts in the field and conduct a detailed feasibility study to achieve the best results within your budget.
 
Remember that optimizing a hydrogen storage design requires a multidisciplinary approach involving mechanical engineering, materials science, and safety considerations. It's advisable to consult with experts in the field and conduct a detailed feasibility study to achieve the best results within your budget.
 +
 +
 +
=='''Phyton Code'''==
 +
To optimize the storage of hydrogen at 8 bar pressure with a 1-liter capacity and a maximum budget of Rp500,000, we can approach it as an optimization problem by using a phyton's code below:
 +
 +
<syntaxhighlight lang="xml">
 +
from scipy.optimize import minimize
 +
 +
# Price and capacity
 +
price_per_unit = 100000  # Price per unit of hydrogen storage
 +
capacity_per_unit = 1  # Capacity of hydrogen storage per unit
 +
 +
# Maximum budget
 +
max_budget = 500000
 +
 +
# Objective function
 +
def objective_function(x):
 +
    return -x * capacity_per_unit
 +
 +
# Constraint function
 +
def budget_constraint(purchase_amount):
 +
    return max_budget - (price_per_unit * purchase_amount)
 +
 +
budget_constraint_eq = {'type': 'ineq', 'fun': budget_constraint}
 +
 +
# Initial value
 +
x0 = 0
 +
 +
# Bounds
 +
bounds = [(0, None)]
 +
 +
# Solve the optimization problem
 +
solution = minimize(objective_function, x0, method='SLSQP', bounds=bounds, constraints=[budget_constraint_eq])
 +
 +
# Print the results
 +
print("Status:", "Optimal" if solution.success else "No solution found")
 +
print("Number of hydrogen storage units to be purchased:", solution.x[0])
 +
print("Total storage capacity:", solution.x[0] * capacity_per_unit, "liters")
 +
print("Total cost:", solution.x[0] * price_per_unit, "Rupiah")
 +
 +
</syntaxhighlight>
 +
 +
we can also use phyton to show graphic between total storage and hydrogen storage optimazation:
 +
 +
<syntaxhighlight lang="xml">
 +
import matplotlib.pyplot as plt
 +
 +
# Price and capacity
 +
unit_price = 100000  # Price per unit of hydrogen storage
 +
unit_capacity = 1  # Capacity per unit of hydrogen storage
 +
 +
# Maximum budget
 +
max_budget = 500000
 +
 +
# Initialize variables
 +
best_unit_count = 0
 +
best_total_capacity = 0
 +
best_total_cost = 0
 +
 +
# Initialize lists for the graph
 +
unit_count_list = []
 +
total_capacity_list = []
 +
 +
# Iteration to find the optimal solution
 +
for unit_count in range(int(max_budget / unit_price) + 1):
 +
    total_capacity = unit_count * unit_capacity
 +
    total_cost = unit_count * unit_price
 +
 +
    if total_capacity > best_total_capacity and total_cost <= max_budget:
 +
        best_unit_count = unit_count
 +
        best_total_capacity = total_capacity
 +
        best_total_cost = total_cost
 +
 +
    # Add data to the lists for the graph
 +
    unit_count_list.append(unit_count)
 +
    total_capacity_list.append(total_capacity)
 +
 +
# Display the results
 +
print("Number of hydrogen storage units to be purchased:", best_unit_count)
 +
print("Total storage capacity:", best_total_capacity, "liters")
 +
print("Total cost:", best_total_cost, "Rupiah")
 +
 +
# Display the graph
 +
plt.plot(unit_count_list, total_capacity_list)
 +
plt.xlabel('Number of Hydrogen Storage Units')
 +
plt.ylabel('Total Storage Capacity (liters)')
 +
plt.title('Hydrogen Storage Optimization')
 +
plt.grid(True)
 +
plt.show()
 +
</syntaxhighlight>

Revision as of 00:19, 5 June 2023

Ronna Hamimah.jpg

Introduction

Hello there! My name is Ronna Hamimah (2106635543) , and I am a dedicated student pursuing a degree in Mechanical Engineering at University of Indonesia. With a passion for unraveling the complexities of machines and systems, I have immersed myself in the fascinating world of engineering. As a student, I strive for excellence in both my academic pursuits and practical applications

Design & Optimization of Pressurized Hydrogen Storage

Optimizing a 1-liter hydrogen storage design within a limited budget requires careful consideration of various factors. Here are a few suggestions to help you achieve a design concept and optimization for storing hydrogen at 8 bar pressure with a capacity of 1 liter and a maximum budget of Rp500,000.

1. Material Selection

Choose lightweight materials that can withstand high-pressure conditions while remaining cost-effective. Composite materials, such as carbon fiber reinforced polymers (CFRP) or aluminum alloys, could be potential options.

2. Tank Design

Opt for a cylindrical shape with reinforced walls to minimize material usage while maintaining structural integrity. Conduct thorough stress analysis to ensure the tank can withstand the desired pressure of 8 bar.

3. Safety Measures

Implement necessary safety features, such as pressure relief valves and rupture discs, to prevent over-pressurization and ensure the integrity of the tank.

4. Insulation

To reduce heat transfer and minimize energy loss, consider incorporating efficient insulation materials, such as foams or vacuum insulation panels.

5. Regulators and Valves

Include efficient pressure regulators and valves to control the release of hydrogen and maintain a stable pressure within the storage system.

6. Cost Analysis

Evaluate different suppliers, materials, and manufacturing methods to find the most cost-effective options within your budget. Consider both initial costs and long-term maintenance expenses.

7. Testing and Certification

Ensure the hydrogen storage design complies with industry standards and safety regulations. Perform thorough testing, including burst tests and leak checks, to verify the integrity of the storage system.


Conducting a comprehensive risk assessment is an essential part of designing any hydrogen storage system. Hydrogen is a highly flammable gas, and ensuring the safety of the storage system is of paramount importance. Here are some key aspects to consider during the risk assessment:

1. Fire and Explosion Hazards:

Hydrogen is highly flammable and can form explosive mixtures with air. Assess the potential for ignition sources, such as electrical equipment, static electricity, or open flames, and implement appropriate safety measures to mitigate the risks.

2. Ventilation:

Adequate ventilation is crucial to prevent the accumulation of hydrogen gas, which can create an explosive atmosphere. Ensure that the storage system is properly ventilated to disperse any leaked hydrogen gas.

3. Pressure Management:

Hydrogen storage systems operate under pressure. Assess the risks associated with over-pressurization or sudden pressure releases, and include pressure relief valves, burst discs, or other pressure safety devices to prevent catastrophic failures.

4. Material Compatibility:

Evaluate the compatibility of storage materials (e.g., cylinders, seals, valves) with hydrogen gas. Hydrogen can cause embrittlement in certain metals, potentially leading to failures. Use materials that are specifically designed for hydrogen storage or have been certified for compatibility.

5. Leak Detection and Monitoring:

Implement systems for detecting and monitoring hydrogen leaks. This can include gas sensors, hydrogen detectors, or leak detection solutions. Early detection of leaks allows for timely intervention and prevents the build-up of hydrogen gas.

6. Training and Safety Procedures:

Provide adequate training to personnel involved in handling, storing, and maintaining the hydrogen storage system. Develop clear safety procedures, emergency response plans, and protocols for handling hydrogen-related incidents.

7. Compliance with Regulations:

Ensure compliance with relevant safety regulations, codes, and standards for hydrogen storage systems. Familiarize yourself with local, national, and international guidelines to ensure the system meets all necessary requirements.


It is highly recommended to involve experienced professionals with expertise in hydrogen safety and risk assessment during the design and implementation of a hydrogen storage system. They can provide valuable insights and help identify and mitigate potential risks associated with the specific storage design and application. Remember that optimizing a hydrogen storage design requires a multidisciplinary approach involving mechanical engineering, materials science, and safety considerations. It's advisable to consult with experts in the field and conduct a detailed feasibility study to achieve the best results within your budget.


Phyton Code

To optimize the storage of hydrogen at 8 bar pressure with a 1-liter capacity and a maximum budget of Rp500,000, we can approach it as an optimization problem by using a phyton's code below:

from scipy.optimize import minimize

# Price and capacity
price_per_unit = 100000  # Price per unit of hydrogen storage
capacity_per_unit = 1  # Capacity of hydrogen storage per unit

# Maximum budget
max_budget = 500000

# Objective function
def objective_function(x):
    return -x * capacity_per_unit

# Constraint function
def budget_constraint(purchase_amount):
    return max_budget - (price_per_unit * purchase_amount)

budget_constraint_eq = {'type': 'ineq', 'fun': budget_constraint}

# Initial value
x0 = 0

# Bounds
bounds = [(0, None)]

# Solve the optimization problem
solution = minimize(objective_function, x0, method='SLSQP', bounds=bounds, constraints=[budget_constraint_eq])

# Print the results
print("Status:", "Optimal" if solution.success else "No solution found")
print("Number of hydrogen storage units to be purchased:", solution.x[0])
print("Total storage capacity:", solution.x[0] * capacity_per_unit, "liters")
print("Total cost:", solution.x[0] * price_per_unit, "Rupiah")

we can also use phyton to show graphic between total storage and hydrogen storage optimazation:

import matplotlib.pyplot as plt

# Price and capacity
unit_price = 100000  # Price per unit of hydrogen storage
unit_capacity = 1  # Capacity per unit of hydrogen storage

# Maximum budget
max_budget = 500000

# Initialize variables
best_unit_count = 0
best_total_capacity = 0
best_total_cost = 0

# Initialize lists for the graph
unit_count_list = []
total_capacity_list = []

# Iteration to find the optimal solution
for unit_count in range(int(max_budget / unit_price) + 1):
    total_capacity = unit_count * unit_capacity
    total_cost = unit_count * unit_price

    if total_capacity > best_total_capacity and total_cost <= max_budget:
        best_unit_count = unit_count
        best_total_capacity = total_capacity
        best_total_cost = total_cost

    # Add data to the lists for the graph
    unit_count_list.append(unit_count)
    total_capacity_list.append(total_capacity)

# Display the results
print("Number of hydrogen storage units to be purchased:", best_unit_count)
print("Total storage capacity:", best_total_capacity, "liters")
print("Total cost:", best_total_cost, "Rupiah")

# Display the graph
plt.plot(unit_count_list, total_capacity_list)
plt.xlabel('Number of Hydrogen Storage Units')
plt.ylabel('Total Storage Capacity (liters)')
plt.title('Hydrogen Storage Optimization')
plt.grid(True)
plt.show()