Conversion profiles for multiple reactor operating scenarios.
A Python tool for analyzing and comparing chemical reactor performance using synthetic kinetic datasets, numerical reaction rate estimation, and engineering visualization.
This project simulates multiple reactor operating scenarios, computes reactor performance metrics, visualizes reactor behavior, and exports analysis summaries for comparative evaluation.
The project combines chemical reaction engineering principles with numerical computing techniques for reactor performance analysis.
The Reactor Performance Analyzer can:
- Generate realistic synthetic reactor datasets
- Calculate reactant conversion
- Compute reaction rates using numerical differentiation
- Compare multiple reactor operating scenarios
- Rank reactor scenarios by average conversion
- Calculate percent performance improvement between scenarios
- Generate engineering plots for reactor analysis
- Export reactor performance summaries to CSV
This project implements several fundamental reaction engineering and numerical analysis concepts.
X = (CA_in − CA_out) / CA_in
rA = −dCA/dt
Reaction rates are estimated numerically using finite-difference methods with NumPy gradient calculations.
The analyzer compares multiple reactor operating conditions including:
- baseline reactor behavior
- faster reaction kinetics
- slower reaction kinetics
These analyses help evaluate reactor performance under different operating conditions.
The analyzer accepts reactor concentration data generated from synthetic kinetic models.
Example dataset:
| Time | CA_out_base | CA_out_fast | CA_out_slow |
|---|---|---|---|
| 0 | 0.97 | 1.01 | 1.01 |
| 1 | 0.76 | 0.46 | 0.89 |
| 2 | 0.56 | 0.22 | 0.79 |
| 3 | 0.39 | 0.08 | 0.69 |
| 4 | 0.31 | 0.04 | 0.63 |
This data can represent:
- simulated reactor experiments
- comparative kinetic studies
- synthetic process data for reactor analysis
Example results generated by the analyzer:
- Average Conversion (Base): 0.464
- Average Conversion (Fast Reaction): 0.698
- Average Conversion (Slow Reaction): 0.237
- Fast Reaction Improvement vs Base: +50.5%
Scenario Ranking:
- Fast Reaction
- Base
- Slow Reaction
The analyzer generates several plots used in reactor performance analysis:
- Conversion vs Time
- Reaction Rate vs Time
- Average Conversion by Scenario
These plots help engineers compare reactor behavior and evaluate reaction performance under different operating conditions.
Reaction rate over time for multiple reactor operating scenarios.
Comparison between average conversions of multiple reactor operating scenarios.
- Generate or load reactor concentration data
- Calculate reactant conversion
- Estimate reaction rates from concentration data
- Compare reactor operating scenarios
- Generate reactor performance plots
- Export performance summaries to CSV
git clone https://github.com/MatthewNguyen865/reactor-performance-analyzer.git
pip install -r requirements.txt
python main.py
reactor-performance-analyzer/
|
|--- core/ # analysis and computation modules
| |--- comparisons.py
| |--- data_extractor.py
| |--- metrics.py
| |--- statistics.py
|
|--- example_plots/ # exported engineering plots
| |--- average_conversion_comparison.png
| |--- conversion_plot.png
| |--- reaction_rate_plot.png
|
|--- output/ # exported analysis summaries
| |--- reactor_summary.csv
|
|--- config.py
|--- data.csv
|--- data_generator.py
|--- main.py
|--- plotting.py
|--- README.md
|--- requirements.txt
The goal of this project is to practice:
- chemical reaction engineering concepts
- numerical data analysis
- scientific programming in Python
- engineering data visualization
- modular software design
- engineering analytics workflows
Planned improvements include:
- support for multiple experimental datasets
- regression-based kinetic parameter estimation
- automated engineering report generation
- support for additional reactor models
- Python
- NumPy
- Pandas
- Matplotlib
Matthew Nguyen
Chemical Engineering Student
Texas A&M University