MEA CO₂ Process Optimization

@vronald183

Hi. I'm a chemical engineer and I'm an expert in process modeling and simulation using Aspen Plus and Aspen Hysys. I read the job description and I can complete the project. If you're interested in my services let me know. Kind regards.

@hayat38402

Hi, how are you doing? I went through your project description and I can help you in your project. I am a professional CHEMICAL ENGINEER with strong experience in handling projects across multiple domains of chemical engineering. I have extensive expertise in Aspen Plus and Aspen HYSYS, which allows me to develop accurate process simulations, perform sensitivity analyses, optimize operating conditions, and design efficient process flowsheets for various chemical and petrochemical systems. I have successfully completed 1000+ Projects for multiple regular clients all over the world. My areas of expertise include:  Process simulation and modeling (Aspen Plus / Aspen HYSYS)  Mass and energy balance calculations  Process design and optimization  Thermodynamics and reaction engineering  Heat exchanger and separation process analysis  Distillation, absorption, and extraction processes  Chemical process report writing and technical documentation We have good command over REPORT WRITING, we can show you many samples of our previous reports. Let’s discuss further details in the message box.

@tayabChemEngr

I have extensive experience optimizing MEA-based CO₂ capture in Aspen Plus, including coupling with external optimizers like MATLAB or Python for multi-objective studies. I will take your existing flowsheet, refine the rate‑based column model, and systematically adjust decision variables (lean loading, solvent circulation, reboiler duty, stage number) subject to constraints like CO₂ slip or column flooding. Using Aspen’s built‑in optimization or a custom script, I will minimize reboiler/condenser duty while maximizing capture efficiency, then translate energy savings into cost of capture. Deliverables include a fully converged Aspen Plus file, the optimization setup (variables, bounds, scripts), a concise report comparing baseline vs. optimized cases (energy per tonne CO₂, capture efficiency, cost), and sensitivity insights. I will reproduce your baseline within 2% and demonstrate measurable gains in at least two targets. I favor Aspen Plus for its rigorous thermodynamics and robust convergence, ensuring reliable results. Ready to begin.

@mzdesmag

Hello sir, Did go through your job description and glad to share that I have enormous experience in working with MEA CO₂ Process Optimization I'm a seasoned programmer and Engineer with quality experience in Flutter, React, Node.JS, SpringBoot, Frontend and Backend Development, Python, Matlab, R studio, C, C++, C#, OpenCV, OpenGL, Tesseract OCR, google vision, Statistical programming/R progamming data analysis Computing for Data Analysis Time Series & Econometric, Machine learning, AI, Deep learning, Matlab and Mathematica, 3D modeling, CAD/CAM,AutoCAD, 2D, Architectural Engineering, SolidWorks, Unity 3D, PCB, Electronics, Arduino, Automation, Embedded and Firmware , IOT, Electrical/Mechanical Engineering I am a TOP Rated Freelancer, and you can check my reviews here as well: https://www.freelancer.com/u/mzdesmag. Looking forward to potentially working together on this project. Thanks and Best regards, Adekunle.

@KestanWriters

As a seasoned professional researcher with a special focus in scientific analysis, my skills align perfectly with your project's needs. In particular, I have extensive experience in data analysis which is crucial for the MEA CO₂ process optimization task you've outlined. I have a great understanding of chemical engineering systems and can employ Aspen Plus or DWSIM to refine or rebuild your existing flow sheet. Moreover, finding innovative solutions and optimizing systems are at the core of my skillset. I am familiar with external optimization routines such as Python and MATLAB that can be used in tandem with Aspen Plus to achieve the most efficient results possible. When it comes to report writing and conveying complex information in a concise yet comprehensive manner, I excel. My report will not only meet but exceed your expectations by comparing baseline and optimized cases, quantifying energy duty per tonne CO₂ removed, capture efficiency and estimated cost of capture along with significant sensitivity insights. To sum up, my proficiency with Aspen Plus, DWSIM, Python and MATLAB coupled with my track record of delivering high-quality scientific reports make me an ideal candidate for your MEA CO₂ optimization project. Let's take this opportunity to push the boundaries of performance for your process!

@Abdulyaqs

i am an optimization algorithm expert who just solved a complex 2D topology problem. I have implemented Genetic Algorithms, Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and multi-objective NSGA-II across engineering domains. For your MEA absorption-stripping train in DWSIM, I will build a rigorous rate-based CO₂ capture model and couple it with an external Python optimizer. I will run NSGA-II to simultaneously minimize energy demand and operating cost while keeping capture ≥90%. I will also benchmark with single-objective GA or PSO if needed. Variables include solvent flow rate, column temperatures, pressure profiles, heat exchanger duties, and reboiler steam demand. The final DWSIM model will converge without manual tweaks across the design space. I will validate thermodynamics against literature, then deliver Pareto fronts, sensitivity plots, a methods report, the executable DWSIM file, and all Python coupling code. Everything open source and reproducible. Your lean loading and steam usage will be clearly reported. Share your flue-gas composition and column dimensions and I will start immediately.

@dvcontact

Hi, The absorber–stripper likely shows strong sensitivity to rich/lean amine loading and reboiler L/G ratio, which is why your current reboiler and condenser duties are high despite the column specs you provided and the natural-gas flue-gas composition. I will: - rebuild/refine your Aspen Plus (or DWSIM) flowsheet using your solvent properties and operating envelope, verify baseline within ±2% of your results - attach an external Python optimisation (or Aspen optimizer) with decision variables (reflux, solvent L/G, stripper pressure, lean loading bounds), constraints, and objective weighting First diagnosis: check solvent heats, CO2 loading isotherms, column hydraulics and reboiler duty coupling. I manage data integrity and convergence risk to avoid unrealistic duty reductions and ensure uptime-ready outputs. Ready to start—send the flowsheet and baseline data and I’ll run an initial convergence check within 24–48 hours. — Smith

@ashiqiitkgp

Hi there, As a Ph.D. researcher specializing in advanced algorithmic optimization and system modeling, I can execute a rigorous multi-objective optimization on your MEA absorption–stripping train. While standard approaches rely on Aspen Plus’s built-in optimizer (which struggles with complex, non-linear multi-objective surfaces), my expertise lies in coupling Aspen with external Python libraries via the COM interface. This enables advanced algorithms (like NSGA-II) to perfectly balance the trade-offs between minimizing reboiler duties, maximizing CO₂ capture, and lowering costs. Here is my execution plan: Baseline Validation: I will map your flowsheet in Aspen Plus (using the eNRTL property method for MEA) and tune parameters to reproduce your baseline within the strict ±2% margin. Rigorous Optimization: I will build the Python-Aspen bridge, defining critical decision variables (L/G ratio, lean loading, stripper pressure, feed stages) against your envelope constraints. Convergence: The algorithm will iterate to find the optimal operating point that delivers measurable improvements across your target metrics. Deliverables: You receive the fully converged Aspen Plus file, the Python script, a baseline-vs-optimized report quantifying energy (GJ/tonne CO₂) and costs, and clear retrofit recommendations. Let's connect to review your flowsheet and baseline data!