How do chemical engineers use computer simulations to optimize processes?

In my experience using the dynamic simulation model of the process will give a more realistic result for plant operations and Troubleshooting. Dynamic model will use the actual equipment and Control valve sizes thus providing an operation oriented result. And various scenarios like turn-down or equipment failure cases can be created to understand the bottlenecks.

Computer Simulations are the Software that can be used to optimize process parameters to predict process behaviors. Mathematics models are incorporated

In my experience I found mathematical models and process simulations are extremely helpful for process optimization. In an operating plant or unit operation no one wishes to disturb the parameters to see the impact on output parameters. As this will impact the product quality and quantity both.Therefore a simulation provides a flexibility to carry out the Design of Experiments and find the best set of operating parameters, which will provide the optimum process output. This way we can avoid/ minimize the disturbances in actual plants.

Process engineers can use computer simulation to feed live plant data and thus optimise the process by comparing the results for each trails by keep the basis of changes.. like what if pressure is reduced or flow-rate is reduced or increased. Simulation are also handy will checking rating or pre-designed facilities or equipment

Chemical engineers use computer simulations to optimize processes by employing computational models that simulate and predict the behavior of chemical systems. These models incorporate fundamental principles of chemistry, physics, and thermodynamics to represent the involved components' interactions, kinetics, and properties. The models can range from simple equations to more complex differential equations. These simulations allow engineers to understand and analyze complex processes, explore various scenarios, and optimize process design and operation. Simulation software provides a platform for constructing process models and running simulations. They are also useful for predicting the behavior of processes at different scales.

Apart from the more conventional design, testing and optimization benefits, simulations can also provide a risk free training environment for operators and plant personnel. Complete process simulations (or digital twins) have advanced to the point where the outputs can be fed into an offline replica of the DCS / PLC, creating a a training environment that allows the user to become familiar with actual plant SCADA. This allows users to practice startup or shutdown sequences, abnormal event management and troubleshooting in a safe environment.

Thermodynamics: The software incorporates thermodynamic models to accurately predict the phase behavior and properties of chemicals under different conditions. Reaction Kinetics: For processes involving chemical reactions, simulation software considers reaction kinetics to predict the conversion of reactants and the formation of products. Heat and Mass Transfer: Engineers can model heat exchangers, distillation columns, and other unit operations to optimize heat and mass transfer processes. Pressure Drop and Fluid Flow: Simulation tools simulate fluid flow through pipes and equipment, accounting for pressure drops, flow rates, and pumping requirements.

And all the above tasks they do super fast. They also help in process selection. Troubleshooting of a running plant can also be done using simulation software.

Chemical engineers use computer simulations to model and optimize processes by digitally testing different conditions, troubleshooting, and employing optimization algorithms. This virtual experimentation helps identify the most efficient and cost-effective operating parameters, enhancing process design and minimizing risks.

Computer simulations are important for chemical engineering to understand the complex behavior of processes, perform various operations without risk involvement. The major importance is in the predictions of changes depending on sustainability and reliability

Having a process simulation model allows to save time and efforts with very accurate results to predict the performance of the process when the process engineers chooses adequately the modeling parameters. Process simulators oftenly are core part during design, plant startups, process troubleshooting and engineer training, this leads to save downtime and optimize process and resources.

Using industrial processes as an example: 1) First the process is to be modelled. A steady state and then dynamic state model can be developed. This is done to meet the target output required from the process. 2) The key parameters of the process which were identified will be varied to see their effect on the output of the process. Based on that the most suitable values would be selected for each parameter and specified in the model. 3) Safety, energy requirements and the economics of the process are to be considered while selecting the optimized values for each process parameter being considered.

Chemical engineers can use computer simulation with DCS system to: >Monitor real-time process performance. >Optimise control parameters for better efficiency >Analyze scenarios and predict system behaviour- Model Predictive Control(MPC) >Implement predictive control strategies >Detect faults and can train operators effectively using Aspen Plus simulation.

Computer simulations are best way to Learn, understand and optimize the process and to predict the newer results. some of the examples I'd like to mention here are in early stage of my career when I first show one of these simulations it made me eager to know more about what is going on behind the scenes I started using and learn through it, also we used to experiment on it the things we can't experiment on the real plant it gave us more insights on how our process and be more efficient and optimized. It thought us how particular equipment needs to be started or stopped, as you all know there are numerous equipment get involved in particular plant which again has numerous logics and interconnectivity it helped us understanding it easily.

Environmental impact simulations have enabled us to evaluate the potential emissions and waste generated by a process. This is crucial for designing processes that minimize the release of harmful substances into the environment, helping us comply with stringent environmental regulations and reduce our ecological footprint.

Some softwares used by chemical engineers for process optimization include: AspenTech: Aspen HYSYS, Aspen Plus, Aspen Exchanger Design & Rating (EDR), Aspen Process Explorer. CHEMCAD: CHEMCAD Suite, CC-THERM, CC-FLASH, CC-PSD (Process Simulation Suite). COMSOL: COMSOL Multiphysics, COMSOL Reaction Engineering Lab, COMSOL Heat Transfer Module. MATLAB/Simulink: MATLAB for numerical computing, Simulink for modeling and simulating dynamic systems. DWSIM: An open-source chemical process simulator. VMGSim: A process simulation software for modeling oil and gas processes. ProSim: ProSimPlus Suite for process simulation and optimization.

I would rather talk about the method for process optimization. These steps need a powerful software with ability to run thermodynamics, HMB, AI and ML modeling, etc. 1- Build the DMX 2- Define the leading & Dependant parameters from the DMX leading & Dependant parameters to the objective function 3- Run the Objective Function 3- Introduce

Software for projecting operation performance in membrane based water systems are other examples. Eg DuPont Wave, Ionpure CEDI, Cadix Ion Exchange, Antiscalant performance software, etc. Many of these and others are proprietary.

By optimizing processes for maximum energy efficiency and minimum waste production, thermodynamic modeling not only reduces environmental impact but also helps in reducing operational costs.

Nowadays, it is important to highlight that with AI and machine learning development, a lot of benefits and good results for the process optimization is becaming more viable.

The challenges associated with FP (First Principles) complexity can be diminished with 1-Reduced Order Model 2-Real data collection from the field Both of above approaches provide a quick path to have an AI inference with ability to predict the KPIs

The benefits include: ? Being able to observe the effect of changes to the parameters that govern a process at little or no cost. ?They are a useful in the selection of the most appropriate values for the different parameters that are associated with a process. ? Generating useful data for the predictive analytics of a process without having to necessarily run that process in real life. ?They help to also save time, that is the time required to conduct multiple experiments. The challenges include: ?The real world is dynamic and hence computer simulations are not 100% accurate. ?Difficulty may arise in optimizing certain novel processes due to their complexities.

I believe that using computer simulations can improve the accuracy of the process optimization that engineers seek. It can be set and tested with lots of different parameters to have a better overview of the desired outcomes. On the other hand, one always has to be aware that, no matter how well the computer simulation is parameterized, it is still a simulation. Therefore, a lot of attention is still needed when trying to scale it up to industrial level.

With the ability to accurately model complex systems and processes. Computer simulation has become an indispensable tool for chemical engineers by providing insights that lead better design, enabling them to understand and predict the behavior of chemical reactions and processes. Additionally, customizable scenarios, real time integration and performance monitoring .

As Professor assistant in chemical engineering with over decade experience in teaching Chemical Engineering software, I believe that chemical engineers will undoubtedly need to learn and master specialized software, especially simulation software, to solve the challenges of the 4th industrial revolution. The development of software has provided additional capabilities for engineers, especially chemical engineers, due to the introduction of new technologies, witch for the future generation of chemical engineers, university lecturers should have a special look at this issue

In my experience, process engineers should prioritize understanding individual instrument mechanisms over relying solely on computerise HMI for data interpretation. For example, in my current plant, when the flow meter that shows a continuous drop, it initially seemed like a pump or clogging issue. However, by examining other related parameters like pressure, acid concentration, and temperature, we discovered they were normal, pointing out that the flow is normal, rather the flowmeter itself is faulty.