SIMULATION FRAMEWORK
FOR THE
PROCESS INDUSTRY

Work with Flowsheets, smarter.

Sync

Sync flowsheets across all your devices.

Version

Keep track with automatic flowsheet versioning.

Sort

Organize flowsheets chronologically or by tags.

Tag

Annotate and access flowsheets with tags and remarks.

Preview

Navigate via flowsheet thumbnail and key flowsheet parameters. 

Share

Share flowsheets within your organization. 

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DASHBOARD

Dashboard is our simulation file management system. It keeps track of simulation flowsheet versions, their purpose, their context, and when, how, and by whom they have been used. 

 

It is for every engineer who works with many flowsheets and where transparency and control over knowledge is a must. 

Design of Experiments (DoE)

Design of Experiments (DoE) enables you to run a series of simulations. Based on a simulation flowsheet, you specify input and output parameters in Excel, VBA, R, or Python. The simulations are run in parallel in the background. 

 

It is for every engineer who samples a design space to find the optimum conditions of a process. 

Take-Home Exercise/Exam (THEE)

Take-Home Exercise/ Exam generates any number of flowsheet simulations for classroom exercises or as individualized exams. 

 

It is for every academic teacher who transforms lectures and seminars from in-class teaching to online self-study and exam settings during the coronavirus pandemic (COVID-19). 

Multivariate Sensitivity Study (MSS)

Multivariate Sensitivity Study calculates the multidimensional solution space (hypercube) of a flowsheet simulation. The number of input parameters can be increased freely, to widen the solution space. Multivariate Sensitivity Studies are calculated on a cluster of instances. 

 

It is for every engineer to visualize solution spaces for multi-objective optimization problems with pareto optimal points to support decision making. 

ANN Surrogate Models 

ANN Surrogate Models replace rigorous first principle models of unit operations or flowsheets. Input and output are related through the pattern of the trained neural network. 

 

It is for every engineer who needs faster model predictions than flowsheet simulators can provide. Surrogate Models run independent of the flowsheet simulator. 

Surrogate Models in Process Simulators

Surrogate Models come from several sources, e.g., process control systems (PCS; plant data) or process simulators (rigorous first-principle modelssimulation data). Sensitivity studies compare the ANN predictions with rigorous calculations.

 

It is for every engineer who verifies that the surrogate model meets the underlying (simulated) physics precisely enough. 

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