Digital process design is “process simulation for the digital age”. It enables rapid exploration of the decision space and accurate quantification of risk using validated high-fidelity models, to arrive at the optimal process design rapidly and systematically.

• gPROMS Process is the first general-purpose modeling environment to support all the key stages and activities of digital process design
• Construction of digital process twins using industry-leading high-fidelity models
• Calibration against experimental or plant data using state-of-the-art parameter estimation and model validation tools
• Global system analysis for rapid exploration of the decision space and quantification of risk
• Multivariate optimization to determine the optimal solution

Yes, gPROMS Process contains a wide range of general process and process-specific models. Key libraries include:

• All standard process models — heat exchangers, distillation and so on — for basic process modeling
• Advanced reactor models — high-fidelity catalytic, thermal cracking and electrochemical reactor models, for rapid and confident design of complex processes
• Adsorption — industry leading adsorption models for fast and robust solution of cyclic separation processes
• Hybrid data driven models — in cases where the physics or chemistry are not sufficiently defined, these can be combined with data-driven models to create hybrid first-principles — data models
• Specialist process-specific models —LNG exchangers, olefins cracking furnaces, polyolefins reactors and so on

Yes, the gPROMS Properties package covers a wide range of systems, including solid phases and reactive systems, and complex compounds such as associating compounds, polymers and electrolytes, within a single properties package.

It is designed to be easily usable by experts and non-experts, with easy configuration of materials, management of databases and results visualization. gPROMS Properties provides a unified approach across all process industry sectors, to ensure sustainability in technology development and maintenance.

gPROMS Properties — capabilities at-a-glance:

• Wide range of systems: gPROMS Properties handles gas and liquid fluid phases, solid phases and reactive systems
• Deals with complex compounds: In addition to standard fluids, gPROMS Properties handles associating compounds, polymers and electrolyte system
• Wide range of models: A wide range of standard industry thermodynamic models are implemented, with the ability to utilize existing parameter databanks and a flexible architecture to add new models
• Tight integration with process modeling: gPROMS properties has robust & efficient algorithms, with a wide range of flash calculation options
• Predictive accuracy: The unique SAFT-ϒ Mie handles situations where little or no experimental data is available
• Usable by experts and non experts: The environment provides easy configuration of materials, management of databases and results visualization

Yes, a key feature of gPROMS modeling environments is the ability to create high-fidelity custom models of processes to capture corporate knowledge and create competitive advantage.

You can easily create and maintain custom models using all the power of the gPROMS platform’s advanced process modeling language — with no need for programming. Models can then be published in libraries for other users across the organization.

Models can be validated against laboratory, pilot or operating data to fit empirical constants such as reaction kinetic parameters and heat transfer coefficients using gPROMS’s state-of-the-art parameter estimation capabilities.

Utilizing corporate knowledge to create competitive advantage:

The custom modeling capability enables you to:

• Create novel process units with novel configurations where suitable standard library models might not exist
• Create your own corporate model libraries
• Take advantage of existing investment in legacy models by moving them to a modern, maintainable platform
• Include more detail than is contained in the standard library models
• Create your own industry-specific flowsheeting simulator

Yes, typical examples include: 

Design, simulation and optimization of distillation columns, either with an equilibrium or a rate-based approach. Leverage in-house High-fidelity physical property modelling for robust and accurate predictions.

The adsorption library provides a robust off-the-shelf process modelling framework with custom modelling embedded throughout and integrated workflows to move from isotherm characterization to evaluation of performance for multi-bed units.

The flow transportation and heat exchange libraries contain the models necessary for complete process modelling.

Yes, typical examples include: 

• Help optimizing design and operation of green hydrogen production and carbon capture processes
• Achieve safe and efficient design and operation of hydrogen storage and distribution technologies
• Integrate production, purification, storage and distribution with end-use to ensure most efficient design

Yes, typical examples and applications include: 

• Pressure Swing Adsorption (PSA)
• Temperature Swing Adsorption (TSA)
• Evaluate true potential of an adsorbent under real process conditions coupling material properties with robust and rigorous physics-based process models
• Understand how current product in the market performs and where to focus to make improvements with respect to efficiency and performance
• Reduced modelling effort through “what-if” analyses
• Guide directions for future fiber sorbent material and process development

Models are built so that they can accommodate the exact level of detail required by the user, from simple heat or mass balance all the way to detailed first principle-modelling and industry accepted correlations.

Yes, gPROMS Process provide a unique technology for: 

• Detailed first-principles model combining full Molecular Weight Distribution (MWD) modelling with rigorous thermodynamics and advanced hydrodynamic modelling
• Predicting the shape of the MWD, not only the average molecular weight
• Predicting impact of polymer structure on its thermodynamic properties, including phase behavior
• Adjusting model parameters to fit production and property data for polymer grades currently manufactured
• Optimizing operating conditions and recipes to maximize production of polymers for selected grades