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List of chemical process simulators
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List of chemical process simulators
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This is a list of software used to simulate the material and energy balances of chemical process plants. Applications for this include design studies, engineering studies, design audits, debottlenecking studies, control system check-out, process simulation, dynamic simulation, operator training simulators, pipeline management systems, production management systems, digital twins.

Software Developer Applications Operating System License URL
Advanced Simulation Library (ASL) Avtech Scientific Process data validation and reconciliation, real-time optimization, virtual sensing and predictive control Windows, Linux, FreeBSD, Mac open-source (AGPLv3) [1]
APMonitor APMonitor MATLAB/Python/Julia-based data reconciliation, real-time optimization, dynamic simulation and nonlinear predictive control Windows, Linux open-source (BSD-2-Clause) [2]
Apros Fortum and VTT Technical Research Centre of Finland Dynamic process simulation for power plants Windows closed-source [3]
ASCEND ASCEND Dynamic process simulation, general purpose language Windows, BSD, Linux open-source (GPLv2) [4]
Aspen Custom Modeler (ACM) Aspen Technology Dynamic process simulation Windows closed-source [5]
Aspen HYSYS Aspen Technology Process simulation and optimization Windows closed-source [6]
Aspen Plus Aspen Technology Process simulation and optimization Windows closed-source [7]
ASSETT Kongsberg Digital Dynamic process simulation Windows closed-source [8]
BatchColumn Fives ProSim Simulation and Optimization of batch distillation columns Windows closed-source [9]
BATCHES Batch Process Technologies, Inc. Simulation of recipe driven multiproduct and multipurpose batch processes for applications in design, scheduling and supply chain management Linux closed-source [10]
BatchReactor Fives ProSim Simulation of reactors in batch mode Windows closed-source [11]
BILCO CASPEO Software to simulate mass balances using a data reconciliation algorithm Windows closed-source [12]
BioSTEAM Yoel Cortes-Pena & BioSTEAM Development Group Design, simulation, and costing of biorefineries under uncertainty Windows, Mac, Linux open-source (BSD-3-Clause) [13]
CADSIM Plus Aurel Systems Inc. Dynamic process simulator with CAD front end and process stream specification flexibility Windows closed-source [14]
ChromWorks YPSO-FACTO Chromatographic process design, simulation & optimization Windows closed-source [15]
CHEMCAD Chemstations Software suite for process simulation Windows closed-source [16]
CHEMPRO EPCON Process Flow Simulation, Fluid Flow Simulation, & Process Equipment Sizing Windows closed-source [17]
Cycad Process CM Solutions Process simulation and drawing package for minerals and metallurgical fields Windows closed-source [18]
Cycle-Tempo Asimptote Thermodynamic analysis and optimization of systems for the production of electricity, heat and refrigeration Windows closed-source [19]
COCO simulator + ChemSep AmsterCHEM Steady state process simulation based on CAPE-OPEN Interface Standard Windows open-source (Coco License 3.4) [20] [21]
D-SPICE Kongsberg Digital Dynamic process simulation Windows closed-source [22]
Design II for Windows WinSim Inc. Process simulation Windows closed-source [23]
Distillation expert trainer ATR Operator training simulator for distillation process closed-source [24]
Dymola Dassault Systèmes Modelica-based dynamic modelling and simulation software Windows, Linux closed-source [25]
DynoChem Scale-up Systems Dynamic process simulation and optimization Windows closed-source [26]
DYNSIM AVEVA Dynamic process simulation Windows closed-source
Dyssol[1] DyssolTEC Dynamic flowsheet simulation of solids processes Windows, Linux open-source (BSD-3-Clause) [27]
DWSIM Daniel Medeiros, Gustavo León and Gregor Reichert Process simulator Windows, Linux, macOS, Android, iOS open-source (GPLv3), freemium [28]
EMSO ALSOC Project Modelling, simulation and optimisation, steady state and dynamic, equation oriented with open source models Windows, Linux closed-source (UI), open-source (library)[29]

[30]

EQ-COMP Amit Katyal Vapor Liquid Equilibrium Software Software-as-a-Service closed-source [59]
FlowTran FlowTran Transient single phase pipeline simulation closed-source [31]
GAMS GAMS General Algebraic Modeling System (GAMS) Windows, Linux, Mac OS, Solaris closed-source [32]
gPROMS PSE Ltd Advanced process simulation and modelling closed-source [33]
HSC Sim Outotec Oyj Advanced process simulation and modelling, Flowsheet simulation Windows closed-source [34]
HYD-PREDIC Amit Katyal Multiphase flow assurance and hydrate modelling Software-as-a-Service closed-source [35]
HYDROFLO Tahoe Design Software Piping System Design with Steady State Analysis Windows closed-source [36]
Indiss Plus® Corys Dynamic process simulator for hydrocarbons, chemicals Windows closed-source [37]
ICAS KT-Consortium Integrated Computer-Aided System Windows closed-source [38]
IDEAS Andritz Automation Dynamic simulator for pulp, oil sands, potash, and hard rock mining Windows closed-source [39]
iiSE Simulator iiSE company Equation oriented chemical process simulator and optimizer Windows, Linux closed-source [40]
INOSIM Inosim Software GmbH Discrete-event dynamic simulation software for mixed batch-continuous processes in the chemical and pharmaceutical industry Windows closed-source [41]
INVIDES Rheinmetall Electronics Visual, dynamic Process Simulation framework for power plants, pipeline systems, upstream, midstream and downstream oil & gas plants, renewable energy plants and hydrogen plants Windows closed-source [91]
IPSE GO SimTech GmbH Process simulation application that works in the browser, provides a visual flowsheet editor and supports online collaboration Software-as-a-Service closed-source [42]
IPSEpro SimTech GmbH Visual process simulation framework with ready-to-use model libraries for power systems, desalination, flue gas cleaning etc. and option to define own model libraries Windows closed-source [43]
ITHACA Element Process General purpose dynamic (continuous and discrete-event) chemical process simulator. Windows freemium, closed-source [44]
JADE GSE Systems Dynamic process simulation Windows closed-source [45]
JModelica.org Modelon AB Process simulation Windows, Linux, macOS closed-source[2] [46]
K-Spice Kongsberg Digital Dynamic process simulation Windows closed-source [47]
LedaFlow Kongsberg Digital Transient multiphase pipeline simulation Windows closed-source [48]
LIBPF simevo C++ Library for process flowsheeting Linux, Windows, macOS closed-source [49]
METSIM Metsim International General-purpose dynamic and steady-state process simulation system Windows closed-source [50]
Modelon Impact Modelon AB General-purpose, multi-domain dynamic and steady-state process and system simulation system Linux (SaaS, on-prem), Windows closed-source [51]
Mimic Simulation Software MYNAH Technologies First-principles dynamic simulator built for software acceptance testing and operator training systems Windows closed-source [52]
Mobatec Modeller Mobatec Advanced Dynamic (Steady-State) Process Modelling Environment Windows closed-source [53]
NAPCON ProsDS Neste Engineering Solutions Oy Dynamic process simulation Windows closed-source [54]
OLGA Schlumberger Transient multiphase pipeline simulation Windows closed-source [55]
OLI Analyzer OLI Systems, Inc. Chemical phase equilibrium simulation featuring electrolytes Windows closed-source [56]
Omegaland OMEGA Simulation Dynamic process simulation Windows closed-source [57]
OptiRamp Statistics & Control, Inc. Real-time Process Simulation and Optimization, Multi variable Predictive Control Windows closed-source [58]
OpenModelica Open-Source Modelica Consortium General purpose simulation Linux, macOS open-source (OSMC-PL 1.2) [59]
PD-PLUS Deerhaven Technical Software Steady-State Modeling of Chemical, Petrochemical, and Refining Processes Windows closed-source [60]
PIPE-FLO Professional Engineered Software Inc. Piping System Simulation and Design Windows closed-source [61]
PIPEFLO Schlumberger Steady state multiphase flowline simulation Windows closed-source [62]
PIPESIM Schlumberger Steady state multiphase flowline simulation Windows closed-source [63]
PEL Suite PEL Software Steady state process simulation Windows closed-source [64]
Petro-SIM KBC Advanced Technologies Dynamic process simulation Windows closed-source [65]
PETROX Petrobras In-house steady state refining process simulator[3] Windows closed-source N/A
Power Plant Simulator & Designer KED GmbH Basic Engineering and Dynamic process simulation for power plants Windows closed-source [66]
Process Engineering ToolS (PETS) Stratus Engineering, Inc. Process Engineering Software Windows closed-source [67]
Process Studio Stamicarbon Simulation Suite for Modeling, Engineering & Training Windows closed-source [68]
Prode Properties Prode Software Thermodynamic Library, Properties of pure fluids and mixtures, Multi phase Equilibria + process simulation Windows, Linux, Android closed-source [69]
Prode Process Interface Prode Software Process simulation, optimization realtime control Windows closed-source [70]
ProMax Bryan Research & Engineering Process simulator capable of modeling oil & gas plants, refineries, and many chemical plants Windows closed-source [71]
ProPhyPlus Fives ProSim Thermodynamic calculation software Windows closed-source [72]
ProSec Fives ProSim Simulation of brazed plate fin heat exchangers Windows closed-source [73]
ProSim DAC Fives ProSim Dynamic adsorption column simulation Windows closed-source [74]
ProSim HEX Fives ProSim Heat Exchangers Simulation Windows closed-source [75]
ProSimPlus Fives ProSim Steady-state simulation and optimization of processes Windows closed-source [76]
ProSimulator Sim Infosystems Process and Power plant simulation Windows closed-source [77]
ProTreat / SulphurPro Optimized Gas Treating Steady state simulation of amine gas sweetening, glycol dehydration, modified Claus SRUs, tail gas clean-up, and post-combustion carbon capture processes Windows closed-source [78]
PRO/II AVEVA Steady state process simulation Windows closed-source [79]
Pyomo Sandia and UC Davis Steady state and dynamic process simulation All Platforms open-source [80]
ROMeo AVEVA Process optimization Windows closed-source [81]
Reaction Lab Scale-up Systems Chemist-oriented kinetic modeling and reaction optimization Windows closed-source [82]
RecoVR VRTech Industrial wastewater management Windows closed-source [83]
REX Optience Reactor Optimization and Kinetic Estimation Windows closed-source [84]
AVEVA Process Simulation

(former SimCentral)

AVEVA Steady state, Fluid flow and Dynamic process simulator. Windows closed-source [85]
SimCreate TSC Simulation Real time, first principle and generic operator training simulations, plant specific emulations and OPC for live plant connections. Windows closed-source [86]
Simulis Thermodynamics Fives ProSim Mixture properties and fluid phase equilibria calculations Windows closed-source [87]
SolidSim (Now in Aspen Plus[4][5]) SolidSim Engineering GmbH Flowsheet simulation of solids processes Windows closed-source [88]
SPEEDUP Aspen Technology Dynamic process simulation Unix, Windows closed-source [89]
SuperPro Designer Intelligen Batch and continuous process simulation. Windows closed-source [90]
SysCAD KWA Kenwalt Australia Steady-state and dynamic process simulation Windows closed-source [91]
UniSim Design Suite Honeywell Process simulation and optimization Windows closed-source [92]
UniSim Competency Suite Honeywell Operator Competency Management and Training Windows closed-source [93]
USIM PAC CASPEO Steady-state simulation and optimization of processes Windows closed-source [94]
Virtuoso Wood PLC Multiphase dynamic process simulator for oil & gas production Windows closed-source [95]
VMG Symmetry Schlumberger Steady state simulation, dynamic process simulation, transient multiphase flowline simulation Windows closed-source [96]
Wolfram SystemModeler Wolfram Research Modelica-based Dynamic multidomain modelling (mechanical, electrical, chemical) Windows, Mac, Linux closed-source [97]
XPSIM Process Simulation Services Steady state and dynamic process simulation, transient multiphase pipeline simulator Windows closed-source [98]

See also

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References

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List of chemical process simulators

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A list of chemical process simulators encompasses software packages designed to model, analyze, and optimize industrial chemical processes through mathematical simulations that integrate principles of , reaction kinetics, , heat and , and equipment performance. These tools allow engineers to predict process outcomes, evaluate design alternatives, and ensure without physical prototyping, serving as a core component in for the chemical, , pharmaceutical, and industries. With commercial development beginning in the 1960s and user-friendly graphical interfaces emerging primarily since the 1980s, they provide graphical interfaces for building flowsheets of entire plants, incorporating extensive databases of chemical components, thermodynamic models, and unit operations. Chemical process simulators are categorized into steady-state models, which focus on balanced conditions for design and optimization, and dynamic models, which simulate time-dependent behaviors for control and safety analysis. They support applications ranging from reactor sizing and column design to and waste reduction, often reducing development costs and timelines in process optimization. Notable commercial examples include Aspen Plus and from AspenTech, renowned for their comprehensive thermodynamic libraries and integration capabilities; gPROMS for advanced dynamic modeling; PRO/II and CHEMCAD for steady-state simulations with robust libraries; and UniSim Design for oil and gas processes. Open-source alternatives such as and COCO Simulator offer accessible options for academic and small-scale use, featuring extensible architectures for custom extensions. Interoperability standards like CAPE-OPEN enable integration across different simulators, addressing limitations in handling complex, multi-scale problems by combining specialized tools for enhanced accuracy and flexibility. This list highlights both established and emerging simulators, reflecting ongoing advancements in computational power, integration, and sustainability-focused modeling to meet evolving industry demands.

Introduction

Definition and Scope

Process simulation is the representation of a chemical process through a that is solved to gather information about the process's behavior, performance, and optimization. These models integrate principles of , kinetics, and to simulate unit operations and entire flowsheets, supporting applications in , and analysis across chemical, , pharmaceutical, and energy industries.

Historical Development

The development of chemical process simulators began in the late 1950s, when major oil companies such as Exxon and Shell created proprietary computational tools to model individual unit operations like and heat exchangers, driven by the need for efficient process design amid growing demands. These early systems relied on mainframe computers and programming, focusing on steady-state calculations without integrated flowsheeting. By the mid-1960s, commercial viability emerged with the launch of the first generic simulators: by Simulation Sciences in 1966, which enabled broader flowsheet simulations, and FLOWTRAN by in the late 1960s, recognized as the world's first commercially viable integrated system. During the 1970s, the field expanded rapidly with the proliferation of mainframe computing, facilitating process optimization in the petrochemical industry; tools like FLOWTRAN were distributed to universities via the Computer Aids for Chemical Engineering (CACHE) consortium starting in 1974, promoting academic adoption and refinement. The 1980s marked a shift toward commercialization and user-friendliness, with the introduction of graphical user interfaces and modular architectures; a key milestone was Aspen Plus in 1982, developed from MIT's ASPEN project (initiated in 1976 for energy-efficient process design) and commercialized by Aspen Technology, which emphasized rigorous thermodynamic models and economic evaluation. In the 1990s, dynamic simulation gained prominence with Hyprotech's HYSYS (launched mid-decade), offering intuitive drag-and-drop interfaces for real-time process analysis, particularly in oil and gas sectors. From the 2000s onward, simulators integrated advanced optimization algorithms and began incorporating for tasks like property prediction and fault detection, enhancing accuracy in complex scenarios. Open-source alternatives emerged as accessible options, exemplified by DWSIM's initial release in , which supported CAPE-OPEN standards for and democratized simulation for education and small-scale industry use. Post-2010, the shift to -based platforms accelerated, enabling scalable, collaborative simulations without heavy local hardware, as seen in tools like AspenTech's cloud deployments and specialized frameworks such as COEL for reaction networks. This evolution reflects broader trends in computational power and digital integration, sustaining simulators' role in sustainable process innovation.

Core Features

Modeling Capabilities

Chemical process simulators provide robust support for modeling unit operations, which are the fundamental building blocks of . These include reactors for chemical reactions, distillation columns for separation by differences, exchangers for transfer, pumps for fluid movement, and separators for phase division, among others. Each unit operation model incorporates customizable parameters such as geometric dimensions, operating pressures and temperatures, efficiency factors, and specifications to accurately represent real-world behavior. A core aspect of these simulators is the implementation of thermodynamic property methods to predict phase equilibria, enthalpies, and transport properties essential for process calculations. Equations of state, such as the Peng-Robinson model, are widely used for high-pressure vapor-liquid equilibrium (VLE) predictions in systems, while activity coefficient models like NRTL (Non-Random Two-Liquid) excel in handling non-ideal liquid mixtures at lower pressures, including liquid-liquid equilibria (LLE). These methods also extend to transport properties, such as and thermal conductivity, often through empirical correlations integrated with the primary thermodynamic framework, ensuring consistent property estimation across multiphase systems. Selection of these methods depends on factors like mixture composition, operating conditions, and data availability, with predictive approaches like employed when experimental parameters are limited. Flowsheeting capabilities enable the interconnection of unit operations into comprehensive process diagrams, facilitating the simulation of entire plants through and balance calculations. Users can define streams linking operations, incorporate loops to model feedback streams, and employ convergence algorithms—such as the Wegstein method for simple recycles or more advanced Newton-Raphson techniques for complex systems—to iteratively solve nonlinear equations until steady-state conditions are achieved. This modular approach allows for efficient analysis of process interactions, optimization of layouts, and identification of bottlenecks without physical prototyping. Integration features in chemical process simulators enhance flexibility by linking to external databases for chemical properties and enabling custom user-defined models. Connections to databases like NIST or DIPPR provide access to extensive pure-component data, including critical properties and interaction parameters, which can be imported to populate simulations accurately. Additionally, standards such as CAPE-OPEN allow for the development and incorporation of bespoke models, often coded in languages like or Python, to address proprietary equipment or novel processes not covered by standard libraries. These capabilities support seamless extension of simulator functionality for specialized applications in research and industry.

Simulation Types

Chemical process simulators support various simulation types to address different aspects of process analysis and design. Steady-state simulation solves material, energy, and composition balances under equilibrium conditions, assuming no time dependency and constant variables over time. This approach simplifies modeling by eliminating time derivatives, enabling efficient evaluation of system configurations, equipment sizing, and optimization of operating conditions such as flow rates and temperatures. It is particularly valuable for initial and feasibility studies, where the focus is on achieving balanced performance without transient effects. Dynamic simulation, in contrast, models time-varying processes by incorporating differential equations that account for accumulation terms, allowing the prediction of transient behaviors such as start-ups, shutdowns, and responses to disturbances. This type is essential for analyzing control strategies, scenarios like emergency depressurization, and operator training, as it captures the full of process variables over time rather than isolated equilibrium points. Unlike steady-state methods, dynamic simulations require more computational resources but provide critical insights into operability and real-world deviations from steady conditions. For instance, they can evaluate how a hydrocracker responds to power failures, informing relief system design and validation. Hybrid and advanced simulation types extend these core modes by integrating optimization, , and detailed spatial modeling. Optimization-integrated simulation embeds algorithmic solvers within the process model to minimize costs, maximize yields, or satisfy constraints, often using modular frameworks for robust steady-state or dynamic optimization. methods introduce stochastic sampling to propagate uncertainties in parameters like thermodynamic properties, enabling probabilistic assessments of process outputs such as in heat pumps, with confidence intervals derived from thousands of iterations. Additionally, integration with (CFD) allows process simulators to couple flowsheet models with detailed reactor simulations, enhancing analysis of mixing and flow distributions in units like stirred tanks for overall plant optimization. These advanced approaches are supported by open standards for seamless interoperability. The choice of simulation type depends on the process development stage and objectives. Steady-state simulation is preferred for early phases focused on feasibility and economic optimization, offering rapid results with lower computational demands. Dynamic simulation is selected for operational and evaluations, such as control tuning or , where time-dependent responses are critical. Advanced types like optimization-integrated or Monte Carlo-CFD hybrids are employed in later stages for handling complexity, uncertainty, or detailed physics, ensuring comprehensive and performance enhancement across the plant lifecycle.

Open-Source Simulators

DWSIM

DWSIM is a free, open-source chemical process simulator that is fully compliant with the CAPE-OPEN standard, enabling seamless integration with other compatible tools. Initially developed in 2004 as Excel VBA macros implementing the Peng-Robinson and a basic flash algorithm, it evolved into a standalone application with a graphical flowsheeting interface by 2008. The software supports both steady-state and dynamic simulation modes, allowing users to model complex processes involving chemical reactions, separations, and heat transfer across multiple platforms including Windows, , macOS, Android, and . Key features of DWSIM include a comprehensive library of built-in thermodynamic models such as Peng-Robinson (PR), Soave-Redlich-Kwong (SRK), NRTL, , GERG-2008, PC-SAFT, and CoolProp, which facilitate accurate property predictions for a wide range of substances. It offers an extensive unit operations palette encompassing mixers, separators, distillation columns, reactors (e.g., and continuous stirred-tank), heat exchangers, and pumps, all accessible through an intuitive drag-and-drop flowsheeting environment. Automation is supported via Python scripting with IronPython integration and an Excel add-in for thermodynamic calculations, enabling custom workflows and data analysis without requiring advanced programming skills. DWSIM is primarily maintained by developer Daniel Wagner Oliveira de Medeiros, with contributions from the CAPE-OPEN Laboratories Network (CO-LaN) community, and is hosted on platforms like SourceForge and GitHub for collaborative development. It has been adopted in educational settings for teaching process simulation fundamentals and in small-scale industrial applications for preliminary design and analysis, with thousands of downloads indicating widespread use among students, educators, and consultants worldwide as of 2025. Recent versions, such as v9.0.5 released in October 2025, have incorporated advanced capabilities for electrolyte systems and solids handling, enhancing its utility for specialized simulations like aqueous processes and multiphase flows. The simulator's strengths lie in its high accessibility for beginners, owing to the user-friendly interface and no-cost licensing under the GNU General Public License v3, making it an ideal entry point for learning concepts. However, it has limitations in advanced optimization routines, relying more on manual adjustments and scripting for complex scenario analyses rather than built-in solvers for large-scale multi-objective problems.

COCO Simulator

The COCO Simulator is a free-of-charge, CAPE-OPEN compliant steady-state flowsheeting environment designed for , originally developed in the as a testing platform for CAPE-OPEN modeling tools and later made available for educational and research use. It consists of four main CAPE-OPEN-based components: COFE (the graphical flowsheeting interface), (thermodynamics package with over 550 chemicals and more than 100 property calculation methods), COUSCOUS (collection of unit operations including mixers, heat exchangers, pumps, and reactors), and CORN (reaction numerics package supporting kinetic and equilibrium reactions). Paired with the ChemSep-LITE tool, which handles equilibrium-based separations for up to 40 components and 300 stages, COCO emphasizes modular simulation of separation processes such as and absorption, enabling users to build and solve flowsheets on Windows platforms (XP or higher). Key features include the solver, which employs a sequential modular approach with hybrid Newton/Wegstein algorithms for recycle streams and supports nested flowsheets as CAPE-OPEN unit operations for extensibility. The environment allows integration of third-party and unit operations via CAPE-OPEN interfaces, facilitating customization without proprietary lock-in, and includes utilities like unit conversion, plotting, and Excel coupling for analysis. Developed and maintained by AmsterCHEM since its inception, COCO received the CAPE-OPEN Award in for advancing standards and is distributed under the (version 3.10), which permits free use and unmodified distribution but prohibits alterations to the core software. A free version suffices for basic steady-state modeling, while optional paid extensions and from AmsterCHEM enable advanced applications, such as custom component development. COCO's strengths lie in its detailed handling of column simulations through ChemSep integration, making it particularly valuable for research in separation processes like vapor-liquid equilibrium modeling with methods. However, for comprehensive process scopes involving dynamic operations or extensive reaction networks, it relies on add-ons or external CAPE-OPEN components, as the base package prioritizes modularity over all-in-one functionality. This design has supported academic studies and process optimization in separations, with examples including ethanol dehydration flowsheets demonstrating coupled reaction-distillation sequences.

ASCEND

ASCEND is an open-source, equation-oriented modeling environment designed for simulating complex chemical processes through declarative mathematical descriptions. Originating as a project at in the late 1970s, it evolved from early efforts in interactive equation solving for applications, such as multicomponent flash calculations. The software operates under the GNU Lesser General Public License (LGPL), enabling free use, modification, and distribution, and supports steady-state simulations on platforms including , Windows, and macOS. Key features of ASCEND include its declarative modeling language, which allows users to define custom equations, variables, and relationships in a structured, text-based format that combines declarative elements with procedural methods for building hierarchical models. This language supports symbolic manipulation, such as generating solve-order graphs to visualize the solution process, and facilitates optimization problems using solvers like CONOPT and . Additionally, ASCEND integrates seamlessly with Python, enabling scripting for model automation, external data access, and extensions through libraries like for graphical interfaces. Development of ASCEND was community-driven from the early until around , following the of its founder, Arthur Westerberg, in 2004, with contributions from volunteers including John Pye for Python bindings and Ben Allan for code maintenance. It has been used in academia for research and teaching advanced modeling techniques, such as in courses at institutions like the . As of 2025, development activity is limited, with the latest version 0.9.8 and no recent updates. ASCEND's strengths lie in its flexibility for modeling non-standard processes through reusable, object-oriented components, though its text-based input can present a steeper compared to graphical tools.

Other Open-Source Simulators

APMonitor is an optimization suite designed for modeling and solving mixed-integer problems in and control, with capabilities for dynamic simulation and real-time optimization of physical systems. It supports through integration with solvers like and is accessible via the open-source Python package, enabling seamless scripting for process engineers. BioSTEAM serves as a specialized platform for simulating production and processes, incorporating unit operations for thermochemical and biochemical pathways along with integrated tools for techno-economic analysis and . Developed in Python, version 2.11.7 as of October 2025, it facilitates rapid scenario evaluation under uncertainty, making it suitable for process optimization. Dyssol provides a framework for dynamic flowsheet of multiphase reactive systems involving granular solids, such as in or , by modeling particle size distributions, shapes, and interactions across unit operations. Its modular structure allows for detailed representation of particulate processes, including breakage, agglomeration, and . OpenModelica functions as a general-purpose modeling environment based on the Modelica language, adaptable for chemical process simulations through libraries that handle dynamic systems like reactors, separations, and heat exchangers. It excels in equation-oriented modeling for transient behaviors in process units, supporting both steady-state and time-dependent analyses. Pyomo offers a Python-based optimization framework for formulating and solving algebraic models in chemical process engineering, including nonlinear and mixed-integer problems for flowsheet optimization, parameter estimation, and design. While not a standalone simulator, it enables custom process simulations by interfacing with solvers like GLPK and Gurobi, often used in conjunction with other tools for comprehensive analysis. These simulators are distributed under permissive open-source licenses, including MIT for GEKKO and BioSTEAM, BSD-3-Clause for Dyssol and Pyomo, and the OSMC Public License for , allowing free download, modification, and community contributions via platforms like . Access is facilitated through official repositories and documentation sites, with active developer support for integration into research and industrial workflows.

Commercial Simulators

Aspen Suite

The Aspen Suite, developed by (AspenTech) since the early 1980s as an outgrowth of a U.S. Department of Energy-funded project at MIT, comprises a family of commercial tools tailored for the chemical and sectors. Central to the suite are Aspen Plus, which specializes in steady-state for applications in bulk chemicals, specialty chemicals, pharmaceuticals, and polymers, and , designed for dynamic simulations prevalent in and gas operations including upstream, , and processes. These tools are extensively adopted in industries requiring precise , optimization, and , with particularly valued for its role in safety analysis and operational planning in hydrocarbon processing. Key features of the Aspen Suite include an extensive thermodynamic database via Aspen Properties, encompassing over 37,000 components, more than 127 property packages, and millions of data points to ensure reliable predictions across diverse conditions. The suite supports advanced optimization capabilities, such as sensitivity analysis, design specification, and case studies, enabling users to evaluate process variables and economic trade-offs efficiently. Additionally, it facilitates seamless integration with external tools, including through the Aspen Simulation Workbook for data exchange and visualization, and Python via the (COM) interface for custom scripting and automation. These integrations enhance workflow flexibility, allowing engineers to link simulation results with data analysis or optimization algorithms. AspenTech maintains ongoing development of the suite, with version 15 released in 2025 incorporating advanced AI features like generative AI for model guidance, of workflows, and predictive insights to accelerate in complex scenarios. Licensing is provided on a subscription basis, bundling software access with maintenance services such as updates and to support enterprise-scale deployments. As an industry standard, the Aspen Suite excels in delivering high-fidelity simulations validated against real-world data, making it indispensable for large-scale industrial applications where accuracy in and process is paramount. However, its comprehensive functionality comes with a steep and substantial computational demands, which can pose challenges for small users or those handling simpler processes without dedicated expertise.

CHEMCAD

CHEMCAD is a commercial chemical process simulation software developed by Datacor, Inc. (following the 2021 acquisition of Chemstations), which has been providing the tool to the process industries since 1988, with roots tracing back to the 1968 Chemical Engineering Simulation System (CHESS). It supports both steady-state and dynamic simulations on the Windows operating system, making it accessible for modeling general chemical processes such as reactors, distillation columns, and heat exchangers. The software is particularly targeted at educational institutions and small to medium-sized enterprises (SMEs), offering an intuitive platform for process design, optimization, and analysis without requiring extensive computational resources. Key features of CHEMCAD include its user-friendly graphical interface, which allows engineers to build and modify flowsheets efficiently, often learnable in 1-2 weeks for those familiar with simulation concepts. It provides built-in libraries for , reactions—including equilibrium, kinetic, and stoichiometric models—and separations such as , absorption, and extraction, enabling comprehensive unit operations modeling. Additionally, integrated economic evaluation modules support cost estimation and profitability analysis, facilitating preliminary feasibility studies for chemical projects. Development of CHEMCAD has evolved through versions, with Version 7 and later introducing enhanced access options via and virtual machines for remote collaboration. Licensing is available in perpetual formats using hardware keys or network managers, as well as annual subscription models for flexible deployment. CHEMCAD's strengths lie in its affordability as an entry point for simulation, with lower costs compared to enterprise-level alternatives, and its simplicity for educational and SME applications. However, it may be less robust for simulating very large-scale industrial plants, where more advanced handling of complex integrations is needed, often leading users to prefer tools like the Aspen Suite for such scenarios.

gPROMS

gPROMS is an advanced equation-oriented and simulation software developed by Process Systems Enterprise (PSE), a company founded as a spin-off from in 1997, with initial development tracing back to the early 1990s under the pioneering work of Michael Pantelides on generalized modeling systems. It supports both steady-state and dynamic simulations, enabling users to build custom models using differential-algebraic equations (DAEs) for complex chemical processes, and has found extensive application in the pharmaceutical and specialty chemicals industries for tasks such as production optimization and process design. Key features of gPROMS include its capability to handle over 100,000 DAEs simultaneously for custom , integrated tools for and operation, and support for real-time applications through parameter estimation and model validation. The software's equation-based approach allows for flexible representation of unit operations and phenomena, distinguishing it as a tool for advanced model-based engineering rather than standard flowsheeting. Following PSE's acquisition by in 2019, gPROMS has evolved to integrate seamlessly with technologies, enabling real-time process monitoring and control as of 2025, while supporting multi-scale modeling that spans from molecular-level interactions—such as phase behavior in active pharmaceutical ingredients—to full plant-scale simulations. Recent advancements include AI-enhanced surrogate modeling for faster computations in large-scale optimizations and broader compatibility with formulated products libraries for specialty chemicals. gPROMS excels in research and development environments due to its high-fidelity predictive accuracy and powerful optimization capabilities, which facilitate innovation in complex, non-standard processes like those in pharmaceuticals. However, its strengths come with limitations, including a steep learning curve that demands significant expertise in mathematical modeling and , high licensing costs, and substantial computational resources required for solving large DAE systems.

PRO/II

PRO/II is a commercial steady-state software developed by , formerly under the SimSci brand, with origins tracing back to the as part of SimSci's efforts to create advanced tools for refining and chemical processes. Originally focused on processing, it runs on Windows platforms and supports rigorous mass and energy balance calculations for applications in oil and gas separation, production, and related industries. The software emphasizes sequential modular simulation, enabling engineers to model complex flowsheets for , revamps, and operational optimization. Key features of PRO/II include extensive assay management capabilities for handling crude oil feedstocks, where users can convert assay data into pseudocomponents for accurate representation in simulations. It offers specialized reactor models, such as the hydroprocessing (HDP) reactor for hydrotreating operations, allowing detailed simulation of desulfurization, denitrogenation, and other reactions in trickle-bed configurations. Additionally, heat integration tools integrate with HTRI software for rigorous design, zone analysis, and utility optimization to enhance energy efficiency in process flowsheets. Recent developments in PRO/II include version 2024 enhancements, such as the unit for simulations, updates to the module for improved cost analysis, new sustainability modules for evaluating CO2 recovery, biofuels production, and metrics like analysis. These updates also incorporate advanced models for hydrotreaters and hydrocrackers, alongside enterprise licensing options that support cloud-based deployment through Simulation for scalable, collaborative use. PRO/II's strengths lie in its optimization for upstream and downstream sectors, providing robust thermodynamic models with over 1,700 pure components tailored for and workflows, which facilitate precise feedstock characterization and performance predictions. However, its limitations include reduced applicability to non- processes, as many built-in methods and component libraries are hydrocarbon-centric, potentially requiring custom extensions for broader chemical applications.

Other Commercial Simulators

UniSim Design, developed by , is a comprehensive steady-state and dynamic simulation tool primarily utilized in the oil and gas sector for , optimization, and operator training simulations. It enables engineers to create realistic process models by accurately calculating physical, transport, separation, and reaction kinetic properties, supporting applications from plant design to . The software's intuitive interface facilitates quick model development and integration with control systems for dynamic scenarios, making it particularly effective for training operators on complex refining and upstream processes. SuperPro Designer, offered by Intelligen, Inc., specializes in simulating bioprocesses, , and operations, with built-in capabilities for economic evaluation and cost estimation. It effectively models both continuous and batch processes, including over 140 unit operations such as reactors, separations, and purification steps, while performing rigorous material, energy, and cost balances. Widely adopted in the industry, the tool supports lifecycle analysis from product development to scale-up, aiding in techno-economic feasibility studies for sustainable . HSC Chemistry, provided by (formerly ), focuses on thermodynamic calculations, chemical equilibria, and simulations, serving industries like and . The software includes a dedicated module (HSC Sim) for mass and energy balances in hydrometallurgical and pyrometallurgical flowsheets, incorporating distributions and mineralogical data. It enables rapid evaluation of reaction conditions and process efficiency on standard computers, with applications in optimizing extraction and environmental impact assessments. ROMeo, from , is an optimization-oriented simulator designed for refining, petrochemical, and chemical processes, integrating rigorous modeling for real-time performance monitoring and . It supports equation-based optimization using thermodynamic data to reconcile process variables and recommend set points, applicable to complex operations including those in fine chemicals production. The tool's capabilities extend to offline studies and integration with for enhanced decision-making in dynamic industrial environments. Commercial chemical process simulators increasingly adopt subscription-based licensing models, providing flexible access via cloud platforms to accommodate varying user needs and reduce upfront costs. As of 2025, updates in these tools emphasize features, such as analysis and green process optimization, alongside AI integration for predictive modeling and autonomous operations to enhance efficiency and environmental compliance.

References

  1. https://normandie-univ.hal.science/hal-04099597v1/file/Application%2520of%2520Multi-Software%2520Engineering%2520A%2520Review%2520and%2520a.pdf
  2. https://www.ncbi.nlm.nih.gov/books/NBK207665/
  3. https://apps.dtic.mil/sti/tr/pdf/ADA294330.pdf
  4. https://www.sciencedirect.com/topics/engineering/process-simulation
  5. https://www.sciencedirect.com/topics/materials-science/process-simulation
  6. https://archives.sciencehistory.org/repositories/3/resources/52
  7. https://cache.org/sites/default/files/winter15-Seider-Evans.pdf
  8. https://www.aspentech.com/en/about-aspentech/35-years-of-innovation/
  9. https://chemicalengineeringguy.com/the-blog/process-simulation/aspen-plus-vs-hysys-whats-the-difference/
  10. https://dwsim.org/index.php/about/
  11. https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2016.00013/full
  12. https://www.aspentech.com/en/about-aspentech
  13. https://www.amazon.com/Modeling-Simulation-Chemical-Process-Systems/dp/1138568511
  14. https://trepo.tuni.fi/bitstream/handle/123456789/23943/Leino.pdf?sequence=3&isAllowed=y
  15. https://utw10182.utweb.utexas.edu/eldridge/ChE473K/drop_folder/Don%27t%20Gamble%20With%20Physical%20Properties.pdf
  16. https://doi.org/10.1016/0378-3812(86)85009-9
  17. https://doi.org/10.1016/B978-0-444-42836-3.50006-7
  18. https://deepblue.lib.umich.edu/bitstream/handle/2027.42/24173/0000432.pdf?sequence=1
  19. https://dwsim.org/
  20. https://www.aspentech.com/en/products/engineering/aspen-custom-modeler
  21. https://www.sciencedirect.com/topics/engineering/steady-state-simulation
  22. https://www.digitalrefining.com/article/1000649/dynamic-simulation-a-tool-for-engineering-problems
  23. https://modelon.com/blog/steady-state-and-dynamic-simulation-what-is-the-difference/
  24. https://www.sciencedirect.com/science/article/pii/S009813540980029X
  25. https://www.sciencedirect.com/science/article/abs/pii/S0098135419300717
  26. https://www.colan.org/techpapers/integrated-process-simulation-and-cfd-for-improved-process-engineering/
  27. https://dwsim.org/wiki/index.php?title=Automation
  28. https://dwsim.org/wiki/index.php?title=Licensing
  29. https://www.cocosimulator.org/
  30. https://www.amsterchem.com/coco.html
  31. https://www.cocosimulator.org/downloads/FlowsheetingWithCOCOandChemsep_Notes.pdf
  32. https://www.cocosimulator.org/index_disclaimer.html
  33. https://www.cocosimulator.org/index_sample.html
  34. https://ascend4.org/ASCEND_history
  35. https://github.com/ascend4/ascend4/blob/python3/LICENSE.txt
  36. https://ascend4.org/ASCEND_overview
  37. https://ascend4.org/Scripting_ASCEND_using_Python
  38. https://ascend4.org/
  39. https://apmonitor.com/
  40. https://apmonitor.com/wiki/index.php/Main/GekkoPythonOptimization
  41. https://pubs.acs.org/doi/10.1021/acssuschemeng.9b07040
  42. https://biosteam.readthedocs.io/
  43. https://www.sciencedirect.com/science/article/pii/S2352711020302855
  44. https://github.com/DyssolTEC/Dyssol-open
  45. https://pubs.acs.org/doi/10.1021/acs.iecr.9b00104
  46. https://www.openmodelica.org/
  47. http://www.pyomo.org/
  48. https://pyomo.readthedocs.io/
  49. https://github.com/BYU-PRISM/GEKKO
  50. https://github.com/BioSTEAMDevelopmentGroup/biosteam
  51. https://github.com/Pyomo/pyomo
  52. https://openmodelica.org/useresresources/license/
  53. https://www.aspentech.com/en/products/engineering/aspen-plus
  54. https://www.aspentech.com/en/products/engineering/aspen-hysys
  55. https://www.aspentech.com/en/resources/brochure/aspen-hysys
  56. https://www.aspentech.com/en/products/engineering/aspen-properties
  57. https://www.aspentech.com/en/products/engineering/aspen-simulation-workbook
  58. https://www.aspentech.com/en/whats-new
  59. https://esupport.aspentech.com/s_resources?src=seo-eam-software&videoId=5798970182001
  60. https://esupport.aspentech.com/T_course?id=a3pUn000000DERlIAO
  61. https://www.prnewswire.com/news-releases/datacor-announces-acquisition-of-chemstations-a-market-leader-in-process-simulation-software-301348441.html
  62. https://www.environmental-expert.com/companies/chemstations-inc-34103
  63. https://www.datacor.com/products/chemcad
  64. https://www.datacor.com/products/chemcad/capabilities
  65. https://chemstations.com/license
  66. https://www.quora.com/What-will-be-better-Aspen-HYSIS-or-ChemCAD
  67. https://press.siemens.com/global/en/pressrelease/siemens-plans-acquire-process-systems-enterprise
  68. https://www.researchgate.net/publication/393974733_The_importance_of_GPROOMS_in_the_Chemical_Industry_Its_Uses_Applications_Limitations_and_Recent_Developments
  69. https://doi.org/10.23919/iccas52745.2021.9649767
  70. https://www.imperial.ac.uk/news/193709/imperial-spin-out-acquired-siemens-digital-industries/
  71. https://www.siemens.com/global/en/products/automation/industry-software/gproms-digital-process-design-and-operations/gproms-modelling-environments/gproms-process.html
  72. https://www.colan.org/process-modeling-environment/gproms/
  73. https://www.siemens.com/global/en/products/automation/industry-software/gproms-digital-process-design-and-operations.html
  74. https://www.businesswire.com/news/home/20210420005688/en/New-gPROMS-Process-Process-Modelling-and-Optimization-for-the-Digital-World
  75. https://www.g2.com/products/gproms/reviews
  76. https://www.aveva.com/en/products/process-simulation/
  77. https://www.aveva.com/en/products/pro-ii-simulation/
  78. https://gulf.avevaselect.com/wp-content/uploads/2023/03/Datasheet-AVEVA-PROII-Simulation.pdf
  79. https://learningacademy.aveva.com/courses/reactor-models-in-aveva-proii-simulation-how-to-configure-the-hydroprocessing-hdp-reactor-1
  80. https://learningacademy.aveva.com/courses/new-features-in-aveva-proii-simulation-2024-1
  81. https://learningacademy.aveva.com/courses/new-features-in-aveva-proii-simulation-2024-economics-unit-updates-1
  82. https://www.scribd.com/document/681228075/AVEVA-PRO-II-Simulation-2023-Product-News
  83. https://www.scribd.com/document/361323980/PRO-II-8-0-Component-and-Thermophysical-Properties-Reference-Manual
  84. https://process.honeywell.com/us/en/products/industrial-software/process-optimization/unisim-design-suite/unisim-design-free-trial
  85. https://process.honeywell.com/us/en/initiative/unisim-design-suite/unisim-feature
  86. https://www.colan.org/process-modeling-environment/unisim-design/
  87. https://www.intelligen.com/products/superpro-overview/
  88. https://www.intelligen.com/products/superpro-product-features/
  89. https://www.intelligen.com/static/biotechnology.html
  90. https://www.metso.com/portfolio/hsc-chemistry/
  91. https://www.metso.com/portfolio/hsc-chemistry/process-simulation-module/
  92. http://heelis.com/
  93. https://www.aveva.com/content/dam/aveva/documents/datasheets/Datasheet_ROMeo-Process-Optimisation_EN.pdf.coredownload.inline.pdf
  94. https://www.aveva.com/en/products/process-optimization/
  95. https://www.aveva.com/en/solutions/operations/value-chain-optimization/romeo-reactor-models/
  96. https://www.hsc-chemistry.com/
  97. https://www.sciencedirect.com/science/article/pii/S2772508125000493
  98. https://www.globenewswire.com/news-release/2025/08/19/3135780/0/en/Artificial-Intelligence-AI-in-Chemicals-Market-Eyes-USD-28-Billion-by-2034-as-Sustainability-and-Digital-Twins-Transform-Production.html
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