As engineers and scientists strive to do more with less, computer modelling has become essential to cut costs, speed development and reduce uncertainty when designing everything from processes to molecules. Flowsheet simulators, a defining tool for every chemical engineer since the 1990s, have seen incremental improvements in power and usability over recent years. Computational fluid dynamics and molecular modelling, in contrast, have had more room to advance, and are now able to replace a great deal of experimental work. Open source simulators offer a serious alternative to commercial software in several areas, while powerful general-purpose modelling tools and “multi-scale” models are blurring the boundaries between different types of simulation.

Prediction is a vital part of the scientific method. Only when we can forecast how a process or a molecule will behave, independently of experiment, can we claim real understanding. Accordingly, mathematical models of physical, chemical and thermal phenomena lie at the core of engineering, many branches of chemistry, and increasingly the biological sciences too.

Much of the mathematics underlying heat and mass transfer dates back to the 18th and 19th centuries. But since it is often easier to write differential equations than to solve them, practical solutions to many engineering design problems had to wait until computers could provide brute-force solutions (“numerical methods”).

Since then, advances in computer power and mathematics have enabled both highly complex time-independent optimizations such as protein folding, and also dynamic simulations of gas flows, combustion modelling, and advanced process control.

Multi-purpose Simulators

For many decades, libraries of numerical methods were available on mainframes and minicomputers to anyone with the skill to write their own mathematical models. But this was difficult stuff, often left to departmental experts and not for one-off use.

In the early 1980s the first spreadsheets – VisiCalc and Lotus 1-2-3 – made microcomputers a practical everyday tool for chemical engineers. Spreadsheets made it much easier to solve the complex sets of simultaneous equations that characterize plant flowsheets, and enabled design improvements through a series of “what-if?” calculations.

Spreadsheets have now been joined by multi-purpose modelling environments such as Mathematica/Wolfram SystemModeler (Wolfram Research, USA), Matlab/Simulink (MathWorks, USA), and dozens of alternatives. Combining flexibility with great power, these can model mathematical functions, process plants, mechanical devices and electrical systems.

The open source Modelica modelling language, for instance, allows users to create and link blocks of equations describing, say, individual items on a flowsheet. In turn, Modelica can be used with a number of commercial front-ends including Wolfram SystemModeler and SimulationX (ITI, Germany).

For the most difficult tasks, multi-purpose simulators can run on high-performance computing (HPC) clusters, often taking advantage of each server’s graphics processing unit (GPU) as well as the main floating point processor (CPU). The most powerful multi-purpose simulators offer ideal platforms for the new trend towards multi-scale modelling (see below).

Computational Fluid Dynamics

Computational fluid dynamics (CFD) uses equations describing turbulence and heat transfer in bulk fluids to model engineering problems involving fluid flow. Applications include aerodynamics, complex flows in reactors and packed beds, dryers and heaters, and combustion processes, including explosions.

20 years ago the first commercial CFD programs were time-consuming to set up and took days or weeks to solve practical problems. As a result, CFD was used only to confirm final designs or as a troubleshooting measure. Today, software advances and affordable HPC allow CFD to provide useful input much earlier in the design process, and to optimize designs via repeated simulations, with minimal input from engineers.

Denmark-based hygienic processing specialist GEA Process Engineering, for example, uses CFD to design and troubleshoot spray dryers and mixers for the food and pharmaceutical industries. The company’s Drynetics modelling technique, introduced in 2008, combines CFD with real-world measurements on actual droplets and particles. Simulation is done on a new HPC cluster with 512 cores, 90 TB of disk space and 2 TB of RAM.

Just as with molecular modelling, CFD has now expanded its reach to multiple engineering disciplines and size scales. In fact, the lines between CFD and structural mechanics – finite element analysis (FEA) – are now so blurred that it makes little sense to refer to “CFD” at all, claimed Bill Clark, Executive Vice President of US simulation company CD-Adapco recently.

As simulation increasingly replaces physical testing, simulation specialists face a great deal of responsibility to come up with the right answers. At the same time their jobs are becoming harder as the problems get bigger. “Customers want to see the big picture, with whole systems rather than individual components, and there are really no easy problems left to solve,” Clark said.

CFD codes such as Star-CD and Star-CCM+ from CD-Adapco, and Fluent and CFX from Ansys (USA), the largest commercial CFD supplier, combine good performance with an all-in-one approach that can make them a good choice for firms new to CFD, notes aerospace CFD expert Dr Chris Nelson. On the other hand, solutions based on separate components — grid generator, flow solver and post-processor – can be more powerful.

Also to consider are the many excellent open source CFD codes, of which OpenFOAM (ESI Group, France) is possibly the best known. Dr Ma Shengwei of the Institute of High Performance Computing, Singapore, says that open source CFD can be just as good as the commercial version (“there are almost no secret recipes”), but depends on skilled personnel and so is not necessarily cheaper.

Flowsheet Simulation

Flowsheet simulation lies at the heart of chemical engineering. Its foundations are mass balances, energy balances, mass transfer, heat transfer, phase equilibria, and reaction modelling.

Compared to molecular modelling or CFD, steady-state simulators are relatively undemanding in terms of computing power. Combined with their smaller market, this means that vendors are more likely to differentiate themselves on the basis of industry focus, ease of use, customer service and license costs than on pure technical performance.

For the oil, gas and chemical industries the traditional market leaders are Aspen Hysys (hydrocarbons) and Aspen Plus (chemicals) from AspenTech; UniSim (developed from the same code base as Hysys) from Honeywell; and SimSci Pro/II from Schneider Electric. ProMax from Bryan Research and Engineering is a strong challenger to Hysys and UniSim, especially among smaller customers. Other important players include ChemCAD (Chemstations), Design II (WinSim), ProSimPlus and the Simulis family (ProSim), and VMGSim (Virtual Materials).

Alongside their flowsheet simulators, all the large vendors supply packages and tools aimed at specialist industries (e.g. fuel cells), processes (e.g. crude units), equipment items (e.g. heat exchangers), and design techniques (e.g. heat recovery networks and financial analysis). Since flowsheet modelling depends on accurate characterization of individual feedstocks and products, databases of physical properties and predictive “equations of state” are key to every simulator. The gap between physical property data within any database and the models within the simulators can either be closed by using specialized software tools like Dechema's Data Preparation Package DPP (Dechema) or in most cases also with inbuilt tools from the different vendors.

Several of the original flowsheet simulators, notably Aspen Plus, have their roots in publicly funded research projects, and open source competitors are available, though not to the same extent as in CFD. A recent review of the open source DWSIM simulator rated it comparable in some ways to Aspen Hysys, ProSim and VMGSim. Both DWSIM and another open source simulator project, EMSO, originate in Brazil.

Different from open source software, but with a similar aim of promoting transparency, is the veteran Cape-Open project that sets standards for the interchange of data in chemical process modelling. A simulation package that complies with Cape-Open standards, for instance, can draw on different physical property databases and add in third-party unit operations such as novel reactor types, as long as these too meet Cape-Open standards.

Process plants rarely operate entirely under steady-state conditions. For complex processes, dynamic effects may dominate operability and safety, especially during startup and shutdown. Many vendors therefore offer dynamic modelling capabilities through either their standard flowsheeting tools or dedicated products. An example of the latter from AspenTech is Advanced Process Control, part of the company’s AspenOne suite, which aids the design of complex control strategies to keep processes running under optimum conditions. Operator training is another important sector for dynamic simulation.

The multi-physics and multi-scale modelling discussed above has direct application to process plant modelling, too. A leading proponent of this “advanced process modelling” approach is Process Systems Enterprise (PSE, UK), with its gPROMS product. Through system-wide optimization based on first-principles models at multiple scales, PSE claims that gPROMS can create benefits beyond the scope of traditional flowsheet simulators.

The article is based on a trend report commissioned by Dechema and written by international trade journalists. Dechema brings together experts from a wide range of disciplines, institutions and generations to stimulate scientific exchange in chemical engineering, process engineering and biotechnology. Dechema is globally known as the organizer of Achema. The world forum and leading trade show for the process industry will again take place 15 - 19 June 2015 in Frankfurt, Germany.