Aspen HYSYS

Anyone with some experience with process simulators, such as HYSYS, knows that the steady state and dynamic worlds have always been separate and distinct. HYSYS is one of the few simulators on the market that connects these two worlds and creates an integrated modeling environment.

Because HYSYS links the steady state and dynamic worlds, you must be familiar with creating steady state simulations before you begin creating dynamic ones. The design and optimization of a chemical process involves the study of both steady state and dynamic behaviour. Steady state models can perform steady state energy and material balances and evaluate different plant scenarios. The design engineer can use steady state simulation to optimize the process by reducing capital and equipment costs while maximizing production.

Steady state simulations can help process engineers in choosing an appropriate design that will meet certain conditions. However, dynamic simulations are required when an engineer is examining controllability and equipment sizing issues. The ability for process engineers to create accurate dynamic simulations quickly is quite new. In the past, creating a dynamic simulation for a new process to test for controllability issues was a luxury that could not be afforded. Now, it is possible for any design to have an associated dynamic simulation that will test the controllability of the process before it is constructed. This is a powerful tool that is quickly gaining use in several industries and companies.Dynamic simulation can help you to better design, optimize, and operate your chemical process or refining plant. Chemical plants are never truly at steady state. Feed and environmental disturbances, heat exchanger fouling, and catalytic degradation continuously upset the conditions of a smooth running process. The transient behaviour of the process system is best studied using a dynamic simulation tool like HYSYS.

With dynamic simulation, you can confirm that the plant can produce the desired product in a manner that is safe and easy to operate. By defining detailed equipment specifications in the dynamic simulation, you can verify that the equipment functions as expected in an actual plant situation. Offline dynamic simulation can optimize controller design without adversely affecting the profitability or safety of the plant.

You can design and test a variety of control strategies before choosing one that is suitable for implementation. You can examine the dynamic response to system disturbances and optimize the tuning of controllers. Dynamic analysis provides feedback and improves the steady state model by identifying specific areas in a plant that have difficulty achieving the steady state objectives.

In HYSYS, the dynamic analysis of a process system can provide insight into the process system when it is not possible with dynamic simulation, you can investigate:

• Process optimization
• Controller optimization
• Safety evaluation
• Transitions between operating conditions
• Startup/Shutdown conditions

The HYSYS dynamic model shares the same physical property packages as the steady state model. The dynamic model simulates the thermal, equilibrium, and reactive behaviour of the chemical system in a similar manner as the steady state model. On the other hand, the dynamic model uses a different set of conservation equations which account for changes occurring over time. The equations for material, energy, and composition balances include an additional “accumulation” term which is differentiated with respect to time. Non-linear differential equations can be formulated to approximate the conservation principles; however, an analytical solution method does not exist.

Therefore, numerical integration is used to determine the process behaviour at distinct time steps. The smaller the time step, the more closely the calculated solution matches the analytic solution. However, this gain in rigour is offset by the additional calculation time required to simulate the same amount of elapsed real time. A reasonable compromise is achieved by using the largest possible step size, while maintaining an acceptable degree of accuracy without becoming unstable.