The acid gas removal unit and the sulfur recovery unit (SRU) are expensive and interdependent units necessary for meeting product specifications and emission regulations. With Aspen HYSYS® V9, you can use a single solution to consider all of the interdependencies of these two units with the most trusted solutions in process engineering.

This “getting started” guide covers the process of creating a new case for Acid Gas Cleaning, setting up component lists and fluid packages, and working in the simulation environment to build the model. It is not meant to be a standalone reference document. Knowledge of Aspen HYSYS V10 is assumed for this guide.

Aspen HYSYS has several options available for modeling pipes and pipelines. Use these approaches, correlations and analysis tools in Aspen HYSYS to solve problems around pipe flow hydraulics and optimize flow and uptime. This Top 8 Questions document recommends best practices from our technical experts.

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Learn about the underlying technology and validation results for the Acid Gas - Physical Solvents Property Package in Aspen HYSYS used for physical solvents in gas-liquid systems, specifically DEPG.

Learn how modeling batch distillation processes within Aspen Plus can put your organization on the innovation fast track. With powerful capabilities for reaction modeling and visual insights into column performance, Aspen Plus enables you to quickly and intuitively maximize distillation equipment effectiveness and reduce batch cycle time.

Are you ready to unlock the game-changing value that asset optimization can deliver? With narrower margins and no room for error, manufacturing leaders are embracing the need for asset optimization. Through asset optimization, companies have increased throughput, significantly reduced costs by millions of dollars, and increased productivity. Don’t be out-maneuvered – join the thousands of companies who have recognized the benefit of implementing the asset optimization vision into their operations.

View this infographic to see how prescriptive maintenance early adopters are reducing downtime and improving reliability – with results in as little as 2 ½ weeks.

Vea esta infografía para conocer cómo la información prescriptiva hizo que los primeros usuarios redujeran el tiempo de inactividad y aumentaran su confiabilidad en tan solo dos semanas y media.

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