Simulation-based Engineering
  CFD model of a pilot-scale CO2 adsorber
  CFD model of a pilot-scale CO2 adsorber (shown in the background).

Simulation-Based Engineering (SBE) is an area that combines the technical knowledge, software development, computational power, data repository, experimental facilities, and unique partnerships to support research in providing timely and accurate solutions for complex power systems. Understanding the performance of complex flows and components used in advanced power systems and having the means to impact their design early in the developmental process provides significant advantages in product design. The simulation based engineering is comprised of two specific subtasks, each with its own goals and objectives.

  • Physics- and Science-Based Modeling
  • Carbon Management Consortium

Traditional scale-up methods do not work well for many of the components that are present in complex power systems. Therefore, science-based models with quantified uncertainty are important tools for reducing the cost and time required for their development.


Reduce uncertainty and time-to-solution in multiphase-CFD for energy applications

Physics- and Science-Based Modeling

Predicts the behavior of complex multiphase flow reactors used in fossil energy technologies. This effort combines theory, computational modeling, experiments, and industrial input. Physics-based computational models and tools are being funded to support the development and deployment of advanced fossil fuel energy devices such as gasifiers and carbon capture reactors.

 

 

 

Carbon Management Consortium (CMC)

The CMC is working to advance computational tools so that they can be used in the acceleration of carbon management and reduction technologies associated with advanced energy systems, such as cogeneration and energy storage. These tools can provide potential benefits to other DOE programs such as biorefining, biofuels, advanced manufacturing, and environmental management. This can be achieved by coupling multi-scale models (from basic data to entire systems) with uncertainty and optimization. The development of these advanced computational tools would enable more comprehensive models of transformational carbon management and advanced energy system technologies to predict and mitigate potential scale up issues much earlier in the development cycle.


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