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Description
Problem Description
When conducting simulations using DAGMC (Direct Accelerated Geometry Monte Carlo), we encounter a scenario where the need arises to differentiate materials that originally are identical but occupy different cells. This differentiation is crucial for allowing each cell to deplete independently or to apply unique temperature fields to each cell.
Currently, to achieve this material differentiation, one has to separate a single cell into multiple cells and generate new .h5m files with renamed materials. This process not only is cumbersome but also significantly increases disk space usage due to the storage requirements of multiple .h5m files that only differ in material names.
Proposed Enhancement
We are seeking to streamline the process of material differentiation within DAGMC simulations, similar to what is achieved with the diff_burnable_mats argument in openmc.deplete.CoupledOperator. The aim is to allow materials that are originally the same but fill different cells to deplete independently. Furthermore, this enhancement should also cater to the application of unique temperature fields to each cell, enabling a more precise simulation of thermal behaviors.
Use Cases
- Independent Cell Depletion: Differentiate materials within the same geometry so that each can deplete independently without the need for duplicating geometry files.
- Unique Temperature Fields per Cell: Apply different temperature fields to each cell, enhancing the simulation's accuracy in scenarios where thermal effects are critical.
Current Workaround
A minimal example demonstrating the current method of achieving this via file duplication can be found here: DAGMC Cell Separation Example. This example highlights the inefficiencies and the significant disk space requirement of the current approach.
Request
We request the development of a feature within OpenMC's DAGMC interface to facilitate the above-described material differentiation process without the need for generating multiple .h5m files. This would greatly enhance the usability of DAGMC for complex simulations and reduce both the computational overhead and disk space requirements.