CAD modeling study on FLUKA and OpenMC for accelerator driven system simulation

A simple method to import CAD mesh format models in FLUKA

BACKGROUND

Monte Carlo (MC) code FLUKA possesses widespread usage and accuracy in the simulation of particle beam radiotherapy. However, the conversion from computer-aided design (CAD) mesh format models to FLUKA readable geometries could not be implemented directly and conveniently. A simple method was required to be developed.

PURPOSE

The present study proposed a simple method to voxelize CAD mesh format files by using a Python-based script and establishing geometric models in FLUKA.

METHODS

Five geometric models including cube, sphere, cone, ridge filter (RGF), and 1D-Ripple Filter (1D-RiFi) were created and exported as CAD mesh format files (.stl). An open-source Python-based script was used to convert them into voxels by endowing X, Y, and Z (following the Cartesian coordinates system) of solid materials in the three-dimensional (3D) grid. A FLUKA (4-2.2, CERN) predefined routine was used to establish the voxelized geometry model (VGM), while Flair (3.2-1, CERN) was used to build the direct geometry model (DGM) in FLUKA for comparison purposes. Uniform carbon ion radiation fields 8×8 cm3 and 4×4 cm3 were generated to transport through the five pairs of models, 2D and 3D dose distributions were compared. The integral depth dose (IDD) in water of three different energy levels of carbon ion beams transported through 1D-RiFis were also simulated and compared. Moreover, the volume between CAD mesh and VGMs, as well as the computing speed between FLUKA DGMs and VGMs were simultaneously recorded.

RESULTS

The volume differences between VGMs and CAD mesh models were not more than 0.6%. The maximum mean point-to-point deviation of IDD distribution was 0.7% ± 0.51% (mean ± standard deviation). The 3D dose Gamma-index passing rates were never lower than 97% with criteria of 1%-1 mm. The difference in computing CPU time was 2.89% ± 0.22 on average.

CONCLUSIONS

The present study proposed and verified a Python-based method for converting CAD mesh format files into VGMs and establishing them in FLUKA simply as well as accurately.

Development of a novel solar energy controllable Linear fresnel photoreactor (LFP) for high-efficiency photocatalytic wastewater treatment under actual weather

Solar-energy-enabled photocatalysis is promising for wastewater treatment. However, due to the changes in the solar position and variable weather conditions, providing optimized light and temperature for photocatalysis under actual weather remains to be a technical difficulty. In this study, a novel Linear fresnel photoreactor (LFP) was firstly developed for wastewater treatment. LFP could achieve effective adjustment of sunlight by flexibly controlling 6 mirrors according to solar position and weather conditions. On sunny condition, LFP could maintain the optimal light irradiance and temperature, while on overcast condition it could provide the highest possible light irradiance and temperature. In the comparative experiments between LFP and Inclined Plate Collector (IPC) (as control reactor) which passively receive sunlight, the Rhodamine B degradation efficiencies in LFP were 2.19 folds, 1.5 folds and 2.28 folds higher than control under the temporarily overcast, totally to slightly overcast and sunny conditions, respectively. In addition, the efficiencies of Amoxicillin degradation and Escherichia coli disinfection in LFP were also 2 folds and 1.37 folds higher than control in sunny conditions, respectively. Furthermore, whole-year estimation indicated that LFP is effective to optimize light irradiance and temperature in typical densely populated areas of the world to achieve high-efficiency wastewater treatment. These results proved that LFP, as an effective solar energy controllable reactor, has great potential in promoting the development of green wastewater treatment infrastructure to improve global public health and achieve eco-friendly society.