Reduced Variance using ADVANTG in Monte Carlo Calculations of Dose Coefficients to Stylized Phantoms
The estimation of dose coefficients of external radiation sources to the organs in phantoms becomes increasingly difficult for lower photon source energies. This study focus on the estimation of photon emitters around the phantom. The computer time needed to calculate a result within a certain preci...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2017-01-01
|
| Series: | EPJ Web of Conferences |
| Online Access: | https://doi.org/10.1051/epjconf/201715306034 |
| _version_ | 1818653253105090560 |
|---|---|
| author | Hiller Mauritius Bellamy Michael Eckerman Keith Hertel Nolan |
| author_facet | Hiller Mauritius Bellamy Michael Eckerman Keith Hertel Nolan |
| author_sort | Hiller Mauritius |
| collection | DOAJ |
| description | The estimation of dose coefficients of external radiation sources to the organs in phantoms becomes increasingly difficult for lower photon source energies. This study focus on the estimation of photon emitters around the phantom. The computer time needed to calculate a result within a certain precision can be lowered by several orders of magnitude using ADVANTG compared to a standard run. Using ADVANTG which employs the DENOVO adjoint calculation package enables the user to create a fully populated set of weight windows and source biasing instructions for an MCNP calculation. |
| first_indexed | 2024-12-17T02:34:57Z |
| format | Article |
| id | doaj.art-8c014c615251475dbfa1a605a8541417 |
| institution | Directory Open Access Journal |
| issn | 2100-014X |
| language | English |
| last_indexed | 2024-12-17T02:34:57Z |
| publishDate | 2017-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | EPJ Web of Conferences |
| spelling | doaj.art-8c014c615251475dbfa1a605a85414172022-12-21T22:06:53ZengEDP SciencesEPJ Web of Conferences2100-014X2017-01-011530603410.1051/epjconf/201715306034epjconf_icrs2017_06034Reduced Variance using ADVANTG in Monte Carlo Calculations of Dose Coefficients to Stylized PhantomsHiller Mauritius0Bellamy Michael1Eckerman Keith2Hertel NolanOak Ridge National Laboratory, Center for Radiation Protection KnowledgeOak Ridge National Laboratory, Center for Radiation Protection KnowledgeOak Ridge National Laboratory, Center for Radiation Protection KnowledgeThe estimation of dose coefficients of external radiation sources to the organs in phantoms becomes increasingly difficult for lower photon source energies. This study focus on the estimation of photon emitters around the phantom. The computer time needed to calculate a result within a certain precision can be lowered by several orders of magnitude using ADVANTG compared to a standard run. Using ADVANTG which employs the DENOVO adjoint calculation package enables the user to create a fully populated set of weight windows and source biasing instructions for an MCNP calculation.https://doi.org/10.1051/epjconf/201715306034 |
| spellingShingle | Hiller Mauritius Bellamy Michael Eckerman Keith Hertel Nolan Reduced Variance using ADVANTG in Monte Carlo Calculations of Dose Coefficients to Stylized Phantoms EPJ Web of Conferences |
| title | Reduced Variance using ADVANTG in Monte Carlo Calculations of Dose Coefficients to Stylized Phantoms |
| title_full | Reduced Variance using ADVANTG in Monte Carlo Calculations of Dose Coefficients to Stylized Phantoms |
| title_fullStr | Reduced Variance using ADVANTG in Monte Carlo Calculations of Dose Coefficients to Stylized Phantoms |
| title_full_unstemmed | Reduced Variance using ADVANTG in Monte Carlo Calculations of Dose Coefficients to Stylized Phantoms |
| title_short | Reduced Variance using ADVANTG in Monte Carlo Calculations of Dose Coefficients to Stylized Phantoms |
| title_sort | reduced variance using advantg in monte carlo calculations of dose coefficients to stylized phantoms |
| url | https://doi.org/10.1051/epjconf/201715306034 |
| work_keys_str_mv | AT hillermauritius reducedvarianceusingadvantginmontecarlocalculationsofdosecoefficientstostylizedphantoms AT bellamymichael reducedvarianceusingadvantginmontecarlocalculationsofdosecoefficientstostylizedphantoms AT eckermankeith reducedvarianceusingadvantginmontecarlocalculationsofdosecoefficientstostylizedphantoms AT hertelnolan reducedvarianceusingadvantginmontecarlocalculationsofdosecoefficientstostylizedphantoms |