Results for Monte Carlo

Publications & Outputs

1. A Monte Carlo Study of Time Varying Coefficient (TVC) Estimation

   Hall, S. G., Gibson, H. D., Tavlas, G. S. & Tsionas, M. G., 1/06/2020, In: Computational Economics. 56, p. 115–130 16 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

2. A method for the prediction of the dose rate distribution in a primary containment vessel of the Fukushima Daiichi Nuclear Power Station

   Okumura, K., Riyana, E. S., Wakaei, S., Maeda, H., Katakura, J., Kamada, S., Joyce, M. J. & Lennox, B., 31/01/2019, In: Progress in Nuclear Science and Technology. 6, p. 108-112 5 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

3. The influence of point defects on the entropy profiles of Lithium Ion Battery cathodes: a lattice-gas Monte Carlo study

   Mercer, M. P., Finnigan, S., Kramer, D., Richards, D. & Hoster, H. E., 1/07/2017, In: Electrochimica Acta. 241, p. 141-152 12 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

4. A comparison of MCNP6-1.0 and GEANT 4-10.1 when evaluating the neutron output of a complex real world nuclear environment: the thermal neutron facility at the Tri Universities Meson facility

   Monk, S. D., Shippen, A., Colling, B. R., Cheneler, D., Al Hamrashdi, H. & Alton, T., 15/05/2017, In: Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms. 399, p. 48-61 14 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

5. QuickMMCTest: quick multiple Monte Carlo testing

   Gandy, A. & Hahn, G., 4/05/2017, In: Statistics and Computing. 27, 3, p. 823-832 10 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

6. A case study of using cosmic ray muons to monitor supercritical CO2 migration in geological formations

   Zhong, J. & Jiang, X., 1/01/2017, In: Applied Energy. 185, 2, p. 1450-1458 9 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

7. A Framework for Monte Carlo based Multiple Testing

   Gandy, A. & Hahn, G., 1/12/2016, In: Scandinavian Journal of Statistics. 43, 4, p. 1046-1063 18 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

8. Cross-validation aggregation for combining autoregressive neural network forecasts

   Barrow, D. K. & Crone, S. F. W. M., 1/10/2016, In: International Journal of Forecasting. 32, 4, p. 1120-1137 18 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

9. Accurate simulations of TEPC neutron spectra using Geant4

   Taylor, G. C., Hawkes, N. & Shippen, A., 11/2015, In: Radiation Physics and Chemistry. 116, p. 186-188 3 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

10. Proposal to characterise legacy Sellafield ponds using SONAR and RadLine™

    Jackson, S., Monk, S., Nye, D., Colling, B. & Stanley, S., 07/2012, In: Applied Radiation and Isotopes. 70, 7, p. 1162-1165 4 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

11. Variation in measured neutron fluence in low radiation environments when altering sensor density on the surface of a sphere

    Monk, S. D., 07/2012, In: Applied Radiation and Isotopes. 70, 7, p. 1288-1290 3 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

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