Bibliografías temáticas / Source term estimation

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Literatura académica sobre el tema "Source term estimation"

Autor: Grafiati
Publicado: 25 de mayo de 2024

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Artículos de revistas sobre el tema "Source term estimation"

1

Long, Kerrie J., Sue Ellen Haupt, and George S. Young. "Assessing sensitivity of source term estimation." Atmospheric Environment 44, no. 12 (2010): 1558–67. http://dx.doi.org/10.1016/j.atmosenv.2010.01.003.

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2

Gudiksen, P. H., T. F. Harvey, and R. Lange. "Chernobyl Source Term, Atmospheric Dispersion, and Dose Estimation." Health Physics 57, no. 5 (1989): 697–706. http://dx.doi.org/10.1097/00004032-198911000-00001.

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3

Bushe, W. Kendal, and Helfried Steiner. "Laminar flamelet decomposition for conditional source-term estimation." Physics of Fluids 15, no. 6 (2003): 1564. http://dx.doi.org/10.1063/1.1569483.

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4

Loewenthal, Dan, and Vladimir Shtivelman. "Source signature estimation using fictitious source and reflector." GEOPHYSICS 54, no. 7 (1989): 916–20. http://dx.doi.org/10.1190/1.1442721.

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Source wavelet estimation is an important step in processing and interpreting seismic data. In the context of this work, the term (source wavelet) includes the pure source signature (the source response measured in a homogeneous medium) along with certain model‐related events (such as the ghost and interbed reflections). An estimate of the source wavelet can be used to increase the resolution of seismic data by signature deconvolution, deghosting, and dereverberation. However, pure source signature determination is of particular importance as a first step in direct inversion schemes, as demons
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5

Lu, Jinshu, Mengqing Huang, Wenfeng Wu, Yonghui Wei, and Chong Liu. "Application and Improvement of the Particle Swarm Optimization Algorithm in Source-Term Estimations for Hazardous Release." Atmosphere 14, no. 7 (2023): 1168. http://dx.doi.org/10.3390/atmos14071168.

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Hazardous gas release can pose severe hazards to the ecological environment and public safety. The source-term estimation of hazardous gas leakage serves a crucial role in emergency response and safety management practices. Nevertheless, the precision of a forward diffusion model and atmospheric diffusion conditions have a significant impact on the performance of the method for estimating source terms. This work proposes the particle swarm optimization (PSO) algorithm coupled with the Gaussian dispersion model for estimating leakage source parameters. The method is validated using experimental
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6

Jing, Yuanqi, Zhonglin Gu, Fei Li, and Kai Zhang. "Gaseous Pollutent Source Term Estimation Based on Adjoint Probability and Regularization Method." E3S Web of Conferences 356 (2022): 05048. http://dx.doi.org/10.1051/e3sconf/202235605048.

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Fast and accurate identification of source locations and release rates is particularly important for improving indoor air quality and ensuring the safety and health of people. Existing methods based on adjoint probability are difficult to distinguish the release rate of dynamic sources, and optimization algorithms based on regularization are limited to analysing only a small amount of potential pollutant source information. Therefore, this study proposed an algorithm combining adjoint equations and regularization models to identify the location and release intensity of pollutant sources in the
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7

Cheng, Kuang, Xiangyu Zhao, Wang Zhou, Yi Cao, Shuang-Hua Yang, and Jianmeng Chen. "Source term estimation with deficient sensors: Traceability and an equivalent source approach." Process Safety and Environmental Protection 152 (August 2021): 131–39. http://dx.doi.org/10.1016/j.psep.2021.05.035.

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8

Nayak, M. K., T. K. Sahu, H. G. Nair, et al. "Bremsstrahlung source term estimation for high energy electron accelerators." Radiation Physics and Chemistry 113 (August 2015): 1–5. http://dx.doi.org/10.1016/j.radphyschem.2015.04.004.

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9

Li, Hui, Jianwen Zhang, and Junkai Yi. "Computational source term estimation of the Gaussian puff dispersion." Soft Computing 23, no. 1 (2018): 59–75. http://dx.doi.org/10.1007/s00500-018-3440-2.

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10

Mazzini, Guido, Tadas Kaliatka, Maria Teresa Porfiri, Luigi Antonio Poggi, Andrea Malizia, and Pasqualino Gaudio. "Methodology of the source term estimation for DEMO reactor." Fusion Engineering and Design 124 (November 2017): 1199–202. http://dx.doi.org/10.1016/j.fusengdes.2017.04.101.

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