Source Term Estimation

Figure 9.21 Example of source term estimation, based on the forward (a) and inverse (b) local-scale modelling in a case of accidental contamination from an unknown release (Baklanov, 2000 [25]). Simulated wind fields and isolines of a - air pollution concentration in surface layer based on forward modelling b - probability density function base on the adjoint problem.

In many cases due to unknown or uncertain parameters of the release, the estimation of source term characteristics, based on environmental pollution monitoring, is a very important issue for emergency response systems. A combination of the forward and inverse (adjoint) modelling approaches allows to solve such environmental risk and emergency management problems (e.g., source-term estimation) more effectively compared with the traditional ways based on only the forward modelling. 

R. Moormann et al., Source Term Estimation for Small-Sized HTRs Status and Further Needs, Extracted from German Safety Analyses Awe/. Tech. 135(3), 183-193 (September 2001). 

The major strength of most of the dense gas models is their rigorous inclusion of the important mechanisms of gravity sliunping, air entrainment, and heat transfer processes. Their primary weakness is related to source term estimation and the high level of skill required of the user. Automatic source term generation models... 

The materials leaving containment are source terms for offsite convective-diffusion transport calculations. Codes. such as CRAC-2 calculate atmospheric diffusion with different probabilities of meteorological conditions to estimate the radiological health effects and costs. 

FIRAC is a computer code designed to estimate radioactive and chemical source-terms as.sociaied with a fire and predict fire-induced flows and thermal and material transport within facilities, especially transport through a ventilation system. It includes a fire compartment module based on the FIRIN computer code, which calculates fuel mass loss rates and energy generation rates within the fire compartment. A second fire module, FIRAC2, based on the CFAST computer code, is in the code to model fire growth and smoke transport in multicompartment stmetures. 

Source Terms and In-Plant Transport the fraction of the inventory that makes it to the environment must be estimated. Computer models are to track the hazardous materials that are released from their process confinement through transport and deposition inside the plant to their release into the environment as a source term for atmospheric and aquatic di.spersion. 

The dominant internal event accident scenarios were used in conjunction with conservative source terms (100% of the core melts, releasing 100% of the noble gases, 100% nf iodine and cesium, and 1% solids), and )ecific meteorological data to estimate e consequences to be well below the lOCFRlOO siting guidelines. 

Emrit, R. et al., A Prioritization of Generic Safety Issues, NUREG-0933 suppliment. Reassessment of the Technical Bases for Estimating Source Terms, Draft, May 1985. Baranowsky, P.W., Evaluation of Station Blackout Accidents at Nuclear Power Plants, May 1985. 

Because estimates of health risk are based on the levels of radionuclides in or near the vicinity properties, the quality of the potential health risk estimates depends upon the availability of appropriate measurement data. Hence, the first steps involved the determination of the appropriate environmental pathways of exposure and developing the source term for the exposure of persons potentially at risk. For our work, the radiological source-term data was based on measurements made principally by the Oak Ridge National Laboratory and the Mound Laboratory. 

The vaporization rate or source term, determined by Equation 3-12, is used in Equation 3-9 to estimate the concentration (in ppm) of a volatile in an enclosure resulting from evaporation of a liquid ... 

The procedure presented above can be easily extended to estimate the joint PDF of a vector of K composition variables fchemical source term (S) inside a CFD grid cell can be estimated by sampling the chemical source term at every... 

The reversible potential for the sulfur dioxide electrolysis is only 0.17 V, less than 10% that of water electrolysis (minimum of 1.23V at 298K and 1 bar) [65,69]. However corrosion problems in the electrolysis step are severe due to the presence of high concentration (about 50%) sulfuric acid. The overall thermal efficiency of the process, considering both thermal and electrical energy input derived from the same heat source, is estimated as 48.8% [116]. However, in terms of economics and process complexity the hybrid cycles face tough competition from advanced water electrolyzers. 

By comparing the measured ratio of each nuclide detected in the water to the T in the water with the calculated ratio for the Cambric source term (Table I), an effective retention factor, E, for each nuclide on the solid debris was estimated as follows. 

Because of their intimate link with energy production in nuclear reactors, fission products and their nuclear data have long occupied an important position in reactor technology. In recent years, interest in short-lived fission-product decay data has increased markedly, as their relevance to different areas of research and technology has become recognized. In addition to their importance for estimation of the fission-product decay-heat source term in nuclear reactors, the increasing attention being focused on the assessment of the hazards associated with the release, transport and... 

Gudiksen, P.H., Harvey, T.F. Lange, R. (1989) Chernobyl source term, atmospheric dispersion and dose estimation. Health Physics, 57, 697-706. 

Example 7.7 Absorption of ammonia vapor by lithium nitrate-ammonia solution The following modeling is from Venegas et al. (2004). For simultaneous heat and mass transfer during the absorption of ammonia vapor by lithium nitrate-ammonia (A) solution droplets, the ammonia concentration profile in the liquid phase can be estimated from the continuity equation without a source term... 

Numerical validation for pesticide movement addresses the question of whether the results generated from the model predict actual experimental values. A few models have been validated by correlating the estimated airborne pesticides and/or the amount on room materials with actual measurements in certain specific cases, van Veen et al. (1999) reported an experiment to validate a painting model of CONSEXPO which describes concentrations of a volatile solvent in room air both during and after the application. The concentrations depended on evaporation, initial concentration of solvent in two layers of paint, volume of paint and removal of solvent by ventilation from the room. Model parameters were either measured from the room before the experiment (ventilation rate, room size, physico-chemical parameters, etc.) from the act of painting (surface painted and amount of paint used), or fixed in advanced (relative size of the two layers of paint, transfer rate between the layers, etc.). The model predicted room concentrations that were within 80 % of the actual measured concentrations (Figure 6.1). Important with respect to the evaporation term is that peak concentrations could be predicted very well, so indicating that the source term is appropriate. 

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