Study On The Coefficient Adaptive Model Of Airborne Radionuclide Diffusion In Nuclear Accident

With the increasing use of nuclear energy, the demand for nuclearaccident evaluation gets higher and higher. When nuclear accident occurs,evaluating the diffusion process of radionuclide released from crevasse inatmosphere and estimating the concentration distribution of radionuclideon the floor can provide a scientific basis to alleviate accident hazard. Inthe real-time consequences assessment system for nuclear accident,Lagrangian puff model is widely used as dispersion model. Our researchgroup developed a Lagrangian puff model SJTUPUFF and programmed itin use of studying some factors influencing the atmospheric dispersionmodel. This article aims to correct and evaluate SJTUPUFF. The maincontent includes:(1) Study on the theory of atmospheric dispersion model’s influencefactor: gridding sensitivity, puff generating rate, lifting height and diffusioncoefficient. Analysis their effect law in detail with experiment data. Thevariation of gridding accuracy has no significant impact; puff generatingrate needs to achieve a balance in computation time and accuracy; theselection of lifting height and diffusion coefficient affects puff modelsignificantly.(2) Diffusion coefficient is one of the key parameters impacting puffmodel, this paper proposed an adaptive method, which could correct thediffusion coefficient in Lagrangian puff model, aiming to improve theaccuracy of calculating the nuclide concentration distribution. This methodused detected concentration data, meteorological data and source releasedata to estimate the actual diffusion coefficient with least square method. After evaluating this diffusion coefficient adaptive method by Kincaid datain Model Validation Kit, and comparing it with traditional Pasquilldiffusion scheme method, the results indicated that this diffusioncoefficient adaptive correction method has improved the accuracy of puffmodel.(3) Compared SJTUPUFF with mature air quality modeling systemCALPUFF recommend by US environmental protection agency andRIMPUFF model in Real-time On DecisiOn Support system. Eachcomparison used different experimental data. Both of the results havesome deviation, but all results are in the same order of magnitude. Thisdeviation can be accepted.In this paper, a Lagrangian puff model’s diffusion coefficient adaptivemethod is proposed, and a dynamic adaptive correction puff model is built.Through evaluating by Kincaid experimental data, we can get the resultthat diffusion coefficient adaptive corrective model is better thantraditional diffusion coefficient model. The new adaptive correction canimprove the accuracy of puff model’s computation. ComparingSUTUPUFF with two mature air dispersion models, we can indicate thatSJTUPUFF can predict the concentration distribution in a relative accuratelevel.