John S. Nasstrom

A Lagrangian stochastic diffusion method for inhomogeneous turbulence

Abstract A Lagrangian stochastic method of solving the diffusion equation for inhomogeneous turbulence is presented in this paper. This numerical method uses (1) a first-order approximation for the spatial variation of the eddy diffusivity and (2) the first three particle position moments to define a skewed, non-Gaussian particle position probability density function. Two cases of the variation of the eddy diffusivity near a boundary are considered. In the first case, the eddy diffusivity varies linearly with height and is zero at the boundary. The method handles this case efficiently and accurately by using the first few terms of the series representation of the analytic solution to construct components of the non-Gaussian position probability density function that are important near the boundary. In the second case, the eddy diffusivity is constant near the boundary, and the well-known solution for this case – a Gaussian function reflected at the boundary – is used. Comparison of numerical simulation results to analytic solutions of the diffusion equation show that this method is accurate. For cases where the eddy diffusivity varies linearly with height to zero at the boundary, we demonstrate that this method can be significantly more efficient than the commonly used method that assumes a Gaussian particle position probability density function.

Atmospheric Dispersion Modeling: Challenges of the Fukushima Daiichi Response

Abstract The U.S. Department of Energy’s (DOE) National Atmospheric Release Advisory Center (NARAC) provided a wide range of predictions and analyses as part of the response to the Fukushima Daiichi Nuclear Power Plant accident including: • Daily Japanese weather forecasts and atmospheric transport predictions to inform planning for field monitoring operations and to provide U.S. government agencies with ongoing situational awareness of meteorological conditions; • Estimates of possible dose in Japan based on hypothetical U.S. Nuclear Regulatory Commission scenarios of potential radionuclide releases to support protective action planning for U.S. citizens; • Predictions of possible plume arrival times and dose levels at U.S. locations; and • Source estimation and plume model refinement based on atmospheric dispersion modeling and available monitoring data. This paper provides an overview of NARAC response activities, along with a more in-depth discussion of some of NARAC’s preliminary source reconstruction analyses. NARAC optimized the overall agreement of model predictions to dose rate measurements using statistical comparisons of data and model values paired in space and time. Estimated emission rates varied depending on the choice of release assumptions (e.g., time-varying vs. constant release rates), the radionuclide mix, meteorology, and/or the radiological data used in the analysis. Results were found to be consistent with other studies within expected uncertainties, despite the application of different source estimation methodologies and the use of significantly different radiological measurement data. The paper concludes with a discussion of some of the operational and scientific challenges encountered during the response, along with recommendations for future work.

A comparison between two stochastic diffusion models in a complex three-dimensional flow

A Random Displacement Model (RDM) and a Langevin Equation Model (LEM) are used to simulate point releases in a complex flow around a building. The flow field is generated by a three-dimensional finite element model that uses the standardk-ε model to parameterize the turbulence. The RDM- and LEM-calculated concentration fields are compared, with particular emphasis on the structure in regions with high turbulence and/or recirculation. RDM and LEM results are similar qualitatively, but RDM tends to predict lower concentration levels. In part this is due to the higher early-time diffusion. However, the expected convergence at later times is prevented by the interaction of the diffusion with the strongly inhomogeneous mean flow.

The National Atmospheric Release Advisory Center modelling and decision-support system for radiological and nuclear emergency preparedness and response

This paper describes the tools and services provided by a national centre for modelling the environmental and health impacts of airborne hazardous materials. This centre can provide emergency decision support information within minutes for a wide range of radiological, nuclear, chemical, and biological hazards from fires, industrial and transportation accidents, radiation dispersal device explosions, hazardous material spills, nuclear power plant accidents and nuclear detonations. Web- and internet-based software provides quick access to advanced modelling tools, as well as expert analyses from the centre. Model predictions include the 3D spatial and time-varying effects of weather, land use and terrain, on scales from the local to regional to global. Tools provide displays of plume predictions with affected population counts, detailed maps, and reports describing model assumptions, contamination and dose levels. On-scene information and measurements are used to refine model predictions.

Overview of hazard assessment and emergency planning software of use to RN first responders.

There are numerous software tools available for field deployment, reach-back, training and planning use in the event of a radiological or nuclear terrorist event. Specialized software tools used by CBRNe responders can increase information available and the speed and accuracy of the response, thereby ensuring that radiation doses to responders, receivers, and the general public are kept as low as reasonably achievable. Software designed to provide health care providers with assistance in selecting appropriate countermeasures or therapeutic interventions in a timely fashion can improve the potential for positive patient outcome. This paper reviews various software applications of relevance to radiological and nuclear events that are currently in use by first responders, emergency planners, medical receivers, and criminal investigators.

Shared- and distributed-memory parallelization of a Lagrangian atmospheric dispersion model

This paper describes parallelization of a 3-D Lagrangian stochastic atmospheric dispersion model using both distributed- and shared-memory methods. Shared-memory parallelism is implemented through the use of OpenMP compiler directives. Distributed-memory parallelism relies on the MPI message-passing library. One or both (using MPI for inter-node and OpenMP for intra-node communication) of the parallel modes can be used depending upon the requirements of the problem and the computational platform available. The distributed-memory version achieves a nearly linear decrease in execution time as the number of processors is increased. As the number of particles per processor is lowered, performance is limited by the decrease in work per processor and by the need to produce one set of output files. The shared-memory version achieves a speedup factor of ∼1.4 running on machines with four processors.

Nuclear/radiological emergency response in the USA

The US Consequence Management (CM) response element uses specific methodologies for dealing with the release of nuclear/radioactive material into the environment and has identified the potential impacts to the public and the environment. This paper will describe the history of how CM evolved, an overview of the current methods and response structure and include technical sections describing the federal response following a nuclear/radiological incident.

Evaluation of the Atmospheric Release Advisory Capability Emergency Response Model for Explosive Sources

The Atmospheric Release Advisory Capability (ARAC) at the Lawrence Livermore National Laboratory (LLNL) uses a modeling system to calculate the impact of accidental radiological or toxic releases to the atmosphere anywhere in the world. Operated for the US Departments of Energy and Defense, ARAC has responded to over 60 incidents in the past 18 years, and conducts over 100 exercises each year. Explosions are one of the most common mechanisms by which toxic particulates are injected into the atmosphere during accidents. Automated algorithms with default assumptions have been developed to estimate the source geometry and the amount of toxic material aerosolized. The paper examines the sensitivity of ARAC`s dispersion model to the range of input values for explosive sources, and analyzes the model`s accuracy using two field measurement programs.

Emergency Response Model Evaluation Using Diablo Canyon Nuclear Power Plant Tracer Experiments

The Lawrence Livermore National Laboratory’s (LLNL) Atmospheric Release Advisory Capability (ARAC) provides real-time emergency response support for accidental radiological releases to the atmosphere at Department of Defense (DOD) and Department of Energy (DOE) facilities throughout the U.S. ARAC uses diagnostic three-dimensional (3-D) dispersion modeling as its primary emergency response tool (Dickerson and Orphan, 1976). The regional (20 to 200 km) modeling system is built around the MATHEW (Mass-Adjusted Three-dimensional Wind field) and ADPIC (Atmospheric Dispersion Particle-In-Cell) models (Sherman, 1978; Lange, 1989). MATHEW adjusts the wind field by variational methods to be mass-conservative and to account for terrain effects. ADPIC calculates the time- and space-varying transport and diffusion (using K-theory) of source material using thousands of Lagrangian “mass” particles on a Eulerian grid. To determine the accuracy and transferability of the MATHEW/ADPIC models to a wide variety of settings and meteorological conditions, the models have been evaluated against numerous tracer experiments over the last decade (Dickerson and Ermak, 1988; Lange, 1989). This paper presents a model evaluation using a tracer experiment in the complex, coastal terrain of the Diablo Canyon Nuclear Power Plant.