Large Eddy Simulations of Turbulent and Buoyant Flows in Urban and Complex Terrain Areas Using the Aeolus Model

Fast and accurate predictions of the flow and transport of materials in urban and complex terrain areas are challenging because of the heterogeneity of buildings and land features of different shapes and sizes connected by canyons and channels, which results in complex patterns of turbulence that can enhance material concentrations in certain regions. To address this challenge, we have developed an efficient three-dimensional computational fluid dynamics (CFD) code called Aeolus that is based on first principles for predicting transport and dispersion of materials in complex terrain and urban areas. The model can be run in a very efficient Reynolds average Navier–Stokes (RANS) mode or a detailed large eddy simulation (LES) mode. The RANS version of Aeolus was previously validated against field data for tracer gas and radiological dispersal releases. As a part of this work, we have validated the Aeolus model in LES mode against two different sets of data: (1) turbulence quantities measured in complex terrain at Askervein Hill; and (2) wind and tracer data from the Joint Urban 2003 field campaign for urban topography. As a third set-up, we have applied Aeolus to simulate cloud rise dynamics for buoyant plumes from high-temperature explosions. For all three cases, Aeolus LES predictions compare well to observations and other models. These results indicate that Aeolus LES can be used to accurately simulate turbulent flow and transport for a wide range of applications and scales.

Current and Prospective Radiation Detection Systems, Screening Infrastructure and Interpretive Algorithms for the Non-Intrusive Screening of Shipping Container Cargo: A Review

The non-intrusive screening of shipping containers at national borders serves as a prominent and vital component in deterring and detecting the illicit transportation of radioactive and/or nuclear materials which could be used for malicious and highly damaging purposes. Screening systems for this purpose must be designed to efficiently detect and identify material that could be used to fabricate radiological dispersal or improvised nuclear explosive devices, while having minimal impact on the flow of cargo and also being affordable for widespread implementation. As part of current screening systems, shipping containers, offloaded from increasingly large cargo ships, are driven through radiation portal monitors comprising plastic scintillators for gamma detection and separate, typically 3He-based, neutron detectors. Such polyvinyl-toluene plastic-based scintillators enable screening systems to meet detection sensitivity standards owing to their economical manufacturing in large sizes, producing high-geometric-efficiency detectors. However, their poor energy resolution fundamentally limits the screening system to making binary “source” or “no source” decisions. To surpass the current capabilities, future generations of shipping container screening systems should be capable of rapid radionuclide identification, activity estimation and source localisation, without inhibiting container transportation. This review considers the physical properties of screening systems (including detector materials, sizes and positions) as well as the data collection and processing algorithms they employ to identify illicit radioactive or nuclear materials. The future aim is to surpass the current capabilities by developing advanced screening systems capable of characterising radioactive or nuclear materials that may be concealed within shipping containers.

Cost-effective approach to lung cancer risk for a radiological dispersal device (RDD) scenario

A release of radioactive material into the environment can lead to hazardous exposure of the population and serious future concerns about health issues such as an increased incidence of cancer. In this context, a practical methodology capable of providing useful basic information from the scenario can be valuable for immediate decisions and future risk assessment. For this work, the simulation of a radiological dispersal device (RDD) filled with americium-241 was considered. The radiation dose simulated by the HotSpot code was used as an input to the epidemiological equations from BEIR V producing the data used to assess the risk of lung cancer development. The methodology could be useful in providing training for responders aimed to the initial support addressed to decision-making for emergency response at the early phase of an RDD scenario. The results from the simulation allow estimating (a) the size of the potentially affected population, (b) the type of protection action considering gender and location of the individuals, (c) the absorbed doses, (d) the matrix of lung cancer incidence predictions over a period of 5 years, and (e) the cost-effectiveness in the initial decision environment.

CHALLENGES FOR PHYSICS-BASED MODELS OF A RADIONUCLIDE DISPERSAL DEVICE

A “dirty bomb” is a type of hypothetical radiological dispersal device (RDD) that has been the subject of significant safety and security concerns given the disruption that would result in a postulated terrorist attack. Reliable and accurate predictions of dispersion of radiological material from an RDD are absolutely necessary for first responders and emergency decision makers to plan effective response strategies. Development of high-fidelity, mechanistic models of a dirty bomb are complicated because dispersion over areas with the greatest risk of contamination is highly sensitive to the source of contaminant particles, and this source term is governed by processes over much smaller temporal and spatial length scales than the dispersion. New work on accelerating high-fidelity models of RDDs has been initiated that looks to incorporate the multiscale aspects of the problem and enhance predictive capabilities that may assist in anti-terrorism activities.