RADTRAN is a program and code for calculating the risks of transporting radioactive materials. The first versions of the program, RADTRAN I and II, were developed for NUREG-0170 (USNRC, 1977), the first environmental impact statement on transportation of radioactive materials. RADTRAN and its associated software have undergone a number of improvements and advances consistent with improvements in computer technology.
This document contains a description of the verification and validation process used for the RADTRAN 5.5 code. The verification and validation process ensured the proper calculational models and mathematical and numerical methods were used in the RADTRAN 5.5 code for the determination of risk and consequence assessments. The differences between RADTRAN 5 and RADTRAN 5.5 are the addition of tables, an expanded isotope library, and the additional User-Defined meteorological option for accident dispersion. 3
This document provides a detailed discussion and a guide for the use of the RadCat 2.0 Graphical User Interface input file generator for the RADTRAN 5.5 code. The differences between RadCat 2.0 and RadCat 1.0 can be attributed to the differences between RADTRAN 5 and RADTRAN 5.5 as well as clarification for some of the input parameters. 3
Abstract not provided.
The Nuclear Regulatory Commission (NRC) approves new package designs for shipping fissile quantities of UF{sub 6}. Currently there are three packages approved by the NRC for domestic shipments of fissile quantities of UF{sub 6}: NCI-21PF-1; UX-30; and ESP30X. For approval by the NRC, packages must be subjected to a sequence of physical tests to simulate transportation accident conditions as described in 10 CFR Part 71. The primary objective of this project was to relate the conditions experienced by these packages in the tests described in 10 CFR Part 71 to conditions potentially encountered in actual accidents and to estimate the probabilities of such accidents. Comparison of the effects of actual accident conditions to 10 CFR Part 71 tests was achieved by means of computer modeling of structural effects on the packages due to impacts with actual surfaces, and thermal effects resulting from test and other fire scenarios. In addition, the likelihood of encountering bodies of water or sufficient rainfall to cause complete or partial immersion during transport over representative truck routes was assessed. Modeled effects, and their associated probabilities, were combined with existing event-tree data, plus accident rates and other characteristics gathered from representative routes, to derive generalized probabilities of encountering accident conditions comparable to the 10 CFR Part 71 conditions. This analysis suggests that the regulatory conditions are unlikely to be exceeded in real accidents, i.e. the likelihood of UF{sub 6} being dispersed as a result of accident impact or fire is small. Moreover, given that an accident has occurred, exposure to water by fire-fighting, heavy rain or submersion in a body of water is even less probable by factors ranging from 0.5 to 8E-6.
RAMTRANS - Nuclear Technology Publishing
Over the years that radioactive material (RAM) transportation risk estimates have been calculated using the RADTRAN code, demand for improved geographic resolution of route characteristics, especially density of population neighboring route segments, has led to code improvements that provide more specific route definition. With the advent of geographic information systems (GISs), the achievable resolution of route characteristics is theoretically very high. The authors have compiled population-density data in 1-kilometer increments for routes extending over hundreds of kilometers without impractical expenditures of time. Achievable resolution of analysis is limited, however, by the resolution of available data. U.S. Census data typically have 1-km or better resolution within densely-populated portions of metropolitan areas but census blocks are much larger in rural areas. Geographic resolution of accident-rate data, especially for heavy/combination trucks, are typically tabulated on a statewide basis. These practical realities cause one to ask what level(s) of resolution may be necessary for meaningful risk analysis of transportation actions on a state or interstate scale.
Estimation of the potential radiological risks associated with highway transport of radioactive materials (RAM) requires input data describing population densities adjacent to all portions of the route to be traveled. Previously, aggregated risks for entire multi-state routes were adequately estimated from population data with low geographic resolution. Current demands for geographically-specific risk estimates require similar increases in resolution of population density adjacent to route segments. With the advent of commercial geographic information systems (GISs) and databases describing highways, U.S. Census Blocks, and other information that is geographically distributed, it became feasible to determine and tabulate population characteristics along transportation routes with 1-kilometer resolution. This report describes an automated method of collecting population data adjacent to route segments (for calculation of incident-free doses) based on a commercial GIS. It also describes a statistical method of resolving remaining resolution issues, and an adaptation of the automation method to collection of data on population under a hypothetical plume of contamination resulting from a potential transportation accident.
Risk Analysis
Application of Executive Order 12898 to risk assessment of highway or rail transport of hazardous materials has proven difficult; the location and conditions affecting the propagation of a plume of hazardous material released in a potential accident are unknown, in general. Therefore, analyses have only been possible in geographically broad or approximate manner. The advent of geographic information systems and development of software enhancements at Sandia National Laboratories have made kilometer-by-kilometer analysis of populations tallied by U.S. Census Blocks along entire routes practicable. Tabulations of total, or racially/ethnically distinct, populations close to a route, its alternatives, or the broader surrounding area, can then be compared and differences evaluated statistically. This paper presents methods of comparing populations and their racial/ethnic compositions using simple tabulations, histograms and Chi Squared tests for statistical significance of differences found. Two examples of these methods are presented: comparison of two routes and comparison of a route with its surroundings.
Recently, a model based on geographic information system (GIS) processing of US Census Block data has made high-resolution population analysis for transportation risk analysis technically and economically feasible. Population density bordering each kilometer of a route may be tabulated with specific route sections falling into each of three categories (Rural, Suburban or Urban) identified for separate risk analysis. In addition to the improvement in resolution of Urban areas along a route, the model provides a statistically-based correction to population densities in Rural and Suburban areas where Census Block dimensions may greatly exceed the 800-meter scale of interest. A semi-automated application of the GIS model to a subset of routes in Nevada (related to the Yucca Mountain project) are presented, and the results compared to previous models including a model based on published Census and other data. These comparisons demonstrate that meaningful improvement in accuracy and specificity of transportation risk analyses is dependent on correspondingly accurate and geographically-specific population density data.
The magnitudes of accident dose risks calculated by the RADTRAN code depend directly on the time span between an accidental release and evacuation of the affected area surrounding potential radionuclide releases. In a previous study of truck and rail transportation accidents, and other incidents requiring evacuations, a lognormal distribution of evacuation times (time span from decision to evacuate until complete) was developed, which provided a better model for this parameter than the practice of using a highly conservative value of 24 hours. However, the distribution did not account for time required for responders to arrive on the scene, to evaluate the hazards to surrounding population and to initiate an evacuation. Data from US Department of Transportation (DOT) accident statistics have been collected and their distribution functions determined. The separate distribution functions were combined into a single, comprehensive distribution which may be sampled to supply values of the RADTRAN input parameter, EVACUATION. A sample RADTRAN calculation illustrating the effect on risks of using the distribution versus the original (24 hour), conservative point-estimate are also presented.
In the transport of radioactive material (RAM), e.g., spent nuclear fuel (SNF), stakeholders are generally most concerned about risks in high population density areas along transportation routes because of the perceived high consequences of potential accidents. The most significant portions of a transcontinental route and an alternative examined previously were evaluated again using population density data derived from US Census Block data. This method of characterizing population that adjoins route segments offers improved resolution of population density variations, especially in high population density areas along typical transport routes. Calculated incident free doses and accident dose risks for these routes, and the rural, suburban and urban segments are presented for comparison of their relative magnitudes. The results indicate that modification of this route to avoid major metropolitan areas through use of non-Interstate highways increases total risk yet does not eliminate a relatively small urban component of the accident dose risk. This conclusion is not altered by improved resolution of route segments adjoining high density populations.
Severe ship accidents and the probability of radioactive material release from spent reactor fuel casks were investigated previously. Other forms of RAM, e.g., plutonium oxide powder, may be shipped in large numbers of packagings rather than in one to a few casks. These smaller, more numerous packagings are typically placed in ISO containers for ease of handling, and several ISO containers may be placed in one of several holds of a cargo ship. In such cases, the size of a radioactive release resulting from a severe collision with another ship is determined not by the likelihood of compromising a single, robust package but by the probability that a certain fraction of 10`s or 100`s of individual packagings is compromised. The previous analysis involved a statistical estimation of the frequency of accidents which would result in damage to a cask located in one of seven cargo holds in a collision with another ship. The results were obtained in the form of probabilities (frequencies) of accidents of increasing severity and of release fractions for each level of severity. This paper describes an extension of the same general method in which the multiple packages are assumed to be compacted by an intruding ship`s bow until there is no free space in the hold. At such a point, the remaining energy of the colliding ship is assumed to be dissipated by progressively crushing the RAM packagings and the probability of a particular fraction of package failures is estimated by adaptation of the statistical method used previously. The parameters of a common, well characterized packaging, the 6M with 2R inner containment vessel, were employed as an illustrative example of this analysis method. However, the method is readily applicable to other packagings for which crush strengths have been measured or can be estimated with satisfactory confidence.
The U.S. Department of Transportation Research & Special Programs Administration (DOT-RSPA) has sponsored a project at Sandia National Laboratories to evaluate the protection provided by current packagings used for truck and rail transport of materials that have been classified as Poison Inhalation Hazards (PIH) and to recommend performance standards for these PIH packagings. Hazardous materials span a wide range of toxicity and there are many parameters used to characterize toxicity; for any given hazardous material, data are not available for all of the possible toxicity parameters. Therefore, it was necessary to select a toxicity criterion to characterize all of the PIH compounds (a value of the criterion was derived from other parameters in many cases) and to calculate their dispersion in the event of a release resulting from a transportation accident. Methodologies which account for material toxicity and dispersal characteristics were developed as a major portion of this project and applied to 72 PIH materials. This report presents details of the PIH material toxicity comparisons, calculation of their dispersion, and their classification into five severity categories. 16 refs., 5 figs., 7 tabs.
The RADTRAN 4 computer code, which calculates estimates of accident dose-risk corresponding to specified transportation scenarios, ascribes doses to potentially exposed members of the public. These persons are modeled as not being evacuated from the affected area for 24 hours following a release of radioactive material. Anecdotal evidence has suggested that this value may be unnecessarily conservative; consequently risk estimates are unnecessarily high. An initial survey of recent trucking accidents, reported in newspapers and other periodicals (1988 through 1994), that involved evacuation of the general population in the affected areas was undertaken to establish the actual time required for such evacuations. Accidents involving hazardous materials other than those which are radioactive (e.g., gasoline, insecticides, other chemicals) but also requiring evacuations of nearby residents were included in the survey. However, the resultant set of sufficiently documented trucking incidents yielded rather sparse data [1]. When the probability density distribution of the truck accident data was compared with that resulting from addition of four other (rail and fixed site) incidents, there was no statistically significant difference between them. Therefore, in order to improve the statistical significance of the data set, i.e., maximize the number of pertinent samples, a search for evacuations resulting from all types of accidents was performed. This resulted in many more references; a set of 48 incidents which could be adequately verified was compiled and merged with the original two data sets for a total of 66 evacuation accounts.
The transportation risk analysis code, RADTRAN 4, computer estimates of incident-free dose consequence and accident dose-risk. The output of the code includes a tabulation of sensitivity of the result to variation of the input parameters for the incident-free analysis. The values are calculated using closed mathematical expressions derived from the constitutive equations, which are linear. However, the equations for accident risk are not linear, in general, and a similar tabulation has not been available. Because of the importance of knowing how accident-risk estimates are affected by uncertainties in the input parameters, a direct investigation was undertaken of the variation in calculated accident dose-risk with changes in individual parameters. A limited, representative group of transportation scenarios was used, initially, to determine which of 23 accident-risk parameters affect the calculated accident dose risk significantly. Many of the parameters were observed to have minimal effect on the output, and others were judged as ``fixed`` either by regulation, convention or standards. The remaining 5 variables were selected for further study through Latin Hypercube Sampling (LHS). LHS yields statistical information from observations (risk calculations) resulting from multiple input-parameter sets compiled from ``random`` sampling of parameter distributions. The LHS method requires fewer observations than classical Monte Carlo methods to yield statistically significant results. This paper presents the preliminary parameter study and LHS application results together with further LHS evaluations of RADTRAN input parameters.