Applied Modeling and Computations in Nuclear Science: The

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Applied Modeling and Computations in Nuclear Science: The Foundation for Risk Assessment and Decision Making 1

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Downloaded by 80.82.77.83 on April 24, 2018 | https://pubs.acs.org Publication Date: November 16, 2006 | doi: 10.1021/bk-2007-0945.ch001

John E. Till and Helen A. Grogan 1

Risk Assessment Corporation, 417 Till Road, Neeses, SC 29107 Cascade Scientific, Inc., 1678 NW Albany Avenue, Bend, OR 97701

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Most of the chapters in this book and the symposium from which they are taken help support a key objective of nuclear science today - developing a thorough understanding of the risks to people exposed to nuclear radiation so that better decisions can be made to manage those risks. This introductory chapter describes how basic research in applied modeling and nuclear science discussed in this book inherently supports the objectives of risk assessment. The chapter also examines the importance of focusing research on areas that most effectively reduce uncertainty in quantifying risk. Finally, the chapter suggests specific areas in the field of applied modeling and computations in nuclear science that need further work to support risk assessment in the future.

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© 2007 American Chemical Society

Semkow et al.; Applied Modeling and Computations in Nuclear Science ACS Symposium Series; American Chemical Society: Washington, DC, 2006.

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Introduction In this brief introductory chapter, we emphasize the importance of basic research in applied modeling and computations in nuclear science, demonstrate how these topics are inherently linked together, and examine how they support a key objective of making better decisions based on understanding risk. Although the connection between nuclear science and risk may appear tenuous, most of the chapters presented here provide input and support to the estimation of risk from radioactive materials released to the environment. This field is known as environmental risk assessment or environmental risk analysis and involves the merging of a number of scientific disciplines to provide quantitative estimates of risk. Risk assessment is a contemporary form of mathematical modeling and computations in nuclear science, which is the topic of this book. Risk assessments consider both humans and the environment as the target of risk. Too frequently, however, they focus on human health alone, with the result that large areas of the environment and entire ecological systems are destroyed in the interests of reducing what are often inconsequential human health risks. Ultimately, a sound decision requires a holistic approach to assessing these risks. Why study risk? Risk is a universal common denominator that allows scientists and decision makers to address the impact of a source. Risk is also a concept that can be readily understood and compared with other activities in life. We define risk to humans as a chance of harm. The chance of harm is generally expressed as the health risk, specifically increased risk of cancer from radionuclides released into the environment from a source. Estimates of risk to people and the environment are used extensively to help guide decision makers in their efforts to invest resources most effectively. This introduction uses examples of our work to emphasize how basic research in applied modeling and computations in nuclear science, as illustrated so profoundly in this symposium, remains the solid foundation for risk science. The chapter also describes several key areas where additional future research needs to be undertaken.

Risk Assessment and Nuclear Science: The Connection Risk assessment and nuclear science are inherently connected. Modem-day risk assessment began with the testing of nuclear weapons as scientists tried to predict the path of radioactive fallout and the dose to people who lived downwind. Early research in this area, more than any other, laid the foundation for the methods we still use today to estimate risk to people from radioactive materials in the environment. More recently, research to reconstruct historical



4 releases of radionuclides to the environment from atmospheric nuclear weapons testing and from nuclear weapons facilities resulted in significant improvements in methods to estimate risk. This research included many new areas of investigation, such as estimation of source terms, transport of radioactive materials in the environment, uptake of radionuclides by humans and biota, and the development of dose and risk coefficients. Each of these scientific disciplines has its foundation in nuclear science. The components that comprise risk assessment today evolved from individual sciences that have been merged gradually (and lately, more frequently) to form the computational methods we now use to estimate risk. Risk can be estimated for present-day releases of materials, and for potential future releases of materials at existing or planned facilities. Such assessments are typically designed to demonstrate compliance with standards. Risk can also be estimated for releases that occurred in the past to help understand the impact of those releases. Although the methods used for the two types of risk assessment differ, there are many similarities in the techniques applied to each. In explaining the process of risk assessment to our colleagues and to the public, we often use the following illustrative equation to express the interdisciplinary nature of this research: Risk = (S · Τ· Ε · D · R) , uvcp

(1)

where S = Τ =

= =

Ε D R u V c

=

Ρ

=

=

=

source term (characterization of the quantity and type of material released) environmental transport (estimation of concentrations in the environment) exposure factors (characteristics of individuals exposed) conversion of intake rate or exposure rate to dose conversion of dose to risk uncertainty analysis validation communication of results public participation.

We will briefly explain each component needed to estimate risk and note how some of the research described in this book contributes to our knowledge of risk science. The source term (S) in the risk equation is the characterization and quantification of the material released to the environment. It is the heart of a risk assessment and has deservedly received significant attention. Our ability to



5 reconstruct or predict a source term directly affects the estimates of risk and thus the credibility of the assessment. Two chapters in this book pertain to a better quantification of the source term. The chapters by Viggato et al. (Thermohydraulic and Nuclear Modeling of Natural Fission Reactors) and Semkow et al (Modeling the Effects of the Trinity Test) help increase our understanding of materials present in sources that could ultimately be released to the environment. A number of other chapters indirectly describe how to better define a source. Examples of these chapters include those that focus on improving detection of radioactivity, as described by Pommé (Dead Time, Pile-up, and Counting Statistics), Keightley (DCÇJSIM: A Simulation Routine for the Validation of 4n β-γ Digital Coincidence Counting Software), Jenkins et al (Corrections for Overdispersion Due to Correlated Counts in Radon Measurements Using Grab Scintillation Cells, Activated Charcoal Devices and Liquid Scintillation Charcoal Devices), as well as by Briichle (Simulation of Elution Curves for Chromatography Columns with a Low Number of Theoretical Plates). The next term in the equation is environmental transport (7). In this step, we estimate the concentrations of a radionuclide in environmental media such as air, soil, sediment, surface water, or groundwater. In some cases, these concentrations can be estimated from direct measurements; in other cases, they must be inferred using mathematical models. Although our understanding of radionuclide transport in the environment has improved greatly over the past several decades, we continue to refine our modeling methods as demonstrated by several chapters in this book. Only one chapter directly addressed environmental transport, by Y u (Modeling Radionuclide Transport in the Environment and Assessing Risks to Humans, Flora, and Fauna - The RESRAD Family of Codes). In addition to environmental transport, we can have radiation transport which is also related to the source term. Two chapters addressed the principles of radiation transport, by Haghighat and Sjoden (Three-Dimensional Particle Transport Methods and Their Applications), as well as by Berlizov (MCNPCP: A Correlated Particle Radiation Source Extension of a General Purpose Monte Carlo N-Particle Transport Code). The next two chapters describe important applications, by Robinson et al. (Creation of Realistic Radiation Transport Models of Radiation Portal Monitors for Homeland Security Purposes) and by O'Brien (A Random-Walk Solution to the Heliospheric Transport Equation). There are no chapters in the symposium related to the next step of the calculation of risk, exposure factors (£), which is understandable since this component of risk assessment is primarily derived from physiological, dietary, and habit data. However, considerable progress continues to be made in this


6 area, particularly with regard to how individuals are characterized for the purpose of determining compliance with regulations. Once exposure is determined, coefficients are used to convert it to a dose (D), which may be internal, external, or an effective dose, or to risk directly. Several of the chapters in the symposium help to improve our understanding of these dose coefficients. The chapters by Miller et ai (Markov Chain Monte Carlo for Internal Dosimetry on a Supercomputer Cluster), Vojtyla (Calculation of the External Effective Dose from a Radioactive Plume by Using Monte Carlo Dose Kernel Integration), and X u (Modeling of Human Anatomy for Radiation Dosimetry: An Example of the VIP-Man Model) provide us with new insight into the dosimetry part of the risk calculation. None of the chapters addresses risk coefficients (R) although this field is of major interest today as evidenced by the extensive research being placed on the effects of low-dose radiation. A number of chapters help improve our understanding of uncertainty (w). Three chapters address issues related to uncertainty of radiation quantification: by Pommé (Problems with the Uncertainty Budget of Half-Life Measurements), Berlizov et al. (Evaluating Detection Limits for Environmental Monitoring Techniques in the Areas of Potential Impact from Nuclear Installations), and Potter (New Approach for the Decision Level and the Detection Limit in Paired Counting When There is Uncertainty Concerning the Expected Blank Count). Two other chapters: by Pommé and Keightley (Count Rate Estimation of a Poisson Process: Unbiased Fit versus Central Moment Analysis of Time Interval Spectra), as well as by Semkow (Bayesian Inference from Binomial and Poisson Processes for Multiple Sampling), discuss inference from the Poisson data encountered in nuclear science. Analysis of uncertainty continues to make important advances in nuclear science and is an area that will continue to require emphasis in the future. Validation (v), communication of results (c), and public participation (p) are not addressed in the symposium but are topics of key importance in risk assessment that are too frequently overlooked by scientists. In our work at Risk Assessment Corporation, we believe that i f the public is the target of risk, then the public should be involved in the risk assessment process. We believe a better product results i f members of the public are encouraged to provide input and i f they become engaged in the process as it occurs rather than waiting until the work is completed. Involving citizens, who are typically not scientists, significantly complicates the process but inevitably strengthens the work, especially in terms of its credibility. Furthermore, communication of the work and its results is best performed by the scientists who conducted the work. It is important to note that several chapters focus on the entire risk equation. The abovementioned chapter by Y u as well as the chapter by Grogan et al.


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7 (Modeling of the Cerro Grande Fire at Los Alamos: An Independent Analysis of Exposure, Health Risk, and Communication with the Public) look at risk assessment objectives in a comprehensive sense and are examples of the computational methods currently used to estimate dose and risk. Finally, the book contains several review chapters of general interest to applied nuclear-science modeling. These include chapters by Oblozinsky (Nuclear Data Analysis and the National Nuclear Data Center), Currie (Some Perspectives on Nuclear Detection and the Blank), and Semkow (Exponential Decay Law and Nuclear Statistics). Obviously, not every chapter in this book can be directly linked to the risk assessment process, but each author presents results that help improve our knowledge and understanding of risk assessment. This continuing evolution and improvement of nuclear science helps us in merging the different scientific disciplines and is critical to decision makers who are the ultimate end users of our work.

Risk Assessment as a Guide to Research in Nuclear Science Risk assessment can provide valuable insight to guide future research in nuclear science because of the "big picture" view it provides of the different sciences that it represents. This holistic approach allows us to identify the largest contributors to uncertainty. As we continue to improve our capability to quantify risk, we are always looking for ways to strengthen the weakest link in the calculation and to reduce the overall uncertainty. This information can be used to help focus our efforts on areas of nuclear science that most effectively reduce uncertainty or provide a better understanding of the results. Listed below are several areas of risk assessment and nuclear science that need more emphasis in the future, based on lessons from our recent work.

Background Radiation Dealing with background concentrations of naturally occurring radionuclides in risk assessment has always been problematic. In most cases, the concentrations in the environment are poorly characterized on a site-specific basis forcing scientists to use data imported from a variety of sources to quantify background for a specific area. This approach does not work well in risk assessment since background concentrations of radionuclides vary widely from one facility to another and between locations for a given facility. As a result, it is difficult to adequately account for background concentrations in a meaningful way in the risk assessment process. Several authors in this book propose new


8 methods for detecting background concentrations of radionuclides that could ultimately lead to better estimates of background in the future.


Uncertainty Improving estimates of uncertainty continues to be one of the most important fields of nuclear science. Although major improvements have been made in methods for uncertainty analysis in risk assessment, much more work is needed in this area. In particular, we need a better understanding of uncertainties associated with dose and risk coefficients, source terms, and environmental transport models. These three areas seem to dominate uncertainties in the overall estimation of risk when uncertainties are involved.

Validation Validation and testing of mathematical models used in nuclear science must continue to be a key focus of work in the future. Although it is impractical to validate estimates of risk to individuals, it is possible to validate and test different components of the risk calculation equation. Validation is particularly important for environmental transport models because, in most cases, it is not possible to measure concentrations at all locations. Therefore, mathematical modeling is the only way to reconstruct or predict concentrations.

Simplification of Risk Estimation Methods Another key area that requires further study is the development of readily available tools that allow a quick determination of radionuclides, pathways, and estimates of risk. These tools are especially needed to support emergency response to a nuclear accident or terrorist event. Although there are a number of computational methods available that could provide this information to decision makers, these computer codes are not easily applied to emergency response. It is crucial that we develop computer software that can quickly convey information about radionuclide behavior in the environment and the relative importance of pathways and radionuclides in terms of risk.


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Conclusions The chapters presented in this book contribute significantly to our knowledge and understanding of applied modeling and computations in nuclear science. The continuation and expansion of this fundamental research is vital to our future. Risk assessment is a form of applied modeling that combines the knowledge of many aspects of nuclear science in estimating risk to humans and the environment. The results of risk assessment can then be used to guide decision makers and help people understand the significance of radioactive materials present in their environment. Risk assessment can also be used to help researchers in nuclear science identify gaps in our knowledge and focus on issues that most effectively reduce uncertainty. This chapter explains the need for continued collaboration in these fundamental sciences and emphasizes the importance of efforts to bring scientists together to share and discuss the results of recent advances. A l l of the authors are commended for taking the time to document their research and share them with the editors of this book so that a lasting record of this knowledge now exists.


Applied Modeling and Computations in Nuclear Science: The

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