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At least 541 records · Page 30

Intercomparison and improvement of two-stream shortwave radiative transfer schemes in Earth system models for a unified treatment of cryospheric surfaces

Abstract. Snow is an important climate regulator because it greatly increases the surface albedo of middle and high latitudes of the Earth. Earth system models (ESMs) often adopt two-stream approximations with different radiative transfer techniques, the same snow therefore has different solar radiative properties depending whether it is on land or on sea ice. Here we intercompare three two-stream algorithms widely used in snow models, improve their predictions at large zenith angles, and introduce a hybrid model suitable for all cryospheric surfaces in ESMs. The algorithms are those employed by the SNow ICe and Aerosol Radiative (SNICAR) module used in land models, dEdd–AD used in Icepack, the column physics used in the Los Alamos sea ice model CICE and MPAS-Seaice, and a two-stream discrete-ordinate (2SD) model. Compared with a 16-stream benchmark model, the errors in snow visible albedo for a direct-incident beam from all three two-stream models are small (<±0.005) and increase as snow shallows, especially for aged snow. The errors in direct near-infrared (near-IR) albedo are small (<±0.005) for solar zenith angles θ<75∘, and increase as θ increases. For diffuse incidence under cloudy skies, dEdd–AD produces the most accurate snow albedo for both visible and near-IR (<±0.0002) with the lowest underestimate (−0.01) for melting thin snow. SNICAR performs similarly to dEdd–AD for visible albedos, with a slightly larger underestimate (−0.02), while it overestimates the near-IR albedo by an order of magnitude more (up to 0.04). 2SD overestimates both visible and near-IR albedo by up to 0.03. We develop a new parameterization that adjusts the underestimated direct near-IR albedo and overestimated direct near-IR heating persistent across all two-stream models for θ>75∘. These results are incorporated in a hybrid model SNICAR-AD, which can now serve as a unified solar radiative transfer model for snow in ESM land, land ice, and sea ice components.

58 GEOSCIENCES↗

Development of an object-oriented ORIGEN for advanced nuclear fuel modeling applications

The ORIGEN package serves as the core depletion and decay calculation module within the SCALE code system. A recent major re-factor to the ORIGEN code architecture as part of an overall modernization of the SCALE code system has both greatly enhanced its maintainability as well as afforded several new capabilities useful for incorporating depletion analysis into other code frameworks. This paper will present an overview of the improved ORIGEN code architecture (including the methods and data structures introduced) as well as current and potential future applications utilizing the new ORIGEN framework. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Systematic uncertainties in the measurement of the neutron lifetime using the Lunar Prospector neutron spectrometer

The lifetime of free neutrons measured in the laboratory has a longstanding disparity of ≈9 s. A space-based technique has recently been proposed to independently measure the neutron lifetime using interactions between the galactic cosmic rays and a low atmosphere planetary body. This technique has not produced competitive results yet due to constraints of nonoptimized data that contain large systematic errors. We use data from the neutron spectrometer on-board NASA's Lunar Prospector, and study two large systematics in the measurement of neutron lifetime: the lunar subsurface temperature and the lunar surface composition. We use the HeCd and HeSn neutron spectrometer data when the spacecraft was in a highly elliptical orbit during the orbit insertion period. We report the neutron lifetime using four different models that each have different choices of surface temperature and composition. The 5° [Prettyman et al ., J. Geophys. Res.: Planets 111, 2005JE002656 (2006)] and 2° [Wilson et al., Phys. Rev. C 104, 045501 (2021)] rebinned maps result in 777.6±11.7 s and 739.6±10.8 s, respectively. For the 20° map (Prettyman et al., 2006), constant equatorial and a latitude-dependent temperature model result in 738.6±10.8 s and 767.3±11.2 s, respectively. Increasing the complexities of the models accounting for the systematic effects increase the measured lifetime. However, the reported measurements are not competitive with the laboratory results due to large unaccounted systematics resulting from nonoptimized measurements and modeling assumptions. This work serves as a study of systematic uncertainties for future neutron lifetime measurements using the space-based technique. We estimate the effect on the lifetime from the choice of temperature model to be to be 28.7 ±15.5 s, and choice of compositional map (for 20° and 5° maps) to be 10.3 ±12.2 s.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Scattering and; Delay, Scale, and Sum Migration

How do we see? What is the mechanism? Consider standing in an open field on a clear sunny day. In the field are a yellow dog and a blue ball. From a wave-based remote sensing point of view the sun is a source of radiation. It is a broadband electromagnetic source which, for the purposes of this introduction, only the visible spectrum is considered (approximately 390 to 750 nanometers or 400 to 769 TeraHertz). The source emits an incident field into the known background environment which, for this example, is free space. The incident field propagates until it strikes an object or target, either the yellow dog or the blue ball. The interaction of the incident field with an object results in a scattered field. The scattered field arises from a mis-match between the background refractive index, considered to be unity, and the scattering object refractive index ('yellow' for the case of the dog, and 'blue' for the ball). This is also known as an impedance mis-match. The scattering objects are referred to as secondary sources of radiation, that radiation being the scattered field which propagates until it is measured by the two receivers known as 'eyes'. The eyes focus the measured scattered field to form images which are processed by the 'wetware' of the brain for detection, identification, and localization. When time series representations of the measured scattered field are available, the image forming focusing process can be mathematically modeled by delayed, scaled, and summed migration. This concept of optical propagation, scattering, and focusing have one-to-one equivalents in the acoustic realm. This document is intended to present the basic concepts of scalar scattering and migration used in wide band wave-based remote sensing and imaging. The terms beamforming and (delayed, scaled, and summed) migration are used interchangeably but are to be distinguished from the narrow band (frequency domain) beamforming to determine the direction of arrival of a signal, and seismic migration in which wide band time series are shifted but not to form images per se. Section 3 presents a mostly graphically-based motivation and summary of delay, scale, and sum beamforming. The model for incident field propagation in free space is derived in Section 4 under specific assumptions. General object scattering is derived in Section 5 and simplified under the Born approximation in Section 6. The model of this section serves as the basis in the derivation of time-domain migration. The Foldy-Lax, full point scatterer scattering, method is derived in Section 7. With the previous forward models in hand, delay, scale, and sum beamforming is derived in Section 8. Finally, proof-of-principle experiments are present in Section 9.

42 ENGINEERING↗

Accurate Holdup Calculations with Predictive Modeling & Data Integration

In facilities that process special nuclear material (SNM) it is important to account accurately for the fissile material that enters and leaves the plant. Although there are many stages and processes through which materials must be traced and measured, the focus of this project is material that is “held-up” in equipment, pipes, and ducts during normal operation and that can accumulate over time into significant quantities. Accurately estimating the holdup is essential for proper SNM accounting (vis-à-vis nuclear non-proliferation), criticality and radiation safety, waste management, and efficient plant operation. Usually it is not possible to directly measure the holdup quantity and location, so these must be inferred from measured radiation fields, primarily gamma and less frequently neutrons. Current methods to quantify holdup, i.e. Generalized Geometry Holdup (GGH), primarily rely on simple source configurations and crude radiation transport models aided by ad hoc correction factors. This project seeks an alternate method of performing measurement-based holdup calculations using a predictive model that employs state-of-the-art radiation transport codes capable of accurately simulating such situations. Inverse and data assimilation methods use the forward transport model to search for a source configuration that best matches the measured data and simultaneously provide an estimate of the level of confidence in the correctness of such configuration. In this work the holdup problem is re-interpreted as an inverse problem that is under-determined, hence may permit multiple solutions. A probabilistic approach is applied to solving the resulting inverse problem. This approach rates possible solutions according to their plausibility given the measurements and initial information. This is accomplished through the use of Bayes’ Theorem that resolves the issue of multiple solutions by giving an estimate of the probability of observing each possible solution. To use Bayes’ Theorem, one must have a model y(x) that maps the state variables x (the solution in this case) to the measurements y. In this case, the unknown state variables are the configuration and composition of the heldup SNM. The measurements are the detector readings. Thus, the natural model is neutral-particle radiation transport where a wealth of computational tools exists for performing these simulations accurately and efficiently. The combination of predictive model and Bayesian inference forms the Data Integration with Modeled Predictions (DIMP) method that serves as foundation for this project. The cost functional describing the model-to-data misfit is computed via a norm created by the inverse of the covariance matrix of the model parameters and responses. Since the model y(x) for the holdup problem is nonlinear, a nonlinear optimization on Q is conducted via Newton-type iterative methods to find the optimal values of the model parameters x. This project comprised a collaboration between NC State University (NCSU), the University of South Carolina (USC), and Oak Ridge National Laboratory (ORNL). The project was originally proposed in seven main tasks with an eighth contingency task to be performed if time and funding permitted; in fact time did not permit commencement of the contingency task and it was not performed. The remaining tasks involved holdup analysis with gamma detection strategies and separately with neutrons based on coincidence counting. Early in the project, and upon consultation with experts in coincidence counting it became evident that this approach is not viable for holdup applications and this task was replaced with an alternative, but valuable investigation that was carried out by the USC partner. Nevertheless, the experimental 4 measurements at ORNL of both gamma and neutron sources for the purpose of constructing Detector Response Functions (DRFs) with the associated uncertainties were indeed completed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains

Abstract. Based on long-term observations at the Southern Great Plains site by the Atmospheric Radiation Measurement (ARM) program for training and validation, a deep-learning model is developed to simulate the daytime evolution of boundary layer clouds (BLCs) from the perspective of land–atmosphere coupling. The model takes ARM measurements (including early-morning soundings and diurnally varying surface meteorological conditions and heat fluxes) as inputs and predicts hourly estimates (including cloud occurrence, the positions of cloud boundaries, and the vertical profile of the cloud fraction) as outputs. The deep-learning model offers good agreement with the observed cloud fields, especially in the accuracy with which cloud occurrence and base height are reproduced. When the inputs are substituted by reanalysis data from ERA5 and MERRA-2, the outputs of the deep-learning model provide a better agreement with observation than the cloud fields extracted from ERA5 and MERRA-2 themselves. Thus, the deep-learning model shows great potential to serve as a diagnostic tool for the performance of physics-based models in simulating stratiform and cumulus clouds. By quantifying biases in clouds and attributing them to the simulated atmospheric state variables versus the model-parameterized cloud processes, this observation-based deep-learning model may offer insights into the directions needed to improve the simulation of BLCs in physics-based models for weather forecasting and climate prediction.

54 ENVIRONMENTAL SCIENCES↗

Free Energy and Heat Capacity

Free energy and heat capacity of actinide elements and compounds are important properties for the evaluation of the safety and reliable performance of nuclear fuel. They are essential inputs for models that describe complex phenomena that govern the behaviour of actinide compounds during nuclear fuel fabrication and irradiation. This chapter introduces various experimental methods to measure free energy and heat capacity to serve as inputs for models and to validate computer simulations. This is followed by a discussion of computer simulation of these properties, and recent simulations of thermophysical properties of nuclear fuel are briefly reviewed.

free energy↗

Corrosion Testing of Refractory inContact with Molten Glasses Designed for Waste Vitrification - VSL Touchpoint Matrix Glasses

It is known that the predictive life of the refractory ceramic liner of nuclear waste glass melters is conservative, as demonstrated by performance of these materials such as in the Defense Waste Processing Facility (DWPF). The motivation for this task is to maximize the useful life of the melters that will be operated at the Waste Treatment and Immobilization Plant (WTP), which will in turn minimize procurement and disposal costs and melter outage times, as well as to identify maximum loadings in the waste glass of those species that corrode melter components. This task was initiated jointly with Pacific Northwest National Laboratory (PNNL) with the objective to develop a methodology and model to enable more accurate prediction of refractory service life under prototypic conditions from laboratory-scale material corrosion tests. Refractory corrosion is generally reported as physical material loss, measured in units of distance (e.g., inch) or as physical material loss rate, measured in units of distance per time (e.g., inch/day). In post-operational melters, the refractory corrosion is measured directly, sometimes reported as corrosion depth. Crucible tests are used in the laboratory to accelerate the refractory corrosion to facilitate a meaningful measurement in a commensurate amount of time. Crucible tests are particularly useful in understanding refractory corrosion across a large glass composition space, where operational testing would be prohibitive. Some of the critical parameters that are known to influence refractory corrosion by molten glass in a crucible test are temperature, system redox, molten salt phases, glass chemistry, and test duration. The majority of data collected for Monofrax® K-3 (hereafter referred to as K-3) corrosion is from crucible tests, but a small amount comes directly from scaled and production melters. Crucible test data has been collected under varying conditions, whereas data collected from operational melters is relatively fewer and represents conditions specific to the melter campaign. The result is that the published data can be grouped and analyzed in multiple ways, not all of which are readily comparable. The Standard Test Method for Isothermal Corrosion Resistance of Refractories to Molten Glass (ASTM C621) outlines the general guidelines used across industry. That method describes a sealed, static test in which the surface area of the refractory coupon and the volume of glass are fixed. A significant portion of the crucible data pertaining to nuclear waste glasses has been collected in a modified configuration; the most notable differences being the surface area of the refractory coupon to volume of the glass and use of a method for bubbling the melt. To our knowledge, the influence of those parameters on the refractory corrosion has not been quantified. In this work, it was determined that static tests and bubbled tests would be performed. Savannah River National Laboratory (SRNL) was tasked with setting up and performing static testing while PNNL was tasked with setting up and performing bubbled testing. Initial activities were performed to establish laboratory methods that reproduce data comparable to existing data sets of K-3 refractory corrosion by low activity waste (LAW) and high-level waste (HLW) glass compositions. Later activities were focused on refining the test parameters to establish a standard test practice to be used between Laboratories and collecting additional data to be used in the enhanced waste glass model development. This document serves primarily to convey the refractory loss measurement results from corrosion testing of K-3 refractory with waste glass compositions developed for use in the WTP melters. The data will be used in the enhanced property/composition models being developed for waste glass vitrification and melter operations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Performance and Safety Parameters for the High Flux Isotope Reactor

A Monte Carlo depletion model for the High Flux Isotope Reactor (HFIR) Cycle 400 and its use in calculating parameters of relevance to the reactor performance and safety during the reactor cycle are presented in this paper. This depletion model was developed to serve as a reference for the design of a low-enriched uranium (LEU) fuel for an ongoing study to convert HFIR from high-enriched uranium (HEU) to LEU fuel; both HEU and LEU depletion models use the same methodology and ENDV/B-VII nuclear data as discussed in this paper. The calculated HFIR Cycle 400 parameters, which are compared when available with measurement data from critical experiments performed at HFIR, data included in the HFIR Safety Analysis Report (SAR), or data reported by previous calculations, provide a basis for verification or updating of the corresponding SAR data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Performance and safety parameters for the high flux isotope reactor

A Monte Carlo depletion model for the High Flux Isotope Reactor (HFIR) Cycle 400 and its use in calculating parameters of relevance to the reactor performance and safety during the reactor cycle are presented in this paper. This depletion model was developed to serve as a reference for the design of a low-enriched uranium (LEU) fuel for an ongoing study to convert HFIR from high-enriched uranium (HEU) to LEU fuel; both HEU and LEU depletion models use the same methodology and ENDF/B-VII nuclear data as discussed in this paper. The calculated HFIR Cycle 400 parameters, which are compared with measurement data from critical experiments performed at HFIR, data included in the HFIR Safety Analysis Report (SAR), or data reported by previous calculations, provide a basis for verification or updating of the corresponding SAR data. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

An overview of the gene regulatory network controlling trichome development in the model plant, Arabidopsis

Trichomes are specialized epidermal cells located on aerial parts of plants and are associated with a wide array of biological processes. Trichomes protect plants from adverse conditions including UV light and herbivore attack and are also an important source of a number of phytochemicals. The simple unicellular trichomes of Arabidopsis serve as an excellent model to study molecular mechanism of cell differentiation and pattern formation in plants. The emerging picture suggests that the developmental process is controlled by a transcriptional network involving three major groups of transcription factors (TFs): the R2R3 MYB, basic helix-loop-helix (bHLH), and WD40 repeat (WDR) protein. These regulatory proteins form a trimeric activator complex that positively regulates trichome development. The single repeat R3 MYBs act as negative regulators of trichome development. They compete with the R2R3 MYBs to bind the bHLH factor and form a repressor complex. In addition to activator–repressor mechanism, a depletion mechanism may operate in parallel during trichome development. In this mechanism, the bHLH factor traps the WDR protein which results in depletion of WDR protein in neighboring cells. Consequently, the cells with high levels of bHLH and WDR proteins are developed into trichomes. A group of C2H2 zinc finger TFs has also been implicated in trichome development. Phytohormones, including gibberellins and jasmonic acid, play significant roles in this developmental process. Recently, microRNAs have been shown to be involved in trichome development. Furthermore, it has been demonstrated that the activities of the key regulatory proteins involved in trichome development are controlled by the 26S/ubiquitin proteasome system (UPS), highlighting the complexity of the regulatory network controlling this developmental process. To complement several excellent recent relevant reviews, this review focuses on the transcriptional network and hormonal interplay controlling trichome development in Arabidopsis.

59 BASIC BIOLOGICAL SCIENCES↗

Generic solar photovoltaic system dynamic simulation model specification

This document is intended to serve as a specification for generic solar photovoltaic (PV) system positive-sequence dynamic models to be implemented by software developers and approved by the WECC MVWG for use in bulk system dynamic simulations in accordance with NERC MOD standards. Two specific dynamic models are included in the scope of this document. The first, a Central Station PV System model, is intended to capture the most important dynamic characteristics of large scale (> 10 MW) PV systems with a central Point of Interconnection (POI) at the transmission level. The second, a Distributed PV System model, is intended to represent an aggregation of smaller, distribution-connected systems that comprise a portion of a composite load that might be modeled at a transmission load bus.

14 SOLAR ENERGY↗

Navajo residential solar energy access as a global model

Here, this case study focuses on the Navajo Nation’s efforts to provided residential power access through solar photovoltaic systems to some of its approximately 34,000 remote off-grid tribal members. The solution the Nation has adopted in collaboration with Sandia National Laboratories offers insights into how the Navajo Tribal Utility Authority’s work could serve as a residential model to meet the needs of the 1.2 billion people globally who are without electrical residential power.

14 SOLAR ENERGY↗

Development of doxorubicin-induced chronic cardiotoxicity in the B6C3F{sub 1} mouse model

Serum levels of cardiac troponins serve as biomarkers of myocardial injury. However, troponins are released into the serum only after damage to cardiac tissue has occurred. Here, we report development of a mouse model of doxorubicin (DOX)-induced chronic cardiotoxicity to aid in the identification of predictive biomarkers of early events of cardiac tissue injury. Male B6C3F{sub 1} mice were administered intravenous DOX at 3 mg/kg body weight, or an equivalent volume of saline, once a week for 4, 6, 8, 10, 12, and 14 weeks, resulting in cumulative DOX doses of 12, 18, 24, 30, 36, and 42 mg/kg, respectively. Mice were sacrificed a week following the last dose. A significant reduction in body weight gain was observed in mice following exposure to a weekly DOX dose for 1 week and longer compared to saline-treated controls. DOX treatment also resulted in declines in red blood cell count, hemoglobin level, and hematocrit compared to saline-treated controls after the 2nd weekly dose until the 8th and 9th doses, followed by a modest recovery. All DOX-treated mice had significant elevations in cardiac troponin T concentrations in plasma compared to saline-treated controls, indicating cardiac tissue injury. Also, a dose-related increase in the severity of cardiac lesions was seen in mice exposed to 24 mg/kg DOX and higher cumulative doses. Mice treated with cumulative DOX doses of 30 mg/kg and higher showed a significant decline in heart rate, suggesting drug-induced cardiac dysfunction. Altogether, these findings demonstrate the development of DOX-induced chronic cardiotoxicity in B6C3F{sub 1} mice. -- Highlights: ► 24 mg/kg was a cumulative cardiotoxic dose of doxorubicin in male B6C3F{sub 1} mice. ► Doxorubicin-induced hematological toxicity was in association with splenomegaly. ► Doxorubicin induced severe testicular toxicity in B6C3F{sub 1} male mice.

60 APPLIED LIFE SCIENCES↗

Quantifying the Impact of Nanoparticle Coatings and Non-uniformities on XPS Analysis: Gold/silver Core-shell Nanoparticles

Abstract or short description: Spectral modeling of photoelectrons can serve as a valuable tool when combined with X-ray photoelectron spectroscopy (XPS) analysis. Herein, a new version of the NIST Simulation of Electron Spectra for Surface Analysis (SESSA 2.0) software, capable of directly simulating spherical multilayer NPs, was applied to model citrate stabilized Au/Ag-core/shell nanoparticles (NPs). The NPs were characterized using XPS and scanning transmission electron microscopy (STEM) to determine the composition and morphology of the NPs. The Au/Ag-core/shell NPs were observed to be polydispersed in size, non-circular, and contain off-centered Au-cores. Using the average NP dimensions determined from STEM analysis, SESSA spectral modeling indicated that washed Au/Ag-core shell NPs were stabilized with a 0.8 nm l

Core-shell nanoparticles↗

Studying biomineralization pathways in a 3D culture model of breast cancer microcalcifications

Microcalcifications serve as diagnostic markers for breast cancer, yet their formation pathway(s) and role in cancer progression are debated due in part to a lack of relevant 3D culture models that allow studying the extent of cellular regulation over mineralization. Previous studies have suggested processes ranging from dystrophic mineralization associated with cell death to bone-like mineral deposition. In this paper, we evaluated microcalcification formation in 3D multicellular spheroids, generated from non-malignant, pre-cancer, and invasive cell lines from the MCF10A human breast tumor progression series. The spheroids with greater malignancy potential developed necrotic cores, thus recapitulating spatially distinct viable and non-viable areas known to regulate cellular behavior in tumors in vivo. The spatial distribution of the microcalcifications, as well as their compositions, were characterized using nanoCT, electron-microscopy, and X-ray spectroscopy. Apatite microcalcifications were primarily detected within the viable cell regions and their number and size increased with malignancy potential of the spheroids. Levels of alkaline phosphatase decreased with malignancy potential, whereas levels of osteopontin increased. Finally, these findings support a mineralization pathway in which cancer cells induce mineralization in a manner that is linked to their malignancy potential, but that is distinct from physiological osteogenic mineralization.

60 APPLIED LIFE SCIENCES↗

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗

Application of Structured Decision Making to Hanford Site Radiological Air Monitoring - 17924

Radiological air monitoring is a component of an Environmental Surveillance (ES) program that has been in operation at the Department of Energy Hanford Site for several decades. The primary objectives of the ES program are protection of human health and the environment (on and off-site) as well as regulatory compliance. The ES program was designed decades ago when the plutonium-production reactors and related facilities at the Hanford Site were operational and air emissions were more widespread and significant than today. We employed a structured decision making (SDM) approach that integrates science with values and preferences to a Hanford Site air monitoring program decision. Specifically, a decision was necessary pertaining to the possible replacement of three air monitoring stations located in the 100 Area of the Hanford Site because the power line that supports these stations was near the end of its lifecycle. Although focused on this specific decision, the SDM model is more broadly applicable to decisions pertaining to adapting the air monitoring network to current Hanford operations. The value focused thinking approach that underlies SDM facilitates transparent and defensible decision making, and aids in communicating monitoring rationale. Some of the fundamental objectives elicited from the decision makers regarding management options for the three air monitoring stations included maximizing the ability to measure releases, minimizing environmental impacts, and maximizing social and economic sustainability. The fundamental objectives were linked to six objectives that could be measured (quantified) to allow a decision-analytic solution to the decision problem. Value functions and preference weights were developed for each of the objectives measures based on information obtained during a project workshop as well as by review and analysis of environmental data. Lastly, a set of five management options was identified that might achieve at least one of the objectives. A Bayes Network was developed as a solution to the decision problem pertaining to the three air stations (the 3 air stations decision). The Bayes Network describes the decision model graphically, and also serves as the computational engine for the decision analysis. The Bayes Network defines the relationship among the five management options and six objectives measures. In addition to the weights and value functions noted above, key inputs to the Bayes Network include a set of probabilities related to the different model states defined by the network. These include the probability of a significant release occurring, the probability that a release would be detected under each of the five management options, and the probability of achieving the other objective measures under each management option. In this manner the Bayesian Network captures the uncertainty in the components of the decision model. Replacing the three air monitoring stations with thermoluminescent dosimeters was identified as the preferred management option. A brief report was developed documenting the SDM model, including the workshop notes and analyses that were used to develop the objectives and model input variable values. This application demonstrates SDM's utility for supporting monitoring program decisions and, critically, providing a transparent and traceable basis for the decision. This relatively simple SDM model also provides a basis for an SDM model for monitoring decisions related to the more complex and holistic goal of achieving ES program objectives. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗