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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Flaw Tolerance Assessment for DOE Standard SNF Dry Storage Canisters - 26550

The U.S. DOE has designed four spent nuclear fuel (SNF) dry storage canisters for storing DOE standardized SNFs. The DOE standard canisters are cylindrical shells with a diameter of 24 inches (610 m) or 18 inches (457 m), a wall thickness of 0.5 inches (12.7 m) or 0.375 inches (9.53 m), and a length of 15 feet (4.57 m) or 10 feet (3.05 m). These DOE canister geometries are completely different from commercial canisters. The latter may experience chloride-induced stress cracking corrosion (CI-SCC) because they are stored near coastal regions. The former may not experience CI-SCC but face different challenges because they are stored in the SNF storage facilities. Because of large residual stresses, mechanical flaws may occur in the DOE canisters during long-distance transportation or lifting handling. To date, only limited structural integrity analyses were carried out through drop tests on the DOE canisters, but a more general flaw tolerance assessment has not been performed. Therefore, the failure assessment diagram (FAD)-based fracture mechanics method, as codified by the latest API 579-1/ASME FFS-1-2021 Edition, is adopted in this work to assess surface flaw tolerance for DOE canisters under operation loading and welding residual stresses (WRS), where the new code-recommended WRS distributions are used. To more adequately consider the transverse distribution of WRS, an equivalent WRS distribution is proposed to account for the WRS reduction with distance from the weld centerline. Moreover, the closed-form solutions of stress intensity factor K, which serves as the crack driving force during subcritical crack growth, are developed from the tabular data of the K factors provided in API 579-1/ASME FFS-1 and used to determine more accurate flaw sizes at flaw instability. Subsequently, the Level 2 assessment procedures with 12 assessment steps, as codified and detailed in API 579-1 and ASME FFS-1, are followed to assess the flaw tolerance for the surface flaws in the DOE standard canisters with consideration of normal or accident operation loads combined with WRS. The assessment results show that the four designs of DOE standard canisters can tolerate all surface flaws that meet the code permitted maximum sizes of a flaw length of 8 inches (i.e., 200 mm) and a flaw depth of 80% wall thickness. This demonstrates that all designs of DOE standard canisters are robust and reliable.

DOE standard canister↗
DOE OSTI2025

Projections of future climate for U.S. national assessments: past, present, future

Climate assessments consolidate our understanding of possible future climate conditions as represented by climate projections, which are largely based on the output of global climate models. Over the past 30 years, the scientific insights gained from climate projections have been refined through model structural improvements, emerging constraints on climate feedbacks, and increased computational efficiency. Within the same period, the process of assessing and evaluating information from climate projections has become more defined and targeted to inform users. As the size and audience of climate assessments has expanded, the framing, relevancy, and accessibility of projections has become increasingly important. This paper reviews the use of climate projections in national climate assessments (NCA) while highlighting challenges and opportunities that have emerged over time. Reflections and lessons learned address the continuous process to understand the broadening assessment audience and evolving user needs. Insights for future NCA development include (1) identifying benchmarks and standards for evaluating downscaled datasets, (2) expanding efforts to gather research gaps and user needs to inform how climate projections are presented in the assessment (3) providing practitioner guidance on the use, interpretation, and reporting of climate projections and uncertainty to better inform decision-making.

Assessment↗
DOE OSTI2016

Fast estimation of dense gas dispersion from multiple continuous CO 2 surface leakage sources for risk assessment

Surface leakage of CO 2 , and associated potential impacts on health, safety, and the environment (HSE) are considered hazards of geologic carbon sequestration (GCS). There are two challenges associated with impact assessment of CO 2 surface dispersion. First, the fact that CO 2 is a dense gas makes its dispersion in air a complex process. Rigorous numerical solutions for modeling concentration distributions are relatively time-consuming. Second, impact assessment requires consideration of uncertainty, e.g., quantification of how much uncertainty is propagated through input parameters to model outputs by carrying out large numbers of model runs. In order to assess the potential consequences of surface leakage of CO 2 , it is useful to have a model that executes very quickly for repeated model calculations (e.g., in Monte Carlo mode) of the atmospheric dispersion of CO 2 (concentrations as a function of space and time). In addition, the model should be able to handle multiple surface leakage sources. In this work, we have extended the nomograph approach of Britter and McQuaid (1988) for estimating dense gas plume length from single leakage source to multiple leakage sources. The method is very fast and therefore amenable to general system-level GCS risk assessment including uncertainty quantification within the framework of the National Risk Assessment Partnership (NRAP) Integrated Assessment Model (IAM). The method is conservative in that it assumes the wind could be from any direction, and it handles multiple sources by a simple superposition approach. The method produces results in reasonable agreement with a sophisticated computational fluid dynamics (CFD) code, but runs in a small fraction of the time.

58 GEOSCIENCES↗
DOE OSTI2015

Applications of aggregation theory to sustainability assessment

In order to aid in transition towards operations that promote sustainability goals, researchers and stakeholders use sustainability assessments. Although assessments take various forms, many utilize diverse sets of indicators that can number anywhere from two to over 2000. Indices, composite indicators, or aggregate values are used to simplify high dimensional and complex data sets and to clarify assessment results. Although the choice of aggregation function is a key component in the development of the assessment, there are few examples to be found in literature to guide appropriate aggregation function selection. This paper develops a connection between the mathematical study of aggregation functions and sustainability assessment in order to aid in providing criteria for aggregation function selection. Relevant mathematical properties of aggregation functions are presented and interpreted. Lastly, we provide cases of these properties and their relation to previous sustainability assessment research. Examples show that mathematical aggregation properties can be used to address the topics of compensatory behavior and weak versus strong sustainability, aggregation of data under varying units of measurements, multiple site multiple indicator aggregation, and the determination of error bounds in aggregate output for normalized and non-normalized indicator measures.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2012

Climate impacts of bioenergy: Inclusion of carbon cycle and albedo dynamics in life cycle impact assessment

Life cycle assessment (LCA) can be an invaluable tool for the structured environmental impact assessment of bioenergy product systems. However, the methodology's static temporal and spatial scope combined with its restriction to emission-based metrics in life cycle impact assessment (LCIA) inhibits its effectiveness at assessing climate change impacts that stem from dynamic land surface-atmosphere interactions inherent to all biomass-based product systems. In this paper, we focus on two dynamic issues related to anthropogenic land use that can significantly influence the climate impacts of bioenergy systems: i) temporary changes to the terrestrial carbon cycle; and ii) temporary changes in land surface albedo-and illustrate how they can be integrated within the LCA framework. In the context of active land use management for bioenergy, we discuss these dynamics and their relevancy and outline the methodological steps that would be required to derive case-specific biogenic CO{sub 2} and albedo change characterization factors for inclusion in LCIA. We demonstrate our concepts and metrics with application to a case study of transportation biofuel sourced from managed boreal forest biomass in northern Europe. We derive GWP indices for three land management cases of varying site productivities to illustrate the importance and need to consider case- or region-specific characterization factors for bioenergy product systems. Uncertainties and limitations of the proposed metrics are discussed. - Highlights: Black-Right-Pointing-Pointer A method for including temporary surface albedo and carbon cycle changes in Life Cycle Impact Assessment (LCIA) is elaborated. Black-Right-Pointing-Pointer Concepts are applied to a single bioenergy case whereby a range of feedstock productivities are shown to influence results. Black-Right-Pointing-Pointer Results imply that case- and site-specific characterization factors can be essential for a more informed impact assessment. Black-Right-Pointing-Pointer Uncertainties and limitations of the proposed methodologies are elaborated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Metal uptake by homegrown vegetables – The relative importance in human health risk assessments at contaminated sites

Risk assessments of contaminated land often involve the use of generic bioconcentration factors (BCFs), which express contaminant concentrations in edible plant parts as a function of the concentration in soil, in order to assess the risks associated with consumption of homegrown vegetables. This study aimed to quantify variability in BCFs and evaluate the implications of this variability for human exposure assessments, focusing on cadmium (Cd) and lead (Pb) in lettuce and potatoes sampled around 22 contaminated glassworks sites. In addition, risks associated with measured Cd and Pb concentrations in soil and vegetable samples were characterized and a probabilistic exposure assessment was conducted to estimate the likelihood of local residents exceeding tolerable daily intakes. The results show that concentrations in vegetables were only moderately elevated despite high concentrations in soil, and most samples complied with applicable foodstuff legislation. Still, the daily intake of Cd (but not Pb) was assessed to exceed toxicological thresholds for about a fifth of the study population. Bioconcentration factors were found to vary more than indicated by previous studies, but decreasing BCFs with increasing metal concentrations in the soil can explain why the calculated exposure is only moderately affected by the choice of BCF value when generic soil guideline values are exceeded and the risk may be unacceptable. - Highlights: • Uptake of Cd and Pb by lettuce and potatoes increased with soil contamination. • Consumption of homegrown vegetables may lead to a daily Cd intake above TDIs. • The variability in the calculated BCFs is high when compared to previous studies. • Exposure assessments are most sensitive to the choice of BCFs at low contamination.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates

Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of error that reduces the predictive performance of the models and confidence in the resulting resource estimates. Our study aims to develop robust data-driven methods with the goals of reducing bias and improving predictive ability. We present and compare nine favorability maps for geothermal resources in the western United States using data from the U.S. Geological Survey's 2008 geothermal resource assessment. Two favorability maps are created using the expert decision-dependent methods from the 2008 assessment (i.e., weight-of-evidence and logistic regression). With the same data, we then create six different favorability maps using logistic regression (without underlying expert decisions), XGBoost, and support-vector machines paired with two training strategies. The training strategies are customized to address the inherent challenges of applying machine learning to the geothermal training data, which have no negative examples and severe class imbalance. We also create another favorability map using an artificial neural network. We demonstrate that modern machine learning approaches can improve upon systems built with expert decisions. We also find that XGBoost, a non-linear algorithm, produces greater agreement with the 2008 results than linear logistic regression without expert decisions, because the expert decisions in the 2008 assessment rendered the otherwise linear approaches non-linear despite the fact that the 2008 assessment used only linear methods. The F1 scores for all approaches appear low (F1 score < 0.10), do not improve with increasing model complexity, and, therefore, indicate the fundamental limitations of the input features (i.e., training data). Until improved feature data are incorporated into the assessment process, simple non-linear algorithms (e.g., XGBoost) perform equally well or better than more complex methods (e.g., artificial neural networks) and remain easier to interpret.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

An approach to urban waterway assessment using holistic values and reciprocity

Current aquatic ecosystem assessment methods and tools often focus on physical, chemical, and biological indicators of ecosystem health. This approach to ecosystem assessment is not always straightforward to execute in urban environments and ignores potential connectivity between social and environmental outcomes. During a workshop at the Symposium on Urbanization and Stream Ecology in Brisbane, Australia in 2023 (SUSE6), we developed an approach to urban aquatic ecosystem assessment that incorporates a holistic perspective. Specifically, our approach considers both environmental (biological, chemical, and physical integrity) and social (community connection, human safety, resource use) values of urban waterways. This approach is inclusive of Indigenous perspectives, such as the concept of reciprocity, whereby consideration of both the environment and society leads to a healthy ecosystem. Here, to highlight how this holistic assessment approach could be used, we present real-world examples that included assessing both environmental and societal values informed by reciprocity or balanced perspectives. This approach can be broadly applied and adapted to specific aquatic ecosystem conditions and projects, providing an inclusive, community-centered approach for assessing the health of waterways in urban environments.

Indigenous knowledge↗
DOE OSTI2014

Predictive Dynamic Security Assessment through Advanced Computing

Abstract— Traditional dynamic security assessment is limited by several factors and thus falls short in providing real-time information to be predictive for power system operation. These factors include the steady-state assumption of current operating points, static transfer limits, and low computational speed. This addresses these factors and frames predictive dynamic security assessment. The primary objective of predictive dynamic security assessment is to enhance the functionality and computational process of dynamic security assessment through the use of high-speed phasor measurements and the application of advanced computing technologies for faster-than-real-time simulation. This paper presents algorithms, computing platforms, and simulation frameworks that constitute the predictive dynamic security assessment capability. Examples of phasor application and fast computation for dynamic security assessment are included to demonstrate the feasibility and speed enhancement for real-time applications.

advanced, computing, security, assessment, predict↗
DOE OSTI2016

WE-B-BRC-00: Concepts in Risk-Based Assessment

Prospective quality management techniques, long used by engineering and industry, have become a growing aspect of efforts to improve quality management and safety in healthcare. These techniques are of particular interest to medical physics as scope and complexity of clinical practice continue to grow, thus making the prescriptive methods we have used harder to apply and potentially less effective for our interconnected and highly complex healthcare enterprise, especially in imaging and radiation oncology. An essential part of most prospective methods is the need to assess the various risks associated with problems, failures, errors, and design flaws in our systems. We therefore begin with an overview of risk assessment methodologies used in healthcare and industry and discuss their strengths and weaknesses. The rationale for use of process mapping, failure modes and effects analysis (FMEA) and fault tree analysis (FTA) by TG-100 will be described, as well as suggestions for the way forward. This is followed by discussion of radiation oncology specific risk assessment strategies and issues, including the TG-100 effort to evaluate IMRT and other ways to think about risk in the context of radiotherapy. Incident learning systems, local as well as the ASTRO/AAPM ROILS system, can also be useful in the risk assessment process. Finally, risk in the context of medical imaging will be discussed. Radiation (and other) safety considerations, as well as lack of quality and certainty all contribute to the potential risks associated with suboptimal imaging. The goal of this session is to summarize a wide variety of risk analysis methods and issues to give the medical physicist access to tools which can better define risks (and their importance) which we work to mitigate with both prescriptive and prospective risk-based quality management methods. Learning Objectives: Description of risk assessment methodologies used in healthcare and industry Discussion of radiation oncology-specific risk assessment strategies and issues Evaluation of risk in the context of medical imaging and image quality E. Samei: Research grants from Siemens and GE.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-B-BRC-01: Current Methodologies in Risk Assessment

Prospective quality management techniques, long used by engineering and industry, have become a growing aspect of efforts to improve quality management and safety in healthcare. These techniques are of particular interest to medical physics as scope and complexity of clinical practice continue to grow, thus making the prescriptive methods we have used harder to apply and potentially less effective for our interconnected and highly complex healthcare enterprise, especially in imaging and radiation oncology. An essential part of most prospective methods is the need to assess the various risks associated with problems, failures, errors, and design flaws in our systems. We therefore begin with an overview of risk assessment methodologies used in healthcare and industry and discuss their strengths and weaknesses. The rationale for use of process mapping, failure modes and effects analysis (FMEA) and fault tree analysis (FTA) by TG-100 will be described, as well as suggestions for the way forward. This is followed by discussion of radiation oncology specific risk assessment strategies and issues, including the TG-100 effort to evaluate IMRT and other ways to think about risk in the context of radiotherapy. Incident learning systems, local as well as the ASTRO/AAPM ROILS system, can also be useful in the risk assessment process. Finally, risk in the context of medical imaging will be discussed. Radiation (and other) safety considerations, as well as lack of quality and certainty all contribute to the potential risks associated with suboptimal imaging. The goal of this session is to summarize a wide variety of risk analysis methods and issues to give the medical physicist access to tools which can better define risks (and their importance) which we work to mitigate with both prescriptive and prospective risk-based quality management methods. Learning Objectives: Description of risk assessment methodologies used in healthcare and industry Discussion of radiation oncology-specific risk assessment strategies and issues Evaluation of risk in the context of medical imaging and image quality E. Samei: Research grants from Siemens and GE.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Battelle Energy Alliance, LLC (BEA) 2016 Self-Assessment Report for Idaho National Laboratory (INL)

This report provides Battelle Energy Alliance’s (BEA) self-assessment of performance for the period of October 1, 2015, through September 30, 2016, as evaluated against the goals, performance objectives, and notable outcomes defined in the Fiscal Year (FY) 2016 Performance Evaluation and Measurement Plan (PEMP). BEA took into consideration and consolidated all input provided from internal and external sources (e.g., Contractor Assurance System [CAS], program and customer feedback, external and independent reviews, and Department of Energy [DOE] Idaho Operations Office [ID] quarterly PEMP reports and Quarterly Evaluation Reports). The overall performance of BEA during this rating period was self-assessed as “Excellent,” exceeding expectations of performance in Goal 1.0, “Efficient and Effective Mission Accomplishment”; Goal 2.0, “Efficient and Effective Stewardship and Operation of Research Facilities”; and Goal 3.0, “Sound and Competent Leadership and Stewardship of the Laboratory.” BEA met or exceeded expectations for Mission Support Goals 4.0 through 7.0 assessing a final multiplier of 1.0. Table 1 documents BEA’s assessment of performance to the goals and individual performance objectives. Table 2 documents completion of the notable outcomes. A more-detailed assessment of performance for each individual performance objective is documented in the closeout reports (see the PEMP reporting system). Table 3 includes an update to “Performance Challenges” as reported in the FY 2015 Self-Assessment Report.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

An Integrated Framework for Risk Assessment of Safety-related Digital Instrumentation and Control Systems in Nuclear Power Plants: Methodology Refinement and Exploration

This report documents activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2023 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a technical basis to support effective, and secure DI&C technologies for digital upgrades/designs. A risk assessment-informed framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk informed capability to quantitatively estimate the safety margin obtained from plant modernization, especially for safety-related DI&C systems, (2) support and supplement existing risk informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems, (4) assure the long-term safety and reliability of safety-related DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals, the LWRS-developed framework provides a means to address relevant technical issues by: (1) defining a risk informed analysis process for DI&C upgrade that integrates hazard analysis, reliability analysis, and consequence analysis, (2) applying risk informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development and deployment of advanced DI&C technologies in nuclear power plants (NPPs). Adding diversity within a system or components is the primary means to eliminate and mitigate CCFs, but diversity also increases system complexity and may not address all sources of systematic failures. Optimization of diversity and redundancy applications for the safety-critical DI&C systems remains a challenge. To deal with the technical issues in addressing potential software CCFs in safety-related DI&C systems of NPPs and supporting relevant design optimization, the proposed framework provides: (a) A best-estimate, risk informed capability to address new technical digital issues quantitatively, focusing on software CCFs in safety-related DI&C systems of NPPs; (b) A common and a modularized platform for DI&C designers, software developers, cybersecurity analysts, and plant engineers to predict and prevent risk in the early design stage of DI&C systems; (c) Technical bases and risk informed insights to assist users address the risk informed alternatives for evaluation of CCFs in safety-related DI&C systems of NPPs; and (d) A risk informed tool that offers a capability of design architecture evaluation of various DI&C systems to support system design decisions in diversity and redundancy applications. The research and development efforts of this project in FY 2023 are focused on refining current methods on software CCF modeling and estimation and exploring additional innovative approaches to risk assessment of DI&C systems to enable a more comprehensive and complete assessment of various safety-related DI&C design architectures. The primary audience of this report are DI&C designers, engineers, and probabilistic risk assessment (PRA) practitioners. This includes stakeholders, such as the nuclear utilities and regulators who consider the deployment and upgrade of DI&C systems, DI&C software developers and reviewers, and cybersecurity specialists. It should be noted that all the analyses are performed for the demonstration of the methodology, not for the evaluation of an actual digital control system. Results are obtained based on limited design information and testing data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Summary of Technical Peer Review on the Risk Assessment Framework proposed in Report INL/RPT-22-68656 for Digital Instrumentation and Control Systems

This report summarizes the peer review activities initiated by Idaho National Laboratory (INL) during fiscal year (FY) 2023 for the evaluation and improvement of the methodology developed under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a technical basis to support effective and secure DI&C technologies for digital upgrades/designs. A framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk-informed capability to quantitatively and accurately estimate the risk impact of plant modernization, considering the introduction of high safety-significant safety-related (HSSSR) DI&C systems, (2) support and supplement existing risk-informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems, (4) assure the long-term safety and reliability of HSSSR DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. The R&D efforts of this project from FY 2019 through FY 2022 were focused on methodology improvement and demonstration of the proposed framework for the risk assessment and design optimization of safety-critical DI&C systems. Collaborations with the nuclear industry have been initiated to support the reliability and risk assessment of their DI&C systems by using the proposed framework. In FY 2023, the framework has reached to a point for a technical peer review and obtain stakeholder feedback. This peer review activity includes coordination of the reviews performed by a group of industry stakeholders, documentation of the peer review suggestions, providing resolutions and responses to the peer review comments. The objective of this technical peer review is to obtain representative feedback on the proposed framework to improve the technical qualities of its methodology and readiness for deployment to the industry. Feedback may identify potential areas for improvement and further development. The Subject Matter experts were invited to review the latest project report documenting the methodology developed in the project and provide evaluations of the technical qualities of the proposed framework and relevant methods. The reviewed project report is “An Integrated Framework for Risk Assessment of High Safety-significant Safety-related Digital Instrumentation and Control Systems in Nuclear Power Plants: Methodology and Demonstration” INL/RPT-22-68656 (short as “INL/RPT-22-68656” in this report). This peer review report documents the technical questions provided for technical peer review and introduces the technical peer reviewers from the stakeholders including nuclear utilities, regulators, and universities. Comments from technical peer reviewers and the resolutions and responses to these comments are outlined. Insights and lessons learned from the technical peer review are summarized in conclusions and future work. The primary audience of this report are DI&C designers, engineers, and probabilistic risk assessment (PRA) practitioners. This includes stakeholders, such as the nuclear utilities and regulators who consider the deployment and upgrade of DI&C systems, DI&C software developers and reviewers, and cybersecurity specialists.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Wind Resource Assessment for Alaska’s Offshore Regions: Validation of a 14-Year High-Resolution WRF Data Set

Offshore wind resource assessments for the conterminous U.S. and Hawai’i have been developed before, but Alaska’s offshore wind resource has never been rigorously assessed. Alaska, with its vast coastline, presents ample potential territory in which to build offshore wind farms, but significant challenges have thus far limited Alaska’s deployment of utility-scale wind energy capacity to a modest 62 MW (or approximately 2.7% of the state’s electric generation) as of this writing, all in land-based wind farms. This study provides an assessment of Alaska’s offshore wind resource, the first such assessment for Alaska, using a 14-year, high-resolution simulation from a numerical weather prediction and regional climate model. This is the longest-known high-resolution model data set to be used in a wind resource assessment. Widespread areas with relatively shallow ocean depth and high long-term average 100-m wind speeds and estimated net capacity factors over 50% were found, including a small area near Alaska’s population centers and the largest transmission grid that, if even partially developed, could provide the bulk of the state’s energy needs. The regional climate simulations were validated against available radiosonde and surface wind observations to provide the confidence of the model-based assessment. The model-simulated wind speed was found to be skillful and with near-zero average bias (−0.4–0.2 m s−1) when averaged over the domain. Small sample sizes made regional validation noisy, however.

17 WIND ENERGY↗
DOE OSTI2019

Simulating 10,000 Years of Erosion to Assess Nuclear Waste Repository Performance

Long-term environmental performance assessments of natural processes, including erosion, are critically important for waste repository site evaluation. Yet, assessing a site’s ability to continuously function is challenging due to parameter uncertainty and compounding nonlinear processes. In lieu of unavailable site data for model calibration, we present a workflow to include multiple sources of surrogate data and reduced-order models to validate parameters for a long-term erosion assessment of a low-level radioactive nuclear waste repository. We apply this new workflow to a low-level waste repository on mesas in Los Alamos National Laboratory in New Mexico. To account for parameter uncertainty, we simulate high-, moderate-, and low-erosion cases. The assessment extends to 10,000 years, which results in large erosion uncertainties, but is necessary given the nature of the interred waste. Our long-term erosion analysis shows that high-erosion scenarios produce rounded mesa tops and partially filled canyons, diverging from the moderate-erosion case that results in gullies and sharp mesa rims. Our novel model parameterization workflow and modeling exercise demonstrates the utility of long-term assessments, identifies sources of erosion forecast uncertainty, and demonstrates the utility of landscape evolution model development. We end with a discussion on methods to reduce assessment uncertainty and increase model confidence.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2014

Uncertainty in Agricultural Impact Assessment

This chapter considers issues concerning uncertainty associated with modeling and its use within agricultural impact assessments. Information about uncertainty is important for those who develop assessment methods, since that information indicates the need for, and the possibility of, improvement of the methods and databases. Such information also allows one to compare alternative methods. Information about the sources of uncertainties is an aid in prioritizing further work on the impact assessment method. Uncertainty information is also necessary for those who apply assessment methods, e.g., for projecting climate change impacts on agricultural production and for stakeholders who want to use the results as part of a decision-making process (e.g., for adaptation planning). For them, uncertainty information indicates the degree of confidence they can place in the simulated results. Quantification of uncertainty also provides stakeholders with an important guideline for making decisions that are robust across the known uncertainties. Thus, uncertainty information is important for any decision based on impact assessment. Ultimately, we are interested in knowledge about uncertainty so that information can be used to achieve positive outcomes from agricultural modeling and impact assessment.

damage assessment↗
NASA NTRSDate not supplied

Independent Reliability Assessment of the NASA GSFC Laser Transmitter for the LISA Program

The Laser Interferometer Space Antenna (LISA) is a partnership between the European Space Agency (ESA) and NASA to build a Gravitational Wave (GW) observatory. The observatory, which consists of a three-spacecraft constellation with a nominal separation of 2.5 million km between each spacecraft, provides a tool for scientists to directly detect gravitational waves generated from various astronomical phenomena in a waveband that is not accessible from Earth. NASA is developing laser transmitters as one of the potential US contributions to LISA. The NASA laser design leverages lessons learned from previous flight missions and included the latest technologies in photonics packaging and reliability engineering to ensure a laser lifetime of >16 years covering integration and test through a possible extended mission phase. As part of the laser development process, NASA’s Goddard Space Flight Center (GSFC) requested support from the NASA Engineering and Safety Center (NESC) to independently assess the Technology Readiness Level (TRL) of the LISA Laser System (LS). The independent assessment included the following tasks: (a) assess the design for weaknesses and suggest improvements to mitigate risks, (b) assess the laser reliability plan for weaknesses and suggest improvements to mitigate risks and improve effectiveness, and (c) assess the current redundancy plan on laser subsystems for weaknesses and suggest improvements to mitigate risks and improve effectiveness. The NESC team comprised of a team of subject matter experts (SMEs) and performed a 12-month review of every aspect of the laser design. We present the assessment findings and the current development progress of the LISA laser to meet the mission requirements with a delivery of a form, fit, and functional TRL6 laser to the LSIA mission by late 2023.

LISA↗