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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Insights into Methodologies and Operational Details of Resource Adequacy Assessment: A Case Study with Application to a Broader Flexibility Framework

Assessing and maintaining resource adequacy (RA) is a core pillar of power systems. However, recent changes in the physical makeup of these systems and the conditions under which these systems must operate have yielded a renewed interest in the methods, metrics, and assumptions that underpin RA assessments. In this paper, we systematically explore a wide range of RA modeling dimensions, including: the objective function and level of operational detail in the underlying model formulation; the quantity (look-ahead) and quality (accuracy) of data that is available for making operational decisions within those models; and the physical configuration of solar photovoltaics (PV) with battery storage hybrid resources. We apply a set of probabilistic RA tools and production cost modeling tools to a realistic test system based loosely on a future Electric Reliability Council of Texas power system dominated by solar PV resources. Under the assumptions of our system and models, we find that multi-stage probabilistic assessments may provide a more robust evaluation of RA by capturing a wider range of operational and system interactions, but this comes at a computational cost of 1-2 orders of magnitude longer run time depending on the specific configuration. In addition, the information on thermal generator availability impacts RA performance by an order of magnitude more than solar resource forecasts, which is driven by the comparatively larger magnitude of thermal outages than solar forecast errors within our test system. Lastly, the flexibility provided by hybrid and other resources can help reduce system load-shedding event frequencies and enable the system to be more robust to inaccurate forecast information, and alternative hybrid inverter sizes can impact RA levels by 1-2 orders of magnitude. Our results point to the importance of a broader flexibility framework to describe the interaction between (1) flexibility "supply" from both physical resource capabilities and operational constraints considered in the modeling, and (2) flexibility "demand" from forecast errors, thermal generator outages, and other sources of uncertainty, as well as their RA impacts. Results are likely sensitive to the system buildout explored; future work could consider additional system configurations and conditions.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
NASA NTRS1990

Error analysis for pulsed maneuvers of a dual-spin spacecraft

The Galileo is a dual-spin interplanetary spacecraft which is scheduled for launch toward Jupiter in October of 1989. The spacecraft has twelve thrusters, located on the rotor, which can be operated in continuous or pulsed modes. In this paper probabilistic error models are presented for the pulsed maneuvers which are used to change the spacecraft's velocity. These models take into account all error sources which might affect the maneuver accuracies, such as wobble, nutation, plume impingement, thrust level variation and misalignment, gyro drift, burn timing errors and mass property uncertainties. The analytic models are sufficiently general so that they may be applied to all spin and dual-spin stabilized spacecraft. When these models are applied to the case of the Galileo spacecraft, the numerical results demonstrate that the spacecraft can achieve the maneuver accuracies required in order to successfully reach Jupiter and perform its scientific mission.

Longuski, James M.↗
DOE OSTI2017

Advanced Seismic Probabilistic Risk Assessment Methodology: Development of Beta 1.0 MASTODON Toolset

Design of nuclear power plant (NPP) facilities to resist natural hazards has been a part of the regulatory process from the beginning of the NPP industry in the United States, but has evolved substantially over time. The original set of approaches and methods was entirely deterministic in nature and focused on a traditional engineering margins-based approach. However, over time probabilistic and risk-informed approaches were also developed and implemented in US Nuclear Regulatory Commission guidance and regulation. A defense-in-depth framework has also been incorporated into US regulatory guidance over time. As a result, today, the US regulatory framework incorporates deterministic and probabilistic approaches for a range of different applications and for a range of natural hazard considerations. Although the US regulatory framework has continued to evolve over time, the tools, methods and data available to the US nuclear industry to meet the changing requirements have not kept pace. Notably, there is room for improvement in the tools and methods available for external event probabilistic risk assessment (PRA), which is the principal assessment approach used in risk-informed regulations and risk-informed decision-making applied to natural hazard assessment and design. Development of a new set of tools and methods that incorporate current knowledge, modern best practice, and state-of-the-art computational resources would lead to more reliable assessment of facility risk and risk insights (e.g., the plant elements and accident sequences that are most risk-significant), with less uncertainty and reduced conservatisms. Development of the next generation tools and methods for external events PRA is ongoing under the Risk Informed Safety Margins Characterization (RISMC) technical pathway. The RISMC toolkit development centers on integration of the tools and methods under a common framework, MOOSE. These tools and methods make use of existing and newly developed tools and methods, coupled with the experience and data gained in the past decades, to define and analyze more realistic risk assessment models. Specific focus in this report is on the capability to model seismic risk using advanced SPRA methods. Over the last year, significant capability has been added to Mastodon to simulate 3-D wave passage effects through nonlinear soil. Verification has demonstrated the capability of Mastodon to model wave passage effects in 1-D, 2-D, and 3-D. Methods have been developed to incorporate probabilistic floor response capabilities. Additional capability will be added to Mastodon over the next year to implement a robust gapping and sliding element for cyclic shaking, web-based verification and user manuals, stochastic finite elements, and frequency independent damping. Verification of added capabilities has occured in parallel with code writing activities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Robotic Planning under Uncertainty in Spatiotemporal Environments in Expeditionary Science

In the expeditionary sciences, spatiotemporally varying environments -- hydrothermal plumes, algal blooms, lava flows, or animal migrations -- are ubiquitous. Mobile robots are uniquely well-suited to study these dynamic, mesoscale natural environments. We formalize expeditionary science as a sequential decision-making problem, modeled using the language of partially-observable Markov decision processes (POMDPs). Solving the expeditionary science POMDP under real-world constraints requires efficient probabilistic modeling and decision-making in problems with complex dynamics and observational models. Previous work in informative path planning, adaptive sampling, and experimental design have shown compelling results, largely in static environments, using data-driven models and information-based rewards. However, these methodologies do not trivially extend to expeditionary science in spatiotemporal environments: they generally do not make use of scientific knowledge such as equations of state dynamics, they focus on information gathering as opposed to scientific task execution, and they make use of decision-making approaches that scale poorly to large, continuous problems with long planning horizons and real-time operational constraints. In this work, we discuss these and other challenges related to probabilistic modeling and decision-making in expeditionary science, and present some of our preliminary work that addresses these gaps. We ground our results in a real expeditionary science deployment of an autonomous underwater vehicle (AUV) in the deep ocean for hydrothermal vent discovery and characterization. Our concluding thoughts highlight remaining work to be done, and the challenges that merit consideration by the reinforcement learning and decision-making community.

Preston, Victoria↗
DOE OSTI2024

Assessing and benchmarking the fidelity of posterior inference methods for astrophysics data analysis

In this era of large and complex astronomical survey data, interpreting, validating, and comparing inference techniques becomes increasingly difficult. This is particularly critical for emerging inference methods like Simulation-Based Inference (SBI), which offer significant speedup potential and posterior modeling flexibility, especially when deep learning is incorporated. We present a study to assess and compare the performance and uncertainty prediction capability of Bayesian inference algorithms – from traditional MCMC sampling of analytic functions to deep learning-enabled SBI. We focus on testing the capacity of hierarchical inference modeling in those scenarios. Before we extend this study to cosmology, we first use astrophysical simulation data to ensure interpretability. We demonstrate a probabilistic programming implementation of hierarchical and non-hierarchical Bayesian inference using simulations derived from the DeepBench software library, a benchmarking tool developed by our group that generates simple and controllable astrophysical objects from first principles. This study will enable astronomers and physicists to harness the inference potential of these methods with confidence.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1992

Buckling of stiffened shells with random initial imperfections, thickness and boundary conditions

The paper proposes a method to predict the buckling load of stiffened, composite shells reliably, where besides the randomness of the initial geometric imperfections also a random variation of the wall thickness and the uncertainty of the precise edge conditions is included in the analysis. The introduction of the variability in the thickness from shell to shell, in an ensemble of nominally identical shells, produced by the same manufacturing procedure is motivated by the growing realization of the importance of thickness variations by composite shells. The probabilistic treatment of the boundary conditions is dictated by the fact that 'true', deterministically specified boundary conditions are unlikely to be realizable in practice.

Elishakoff, I.↗
NASA NTRS2015

Common Cause Failure Modeling

Common Cause Failures (CCFs) are a known and documented phenomenon that defeats system redundancy. CCFS are a set of dependent type of failures that can be caused by: system environments; manufacturing; transportation; storage; maintenance; and assembly, as examples. Since there are many factors that contribute to CCFs, the effects can be reduced, but they are difficult to eliminate entirely. Furthermore, failure databases sometimes fail to differentiate between independent and CCF (dependent) failure and data is limited, especially for launch vehicles. The Probabilistic Risk Assessment (PRA) of NASA's Safety and Mission Assurance Directorate at Marshall Space Flight Center (MFSC) is using generic data from the Nuclear Regulatory Commission's database of common cause failures at nuclear power plants to estimate CCF due to the lack of a more appropriate data source. There remains uncertainty in the actual magnitude of the common cause risk estimates for different systems at this stage of the design. Given the limited data about launch vehicle CCF and that launch vehicles are a highly redundant system by design, it is important to make design decisions to account for a range of values for independent and CCFs. When investigating the design of the one-out-of-two component redundant system for launch vehicles, a response surface was constructed to represent the impact of the independent failure rate versus a common cause beta factor effect on a system's failure probability. This presentation will define a CCF and review estimation calculations. It gives a summary of reduction methodologies and a review of examples of historical CCFs. Finally, it presents the response surface and discusses the results of the different CCFs on the reliability of a one-out-of-two system.

Hark, Frank↗
NASA NTRS2016

Common Cause Failure Modeling

Common Cause Failures (CCFs) are a known and documented phenomenon that defeats system redundancy. CCFS are a set of dependent type of failures that can be caused by: system environments; manufacturing; transportation; storage; maintenance; and assembly, as examples. Since there are many factors that contribute to CCFs, the effects can be reduced, but they are difficult to eliminate entirely. Furthermore, failure databases sometimes fail to differentiate between independent and CCF (dependent) failure and data is limited, especially for launch vehicles. The Probabilistic Risk Assessment (PRA) of NASA's Safety and Mission Assurance Directorate at Marshal Space Flight Center (MFSC) is using generic data from the Nuclear Regulatory Commission's database of common cause failures at nuclear power plants to estimate CCF due to the lack of a more appropriate data source. There remains uncertainty in the actual magnitude of the common cause risk estimates for different systems at this stage of the design. Given the limited data about launch vehicle CCF and that launch vehicles are a highly redundant system by design, it is important to make design decisions to account for a range of values for independent and CCFs. When investigating the design of the one-out-of-two component redundant system for launch vehicles, a response surface was constructed to represent the impact of the independent failure rate versus a common cause beta factor effect on a system's failure probability. This presentation will define a CCF and review estimation calculations. It gives a summary of reduction methodologies and a review of examples of historical CCFs. Finally, it presents the response surface and discusses the results of the different CCFs on the reliability of a one-out-of-two system.

Hark, Frank↗
DOE OSTI2016

Transitions From Stochastic to Point Kinetics Models In Fissile Solutions

Fissile solutions form an integral part of the fuel cycle, being used to store and process both fresh fuel and waste. Fissile solutions are also found within Aqueous Homogeneous Reactors (AHRs) including research reactors such as CRAC and SILENE and also potential future systems which could be used for the production of medical isotopes. In the case of fissile solutions in the fuel cycle, avoiding criticality is a priority but accidents have occurred in which a significant number of fissions occurred. In the case of AHRs, a sustained neutron population and fission rate is desired. In both cases the ability to simulate transients where changes in reactivity cause the neutron population to increase are important. A popular method for the simulation of such transients is the point kinetic method which allows the capture of the major features of a transient at a fraction of the computational runtime and code complexity of more comprehensive modelling technologies. A limitation of the point kinetics method and other mainstream methods of predicting neutron behaviour is that they assume the neutron population is large enough that the mean behaviour will be observed. When the neutron population is low, however, the deviation around the mean behaviour is expected to be relatively large as there is an aleatoric uncertainty arising from the uncertain fate of individual neutrons. Such limitations are of particular importance when the reactivity of a system is rapidly increasing while the neutron population is low, which is often true in accident scenarios involving fissile solutions. This provides the motivation for the coupling of point kinetics and a probabilistic models of fissile solutions. This summary aims to explore some of the behaviours resulting from a low neutron population and rising reactivity using a coupled probabilistic and point kinetics model of a fissile solution. As the effects of a low neutron population are the primary concern of this summary, the point kinetics and thermal hydraulic models used will be relatively simple but these models should be sufficient to capture the most important behaviours of the system in the first minute or so of a transient. This work is an extension of the work found in [1]. In that work the methodology was applied to fast pulses produced by systems such as Godiva and its results were found to compare favourably to experimental and analytical results, such as the burst wait time, in [2]. This work focuses on the application of this methodology to a fissile solution but the method could be applied to a number of criticality safety or reactor operation scenarios through suitable modification of the point kinetics model and would produce a more accurate prediction of the peak power obtained when a system first becomes critical compared to the use of a standard point kinetics model. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

IMAGING ANALYSIS OF THE HARD X-RAY TELESCOPE ProtoEXIST2 AND NEW TECHNIQUES FOR HIGH-RESOLUTION CODED-APERTURE TELESCOPES

Wide-field (≳100 deg{sup 2}) hard X-ray coded-aperture telescopes with high angular resolution (≲2′) will enable a wide range of time domain astrophysics. For instance, transient sources such as gamma-ray bursts can be precisely localized without the assistance of secondary focusing X-ray telescopes to enable rapid followup studies. On the other hand, high angular resolution in coded-aperture imaging introduces a new challenge in handling the systematic uncertainty: the average photon count per pixel is often too small to establish a proper background pattern or model the systematic uncertainty in a timescale where the model remains invariant. We introduce two new techniques to improve detection sensitivity, which are designed for, but not limited to, a high-resolution coded-aperture system: a self-background modeling scheme which utilizes continuous scan or dithering operations, and a Poisson-statistics based probabilistic approach to evaluate the significance of source detection without subtraction in handling the background. We illustrate these new imaging analysis techniques in high resolution coded-aperture telescope using the data acquired by the wide-field hard X-ray telescope ProtoEXIST2 during a high-altitude balloon flight in fall 2012. We review the imaging sensitivity of ProtoEXIST2 during the flight, and demonstrate the performance of the new techniques using our balloon flight data in comparison with a simulated ideal Poisson background.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2016

Imaging Analysis of the Hard X-Ray Telescope ProtoEXIST2 and New Techniques for High-Resolution Coded-Aperture Telescopes

Wide-field (greater than or approximately equal to 100 degrees squared) hard X-ray coded-aperture telescopes with high angular resolution (greater than or approximately equal to 2 minutes) will enable a wide range of time domain astrophysics. For instance, transient sources such as gamma-ray bursts can be precisely localized without the assistance of secondary focusing X-ray telescopes to enable rapid followup studies. On the other hand, high angular resolution in coded-aperture imaging introduces a new challenge in handling the systematic uncertainty: the average photon count per pixel is often too small to establish a proper background pattern or model the systematic uncertainty in a timescale where the model remains invariant. We introduce two new techniques to improve detection sensitivity, which are designed for, but not limited to, a high-resolution coded-aperture system: a self-background modeling scheme which utilizes continuous scan or dithering operations, and a Poisson-statistics based probabilistic approach to evaluate the significance of source detection without subtraction in handling the background. We illustrate these new imaging analysis techniques in high resolution coded-aperture telescope using the data acquired by the wide-field hard X-ray telescope ProtoEXIST2 during a high-altitude balloon flight in fall 2012. We review the imaging sensitivity of ProtoEXIST2 during the flight, and demonstrate the performance of the new techniques using our balloon flight data in comparison with a simulated ideal Poisson background.

balloons - instrumentation: detectors - techniques↗
DOE OSTI2015

Development of criticality risk evaluation method for fuel debris in Fukushima Dai-ichi NPS - 14373

After the accident of Fukushima Dai-ichi Nuclear Power Station, there has been still damaged nuclear fuel in the reactor buildings, which is called 'fuel debris' and contains an amount of fissile materials show that it is currently subcritical, which must be kept until finishing retrieval work. In the latest plan, retrieving fuel debris is to start in 2025. The International Research Institute for Nuclear Decommissioning, IRID, has been developing the technology for decontamination in reactor building. A developed method will be reviewed and granted by the Nuclear Regulatory Authority in Japan, NRA, before the start of the retrieving. Criticality risk information will be needed for decision making on following two subcriticality issues, -Criticality control of fuel debris to keep is subcritical until the end of retrieval work. -Safe operation for retrieving fuel debris to keep it subcritical. Because fuel debris has been out of criticality control and the key condition for its current subcriticality is unknown, it is important to obtain criticality risk information as soon as possible. Applying conventional Probabilistic Safety Assessment, PSA, to fuel debris is difficult, because it is based on the probability of becoming out of criticality control due to troubles such as equipment failure, operation mistake and so on. A new method, which has been developed by Japan Atomic Energy Agency to technically support the NRA, is designed to estimate criticality risk based on a probability distribution of k{sub eff} due to uncertainty of composition and geometry of fuel debris, which method will provide risk information for the two subcriticality issues as well as for the tolerance level of criticality risk if it is unavoidable. Developed method contains four steps: two steps of analysis of criticality risk and two steps of quantification of the risk. A procedure of risk quantification has been defined, in which systematic analysis of criticality risk can be done by making 'status matrix'. A trial analysis by using the procedure shows that some events which can initiate criticality are able to be supposed to happen during maintenance period until the beginning of retrieving fuel debris, and that analysis also indicates countermeasures should be considered as soon as possible in order to reduce criticality risk for public and workers. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1995

Probabilistic Analysis of Large-Scale Composite Structures Using the IPACS Code

An investigation was performed to ascertain the feasibility of using IPACS (Integrated Probabilistic Assessment of Composite Structures) for probabilistic analysis of a composite fan blade, the development of which is being pursued by various industries for the next generation of aircraft engines. A model representative of the class of fan blades used in the GE90 engine has been chosen as the structural component to be analyzed with IPACS. In this study, typical uncertainties are assumed in the level, and structural responses for ply stresses and frequencies are evaluated in the form of cumulative probability density functions. Because of the geometric complexity of the blade, the number of plies varies from several hundred at the root to about a hundred at the tip. This represents a extremely complex composites application for the IPACS code. A sensitivity study with respect to various random variables is also performed.

Lemonds, Jeffrey↗
DOE OSTI2013

PROBABILISTIC CATALOGS FOR CROWDED STELLAR FIELDS

We present and implement a probabilistic (Bayesian) method for producing catalogs from images of stellar fields. The method is capable of inferring the number of sources N in the image and can also handle the challenges introduced by noise, overlapping sources, and an unknown point-spread function. The luminosity function of the stars can also be inferred, even when the precise luminosity of each star is uncertain, via the use of a hierarchical Bayesian model. The computational feasibility of the method is demonstrated on two simulated images with different numbers of stars. We find that our method successfully recovers the input parameter values along with principled uncertainties even when the field is crowded. We also compare our results with those obtained from the SExtractor software. While the two approaches largely agree about the fluxes of the bright stars, the Bayesian approach provides more accurate inferences about the faint stars and the number of stars, particularly in the crowded case.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

A Preliminary Probabilistic Performance Assessment Model for Radiological and Chemical Contamination at the West Valley Site, New York - 19295

The New York State Energy Research and Development Authority (NYSERDA) is the owner of the Western New York Nuclear Service Center (WNYNSC), a 1,351-ha site located approximately 48 km south of Buffalo, New York. In 1962, Nuclear Fuel Services, Inc. (NFS) entered into agreements with the Atomic Energy Commission and New York State to construct the first commercial reprocessing plant of nuclear fuel in the United States at the WNYNSC. NFS built and operated the spent fuel reprocessing plant and waste disposal facilities, processing 640 Mg (640 metric tons) of spent nuclear fuel from 1966 to 1972 under an Atomic Energy Commission license. Nuclear fuel reprocessing operations halted in 1972 and never restarted, leaving behind radioactive and chemical wastes. The reprocessing wastes include high-level waste (HLW), so U.S. Department of Energy (DOE) was compelled to complete certain waste management activities under the West Valley Demonstration Project (WVDP) Act of 1980, including decommissioning of WVDP facilities. As collaborating agencies, NYSERDA and the DOE are tasked with making decisions about decommissioning and risk reduction for the West Valley Site. Neptune and Company, Inc. (Neptune) was contracted to develop a probabilistic performance assessment (PPA) model to assist the agencies in their decision making process for decommissioning the WVDP and WNYNSC. One important tool that is needed in order to inform the decision-making process is a science-based model of the contamination at the West Valley Site and its potential implications for human health and the environment. The West Valley PPA Model (the Model), developed using the GoldSim modeling software, is a tool intended to provide support for decision making with uncertainty, in a manner that is transparent, defensible, and robust. The PPA Model includes contaminant transport and health effects components, and is organized around geographically-organized contaminated facilities. These include the waste disposal areas licensed by the U.S. Nuclear Regulatory Commission and the State of New York, a waste tank farm for storage of HLW resulting from reprocessing operations, and several areas contaminated with radioactive and chemical constituents. The Model evaluates contaminant transport from these sources to points of exposure across the site and into receiving surface waters and sediments. Hypothetical people and wildlife are exposed to contamination at these locations, and the effects of these exposures are evaluated. Contaminant transport processes to be evaluated in the Model include groundwater and surface water transport, contaminant translocation by plants and animals, diffusion in subsurface air and water, and erosion of the Site. The evaluation of exposures to people in this preliminary model is limited to a resident farmer scenario, and ecological assessment is performed at the level of a screening analysis. The results of these preliminary evaluations inform future model developments. Model results are subjected to sensitivity analysis in order to determine those pathways and parameters that are most significant in influencing the results. This information allows analysts and decision makers to focus on those aspects of Site behavior and processes that contribute most to overall uncertainty. With this information, the Supplemental Environmental Impact Statement (SEIS) can inform defensible decisions regarding remediation of the Site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

A Decision-Based Iterative Modeling Framework for Probabilistic Performance Assessments - 18441

Radiological probabilistic performance assessments (PPAs) employ highly complex computer models to simulate the release of radionuclides from wastes in an engineered disposal facility, migration of these radionuclides over time, and resulting radiological dose to potentially exposed individuals. An iterative approach to PPA modeling is described to help define the appropriate complexity of the computer model. An initial model is developed that addresses all relevant processes and media, but that employs preliminary statistical parameter distributions to minimize the initial effort expended. Where appropriate, transport and exposure submodels with simplifying assumptions are also used in the initial model. Different assumptions and boundaries may be explored with the initial model to assess their importance in constraining model results. Exploration of the results of the initial model are used to determine the benefits of model refinements, and to guide such refinements to focus on specific areas of the model that most influence the model outputs of interest. This approach promotes efficiency and model parsimony, but does not compromise defensibility when performed in a transparent manner. Key model boundaries for a PPA include the time frame of the modeling (temporal boundaries), where future human receptors may be located (spatial boundaries), and what types of land uses and activities may exist in the future (exposure scenarios). Simplified transport and exposure models can be useful in helping decision makers and stakeholders establish such boundaries by analyzing the consequences of selecting different bounds and understanding which assumptions and boundaries have the greatest influence on the magnitude and distribution of model results. Pathway analysis and parameter sensitivity analysis performed on PPA model results are key components of the iterative modeling approach. The objective of pathway analysis is to identify the critical radionuclides and pathways contributing to radiation dose during the modeling performance period. An environmental 'pathway' is described by the connections from a waste package or cell in the disposal facility to a future human exposure event. These connections are commonly visualized using graphical means. A simple example of a potentially complete pathway for radon-222 is: radium-containing waste → radon emanation → upwards diffusion in cap material → diffusion/advection into a future building → inhalation exposure to a building occupant Parameter sensitivity analysis is conducted on the results of a PPA to identify those specific model input parameters whose distribution of values contributes the most to the distribution of target model output, such as annual radiation dose. Pathway and sensitivity analyses on initial modeling results provide information for guiding subsequent model development, and possibly interim decisions, by informing questions tied to the modeling objectives and performance criteria. For example, questions related to radiological doses from existing disposals may include: 1. Is radiation dose from radiological exposures either obviously negligible or obviously unacceptable based on initial modeling results? 2. If dose is not obviously negligible or unacceptable relative to applicable performance criteria, what model refinements would reduce uncertainty in the results to better inform decisions? (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Cluster 1: commercializing additive manufacturing—hurdles in materials characterization and testing

A major challenge in the commercialization of additive manufactured (AM) materials and processes is the ability to achieve acceptance of processes and products. There has been some progress towards acceptance has been made by adapting legacy qualification paradigms to match with the very limited process control and monitoring offered by AM machines. The opportunity for in-situ measurement can provide process monitoring and control perhaps changing the way we qualify parts however it is limited by lack of adequate process measurement methods. New measurement techniques, sensors and correlations to relevant phenomena are needed that enable process control and monitoring for consistently producing high quality articles. Beyond process data we need to characterize uncertainties of performance in all aspects of material, process and final part. These are prerequisites to achieving articles that are indeed worthy of materials characterization efforts that establish a microstructural reference of desirable performance through process-structure-property relations. Only then can industry apply physics based understanding of the material, part and process to probabilistically predict performance of an AM part. Our paper provides a brief overview, discussion of hurdles and key areas where R&D investment is needed.

36 MATERIALS SCIENCE↗
NASA NTRS1972

Mariner Venus-Mercury 1973 mission solar proton environment: fluence and dose

A derivation is presented for proton fluence over the duration of the Mariner Venus-Mercury 1973 (MVM73) mission in terms of a relatively constant, low energy component, the solar wind, and a probabilistic high energy component from discrete solar events. An updated correlation of yearly energetic proton fluence with yearly average sunspot number is presented. This correlation and sunspot cycle forecasts for the period of the MVM73 mission (late 1973 through early 1975) form the basis for the high energy proton fluence estimates with various confidence levels. Uncertainties in the probability estimates and in calculation of the scaling with distance from the Sun are discussed. Selection of a particular 95-percentile model as the design constraint is recommended, and reasons are presented for not using the worst-case model. Interior fluences were calculated and expressed in terms useful for spacecraft design.

Thomas, J. R.↗