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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2016

TH-CD-209-09: Quickly Identifying Good Candidates for Proton Therapy From Geometric Considerations

Purpose: We developed a knowledge-based model that can predict the patient-specific benefits of proton therapy based upon geometric considerations. The model could also aid patient selection in model-based clinical trials or help justify clinical decisions to insurance companies. Methods: The knowledge-based method trains a model upon existing proton treatment plans, exploiting correlations between dose and distance-to-target. Each OAR is split into concentric subvolumes surrounding the target volume, and a skew-normal PDF is fit to the dose distribution found within each shell. The model learns from shared trends in how the best-fit skew-normal parameters depend upon distance-to-target. It can then predict feasible OAR DVHs for a new patient (without a proton plan) based upon their geometry. The expected benefits of proton therapy are assessed by comparing the predicted DVHs to those of an IMRT plan, using a metric such as the equivalent uniform dose (EUD). Results: A model was trained for clival chordoma, owing to its geometric complexity and the multitude of nearby OARs. The model was trained using 20 patients and validated with a further 20 patients, and considers several different OARs. The predicted EUD was in good agreement with that of the actual proton plan. The coefficient of determination (R-squared) was 85% overall, 92% for cochleas, 80% for optic chiasm and 79% for spinal cord. The model exhibited no signs of bias or overfitting. When compared to an IMRT plan, the model could classify whether a patient will experience a gain or a loss with an accuracy between 75% and 95%, depending upon the OAR. Conclusion: We developed a model that can quickly and accurately predict the patient-specific benefits of proton therapy in clival chordoma patients, though models could be trained for other tumor sites. This work is funded by National Cancer Institute grant U19 CA 021239.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Calcium Phosphate Constraints in HLW Glasses: Phosphate Liquidus Model

About 50 million gallons of high-level mixed waste is currently stored in underground tanks at the United States Department of Energy’s (DOE’s) Hanford site in the State of Washington. The Hanford Tank Waste Treatment and Immobilization Plant (WTP) will provide DOE’s Office of River Protection (ORP) with a means of treating this waste by vitrification for subsequent disposal. The tank waste will be separated into low- and high-activity waste fractions, which will then be vitrified respectively into Immobilized Low Activity Waste (ILAW) and Immobilized High Level Waste (IHLW) products. The ILAW product will be disposed in an engineered facility on the Hanford site while the IHLW product is designed for acceptance into a national geological disposal facility for high-level nuclear waste. The ILAW and IHLW products must meet a variety of requirements before they can be accepted for disposal. Glass property-composition models will be used to control the vitrification process at the WTP to ensure that the glass meets product quality and processability requirements. The quality and the validity ranges of the property-composition models and the supporting database will greatly influence waste treatment operations, including the waste loading that is achievable in the glass for each waste composition. The current baseline models for operation of the WTP were developed under the Bechtel National, Inc. (BNI) WTP contract. These models were based on LAW and HLW glass property data over a range of compositions that was guided primarily by the WTP contract and the set of tanks specified therein. The HLW testing was directed towards waste streams from the then-planned early feed tanks for the WTP (i.e., AZ-101, AZ-102, C-106/AY-102, and C-104/AY-101). These wastes are high in iron (AZ-101, AZ-102, and C-106/AY-102) or thorium (C-104/AY-101). While the baseline models may be adequate for commissioning of the facility and processing of the specified tanks, refinements and extensions or augmentations of these models will be required to process the balance of the tank waste inventory. The overall mission of the WTP will require the immobilization of tank waste compositions that are variously dominated by mixtures of aluminum, chromium, bismuth, iron, phosphorous, zirconium, and sulfur compounds as waste-loading-limiting components. Further, the WTP contract includes minimum waste loading requirements that are generally rather modest while loadings significantly higher than those in the current baseline are likely achievable. In order to achieve these higher waste loadings and to expand the applicable composition regions, new models will be needed to support the optimized operation of the WTP. Since the development of the baseline WTP models, ORP directed a program of work at the Vitreous State Laboratory (VSL) to examine various approaches for optimization of the performance of the WTP, including increasing the waste loadings in the LAW and HLW glass products. That work involved HLW rich in Al, Al+Na, Cr, Bi, S, Zr, Sr, P and Fe, in contrast to old baseline models that were based mostly on HLW tanks that were high in Fe, with one other that was also high in Th. Glass property data collected under the ORP program were compiled and combined with data collected to develop the WTP models. The combined databases have been used to update pre-existing HLW composition models or to develop new models for properties such as Product Consistency Test (PCT) responses, spinel crystallization (one-percent crystal fraction temperature, T 1% ), melt viscosity, melt electrical conductivity, nepheline formation upon slow cooling (i.e., Canister Centerline Cooling [CCC]), and Toxicity Characteristic Leach Procedure (TCLP) Cd response. While spinel is typically the most commonly occurring phase in HLW glasses, other phases can be limiting depending on the waste and glass composition. For example, various phosphate phases can become important as the phosphorus content increases. Lithium phosphate crystallization can impact PCT releases of HLW glasses, while calcium phosphate phases forming in the cold-cap can deleteriously impact feed processing in the melter. At present, however, no models exist that relate glass composition and crystallization of phosphate phases in general and calcium phosphate in particular. The present work was therefore directed towards the initial development of such models. Future work may be directed at studying amorphous phase separation in high phosphate HLW glasses. Within the River Protection Project, feed compositions are projected using the Hanford Tank Waste Operations Simulator (HTWOS), a dynamic computer model that tracks the waste through storage, retrieval, feed staging, and treatment processes. A review of the HTWOS data shows that WTP will process 4106 batches of HLW glass for the overall mission (System Plan Rev. 6, ORP-11242), each with its own waste feed and glass composition. Some of the projected HTWOS feed batches are expected to have relatively high concentrations of phosphorous compared to typical HLW streams. In the 4106 batches of HLW for the overall WTP mission P 2 O 5 varies from 0.59 wt% to 13.00 wt%, with 95 batches containing at least 10 wt% P 2 O 5 . Occurrences of phosphate crystals have commonly been noted in glasses with high bismuth and phosphorus contents. In addition, recently collected data from a set of statistically designed HLW matrix glasses prepared and characterized to support enhancement of the HLW glass property-composition models identified apatite in a number of glass samples. However, the current HLW model for crystallization (one-percent crystal fraction temperature) is applicable only to spinel crystallization in glasses. Previous projections of waste loadings and glass volume (such as those in System Plan Rev. 6, ORP-11242) have used preliminary constraints for calcium phosphate crystallization that are based on the limited available data. Additional data and improved constraints or, preferably, models that relate glass composition to crystallization of phosphate-containing phases, are therefore needed to support HLW vitrification at the WTP. The present study focuses on the development of such a model based on data from previously characterized glasses and a set of newly fabricated glasses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Real-time global flood estimation using satellite-based precipitation and a coupled land surface and routing model

A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood monitoring parameters for the latitude band 50°N–50°S at relatively high spatial (~12 km) and temporal (3 hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Evaluation results are slightly better for the research-quality input and significantly better for longer duration events (3 day events versus 1 day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is ~0.9 and the false alarm ratio is ~0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30°S–30°N) gives positive daily Nash-Sutcliffe Coefficients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. Finally, there were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.

flood modelling, flood detection, VIC, DRT, DRIVE,↗
DOE OSTI2025

Global Methane Budget 2000–2020

Abstract. Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. CH4 is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2), and both emissions and atmospheric concentrations of CH4 have continued to increase since 2007 after a temporary pause. The relative importance of CH4 emissions compared to those of CO2 for temperature change is related to its shorter atmospheric lifetime, stronger radiative effect, and acceleration in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in quantifying the factors responsible for the observed atmospheric growth rate arise from diverse, geographically overlapping CH4 sources and from the uncertain magnitude and temporal change in the destruction of CH4 by short-lived and highly variable hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to improve, synthesise, and update the global CH4 budget regularly and to stimulate new research on the methane cycle. Following Saunois et al. (2016, 2020), we present here the third version of the living review paper dedicated to the decadal CH4 budget, integrating results of top-down CH4 emission estimates (based on in situ and Greenhouse Gases Observing SATellite (GOSAT) atmospheric observations and an ensemble of atmospheric inverse-model results) and bottom-up estimates (based on process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). We present a budget for the most recent 2010–2019 calendar decade (the latest period for which full data sets are available), for the previous decade of 2000–2009 and for the year 2020. The revision of the bottom-up budget in this 2025 edition benefits from important progress in estimating inland freshwater emissions, with better counting of emissions from lakes and ponds, reservoirs, and streams and rivers. This budget also reduces double counting across freshwater and wetland emissions and, for the first time, includes an estimate of the potential double counting that may exist (average of 23 Tg CH4 yr−1). Bottom-up approaches show that the combined wetland and inland freshwater emissions average 248 [159–369] Tg CH4 yr−1 for the 2010–2019 decade. Natural fluxes are perturbed by human activities through climate, eutrophication, and land use. In this budget, we also estimate, for the first time, this anthropogenic component contributing to wetland and inland freshwater emissions. Newly available gridded products also allowed us to derive an almost complete latitudinal and regional budget based on bottom-up approaches. For the 2010–2019 decade, global CH4 emissions are estimated by atmospheric inversions (top-down) to be 575 Tg CH4 yr−1 (range 553–586, corresponding to the minimum and maximum estimates of the model ensemble). Of this amount, 369 Tg CH4 yr−1 or ∼ 65 % is attributed to direct anthropogenic sources in the fossil, agriculture, and waste and anthropogenic biomass burning (range 350–391 Tg CH4 yr−1 or 63 %–68 %). For the 2000–2009 period, the atmospheric inversions give a slightly lower total emission than for 2010–2019, by 32 Tg CH4 yr−1 (range 9–40). The 2020 emission rate is the highest of the period and reaches 608 Tg CH4 yr−1 (range 581–627), which is 12 % higher than the average emissions in the 2000s. Since 2012, global direct anthropogenic CH4 emission trends have been tracking scenarios that assume no or minimal climate mitigation policies proposed by the Intergovernmental Panel on Climate Change (shared socio-economic pathways SSP5 and SSP3). Bottom-up methods suggest 16 % (94 Tg CH4 yr−1) larger global emissions (669 Tg CH4 yr−1, range 512–849) than top-down inversion methods for the 2010–2019 period. The discrepancy between the bottom-up and the top-down budgets has been greatly reduced compared to the previous differences (167 and 156 Tg CH4 yr−1 in Saunois et al. (2016, 2020) respectively), and for the first time uncertainties in bottom-up and top-down budgets overlap. Although differences have been reduced between inversions and bottom-up, the most important source of uncertainty in the global CH4 budget is still attributable to natural emissions, especially those from wetlands and inland freshwaters. The tropospheric loss of methane, as the main contributor to methane lifetime, has been estimated at 563 [510–663] Tg CH4 yr−1 based on chemistry–climate models. These values are slightly larger than for 2000–2009 due to the impact of the rise in atmospheric methane and remaining large uncertainty (∼ 25 %). The total sink of CH4 is estimated at 633 [507–796] Tg CH4 yr−1 by the bottom-up approaches and at 554 [550–567] Tg CH4 yr−1 by top-down approaches. However, most of the top-down models use the same OH distribution, which introduces less uncertainty to the global budget than is likely justified. For 2010–2019, agriculture and waste contributed an estimated 228 [213–242] Tg CH4 yr−1 in the top-down budget and 211 [195–231] Tg CH4 yr−1 in the bottom-up budget. Fossil fuel emissions contributed 115 [100–124] Tg CH4 yr−1 in the top-down budget and 120 [117–125] Tg CH4 yr−1 in the bottom-up budget. Biomass and biofuel burning contributed 27 [26–27] Tg CH4 yr−1 in the top-down budget and 28 [21–39] Tg CH4 yr−1 in the bottom-up budget. We identify five major priorities for improving the CH4 budget: (i) producing a global, high-resolution map of water-saturated soils and inundated areas emitting CH4 based on a robust classification of different types of emitting ecosystems; (ii) further development of process-based models for inland-water emissions; (iii) intensification of CH4 observations at local (e.g. FLUXNET-CH4 measurements, urban-scale monitoring, satellite imagery with pointing capabilities) to regional scales (surface networks and global remote sensing measurements from satellites) to constrain both bottom-up models and atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) integration of 3D variational inversion systems using isotopic and/or co-emitted species such as ethane as well as information in the bottom-up inventories on anthropogenic super-emitters detected by remote sensing (mainly oil and gas sector but also coal, agriculture, and landfills) to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GKQ9-2RHT (Martinez et al., 2024).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

New Mechanistic Models of Long Term Evolution of Microstructure and Mechanical Properties of Nickel Based Alloys

The report describes the development of a discrete element method (DEM) based modeling approach to quantitatively predict deformation and failure of typical nickel based superalloys. A series of experimental data, including microstructure and mechanical property characterization at 600°C, was collected for a relatively simple, model solid solution Ni-20Cr alloy (Nimonic 75) to determine inputs for the model and provide data for model validation. Nimonic 75 was considered ideal for this study because it is a certified tensile and creep reference material. A series of new DEM modeling approaches were developed to capture the complexity of metal deformation, including cubic elastic anisotropy and plastic deformation both with and without strain hardening. Our model approaches were implemented into a commercially available DEM code, PFC3D, that is commonly used by engineers. It is envisioned that once further developed, this new DEM modeling approach can be adapted to a wide range of engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Demand Response for Thermal Fairness in District Heating Networks

District Heating (DH) networks are complex thermal grids wherein a centrally heated fluid is circulated through a network of pipes and heat exchangers to meet the heating needs of residential and commercial buildings. Several factors can lead to inefficient and unfair energy distribution among consumers in these networks. These include varying levels of building insulation, distance of individual buildings from the central energy source, and thermal losses in network pipes. Moreover, shortage of energy at the central energy source and extreme weather conditions can exacerbate these issues, leading to differing levels of thermal comfort and customer disgruntlement in the long run. In this paper, we propose and study a demand response scheme that attempts to ensure thermal fairness among energy consumers in modern thermal grids. We develop optimization formulations based on thermodynamic models of DH networks, which determine optimal energy flow for individual buildings in order to achieve thermal fairness across the network. Our experimental results using physics based models for DH networks show that it is possible to achieve network level thermal fairness based social welfare objectives by controlling network parameters such as mass flow rates of water to the consumer premises and the supply water temperature, even when some network parameters like building thermal characteristics remain unknown.

Bhattacharya, Saptarshi↗
DOE OSTI2023

Reducing warpage in a hybrid large-scale additive manufacturing and compression molding process

In recent years, a hybrid manufacturing process, developed by combining extrusion-based large-scale additive manufacturing (AM) and compression molding (CM) techniques, has shown promising outcomes for producing structurally functional parts. The process can be used with both short fiber-reinforced composites and neat polymers and hence, even multi-material parts can be manufactured easily. This process offers the advantages of structural enhancement by having a desired fiber orientation using a large-scale AM process, as well as rapid manufacturing capability using a CM process. In the large-scale AM process, the alignment of fibers in the deposition direction enables significant improvement in the mechanical properties of the manufactured parts. However, the anisotropy resulting from the directional arrangement of fibers also introduces challenges related to warpage in the produced parts. This study aims to identify the causes of warpage and propose strategies to mitigate it. The research involves the use of preforms manufactured through the large-scale AM, which are then combined with the neat resin for CM manufacturing. A finite element-based numerical simulation model is developed, employing a sequentially coupled thermomechanical approach. Through a parametric study using the simulation models, optimization of printing direction and preform geometry is performed to minimize warpage. This contributes to the advancement and wider adoption of AM/CM hybrid manufacturing to produce structurally functional parts.

Jo, Eonyeon↗
DOE OSTI2020

ICME for Creep of Ni-Base Superalloys in Advanced Ultra-Supercritical Steam Turbines

The goal of this project contains three major aspects: (1) critical assessment of existing experimental data, (2) critical assessment of existing modeling capabilities and (3) development of new modeling capabilities that are critical but currently missing in predicting long-term creep behavior of Ni-base superalloys used in advanced ultra- supercritical (A-USC) steam turbines for coal-fired power plants. The project uses advanced materials informatics to datamine the experimental data, uncertainty quantification tools to rigorously assess existing creep-life models, and integration of phase-field and FFT-based crystal plasticity to develop a multi-scale, physics-based, microstructure-sensitive creep model.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2013

Dynamic Evolution of Cement Composition and Transport Properties under Conditions Relevant to Geological Carbon Sequestration

Assessing the possibility of CO{sub 2} leakage is one of the major challenges for geological carbon sequestration. Injected CO{sub 2} can react with wellbore cement, which can potentially change cement composition and transport properties. In this work, we develop a reactive transport model based on experimental observations to understand and predict the property evolution of cement in direct contact with CO{sub 2}-saturated brine under diffusion-controlled conditions. The model reproduced the observed zones of portlandite depletion and calcite formation. Cement alteration is initially fast and slows down at later times. This work also quantified the role of initial cement properties, in particular the ratio of the initial portlandite content to porosity (defined here as φ), in determining the evolution of cement properties. Portlandite-rich cement with large φ values results in a localized “sharp” reactive diffusive front characterized by calcite precipitation, leading to significant porosity reduction, which eventually clogs the pore space and prevents further acid penetration. Severe degradation occurs at the cement–brine interface with large φ values. This alteration increases effective permeability by orders of magnitude for fluids that preferentially flow through the degraded zone. The significant porosity decrease in the calcite zone also leads to orders of magnitude decrease in effective permeability, where fluids flow through the low-permeability calcite zone. The developed reactive transport model provides a valuable tool to link cement–CO{sub 2} reactions with the evolution of porosity and permeability. It can be used to quantify and predict long-term wellbore cement behavior and can facilitate the risk assessment associated with geological CO{sub 2} sequestration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Simulation of Heterogeneous Atom Probe Tip Shape Evolution during Field Evaporation Using a Level Set Method and Different Evaporation Models

Accurate reconstruction of spatial positions of field evaporated ions from detector patterns depends on a correct understanding of the tip shape evolution and evaporation laws of component atoms. Reconstruction artifacts introduced in the heterogeneous tip can be contributed by the assumption on homogeneous evaporation behavior. A level set method based specimen shape evolution model is developed in this study to simulate the evaporation of synthetic layered-structured atom probe tip. The simulation results of the shape evolution by the present level set model agree well with the literature data using other numerical approaches, i.e. finite difference method. The asymmetric evolving shape predicted by the level set model demonstrates that the complex evaporation behavior of heterogeneous tips and interface curvature can potentially lead to the tip reconstruction distortion. Compared with other shape evaporation methods the new method provides considerably higher resolution and computational efficiency with the aid of the intrinsic subgrid scale accuracy.

atom probe tomography, field evaporation, tip shap↗
DOE OSTI2014

Application of Crunch-Flow Routines to Constrain Present and Past Carbon Fluxes at Gas-Hydrate Bearing Sites

In November 2012, Oregon State University initiated the project entitled: Application of Crunch-Flow routines to constrain present and past carbon fluxes at gas-hydrate bearing sites. Within this project we developed Crunch-Flow based modeling modules that include important biogeochemical processes that need to be considered in gas hydrate environments. Our modules were applied to quantify carbon cycling in present and past systems, using data collected during several DOE-supported drilling expeditions, which include the Cascadia margin in US, Ulleung Basin in South Korea, and several sites drilled offshore India on the Bay of Bengal and Andaman Sea. Specifically, we completed modeling efforts that: 1) Reproduce the compositional and isotopic profiles observed at the eight drilled sites in the Ulleung Basin that constrain and contrast the carbon cycling pathways at chimney (high methane flux) and non-chimney sites (low methane, advective systems); 2) Simulate the Ba record in the sediments to quantify the past dynamics of methane flux in the southern Hydrate Ridge, Cascadia margin; and 3) Provide quantitative estimates of the thickness of individual mass transport deposits (MTDs), time elapsed after the MTD event, rate of sulfate reduction in the MTD, and time required to reach a new steady state at several sites drilled in the Krishna-Godavari (K-G) Basin off India. In addition we developed a hybrid model scheme by coupling a home-made MATLAB code with CrunchFlow to address the methane transport and chloride enrichment at the Ulleung Basins chimney sites, and contributed the modeling component to a study focusing on pore-scale controls on gas hydrate distribution in sediments from the Andaman Sea. These efforts resulted in two manuscripts currently under review, and contributed the modeling component of another pare, also under review. Lessons learned from these efforts are the basis of a mini-workshop to be held at Oregon State University (Feb 2014) to instruct graduate students (OSU and UW) as well as DOE staff from the NETL lab in Albany on the use of Crunch Flow for geochemical applications.

03 NATURAL GAS↗
DOE OSTI2022

Statistical analysis of S—N type environmental fatigue data of Ni-base alloy welds using weibull distribution

In this study, the probabilistic fatigue life model for Ni-base alloys was developed based on the Weibull distribution using statistical analysis of fatigue data reported in NUREG/CR-6909 and the new fatigue data of Alloy 52M/152 and 82/182. The developed Weibull model can consider right-censored data (i.e., non-failed data) and quantify the improved safety (or reliability) based on the level of failure probability. The overall margin in the current fatigue design limit model (ASME design curve + NUREG/CR-6909 F en model) is similar to that of the Weibull model with a cumulative failure probability of approximately 2.5%. The margin in the current fatigue design limit model demonstrated inconsistencies for the Ni-base alloy weld data, whereas the Weibull model showed a consistent margin. Therefore, the Weibull model can systematically mitigate the excessive safety margin.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Contribution to Fusion Materials (Semiannual Report)

The objectives of this work are the following: (1) The application of micro and mesoscale modeling techniques to study dislocation properties in ferritic and W-based materials; and (2) The development of computational models and tools to study damage accumulation in >1 dpa (fusion-like) conditions, both for Fe and W-based alloys. The high-temperature strength of structural ferritic alloys (ferritic/martensitic steels, ODS steels, bcc refractory alloys) hinges on the thermal stability of second phase particles and their interactions with dislocations. Irradiation damage can modify the structure and stability of both the particles and dislocations, particularly by the introduction of gas atoms, point defects and point defect clusters. The three aspects of materials strength that we are studying are: (a) Computation of dislocation mobility functions (stress-velocity relations) as a function of temperature and dislocation character. This will be done via molecular dynamics (MD) simulations of single dislocation motion under applied shear stress. This is a fundamental input to dislocation dynamics (DD) simulations and also provides fundamental insights into the high-temperature plastic behavior of ferritic materials. (b) Simulations of dislocation-obstacle interactions using MD and DD. This subtask includes simulating the effect on dislocation glide of precipitates (e.g., α' Cr precipitates), ODS particles, and irradiation induced defect clusters (e.g. voids, dislocation loops, etc.). (c) Implementation of this information (dislocation mobilities and dislocation-defect interaction rules) into DD codes that will allow us to study plasticity of single crystals Fe alloys under relevant irradiation conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development of Predictive Models for Advanced Reactor Autonomous Control

Advanced reactor designs including microreactors and small modular reactors will contribute to the clean production of cheap energy, and autonomous control for advanced reactors is an appealing option for reducing cost. However, there is a lack of industry experience applying autonomous control for advanced nuclear reactors. To accelerate the development and industry acceptance of autonomous control software for nuclear reactors, we aim to demonstrate autonomous control of the Purdue University research reactor (PUR-1) using INL-developed model predictive control (MPC) methods. To prepare for this demonstration, data-driven predictive models based on process data collected from PUR-1 have been developed and integrated with MPC and used to control a physics-based model of PUR-1. A data-driven dynamics model and a gated recurrent unit (GRU) network were both trained on process data from PUR-1. The dynamics model was shown to effectively control the reactor model with MPC when provided reactivity as a control variable but failed to control the model through the control rod positions. The GRU network produced more accurate predictions than the dynamics model when evaluated on operational data, and future work will include the evaluation of the GRU network in the controller.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Long-term nitrogen dioxide exposure assessment using back-extrapolation of satellite-based land-use regression models for Australia

Highlights: • We assessed how well a year-2006 satellite-based LUR model captures historical NO{sub 2}. • We used three methods to estimate annual mean NO{sub 2} during 1990–2005. • We measured their performance using standard LUR validation techniques. • Back-extrapolated 2006 levels captured up to 76% of spatial variability (90–05). Assessing historical exposure to air pollution in epidemiological studies is often problematic because of limited spatial and temporal measurement coverage. Several methods for modelling historical exposures have been described, including land-use regression (LUR). Satellite-based LUR is a recent technique that seeks to improve predictive ability and spatial coverage of traditional LUR models by using satellite observations of pollutants as inputs to LUR. Few studies have explored its validity for assessing historical exposures, reflecting the absence of historical observations from popular satellite platforms like Aura (launched mid-2004). We investigated whether contemporary satellite-based LUR models for Australia, developed longitudinally for 2006–2011, could capture nitrogen dioxide (NO{sub 2}) concentrations during 1990–2005 at 89 sites around the country. We assessed three methods to back-extrapolate year-2006 NO{sub 2} predictions: (1) ‘do nothing’ (i.e., use the year-2006 estimates directly, for prior years); (2) change the independent variable ‘year’ in our LUR models to match the years of interest (i.e., assume a linear trend prior to year-2006, following national average patterns in 2006–2011), and; (3) adjust year-2006 predictions using selected historical measurements. We evaluated prediction error and bias, and the correlation and absolute agreement of measurements and predictions using R{sup 2} and mean-square error R{sup 2} (MSE-R{sup 2}), respectively. We found that changing the year variable led to best performance; predictions captured between 41% (1991; MSE-R{sup 2} = 31%) and 80% (2003; MSE-R{sup 2} = 78%) of spatial variability in NO{sub 2} in a given year, and 76% (MSE-R{sup 2} = 72%) averaged over 1990–2005. We conclude that simple methods for back-extrapolating prior to year-2006 yield valid historical NO{sub 2} estimates for Australia during 1990–2005. These results suggest that for the time scales considered here, satellite-based LUR has a potential role to play in long-term exposure assessment, even in the absence of historical predictor data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Pre-Shot Simulations of Near-Field and Far-Field Ground Motion for the Source Physics Experiment (SPE) Explosions at the Climax Stock, Nevada National Security Site: SPE3

The Source Physics Experiment (SPE) is designed to improve ground motion prediction capabilities for underground nuclear testing through the development of new physics-based models together with validation via new chemical explosion data. The SPE shots consist of different size and depth chemical explosions in a granite borehole at the Climax Stock on the Nevada National Security Site (NNSS). The third shot in the series (SPE3) will be the same size (1000 kg TNT equivalent) and depth (45 m canister centroid) as the previous shot (SPE2). The main purpose of the SPE3 is to investigate the effects of the damage zone caused by the SPE2 chemical explosion on the SPE3 explosion, keeping all other parameters (e.g. size, depth, explosive type) the same. This SPE3 pre-shot report addresses progress made in simulation of the expected wavefield in the both the near- and the far-field. In this report we consider the far-field to be where seismic wave motion can be characterized by elastic or visco-elastic approximations, in contrast to the near-field where other, often non-linear effects, play a major role. The current simulations build on previous work from the SPE1 and SPE2 shots. The simulations are intended to highlight differences between SPE2 and SPE3 using a variety to approximations intended to mimic the expected effect of the damage zone. The simplest physics of damage zone effects suggest changes in the source region material properties (density, velocity), and in the yield strength (coupling) of the rock, should both impact the far-field signal. We can illustrate this in a simplistic way for P-waves in Figure A using the empirical Mueller-Muphy (1971) far-field explosion model (MM). First if the SPE2 explosion-induced damage reduces velocities and densities without affecting the yield strength or coupling, then by energy conservation the amplitudes for SPE 3 would increase as shown in the top of Figure A. Similarly if the explosion induced damage increased density (say by compacting pore space) the amplitude would decrease. This impedance effect, where the product of the density, wave-velocity, and ground-velocity squared is conserved, is well known. The second and harder effect to quantify, are changes in the energy coupling or yield strength. In the simple MM model this is represented by the coupling factor between cavity radius and yield. If we assume the granite was slightly weakened by SPE2 such that the cavity radius increases slightly then the overall amplitudes of SPE3 decrease relative to SPE2 as shown in the bottom of Figure A. In reality both effects, may exist due to the damage zone, and furthermore we know they are interrelated in complex ways. For S-waves we expect even more complex effects due to motion on joints and faults. For this reason we are developing physics-based near field simulation models coupled to far-field propagation codes to predict the overall effects of changes in the source emplacement region on observed signals. Near-field simulations have been performed using the Eulerian code (GEODYN). An ensemble model, calibrated to match records from past large-scale nuclear events is used. Both 2D axisymmetric (no faults) and fully three-dimensional GEODYN calculations (with /without faults) were conducted in which the damage zones sustained by SPE2 are retained as the initial condition for the SPE3 calculations. The results indicate that the waveform peak amplitudes are slightly decayed since the ensemble model includes no softening mechanism. The pulse widths are reduced, indicating the energy is dissipated more by the damage zone as expected. The dominant motions calculated in all the scenarios are spherically symmetric and non-spherical components are small as seen for the SPE2 calculations. The arrival time of the SPE3 waveform at the boreholes is shorter than SPE2 due to compaction during the previous explosion. As shown in the SPE 1 and 2 observations shear waves are generated, indicating the potential contributions from the induced motion on distributed joints. The effects of joints are evaluated using the Lagrangian hydrocode (GEODYN-L), which was benchmarked against the GEODYN calculations for the ensemble model. A new granite model calibrated for samples from the SPE site is used. The new model includes effects of poroelasticity and water saturation and may be scaled allowing application to both small and large scales. Parametric tests were performed to evaluate the effect of joints within the granite and the results demonstrate that in situ joints introduce anisotropy and significant tangential motions.

58 GEOSCIENCES↗
DOE OSTI2024

Decision-making based on Markov decision process in integrated artificial reasoning framework—Part I: Theory

This paper presents a decision-making framework based on an integrated artificial reasoning framework and Markov decision process (MDP). The integrated artificial reasoning framework provides a physics-based approach that converts system information into state transition models, and the analysis result will be represented by the transition probabilities that can be used with an MDP to find a traceable and explainable optimal pathway. A dynamic Bayesian network (DBN) is well suited for representing the structure of an MDP. The causality information among process variables (or among subsystems) is mathematically represented in a DBN by the conditional probabilities of the node’s states provided different probabilities of the parent node’s states. To define node states in a physically understandable manner, we used multilevel flow modeling (MFM). An MFM follows the fundamental energy and mass conservation laws and supports the selection of process variables that represent the system of interest so that causal relations among process variables are properly captured. An MFM-based DBN supports developing state transition models in an MDP to capture the effect of process variables of system having physical relations. The operators of the target system can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from component degradation or random failures. We analyzed a simplified exemplary system to illustrate an optimal operational policy using the suggested approach.

Markov decision process↗
DOE OSTI2019

Branching of hydraulic cracks enabling permeability of gas or oil shale with closed natural fractures

While hydraulic fracturing technology, aka fracking (or fraccing, frac), has become highly developed and astonishingly successful, a consistent formulation of the associated fracture mechanics that would not conflict with some observations is still unavailable. It is attempted here. Classical fracture mechanics, as well as current commercial software, predict vertical cracks to propagate without branching from the perforations of the horizontal well casing, which are typically spaced at 10 m or more. However, to explain the gas production rate at the wellhead, the crack spacing would have to be only about 0.1 m, which would increase the overall gas permeability of shale mass about 10,000×. This permeability increase has generally been attributed to a preexisting system of orthogonal natural cracks, whose spacing is about 0.1 m. However, their average age is about 100 million years, and a recent analysis indicated that these cracks must have been completely closed by secondary creep of shale in less than a million years. Here it is considered that the tectonic events that produced the natural cracks in shale must have also created weak layers with nanocracking or microcracking damage. It is numerically demonstrated that seepage forces and a greatly enhanced permeability along the weak layers, with a greatly increased transverse Biot coefficient, must cause the fracking to engender lateral branching and the opening of hydraulic cracks along the weak layers, even if these cracks are initially almost closed. A finite element crack band model, based on a recently developed anisotropic spherocylindrical microplane constitutive law, demonstrates these findings [Rahimi-Aghdam S, et al. (2018) arXiv:1212.11023].

04 OIL SHALES AND TAR SANDS↗