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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Finite boundary effects on the spherical Rayleigh–Taylor instability between viscous fluids

For the Rayleigh–Taylor unstable arrangement of a viscous fluid sphere embedded in a finite viscous fluid spherical shell with a rigid boundary and a radially directed acceleration, a dispersion relation is developed from a linear stability analysis using the method of normal modes. [Formula: see text] is the radially directed acceleration at the interface. ρ i denotes the density, μ i is the viscosity, and R i is the radius, where i = 1 is the inner sphere and i = 2 is the outer sphere. The dispersion relation is a function of the following dimensionless variables: viscosity ratio [Formula: see text], density ratio [Formula: see text], spherical harmonic mode n, [Formula: see text], [Formula: see text], and the dimensionless growth rate [Formula: see text], where σ is the exponential growth rate. We show that the boundedness provided by the outer spherical shell has a strong influence on the instability behavior, which is reflected not only in the modulation of the growth rate but also in the selection of the most unstable modes that are physically possible. This outer boundary effect is quantified by the relative magnitude of the radius ratio H. We find that when H is close to unity, lower order harmonics are excluded from becoming the most unstable within a vast region of the parameter space. In other words, the effect of H has precedence over the other controlling parameters d, B, and a wide range of s in establishing what the lowest most unstable mode can be. When H ~ 1, low order harmonics can become the most unstable only for s >> 1. However, in the limit when s → ∞, we show that the most unstable mode is n = 1 and derive the dispersion relation in this limit. The exclusion of most unstable low order harmonics caused by a finite outer boundary is not realized when the outer boundary extends beyond a certain threshold length-scale in which case all modes are equally possible depending on the value of B.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2017

Attribution of the July–August 2013 heat event in Central and Eastern China to anthropogenic greenhouse gas emissions

In the midsummer of 2013, Central and Eastern China (CEC) was hit by an extraordinary heat event, with the region experiencing the warmest July-August on record. To explore how human-induced greenhouse gas emissions and natural internal variability contributed to this heat event, we compare observed July-August mean surface air temperature wit h that simulated by climate models. We find that both atmospheric natural variability and anthropogenic factors contributed to this heat event. This extreme warm midsummer was associated with a positive high-pressure anomaly that was closely related to the stochastic behavior of atmospheric circulation. Diagnosis of CMIP5 models and large ensembles of two atmospheric models indicates that human influence has substantially increased the chance of warm mid-summers such as 2013 in CEC, although the exact estimated increase depends on the selection of climate models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Suppressing Quantum Circuit Errors Due to System Variability

We present a quantum circuit optimization technique that takes into account the variability in error rates that is inherent across present-day noisy quantum computing platforms. This method can be run after qubit routing or postcompilation and consists of computing isomorphic subgraphs to input circuits and scoring each using heuristic cost functions derived from system calibration data. Using an independent standard algorithmic test suite, we show that it is possible to recover on average nearly 40% of missing fidelity using better qubit selection via efficient to compute cost functions. We demonstrate additional performance gains by considering qubit placement over multiple quantum processors. The overhead from these tools is minimal with respect to other compilation steps, such as qubit routing, as the number of qubits increases. As such, our method can be used to find qubit mappings for problems at the scale of quantum advantage and beyond.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

SCALE Analyses of Scenarios in the Molten Salt Reactor Fuel Cycle

In support of the US Nuclear Regulatory Commission non-light-water reactor fuel cycle demonstration project, the capabilities of SCALE 6.3.1 for radionuclide characterization, criticality, and shielding were demonstrated through several scenarios in a molten salt reactor (MSR) nuclear fuel cycle. Three scenarios were selected for this study, with the molten salt breeder reactor (MSBR) serving as the reference design. The original thorium-based fuel salt used in MSBR was replaced with a 235 U-enriched fuel salt to better reflect anticipated future MSR concepts. The first scenario focused on the fuel salt preparation stage. Criticality analyses, using SCALE/CSAS-Shift and SCALE/SAMPLER, examined potential critical configurations in the fresh fuel salt container based on variables such as 235 U enrichment, UF 4 molar fraction, temperature, and container geometry. The second scenario explored the release of fission products during reactor operation in which the tritium buildup in the primary fuel salt was quantified through depletion calculations using SCALE/TRITON with continuous fuel makeup and fractional fission product removal. This scenario also assessed radioactivity levels in the off-gas system (OGS), quantifying radiotoxic nuclides that could be released into the environment. SCALE/SAMPLER was employed to perform uncertainty quantification to identify key operating parameters influencing the buildup of radiotoxic nuclides in the OGS. Additionally, radiation dose rates were calculated using SCALE/MAVRIC to estimate the maximum exposure levels within the reactor cell complex during operation. The final scenario evaluated the decay heat and radioactivity of the primary fuel salt collected in the drain tank, as well as the radiation dose rate outside the building from the presence of the drain tank. Overall, the application of SCALE’s various capabilities for radionuclide inventory generation, criticality analysis, and shielding in MSR fuel cycles was successfully demonstrated across these scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE↗

DOE OSTI2020

An Overview of Neutron Irradiated SiC Layer Behavior using Micro-and Nano-Characterization Techniques

The complexity of fission product distribution and composition within the SiC layer of tristructural isotropic (TRISO) coated particles, irradiation effects on the SiC structure as well as the variable nature of metallic fission product release, has led to the exploration of multiple micro- and nano-characterization techniques. The fine scale of the fission product precipitates necessitates unique learnings and application of electron microscopic techniques with irradiated fuel during the Advanced Gas Reactor (AGR)-1 experiment analysis. A summarized discussion on the specific advanced techniques with associated method development for TRISO coated particles is provided followed by the down selected techniques currently considered to provide the highest impact. Techniques considered are electron probe micro-analyzer (EPMA), scanning transmission electron microscopy (STEM), and Precession electron diffraction (PED). SiC grain boundary characteristics are evaluated due to the mobility of specific fission products through grain boundaries. PED was performed for understanding the role of grain boundary character on fission product transport. One set of comparative analyses between AGR-1 and AGR-2 particles leads to a finding that the AGR-1, high-Ag-retention particle, had statistically more coincidence site lattice (CSL)-related grain boundaries (but fewer low-angle grain boundaries), compared to the AGR-2 particle. This implies that CSL-related grain boundaries may have a direct influence on Ag retention. However, precipitates were found on a relatively small fraction of CSL-related grain boundaries in both particles. In another set of comparison between AGR-1 and AGR-2 particles that were subjected to safety testing, there is significant differences in average SiC grain boundary distributions, but the fission product distributions on these grain boundaries are very similar.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Micro- and Nano-techniques for the Study of Fission Product Precipitation in SiC Layer

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

Simulation of Spent Nuclear Fuel loading into a Final Waste Repository

Previous work towards studying repository loading have used: - spent nuclear fuel (SNF) with an average burnup composition; - a lumped capacitance thermal model for calculating temperature in a Cyclus repository model. The goal of this work is to improve on the repository models and use U.S. historical SNF inventory data in simulations to more accurately study the loading of a waste repository. These goals will be achieved by: - using UNF-ST-and-DARDS Unified Database (UDB) that has historic assembly-specific data (e.g, isotopic composition, heat) in Cyclus simulations; - implementing a more accurate thermal model within a Cyclus repository model. Objectives: - Create a Cyclus spent fuel conditioning model that packages spent fuel bundles into packages which have user-defined properties. - Create a Cyclus medium-fidelity repository model that gives accurate time and spatial dependent temperature values and loads the repository based on a user-selected loading strategy. Cyclus is an agent-based extensible framework for modeling flow of material through user-defined nuclear fuel cycles. In Cyclus, each facility in the fuel cycle is modeled individually and the facilities interact with one another as independent agents. The spent fuel conditioning model accepts spent fuel bundles and puts them into a cylindrical waste package. In the spent fuel conditioning model, the user can define variables: For each layer, radius, thermal conductivity, thermal diffusivity; For each package, Number of spent fuel bundles, Radius and height. The waste repository model accepts waste packages and emplaces them into available positions within the waste repository based on a thermal criteria. The thermal criteria is a temperature limit at the interface between the waste package surface and the host geology, that is set based on the repository's host geology. In the waste repository model, the user can define the variables: Capacity, Distance between waste packages, Distance between drifts, Repository host geology, Loading Strategy. After the addition of new waste packages at each time step, the waste repository model recalculates the temperature at each location in the repository. If the addition of this new package causes its temperature to exceed the thermal limit, it will be placed back into the buffer. A thermal model that relies on a transient 'outside' model and quasi-steady-state 'inside' model is used to accurately determine the temperature in the repository. The 'outside' model assumes a homogenous medium with the Engineered Barrier System (EBS) replaced by the geologic medium. Temperature solutions for the central waste package, adjacent point and line sources are superimposed to calculate the temperature at specific points in the repository. The central drift consists of one finite line source which represents the central waste package. The central drift also consists of point sources that represent neighboring waste packages in the central drift. The neighboring drifts are represented by infinite line sources. The 'inside' model is considered to be at a quasi-steady-state condition because EBS has a relatively low thermal mass compared to the infinite geologic medium. The steady state calculation is performed at each time step with the heat source and interface temperature as boundary conditions. Future Work: Run Cyclus simulations with U.S. historical SNF inventory data, the spent fuel conditioning and repository models to study how waste package acceptance strategies impact repository loading.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Weatherization Assistant NEAT/MHEA

The software provides a measure selection technique indicating cost effective retrofit activities that can be applied to a home using a standard Savings to Investment Ratio (SIR). Users must provide an input file describing the characteristics of the home to be evaluated. The software takes the input data provided and calculates energy savings and cost savings predicted for a standard set of measures given the input parameters. The Weatherization Assistant computes estimates of pre-retrofit whole building space heating and cooling energy consumptions based on the house description data supplied by the user. The consumptions are computed using a monthly heating and cooling variable base degree-day method by algorithms similar to those developed for the CIRA program [LBL, 1982]. The building consumptions are needed in computing the energy savings from measures affecting the efficiencies of the heating and cooling equipment. Weatherization Assistant then computes the energy savings and costs for each individual measure applicable to the building described as if it were the only measure installed in the house. From these energy savings, a discounted dollar savings over the life of each measure is computed. The ratio of this dollar savings to the cost of installing the measure, the "savings-to-investment ratio" (SIR), is used in an initial ranking of the measures' effectiveness. The "interacted" savings and SIR of measures are then determined assuming the measures are added to the house collectively, in order of their ranking, e.g., the second ranked measure is installed in the house initially described by the user after having been modified by the first ranked measure. If this second-ranked measure's updated SIR is greater than a user-defined limit, the measure is left implemented, else it is removed so that the next measure's effectiveness is not dependent on it. The choice between two mutually exclusive measures (such as different levels of insulation) is made on the basis of their "net present value" (NPV), the difference of life-time savings and installation cost, rather than their SIR. This has been shown to be the more correct criterion on which to base the selection between two measures, both of which cannot be installed. The audit computes and reports to the user the energy savings, discounted dollar savings, installation cost, and SIR for each measure considered cost-effective. For those with SIR greater than the user-designated cutoff, a materials list gives the material name, type, and quantity required for installation of the measure. Weatherization Assistant permits entry of pre-retrofit billing data for gas or electrically heated homes or homes with electric air-conditioning. The user may then make the decision to have the savings of the measures adjusted to reflect the difference in billed consumption and that predicted by the program.

Gettings, Michael↗

DOE OSTI2019

Hybrid Inverse Parameter Identification of Fully Coupled Ductile Damage Model for Steel Sheet DP600 with Two Different Algorithms: Trust Region and Genetic Algorithms

Ductile damage model has been widely regarded as a valuable method to predict the failure of sheet metal. Based on the thermodynamic theory and continuum damage mechanics, the fully coupled ductile damage model can be developed, which also can better predict the initiation and growth of the fracture. But the identifications of model parameters with theoretical methodology are difficult due to the complex coupling relationships existing among all state variables. The inverse methodology is regarded as a good method to resolve the problem. In this paper, the recently proposed fully coupled ductile damage model is chosen to investigate the deformation behavior of DP600 steel, in which the mixed saturation isotropic and kinematic hardenings are taken into account and fully coupled with the ductile damage. During the identification process, the least square formula of the error between experimental and numerical results is selected as the target function. The trust region algorithm and genetic algorithm are used with the help of MATLAB for the identification of three damage parameters. Finally, by comparing the experimental and numerical results, the validations of two algorithms are proved. The efficiency of the optimization process with trust region algorithm is higher, but with lower accuracy. Meanwhile, the optimization process is greatly affected by the chosen initial values of the ductile damage parameters.

36 MATERIALS SCIENCE↗

DOE OSTI2023

The value of fusion energy to a decarbonized United States electric grid

Fusion could be a part of future decarbonized electricity systems, but it will need to compete with other technologies. In particular, pulsed tokamak plants have a unique operational mode, and evaluating which characteristics make them economically competitive can help select between design pathways. Using a capacity expansion and operations model, here we determined cost thresholds for pulsed tokamaks to reach a range of penetration levels in a future decarbonized US Eastern Interconnection. The required capital cost to reach a fusion capacity of 100 GW varied from $2,700 to $7,500 kW -1 , and the equilibrium penetration increases rapidly with decreasing cost. The value per unit power capacity depends on the variable operational cost and on the cost of its competition, particularly fission, much more than on the pulse cycle parameters. These findings can therefore provide initial cost targets for fusion more generally in the United States.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Environmental stress mediates groundwater microbial community assembly

Community assembly describes how different ecological processes shape microbial community composition and structure. How environmental factors impact community assembly remains elusive. Here we sampled microbial communities and >200 biogeochemical variables in groundwater at the Oak Ridge Field Research Center, a former nuclear waste disposal site, and developed a theoretical framework to conceptualize the relationships between community assembly processes and environmental stresses. We found that stochastic assembly processes were critical (>60% on average) in shaping community structure, but their relative importance decreased as stress increased. Dispersal limitation and ‘drift’ related to random birth and death had negative correlations with stresses, whereas the selection processes leading to dissimilar communities increased with stresses, primarily related to pH, cobalt and molybdenum. Assembly mechanisms also varied greatly among different phylogenetic groups. As a result, our findings highlight the importance of microbial dispersal limitation and environmental heterogeneity in ecosystem restoration and management.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Rational Selection of Transition-Metal Oxide Electrocatalysts from Structure Electronic Structure-Activity Relations: The Role of Defects, Strain, and Sub-Surface Layering

This BES research investigates the physicochemical properties of metal oxides and how they affect electrocatalytic functionalities. The goal is to develop a predictive framework for realizing top-performing electrocatalytic materials for energy-critical reactions. The hypothesis is that well-defined thin films allow detailed mapping of structural-activity relationships because flat surfaces are more straightforward to characterize. Furthermore, the well-defined nature of thin-film metal oxides allows precise tuning of structural and chemical variables for structure-activity-relationship mapping. The proposed research has two technical objectives. The first is to experimentally assess whether the binding energies of surface oxygen can serve as an activity descriptor for oxygen electrocatalysis on metal oxides and then how to control them by tuning the structure and chemical variables. The second is to find the rate-limiting process in oxygen electrocatalysis and other small-molecule reactions. Similar mechanistic insights have been developed on well-defined platinum surfaces but not yet on oxides. This research addresses this gap and uses electrochemistry and X-ray photoemission spectroscopy to study oxide surface chemistry. The obtained insights are collectively analyzed to reveal how the oxides’ structural and chemical variables affect kinetics and can be used to design more active electrocatalysts for energy-critical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Data-driven modeling of power generation for a coal power plant under cycling

Increased penetration of renewables for power generation has negatively impacted the dynamics of conventional fossil fuel-based power plants. The power plants operating on the base load are forced to cycle, to adjust to the fluctuating power demands. This results in an inefficient operation of the coal power plants, which leads up to higher operating losses. To overcome such operational challenge associated with cycling and to develop an optimal process control, this work analyzes a set of models for predicting power generation. Moreover, the power generation is intrinsically affected by the state of the power plant components, and therefore our model development also incorporates additional power plant process variables while forecasting the power generation. We present and compare multiple state-of-the-art forecasting data-driven methods for power generation to determine the most adequate and accurate model. We also develop an interpretable attention-based transformer model to explain the importance of process variables during training and forecasting. The trained deep neural network (DNN) LSTM model has good accuracy in predicting gross power generation under various prediction horizons with/without cycling events and outperforms the other models for long-term forecasting. The DNN memory-based models show significant superiority over other state-of-the-art machine learning models for short, medium and long range predictions. The transformer-based model with attention enhances the selection of historical data for multi-horizon forecasting, and also allows to interpret the significance of internal power plant components on the power generation. This newly gained insights can be used by operation engineers to anticipate and monitor the health of power plant equipment during high cycling periods.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2026

Assessing the Accuracy of Property Model Predictions for Cost Optimization of Desalination Technologies

Accurate modeling of seawater thermophysical and thermodynamic properties is critical for optimizing desalination processes. This study compares three seawater property models, a Reaktoro multicomponent model, the thermophysical seawater properties library from the Massachusetts Institute of Technology, and a simplified sodium chloride model, in the context of levelized cost of water (LCOW) minimization for reverse osmosis (RO) and mechanical vapor compression systems. Process simulations and cost optimizations reveal that although all three models yield comparable LCOW and specific energy consumption (SEC) estimates under baseline conditions, deviations among their predictions increase with salinity. Relative differences in LCOW and SEC reach up to 6% and 8%, respectively. RO results show greater variability due to differences in osmotic pressure predictions, which affect pressure constraints at high recoveries. Computational performance varies substantially; specifically, Reaktoro simulations are up to 28 times slower than empirical models due to their detailed equilibrium calculations. These results suggest that empirical models offer acceptable accuracy for routine desalination process design, while Reaktoro provides advantages in scenarios requiring detailed speciation, such as scaling or pH adjustment studies. These findings underscore the importance of selecting appropriate property models based on the modeling objective of desalination applications and motivate future work integrating thermodynamic rigor with empirical efficiency.

Physical and chemical properties↗

DOE OSTI2023

Knowledge of lactation amenorrhea method among postpartum women in Ethiopia: a facility-based cross-sectional study

While the importance of knowledge about contraceptives in improving their utilization and thereby reducing the risk of unintended pregnancies is well documented, there are limited studies documented about the Lactational Amenorrhea Method (LAM). Thus, understanding the knowledge of postpartum mothers about LAM is essential for designing tailored interventions. This study assessed the level of knowledge about LAM and its associated factors among postpartum mothers in Ethiopia. A facility-based cross-sectional study was conducted among 3148 randomly selected postpartum participants. The study utilized multistage sampling approach in hospitals located across five regions and one city administration in Ethiopia. Data were collected using face-to-face interviews at discharge. A participant was categorized as having knowledge of LAM if she correctly answered the three LAM criteria: amenorrhea, the first 6 months, and exclusive breast feeding. A binary logistic regression model was used to identify factors associated with knowledge of LAM. Variables with p < 0.25 in the binary logistic regression were included in the multiple logistic regression. Then, associations were described using the adjusted odds ratio (AOR) along with the 95% confidence interval (CI), and statistical significance was declared at p < 0.05. Only four in 10 participants (40.6%; 95% CI 38.9–42.3) had knowledge of LAM. Participants who attended college or above educational level (AOR = 2.1, 95% CI 1.5–2.8), those with parity of two (AOR = 2.3; 95% CI 1.6–3.6) or more than two (AOR = 2.4; 95% CI 1.5–4.0), those who expressed a desire for further fertility (AOR = 1.3; 95% CI 1.1–1.5), individuals who received counselling on LAM (AOR = 3.0; 95% CI 2.6–3.7), and those who gave birth in hospital (AOR = 2.6; 95% CI 1.4–2.6) had higher odds of knowledge about LAM, compared to their counter parts. In contrary, participants resided far away from health facilities had 30% lower odd of knowledge about LAM compared to those resided near the health facilities (AOR = 0.70; 95% CI 0.6–0.8). The proportion of participants who had knowledge of LAM was low. Strengthening counseling about LAM during antenatal care and delivery with due attention to women with limited access to health facilities should be considered for increasing their level of knowledge on LAM.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Pump and Treat Impacts on Aquifer Conditions and the Development of System-wide Performance Strategies - 19077

The 200 West pump-and-treat (P and T) system on the Hanford Site's Central Plateau currently treats multiple contaminants within the 200-ZP-1 Operable Unit (OU). Initially designed to support the 200-ZP1 Remedial Action Objectives, the use of the P and T system has evolved over time to address contaminants from other regions of the aquifer as well. The P and T system currently receives water from other regions within the Central Plateau that are biogeochemically distinct, treating groundwater with elevated concentrations of carbon tetrachloride, cyanide, uranium, technetium-99, and nitrate. Given the varying geochemical signatures from current and potential future sources, combined with the operational conditions and amendments used for treatment processes, there is a need to identify the impacts of the P and T system on the aquifer and aquifer impacts on P and T performance. To this end, initial laboratory analyses and geochemical modeling efforts focused on characterizing the baseline geochemical environment for the aquifer in the 200-ZP-1 OU. Several sediment characterization techniques, including geologic descriptions, water and acid extractions, and microbiological measurements were selected to determine key geochemical and microbiological constituents for the baseline, prior to injection of the effluent from the treatment plant. Different geochemical components within sediment samples from the aquifer were identified that may significantly affect how the sediments react to P and T injection water. Batch experiments were also used to identify aquifer impacts on operational performance and support development of some column studies. These experiments were designed to test and evaluate variable P and T effluents using actual effluent solutions from the treatment plant as well as simulated Hanford groundwater at different temperatures to identify the important geochemical and biological reactions that might occur within the aquifer. Initial results were used for geochemical modeling of the effluents and batch experiments. These results, along with the baseline data obtained from the initial sediment characterization, are intended to feed into the design of the column studies and inform conceptual models and modeling efforts for evaluating the fate and transport of introduced contaminants and co-injectates, and their short- and long-term impact on the aquifer-system injection capacity. This evaluation is designed to provide additional information on the major geochemical and microbiological reactions that are driven by the injection of the P and T effluent into the aquifer. Reactive transport modeling of the laboratory experiments and extrapolation to a larger-scale modeling domain provide information that can be used for predictive evaluations of system performance based on P and T operational changes and aquifer mass loading and capacity estimates. This information can be used to address combined subsurface and operational challenges, such as the need for frequent well redevelopment to maintain injection capacity. This information also provides the technical basis for decisions related to the P and T system operations that support remedy optimization efforts and short- and long-term remedy decisions related to multiple OUs on the Hanford Site Central Plateau. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

An isothermal forming process with multi-stage variable speed for magnesium component assisted by sensitivity analysis

We have developed a multi-stage variable speed (MSV) isothermal forming process based on strain rate sensitivity (SRS) analysis, and successfully produced a large size of rib-web component of magnesium alloy from a cylindrical billet. The obtained rib-web component has been processed into parts for mechanical properties examination and the examination results met the standard of being safely used in aircrafts. The process parameters of the forming technology and microstructure change were explicitly linked by the SRS coefficient. The finite element (FE) simulation and SRS distribution were implemented to identify the relationship among process parameters, shaping characteristics, and microstructure development. The MSV speed process was employed for reducing the forming load, refining grain sizes and increasing the strength of the component. With the selected process parameters the maximum forming load was reduced to be less than 20 MN, which is 55.3% lower than that used in the same process with the initial constant speed unchanged. Fine dynamic recrystallization (DRX) were observed from all parts of the forged cover plate including the convex, ribs, and web region. It was also found that higher strain resulted in more uniform distribution of fine ß-Mg17Al12 precipitates and larger DRX volume fraction. Importantly the developed isothermal forming process with severe plastic deformation can be applied for obtaining grain refinement so improving the mechanical properties of Mg products.

Magnesium alloy, Isothermal forming, Multi-stage v↗