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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Techno-Economic Analysis of Gas-Liquid Contactors for Tritium Extraction from Lead-Lithium

To enable a sustainable fuel cycle, any deuterium-tritium fusion reactor must breed its tritium fuel onsite. Lead-lithium (PbLi), a eutectic metal, is a leading liquid breeder material for tritium generation. One challenge with PbLi blanket technology is the extraction of tritium from the molten eutectic. Three technologies are the focus of worldwide research: the vacuum permeator, the vacuum sieve tray, and the gas-liquid contactor (GLC). The present work offers a methodology for designing, sizing, optimizing, and costing a trickle-bed GLC. Here, we analyzed tritium extraction from PbLi using MELODIE experimental data by applying traditional packed bed mass transfer efficiency models along with supplementary models, like film theory. Our analysis revealed that traditional packed bed mass transfer efficiency models do not fit the MELODIE loop experimental data. Moreover, uncertainty in PbLi solubility resulted in a 325-fold increase in required gas flow rates when comparing identical packing heights. The film theory liquid mass transfer coefficient, Delt-Olujic wettability model, and Reiter tritium solubility values fit the MELODIE data best and were used both in the design and to conduct the economic analysis. Techno-economic analysis of the GLC was performed to evaluate three design sizes, all achieving a minimum extraction efficiency of 90 [%] for a total tritium extraction of 31 [kg/yr].

Fusion Fuel Cycle↗
DOE OSTI2020

An Evaluation of the Economic and Resilience Benefits of a Microgrid in Northampton, Massachusetts

Recent developments and advances in distributed energy resource (DER) technologies make them valuable assets in microgrids. This paper presents an innovative evaluation framework for microgrid assets to capture economic benefits from various grid and behind-the-meter services in grid-connecting mode and resilience benefits in islanding mode. In particular, a linear programming formulation is used to model different services and DER operational constraints to determine the optimal DER dispatch to maximize economic benefits. For the resiliency analysis, a stochastic evaluation procedure is proposed to explicitly quantify the microgrid survivability against a random outage, considering uncertainties associated with photovoltaic (PV) generation, system load, and distributed generator failures. Optimal coordination strategies are developed to minimize unserved energy and improve system survivability, considering different levels of system connectedness. The proposed framework has been applied to evaluate a proposed microgrid in Northampton, Massachusetts that would link the Northampton Department of Public Works, Cooley Dickenson Hospital, and Smith Vocational Area High School. The findings of this analysis indicate that over a 20-year economic life, a 441 kW/441 kWh battery energy storage system, and 386 kW PV solar array can generate $2.5 million in present value benefits, yielding a 1.16 return on investment ratio. Results of this study also show that forming a microgrid generally improves system survivability, but the resilience performance of individual facilities varies depending on power-sharing strategies.

25 ENERGY STORAGE↗
DOE OSTI2022

NRAP-Open-IAM: NRAP Open Source Integrated Assessment Model

Note: This is the last version (a2.6.1) of NRAP-Open-IAM released during NRAP Phase II in 2022. The latest version of NRAP-Open-IAM is available here: https://edx.netl.doe.gov/dataset/phase-iii-nrap-open-iam NRAP-Open-IAM is an open-source software product that enables quantification of containment effectiveness and leakage risk at storage sites in the context of system uncertainties and variability. NRAP-Open-IAM represents the next-generation in a line of systems-based computational models developed for quantitative geological carbon storage (GCS) risk assessment. The model comprises a set of reduced-order and analytical models of various components of the GCS system, potential leakage pathways, receptors of concern including impact to groundwater resources and the atmosphere, a framework to support stochastic simulation, time stepping, uncertainty quantification, other analytical functionality for scenario and risk-performance evaluation, and a basic graphical user interface to support scenario development, data input simulation definition, and basic post-processing and results display. As the NRAP Open-IAM functionality continues to evolve, we continue to add to its capability to develop quantitative, probabilistic, and time-dependent profiles of the evolution of risk at a GCS site and evaluate the influence of uncertain parameters on uncertainty in predicted risk. It can be used to quantify the dynamics of reservoir saturation plume and pressure-affected area, for evaluation of the area of potential groundwater impact (i.e., Area of Review) and monitoring requirements to support cost and regulatory analysis, and for consideration of different post-injection site care and closure scenarios. This submission contains the current version of NRAP-Open-IAM available for evaluation and testing. To use the NRAP-Open-IAM, download the source code (https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/4c24a3da-3b40-4ffe-9892-c807ae9f8760) then open the NRAP-Open-IAM user's guide (https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/8b27335a-343c-4836-b8a3-3ad0bdc9e669) to read more about the tool. Installation instructions for Windows, Mac, and Linux can be found in the "installers" folder of the extracted NRAP-Open-IAM folder and describe setup of environment (e.g., Python libraries) needed for proper work of the tool. Test of installation can be done by running "python openiam_setup_tests.py" in the "setup" folder. The installation test also runs a test suite to see if the NRAP-Open-IAM has been installed correctly. To run the test suite separately, run "python iam_test.py" in the "test" folder. User's guide: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/8b27335a-343c-4836-b8a3-3ad0bdc9e669 Developer's guide: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/3bc6ee7d-609d-4eb6-80ba-fa6130ee0313 Reservoir simulation data used in some examples distributed with NRAP-Open-IAM: - Kimberlina: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/eb62cece-61b2-4037-9b6d-32407dde2ab8 - Kimberlina (compartmentalized): https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/366f9530-3b32-4b84-affe-ab2df1d9a8b5 - FutureGen 2.0: https://edx.netl.doe.gov/dataset/futuregen-2-0-1008-simulation-reservoir-lookup-table NRAP-Open-IAM GitLab repository: https://gitlab.com/NRAP/OpenIAM Related publications: - Bacon, D., Yonkofski, C., Brown, C., Demirkanli, D. and Whiting, J., 2019. Risk-based post injection site care and monitoring for commercial-scale carbon storage: Reevaluation of the FutureGen 2.0 site using NRAP-Open-IAM and DREAM. International Journal of Greenhouse Gas Control 90: 102784. - Bacon, D. Demirkanli, D., and White, S., 2020. Probabilistic risk-based Area of Review (AoR) determination for a deep-saline carbon storage site. International Journal of Greenhouse Gas Control 102: 103153. - Harp, D., Oldenburg, C., and Pawar, R., 2019. A metric for evaluating conformance robustness during geologic CO2 sequestration operations. International Journal of Greenhouse Gas Control 85: 100-108. - Lackey, G., Vasylkivska, V., Huerta, N., King, S., and Dilmore, R., 2019. Managing well leakage risks at a geologic carbon storage site with many wells, International Journal of Greenhouse Gas Control, 88 :182-194. - Vasylkivska, V., Dilmore, R., Lackey, G., Zhang, Y., King, S., Bacon, D., Chen, B., Mansoor, K., and Harp, D., 2021. NRAP-Open-IAM: A flexible open-source integrated assessment model for geologic carbon storage risk assessment and management, Environmental Modelling & Software, 143: 105114. Presentations: - Chen, B., Harp, D., and Pawar, R., A data assimilation approach (ES-MDA) coupling with NRAP-Open-IAM for quantifying uncertainty reduction in geological CO2 sequestration. AGUFM 2019: T44A-02. - Chen, B., and Harp, D., Improving risk analysis precision for geologic CO2 sequestration by quantifying the uncertainty reduction before and after acquiring monitoring data. 14th Greenhouse Gas Control Technologies Conference, Melbourne, Australia, 2018, pp. 21-26. - Harp, D., National Risk Assessment Partnership Task 2: Containment Assurance. No. LA-UR-19-28654, Los Alamos National Laboratory (LANL), Los Alamos, NM (United States), 2019. - Vasylkivska, V., King, S., Bacon, D., Harp, D., Chen, B., Mansoor, K., Onishi, T., Yang, Y., Zhang, Y., and Keating, E., NRAP-Open-IAM: An open-source integrated assessment model, poster, Mastering the Subsurface Through Technology Innovation, Partnerships and Collaboration: Carbon Storage and Oil and Natural Gas Technologies Review Meeting, Pittsburgh, PA, August 13-16, 2018. - Vasylkivska, V., Lackey, G., King, S., Wentworth, A., Huerta, N., Creason, C., DiGiulio, J., Yang, Y., and Dilmore, R., Long-term risk analysis of a geologic CO2 storage project during the post-injection period, SIAM Conference on Computational Science and Engineering, Spokane, WA, February 25-March 1, 2019. - Vasylkivska, V., Overview of the NRAP-Open-IAM tool for carbon storage (beta release), 2019 Annual NRAP Tool Users Meeting, Pittsburgh, PA, August 27, 2019. - Vasylkivska, V., Bacon, D., Chen, B., Dilmore, R., Harp, D., King, S., Lackey, G., Lindner, E., Liu, G., Mansoor, K. and Zhang, Y., NRAP-Open-IAM: A new, open-source code for integrated assessment of geologic carbon storage containment effectiveness and leakage risk, poster, American Geophysical Union Fall Meeting 2020 (virtual meeting), December 2020. - Vasylkivska, V., NRAP open-source integrated assessment model and relevant application, oral presentation, NRAP workshop "NRAP Tools for Geologic Carbon Storage Risk-Based Decision Making" held in conjunction with Groundwater Protection Council (GWPC) 2021 Annual Forum (virtual meeting), Salt Lake City, UT, September 2021. - Vasylkivska, V., NRAP-Open-IAM: open-source integrated assessment model, digital poster/demonstration, software demonstration session, 2022 Carbon Management Project Review Meeting, August 16, 2022

AoR↗
DOE OSTI2022

Insights into pathological mechanisms and interventions revealed by analyzing a mathematical model for cone metabolism

This work analyzes a mathematical model for the metabolic dynamics of a cone photoreceptor, which is the first model to account for energy generation from fatty acids oxidation of shed photoreceptor outer segments (POS). Multiple parameter bifurcation analysis shows that joint variations in external glucose, the efficiency of glucose transporter 1 (GLUT1), lipid utilization for POS renewal, and oxidation of fatty acids affect the cone’s metabolic vitality and its capability to adapt under glucose-deficient conditions. The analysis further reveals that when glucose is scarce, cone viability cannot be sustained by only fueling energy production in the mitochondria, but it also requires supporting anabolic processes to create lipids necessary for cell maintenance and repair. In silico experiments are used to investigate how the duration of glucose deprivation impacts the cell without and with a potential GLUT1 or oxidation of fatty acids intervention as well as a dual intervention. The results show that for prolonged duration of glucose deprivation, the cone metabolic system does not recover with higher oxidation of fatty acids and requires greater effectiveness of GLUT1 to recover. Finally, time-varying global sensitivity analysis (GSA) is applied to assess the sensitivity of the model outputs of interest to changes and uncertainty in the parameters at specific times. The results reveal a critical temporal window where there would be more flexibility for interventions to rescue a cone cell from the detrimental consequences of glucose shortage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

DESI complete calibration of the colour–redshift relation (DC3R2): results from early DESI data

We present initial results from the Dark Energy Spectroscopic Instrument (DESI) complete calibration of the colour–redshift relation (DC3R2) secondary target survey. Our analysis uses 230 k galaxies that overlap with KiDS-VIKING ugriZYJHK s photometry to calibrate the colour–redshift relation and to inform photometric redshift (photo-z) inference methods of future weak lensing surveys. Together with emission line galaxies (ELGs), luminous red galaxies (LRGs), and the Bright Galaxy Survey (BGS) that provide samples of complementary colour, the DC3R2 targets help DESI to span 56 percent of the colour space visible to Euclid and LSST with high confidence spectroscopic redshifts. The effects of spectroscopic completeness and quality are explored, as well as systematic uncertainties introduced with the use of common Self-Organizing Maps trained on different photometry than the analysis sample. We further examine the dependence of redshift on magnitude at fixed colour, important for the use of bright galaxy spectra to calibrate redshifts in a fainter photometric galaxy sample. We find that noise in the KiDS-VIKING photometry introduces a dominant, apparent magnitude dependence of redshift at fixed colour, which indicates a need for carefully chosen deep drilling fields, and survey simulation to model this effect for future weak lensing surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Bayesian analysis of the 86 Sr ⁢(𝛼,𝛼) reaction to constrain the 86 Sr ⁢(𝛼,𝑛) cross section at astrophysical energies

The alpha optical model potential (𝛼-OMP ) is a phenomenological approach used to describe elastic scattering where multiple reaction channels are open. It is one of the most critical inputs for the calculation of thermonuclear reaction rates in explosive stellar environments, but uncertainties within the 𝛼-OMP lead to imprecise predictions hindering comparisons between calculations and observations. In order to improve the precision of the 𝛼-OMP, additional nuclear physics data are required. In this paper, a measurement of the 86 Sr (𝛼, 𝛼) elastic scattering cross section at multiple energies is reported. Here, a local optical potential is constructed via a fully Bayesian analysis of the elastic scattering data. The resulting uncertainties on the low-energy cross sections relevant to nuclear astrophysics are then calculated and shown to be on the order of 50%.

59 ≤ A ≤ 89↗
DOE OSTI2026

Determination of nuclear PDFs using Markov chain Monte Carlo methods

Global QCD analyses of nuclear parton distribution functions (nPDFs) have traditionally relied on the Hessian method for uncertainty estimation. However, the inherent Gaussian approximation and reliance on local curvature often prove insufficient for nPDF fits, which are frequently characterized by limited data constraints and non-Gaussian likelihoods. In this paper, we present the first nPDF determination based on Markov Chain Monte Carlo (MCMC) techniques, implemented within the nCTEQ framework using an adaptive Metropolis-Hastings algorithm. The MCMC approach enables a direct mapping of the posterior distribution and reveals a highly nontrivial parameter-space structure, including multiple modes and pronounced non-Gaussian behavior, particularly for the valence PDFs. We perform the first single-nucleus global analysis of lead PDFs using exclusively lead data and compare it to a multi-nuclei fit employing a standard analytic A dependence. The inclusion of lighter nuclei reduces quark uncertainties and modifies the shape of the lead PDFs, while leaving the gluon distribution largely unaffected. A complementary Hessian analysis exposes systematic limitations of the Gaussian approximation. Our results demonstrate that MCMC methods provide a more reliable framework for uncertainty quantification in nPDF determinations.

Derakhshanian, N. [Institute of Nuclear Physics Po↗
DOE OSTI2022

Effects of Intrusive Confining Units on Groundwater Flow at Pahute Mesa, Nevada National Security Site

Geological, geophysical, hydrogeological, and hydrological evidence indicates that feeder dikes to rhyolitic lava flows may play a role as confining units in the groundwater flow system underlying the Pahute Mesa (PM) area of underground nuclear testing at the Nevada National Security Site (NNSS) (Figure 1). Of geological significance, the PM testing area is largely situated within the Silent Canyon caldera complex (SCCC), which includes both tuffs and lavas that were fed by (and are connected to) intrusive rock units such as feeder dikes prior to and during volcanic eruptions (Orkild et al., 1968; Byers et al., 1976a). Groundwater modeling results presented in this report support extension of “pool-dam” and “breach scenario” concepts presented in Jackson and Fenelon (2018) and Jackson et al. (2021) to low-permeability intrusive confining units (ICUs) such as feeder dikes that are expected to dissect and ring silicic calderas. As laterally extensive, steeply-dipping, and sub-parallel planar structures, ICUs may further compartmentalize groundwater flow in some areas of the volcanic aquifer system at PM. ICUs may explain unusually high horizontal hydraulic gradient southwest of Cheshire. Breaching of an ICU within which the Cheshire test was emplaced may explain changes in water levels before and after the Cheshire test was detonated in the U-20n emplacement hole on 2/14/76 (USDOE, 2015b). This analysis of the effects of ICUs on groundwater flow at PM addresses a need to evaluate uncertainty in the conceptual model or structural aspects of hydrologic source term (HST) or corrective action unit (CAU) models for groundwater flow and contaminant transport (FFACO, 1996, as amended). At Cheshire and possibly other test locations at PM, downgradient extent of radionuclide contamination may be overpredicted by not including the confining effects of ICUs. On the other hand, contaminant extent may be underpredicted by not considering transient flow effects and/or the re-equilibrated flow field caused by breaching of an ICU by an underground nuclear test. Near Cheshire, the effects of ICUs may be most apparent and impactful to the groundwater flow system at PM because of an unusual combination of thickness, extent, and frequency of dikes transecting the saturated CHLFA4 aquifer and feeding into the overlying unsaturated rhyolite lava of Windy Wash. Chapters 2, 3, and 4 present geological, geophysical, hydrogeological, and hydrological evidence for ICUs at PM. Chapters 5 and 6 examine effects of ICUs on groundwater flow including analysis by groundwater modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Robust trajectory-constrained frequency control for microgrids considering model linearization error

Grid supportive modes integrated within inverter-based resources can improve the frequency response of renewable-rich microgrids. The synthesis of grid supportive modes to guarantee frequency trajectory constraints under a predefined disturbance set is challenging but essential. To tackle this challenge, a numerical optimal control (NOC)-based control synthesis methodology is proposed. Without loss of generality, a wind-diesel fed microgrid is studied, where we aim to design grid supportive functions in the wind turbine. In the control design, linearized models are used, and the linearization-induced errors are quantitatively analyzed by reachability and interval arithmetics and represented in the form of interval uncertainties. Then, the NOC problem can be formulated into a robust mixed-integer linear program. The control structure is strategically configured into two levels to realize online deployment. The proposed control is verified on the modified 33-node microgrid with a full-order three-phase nonlinear model in Simulink. In conclusion, the simulation results show the effectiveness of the proposed control paradigm and the necessity of considering linearization-induced uncertainty.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Characterizing How Meteorological Forcing Selection and Parameter Uncertainty Influence Community Land Model Version 5 Hydrological Applications in the United States

Despite the increasing use of large-scale Land Surface Models (LSMs) in predicting hydrological responses in extreme conditions, there's a critical gap in understanding the uncertainties in these predictions. This study addresses this gap through a detailed diagnostic evaluation of the uncertainties arising from meteorological forcing selection and model parametrization in hydrological simulations of the Community Land Model version 5 (CLM5). CLM5 is configured at a spatial scale of about 12-km to simulate runoff processes for 464 headwater watersheds, selected from the Catchment Attributes for Large-Sample Studies (CAMELS) dataset to be representative of physiographic and climatic gradients across the conterminous United States. For each watershed, CLM5 is driven by five commonly used gridded forcing datasets in combination with a large ensemble (> 1200) of key CLM5 hydrologic parameters. Our results suggest that uncertainty in CLM5 runoff simulations resulting from both forcing and parametric sources is markedly higher in arid regions, e.g., Great Plains and Midwest regions. Uncertainty in low flow is dominated by parametric uncertainty, while the selection of meteorological forcing contributes more dominantly to high flow and seasonal flows during fall and spring. Our analysis also demonstrates that the selection of forcing datasets and the metrics used to calibrate CLM5 significantly impact the model’s predictive accuracy in extreme event severity for both floods and droughts. Overall, the results from this study highlight the need to understand and account for forcing and parametric uncertainties in CLM5 simulations, particularly for hazard and risk assessments addressing hydrologic extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Exploring HOD-dependent systematics for the DESI 2024 Full-Shape galaxy clustering analysis

We analyze the robustness of the DESI 2024 cosmological inference from the full shape of the galaxy power spectrum to uncertainties in the Halo Occupation Distribution (HOD) model of the galaxy-halo connection and the choice of priors on nuisance parameters. We assess variations in the recovered cosmological parameters across a range of mocks populated with different HOD models and find that shifts are often greater than 20% of the expected statistical uncertainties from the DESI data. We encapsulate the effect of such shifts in terms of a systematic covariance term, C HOD , and an additional diagonal contribution quantifying the impact of our choice of nuisance parameter priors on the ability of the effective field theory (EFT) model to correctly recover the cosmological parameters of the simulations. These two covariance contributions are designed to be added to the usual covariance term, C stat , describing the statistical uncertainty in the power spectrum measurement, in order to fairly represent these sources of systematic uncertainty. This novel approach should be more general and robust to the choice of model or additional external datasets used in cosmological fits than the alternative approach of adding systematic uncertainties to the recovered marginalised parameter posteriors. We compare the approaches within the context of a fixed ΛCDM model and demonstrate that our method gives conservative estimates of the systematic uncertainty that nevertheless have little impact on the final posteriors obtained from DESI data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Explainable Bayesian Neural Network for Probabilistic Transient Stability Analysis Considering Wind Energy

While several data-driven models have been developed for transient stability assessment, how to consider the uncertainties from load and renewable generations and provide interpretation of data-driven assessment results are still open. This paper proposes an explainable Bayesian Neural Network (BNN) for probabilistic transient stability assessment (TSA). By extracting the uncertainties from loads and wind farms, the BNN model can make a reliable prediction and quantify the prediction uncertainties. We also develop the Gradient Shap algorithm to make the global and local explanations for the probabilistic TSA model, a significant advantage over existing black-box data-driven methods. Numerical results on the modified IEEE 39-bus system show that the proposed method outperforms the existing methods in terms of prediction accuracy and uncertainty quantification capabilities. The explainability of the proposed method allows system operators to design preventive controls for enhancing system stability.

Bayesian Neural Network↗
DOE OSTI2020

The Southern Stellar Stream Spectroscopic Survey (S{sup 5}): Chemical Abundances of Seven Stellar Streams

We present high-resolution Magellan/MIKE spectroscopy of 42 red giant stars in seven stellar streams confirmed by the Southern Stellar Stream Spectroscopic Survey (S {sup 5}): ATLAS, Aliqa Uma, Chenab, Elqui, Indus, Jhelum, and Phoenix. Abundances of 30 elements have been derived from over 10,000 individual line measurements or upper limits using photometric stellar parameters and a standard LTE analysis. This is currently the most extensive set of element abundances for stars in stellar streams. Three streams (ATLAS, Aliqa Uma, and Phoenix) are disrupted metal-poor globular clusters, although only weak evidence is seen for the light-element anticorrelations commonly observed in globular clusters. Four streams (Chenab, Elqui, Indus, and Jhelum) are disrupted dwarf galaxies, and their stars display abundance signatures that suggest progenitors with stellar masses ranging from 10{sup 6} to 10{sup 7} M {sub ⊙}. Extensive description is provided for the analysis methods, including the derivation of a new method for including the effect of stellar parameter correlations on each star’s abundance and uncertainty. This paper includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Probabilistic Look-ahead Contingency Analysis Integration with Commercial Tool and Practical Data

This paper presents an initial effort of integrating a smart sampling-based probabilistic look-ahead contingency analysis algorithm with General Electric (GE) Grid Solutions’ commercial energy management system (EMS) tool as a proof-of-concept for a seamless research tool integration using real world large-scale grid data. With the increasing impact of random forces such as variable generation and load, their stochastic behaviors cannot be ignored. However, the current practices are still dominated by deterministic tools. They are becoming increasingly inadequate for the future grid. The developed look-ahead contingency analysis algorithm incorporates forecast errors of variable energy and load to address the challenges brought by the increasing uncertainty of power system. The algorithm can reveal the potential violations caused by the variance of variable energy and load that are not normally detected by traditional deterministic approaches. To test its performance under practical environments ( real data with real commercial tool), significant efforts have been made to prepare test cases, modify GE EMS tool, and adapt an extreme value distribution algorithm to analyze the GE EMS’s violation-only outputs. The test results clearly demonstrate the effectiveness of the developed algorithm as new transformer violations that were not previously detected have been identified. This performance provides better situational awareness to engineers for their decision-making process under uncertainty. Moreover, with the discussion of computational performance and future work, this paper has shown a clear path for integrating the probabilistic algorithm with commercial tools to make us better equipped for the changing power system.

Modeling and simulation of power systems, constrai↗
DOE OSTI2022

Uncertainty quantification in breakup reactions

Breakup reactions are one of the favored probes to study loosely bound nuclei, particularly those in the limit of stability forming a halo. In order to interpret such breakup experiments, the continuum discretized coupled channel method is typically used. In this study, the first Bayesian analysis of a breakup reaction model is performed. Herein we use a combination of statistical methods together with a three-body reaction model (the continuum discretized coupled channel method) to quantify the uncertainties on the breakup observables due to the parameters in the effective potential describing the loosely bound projectile of interest. The combination of tools we develop opens the path for a Bayesian analysis of not only breakup processes, but also a wide array of complex processes that require computationally intensive reaction models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

How do mirror charge radii constrain density dependence of the symmetry energy?

It has recently been suggested that differences in the charge radii of mirror nuclei (Δ$R^{mirr}_{ch}$) are strongly correlated with the neutron-skin thickness ($R_{skin}$) of neutron-rich nuclei and with the slope of the symmetry energy ($L$). To test this assumption, we present ab initio calculations of $R_{skin}$ in 48 Ca and 208 Pb, Δ$R^{mirr}_{ch}$ in 36 Ca$-$ 36 S, 38 Ca$-$ 38 Ar, 41 Sc$-$ 41 Ca, 48 Ni$-$ 48 Ca, 52 Ni$-$ 52 Cr, and 54 Ni$-$ 54 Fe mirror pairs, and $L$. Employing the recently developed 34 chiral interaction samples, identified by the history matching approach, we conduct rigorous statistical analysis of correlations among Δ$R^{mirr}_{ch}$, $R_{skin}$ and $L$, accounting for quantified uncertainties from low-energy constants of chiral interaction, chiral effective field theory truncation and many-body method approximation. The ab initio results reveal an appreciable Δ$R^{mirr}_{ch}$ $-$ $L$ correlation in $fp$-shell mirror pairs. However, contrary to previous studies, the present calculation finds that the studied $sd$-shell mirror pairs do not exhibit any Δ$R^{mirr}_{ch}$ $-$ $L$ correlation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Hybrid-Supported Bilayers Formed with Mixed-Charge Surfactants on C 18 -Functionalized Silica Surfaces

Mixtures of cationic-anionic surfactants have been demonstrated to spontaneously form ordered monolayers at hydrophobic-hydrophilic boundaries including air-water and oil-water interfaces. Here, confocal Raman microscopy is used to investigate the structure of hybrid-supported surfactant bilayers (HSSBs) formed by deposition of a distal leaflet of mixed cationic-anionic surfactants onto a proximal leaflet of n-alkane (C 18 ) chains on the interior surfaces of chromatographic silica particles. The surface coverage of the two surfactants in a hybrid bilayer was determined from carbon analysis and the relative Raman scattering of their respective head-groups. Within the measurement uncertainty, the stoichiometric ratio of the two surfactants is one-to-one, equivalent to mixed-charge-surfactant monolayers at air-water and oil-water interfaces and consistent with the role of the head-group electrostatic interactions in their formation. When self-assembled on the hydrophobic surface, pairs of oppositely-charged n-alkyl-chain surfactants resemble a phospholipid (phosphati¬dylcholine) molecule, with its zwitterionic head group and two hydrophobic acyl-chain tails. Indeed, the structure of these hybrid-supported surfactant bilayers on C 18 -modified silica surfaces is similar to that of hybrid-supported lipid bilayers (HSLBs) on the same supports, but with denser and more-ordered n-alkyl chains. Hybrid-supported surfactant bilayers exhibit a melting phase transition (gel to liquid-crystalline phase) with structural and energetic characteristics similar to hybrid-supported bilayers prepared from a zwitterionic phospholipid of the same alkyl chain length. These mixed-charge surfactants on n-alkane modified silica are stable in water over time (months), results that suggest the potential use of these hybrid bilayers for generating supported lipid bilayer-like surfaces or for separation applications.

36 MATERIALS SCIENCE↗