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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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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Double-differential Measurements of Mesonless Charged-current Muon Neutrino Interactions on Argon with Final-State Protons using the MicroBooNE Detector

This note reports the first double-differential measurements of charged-current $ν_µ$ scattering on argon leading to final states containing zero mesons and one or more protons. This event topology (hereafter abbreviated as CC0$πNp$) is the most common at the neutrino energies typically produced by the Fermilab Booster Neutrino Beam. A detailed understanding of neutrino-argon scattering in the CC0$πNp$ channel is therefore crucial for the success of the precision neutrino oscillation analyses planned for the Short-Baseline Neutrino (SBN) program. This remains true for the upcoming Deep Underground Neutrino Experiment (DUNE), but the higher mean neutrino energy used there will ensure that more inelastic reaction modes, such as single pion production, will also play a major role. The analysis described in this note builds on a previous MicroBooNE study of the CC0$πNp$ channel which obtained the first single-differential cross-section measurements on an argon target. Since that foundational work, significant improvements have been made to MicroBooNE’s simulation software, event reconstruction algorithms, and procedure for calculating systematic uncertainties. When combined with a larger dataset (corresponding to a beam exposure of 6.79 × 10 20 protons-on-target versus 1.60 × 10 20 in Ref. [3]), these enhancements allow the important CC0$πNp$ channel to be studied in more detail. This note begins with a description of the data and simulation samples used as input to the analysis. Section 3 then defines the CC0$πNp$ signal event topology, and Section 4 describes a set of selection criteria designed to identify these events in MicroBooNE data. Binning schemes are then defined in Section 5 for two double-differential measurements of event rates. The first of these considers the momentum and scattering cosine of the outgoing muon, while the second reports the same observables for the leading proton, i.e., the final-state proton with the largest momentum. After a discussion of systematic uncertainties in Section 6, the note concludes by comparing the predictions of MicroBooNE Monte Carlo (MC) simulations to the measured double-differential distributions. These results will form the basis for a future extraction of flux-averaged double-differential CC0$πNp$ cross sections that will be immediately comparable to the theoretical predictions of multiple neutrino event generators. The selection described herein may also be used to study various other observables in CC0$πNp$ events, including those which are sensitive to correlations between leptonic and hadronic kinematics in the final state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

NEAMS-Multiphysics MOOSE End Year Framework Activities FY20

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a general finite element package meant for high performance solution of multiphysics problems in science and engineering. In this report, we present additions and enhancements to MOOSE funded by the Nuclear Engineering Advanced Modeling and Simulation (NEAMS) program. NEAMS-funded MOOSE framework library improvements include: expansion of support for multi-level multi-application restart; enhancement of coupling between native MOOSE applications and external libraries; addition of a sparse automatic differentiation (AD) container enabling non-local degree of freedom coupling; block-specific quadrature rules; further development of an eigenvalue executioner; faster setup of periodic boundary conditions; and creation of a mesh meta-data system streamlining simulation startup. Besides developing the framework library, NEAMS funds were used to overhaul a swath of important MOOSE infrastructure in order to substantially improve user experience. These critical infrastructure changes included adapting MOOSE to python 3, improving the test harness to catch race conditions, and most importantly transitioning MOOSE to use Conda, a globally known packaging system, that greatly eases software adoption.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Inclusive Charged-Current Electron Neutrino Interactions in SBND

The Short-Baseline Near Detector (SBND), a 112 ton liquid argon time projection chamber (LArTPC), is the near detector of the Short- Baseline Neutrino Program at Fermilab. Due to its proximity to the Booster Neutrino Beam target, SBND has already seen a record-breaking number of electron neutrino interactions on argon. We present preliminary results from SBND’s differential inclusive electron neutrino charged-current analysis from our first year of beam data, selecting over 2,000 interactions. This analysis will present the largest sample of electron neutrinos on argon to date, as well as the first differential cross section measurement of electron neutrinos. This poster will give an overview of the selection, cross-section extraction, and demonstrate SBND’s detector and electromagnetic shower reconstruction performance through data/MC comparisons.

Tung, Lynn [Chicago U.]↗
DOE OSTI2020

Nanometer-Scale Correlations in Aqueous Salt Solutions

The intermediate-range (1–4 nm) correlation of cations, an- ions, and water in aqueous alkaline earth salt solutions is measured using synchrotron X-ray diffraction. We differentiate from the entire solution structure factor, S(Q), a separate region at low Q (<1 °A-1) containing local diffraction maxima (pre-peaks) that indicate nanometer-scale oscillatory behavior. These features are quantitatively reproduced with classical molecular dynamics simulations. At high concentrations, the pre-peaks emerge from correlations arising from existence of small quasi close-packed lattice- like structures comprised of cation hydration spheres. We also analyze the concentration dependence of the pre-peak and discuss the overall results in light of the rich literature dealing with intermediate-range correlations underlying universal phenomena in concentrated electrolytes. The authors were supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences. Pacific Northwest National Laboratory (PNNL) is operated by Battelle for the U.S. Department of Energy under Contract No. DE-AC05-76RL01830. Computing resources were generously allocated by PNNL's Institutional Computing program. DOE Contract No. DEAC02- 06CH11357 supports operation of the Advanced Photon Source at Argonne National Laboratory.

Chemical physics, nucleation, Madelung potential↗
DOE OSTI2024

Deconvoluting XPS Spectra of La-Containing Perovskites from First-Principles

Perovskite-based oxides are used in electrochemical CO 2 and H 2 O reduction in electrochemical cells due to their compositional versatility, redox properties and stability. However limited knowledge exists on the mechanisms driving these processes. Toward this understanding, herein we probe the core level binding energy shifts of water-derived adspecies (H, O, OH, H 2 O) as well as the adsorption of CO 2 on LaCoO 3 and LaNiO 3 and we correlate the simulated peaks with experimental Temperature Programmed X-ray Photoelectron Spectroscopy (TPXPS) results. We find the strong adsorption of such chemical species can affect the antiferromagnetic ordering of LaNiO 3 . The adsorption of such adspecies is further quantified through Bader and differential charge analyses. We find the higher O 1s core level binding energy peak for both LaCoO 3 and LaNiO 3 corresponds to adsorption of water-related species and CO 2 , while the lower energy peak is due to lattice oxygen. We further correlate these DFT-based core level O 1s binding energies with the TPXPS measurements to quantify the decrease of the O 1s contribution due to desorption of adsorbates and the apparent increase of the lattice oxygen (both bulk and surface) with temperature. Finally, we quantify the influence of adsorbates on the La 4d, Co 2p and the Ni 3p core level binding energy shifts. This work demonstrates how theoretically generated XPS data can be utilized to predict species-specific binding energy shifts to assist in the deconvolution of the experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Convex relaxation for Fokker–Planck equation

We propose an approach to directly estimate the moments or marginals for a high-dimensional equilibrium distribution in statistical mechanics by solving the high-dimensional Fokker–Planck equation in terms of low-order cluster moments or marginals. With this approach, we bypass the exponential complexity of estimating the full high-dimensional distribution and directly solve the simplified partial differential equations for low-order moments/marginals. Moreover, the proposed moment/marginal relaxation is fully convex and can be solved via off-the-shelf solvers. We further propose a time-dependent version of the convex programs to study non-equilibrium dynamics. In a specific setting, we show the proposed method can recover a mean-field-type equilibrium density. Numerical results are provided to demonstrate the performance of the proposed algorithm for high-dimensional systems.

Chen, Yian↗
DOE OSTI2020

New high statistics results from the MINERvA experiment Medium Energy run

The MINERvA experiment has completed its physics run using the 6 GeV, on-axis NuMI ME beam at Fermilab. The experiment received a total of 12 x 10^20 protons on target in both neutrino and antineutrino mode running. This allows MINERvA a new level of statistics in neutrino interaction measurements with the ability to measure multi-dimensional differential cross sections. In addition, in order to make the most of this jump in statistics, a new level of precision in fluxprediction has been achieved. We present results from MINERvA's Medium Energy (ME) physics program, including the new kinematic regimes that are now accessible.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

A Two-Stage Decomposition Approach for AC Optimal Power Flow

The alternating current optimal power flow (AC-OPF) problem is critical to power system operations and planning, but it is generally hard to solve due to its nonconvex and large-scale nature. Furthermore, this paper proposes a scalable decomposition approach in which the power network is decomposed into a master network and a number of subnetworks, where each network has its own AC-OPF subproblem. This formulates a two-stage optimization problem and requires only a small amount of communication between the master and subnetworks. The key contribution is a smoothing technique that renders the response of a subnetwork differentiable with respect to the input from the master problem, utilizing properties of the barrier problem formulation that naturally arises when subproblems are solved by a primal-dual interior-point algorithm. Consequently, existing efficient nonlinear programming solvers can be used for both the master problem and the subproblems. The advantage of this framework is that speedup can be obtained by processing the subnetworks in parallel, and it has convergence guarantees under reasonable assumptions. The formulation is readily extended to instances with stochastic subnetwork loads. Numerical results show favorable performance and illustrate the scalability of the algorithm which is able to solve instances with more than 11 million buses.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Quantum Computing Strategy 2026

Quantum computing (QC) is a rapidly maturing technology with the potential for revolutionary impacts on stockpile stewardship science and national security. Recent developments in fault-tolerant architectures have compressed vendor roadmaps, and predictions of a production-ready quantum computer by the mid-2030s are becoming increasingly credible. This strategy provides a roadmap for integrating QC into the Advanced Simulation and Computing (ASC) program by investing in four strategic focus areas: 1. Develop Capabilities in Mission-Relevant Quantum Applications: ASC will prioritize developing quantum-ready applications in mission areas that have shown significant promise for quantum advantage, including simulations of materials in extreme environments, nuclear dynamics, solving linear and nonlinear partial differential equations, and uncertainty quantification. These applications directly support stockpile stewardship science and modernization objectives. 2. Conduct R&D in Algorithms, Software, and Hardware: Sustained research into quantum algorithms, robust software tools, and quantum hardware is essential. ASC will develop efficient quantum algorithms; invest in quantum compilers, debuggers, and performance tools; and explore specialized quantum hardware tailored to NNSA’s unique requirements. 3. Engage with Vendors and Partners: Early and active collaboration with commercial quantum hardware vendors and academic partners is critical. Through testbeds, co-design agreements, and quantum demonstration facilities, ASC will influence hardware design, gain early access to emerging technologies, and ensure that quantum platforms evolve to meet mission needs. 4. Build Knowledge, Experience, and Workforce: Expanding and upskilling the quantum-trained workforce is essential to long-term success. This includes hiring, internal training, university outreach, and postdoctoral support to ensure ASC maintains the expertise required to operate, program, and integrate quantum systems as they become available. While quantum computing will never replace classical computing, it has the potential to solve certain problems with speed and accuracy that would be unachievable using any conceivable classical high-performance computing (HPC) system. By investing strategically in QC, ASC will help propel the emergent QC industry, maintain U.S. technological leadership, ensure mission readiness, and position itself to rapidly adopt quantum technologies as they mature.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Impact of Higher Fidelity Design Iterations on Critical System Criteria

Nuclear criticality experiments are effective at informing the performance of nuclear data libraries across many applications. This work explores the implications of refining critical experiment MCNP models from their low fidelity optimization phase to penultimate neutronic models. Specifically, this work is focused on two series of plutonium fueled experiments funded through internal programs at Los Alamos National Laboratory building off previous efforts under the EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) collaboration. Thales, the first of the two collaborations, is a fast spectrum Ta-reflected plutonium experiment to support operations at PF-4. The second experiment are twin configurations designed to target the intermediate energy cross sections in 239 Pu. Motivation for this experiment stems from the PARallel Approach of Differential and InteGral Measurements (PARADIGM) collaboration which hopes to achieve a significant reduction in 239 Pu cross section uncertainties in the intermediate region.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Pyomo.DOE: An open-source package for model-based design of experiments in Python

Predictive mathematical models are a cornerstone of science and engineering. Yet selecting, calibrating, and validating said science-based models often remains an art in practice. Model-based design of experiments (MBDoE) provides a systematic framework to maximize information gain from experiments while minimizing time and resource costs. But MBDoE remains limited to niche application areas, in part because practitioners must integrate expertise in statistics, computational optimization, and modeling. To help reduce this barrier, we introduce Pyomo.DOE, an open-source package for MBDoE. Pyomo.DOE uses a nonlinear sensitivity analysis code k_aug to quickly approximate the Fisher information matrix and leverages a new stochastic programming abstraction. We demonstrate Pyomo.DOE with the first application of MBDoE to fixed-bed breakthrough experiments, which highlights the power of Pyomo.DOE to quantify the value of experimental modifications a priori for large-scale partial differential-algebraic equation (PDAE) models. Here we also provide a mathematical primer on MBDoE targeted at general chemical engineers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

CO2 Sorption in Ionic Liquid Crystals

Ionic liquid crystals (ILCs) have an affinity for certain polarizable gases such as CO2, due to their similarity to ionic liquids. We investigated three ILCs in the [1-alkyl-3-methylimidazolium+] family: n=12,14 with [BF4-] and [PF6-]: liquid crystalline analogues to ionic liquids with moderate (e.g., 1-2 mol%) CO2 solubility at atmospheric conditions: [1-butyl-3-methylimidazolium+] with [BF4-] and [PF6-]. While ionic liquids show high CO2 solubility, regenerating the CO2 is a high-energy process. Liquid crystals show low CO2 solubility but have a much lower regeneration energy requirement. Will ionic liquid crystals uptake CO2? What are the energy requirements of regenerating CO2? Conclusions: 1. C12mim BF4- shows the highest sorption at 0.12 wt% CO2 in the isotropic phase vs. C14mim BF4- with 0.097 wt% in the smectic phase. We hypothesize that the increase in chain length affects the free volume of the smectic vs. isotropic phase of C14mim BF4-, increasing the latter. 2. The change in anion from BF4- to PF6- decreased the sorption to an insignificant level more analogous to a physical adsorption onto the material in all phases. We hypothesize that the change in anion to the larger, less charge dense PF6- decreased the attractive forces between CO2 and the anion. 3. 0.12 wt% of CO2 in C12mim BF4- is small but significant. This in combination with the room temperature release of CO2 after only requiring refrigeration temperatures to occlude the CO2, making ionic liquid crystals promising materials for future.

carbon dioxide sorption↗
DOE OSTI2021

Model-based and Model-free Designs for an Extended Continuous-time LQR with Exogenous Inputs

We present an extended linear quadratic regulator (LQR) design for continuous-time linear time-invariant (LTI) systems in the presence of exogenous inputs. We first propose a model-based solution with cost minimization guarantees for states and inputs using dynamic programming (DP). The control law consists of a combination of the optimal state feedback and an additional optimal term dependent on the exogenous inputs. The control gains for the two components are obtained by solving a set of matrix differential equations. We provide these solutions for both finite horizons and steady-state cases. In the second part of the paper, we formulate a reinforcement learning (RL) based algorithm which does not need any model information except the input matrix, and can compute an approximate steady-state LQR gain using measurements of the states, the control inputs, and the exogenous inputs. Both model-based and data-driven optimal control algorithms are tested with a numerical example under different exogenous inputs showcasing the effectiveness of the designs.

Mukherjee, Sayak↗
DOE OSTI2022

dfdjaxGP

A small python package to fit Gaussian processes using Jax and leveraging the automatic differentiation in Jax to predict arbitrary derivatives from the GP. This package is meant to supplement the scientific community use of Gaussian process prediction with derivatives. The package is designed to smoothly work standalone or be used with the numpyro probabilistic programming language.

Grosskopf, Micheal↗
DOE OSTI2022

On the Convergence of Overlapping Schwarz Decomposition for Nonlinear Optimal Control

Here, we study the convergence properties of an overlapping Schwarz decomposition algorithm for solving nonlinear optimal control problems (OCPs). The algorithm decomposes the time domain into a set of overlapping subdomains, and solves all subproblems defined over subdomains in parallel. The convergence is attained by updating primal-dual information at the boundaries of overlapping subdomains. We show that the algorithm exhibits local linear convergence, and that the convergence rate improves exponentially with the overlap size. We also establish global convergence results for a general quadratic programming, which enables the application of the Schwarz scheme inside second-order optimization algorithms (e.g., sequential quadratic programming). The theoretical foundation of our convergence analysis is a sensitivity result of nonlinear OCPs, which we call "exponential decay of sensitivity" (EDS). Intuitively, EDS states that the impact of perturbations at domain boundaries (i.e., initial and terminal time) on the solution decays exponentially as one moves into the domain. Here, we expand a previous analysis available in the literature by showing that EDS holds for both primal and dual solutions of nonlinear OCPs, under uniform second-order sufficient condition, controllability condition, and boundedness condition. We conduct experiments with a quadrotor motion planning problem and a partial differential equations (PDE) control problem to validate our theory, and show that the approach is significantly more efficient than alternating direction method of multipliers and as efficient as the centralized interior-point solver.

42 ENGINEERING↗
DOE OSTI2021

Dual-Salt Electrolytes to Effectively Reduce Impedance Rise of High-Nickel Lithium-Ion Batteries

Simply mixing several lithium salts in one electrolyte to obtain blended salt electrolytes has been demonstrated as a promising strategy to formulate advanced electrolytes for lithium metal batteries (LMBs) and lithium-ion batteries (LIBs). In this study, we report the use of dual-salt electrolytes containing lithium hexafluorophosphate (LiPF6) and lithium difluorophosphate (LiDFP) in ethylene carbonate/ethyl methyl carbonate (EC/EMC) mixture and tested them in layered high-nickel LIB cells. LiNi 0.94 Co 0.06 O 2 was synthesized through a coprecipitation method and was used as a representative high-nickel cathode for the U.S. DOE realizing next-generation cathode (RNGC) deep dive program. The ionic conductivity of dual-salt electrolytes can be maintained by controlling the amount of LiDFP. Techniques including 1 H Nuclear Magnetic Resonance (NMR), X-ray photoelectron spectroscopy (XPS), inductively coupled plasma-mass spectrometry (ICP-MS), and differential voltage analysis (DVA) were used to understand the improved performance. Additionally, the multifaceted benefits of using the dual-salt electrolytes include (1) reduced transesterification, (2) formation of a stable cathode electrolyte interface, and (3) mitigation of cathode degradation at high voltages, especially stabilization of oxide particles during the H 2 <-> H 3 transformation.

25 ENERGY STORAGE↗
DOE OSTI2022

Random field optimization

Herein we present a new modeling paradigm for optimization that we call random field optimization. Random fields are a powerful modeling abstraction that aims to capture the behavior of random variables that live on infinite-dimensional spaces (e.g., space and time) such as stochastic processes (e.g., time series, Gaussian processes, and Markov processes), random matrices, and random spatial fields. This paradigm involves sophisticated mathematical objects (e.g., stochastic differential equations and space-time kernel functions) and has been widely used in neuroscience, geoscience, physics, civil engineering, and computer graphics. Despite of this, however, random fields have seen limited use in optimization; specifically, existing optimization paradigms that involve uncertainty (e.g., stochastic programming and robust optimization) mostly focus on the use of finite random variables. This trend is rapidly changing with the advent of statistical optimization (e.g., Bayesian optimization) and multi-scale optimization (e.g., integration of molecular sciences and process engineering). Our work extends a recently-proposed abstraction for infinite-dimensional optimization problems by capturing more general uncertainty representations. Moreover, we discuss solution paradigms for this new class of problems based on finite transformations and sampling, and identify open questions and challenges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

First Principles Nonadiabatic Excited-State Molecular Dynamics in NWChem

Computational simulation of non-adiabatic molecular dynamics is an indispensable tool for understanding complex photoinduced processes such as internal conversion, energy transfer, charge separation, and spatial localization of excitons, to name a few. Here, we report an implementation of the fewest-switches surface hopping algorithm in the NWChem computational chemistry program. Here the surface hopping method is combined with linear-response time-dependent density functional theory calculations of adiabatic excited state potential energy surfaces. To treat quantum transitions between arbitrary electronic Born{Oppenheimer states, we have implemented both numerical and analytical differentiation schemes for derivative non-adiabatic couplings. A numerical approach for the time-derivative non-adiabatic couplings together with an analytical method for calculating non-adiabatic coupling vectors is an efficient combination for surface hopping approaches. Additionally, electronic decoherence schemes and a state reassigned unavoided crossings algorithm are also implemented to improve the accuracy of the simulated dynamics and to handle trivial unavoided crossings. We apply our code to study the ultrafast decay of photoexcited benzene, including a detailed analysis of the potential energy surface, population decay time scales, and vibrational coordinates coupled to the excitation dynamics. The development presented in this work is a baseline for future implementations of more sophisticated frameworks for simulating of non-adiabatic molecular dynamics in NWChem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗