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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Applying Quantum Computing to Simulate Power System Dynamics

Power system dynamics are generally modeled by high dimensional nonlinear differential-algebraic equations due to a large number of generators, loads, and transmission lines. Thus, its computational complexity grows exponentially with the system size. This paper demonstrates the potential use of quantum computing algorithms to model the power system dynamics. Leveraging a symbolic programming framework, we equivalently convert the power system dynamics’ differential algebraic equations (DAEs) into ordinary differential equations (ODEs), where the data of the state vector can be encoded into quantum computers via amplitude encoding. The system's nonlinearity is captured by Taylor polynomial expansion, the quantum state tensor, and Hamiltonian simulation, whereas state variables can be updated by a quantum linear equation solver. Our results show that quantum computing can simulate the dynamics of the power system with high accuracy, whereas its complexity is polynomial in the logarithm of the system dimension. Our work also illustrates the use of scientific machine learning tools for implementing scientific computing concepts, e.g., Taylor expansion, DAEs/ODEs transform, and quantum computing solver, in the field of power engineering.

Tran, Huynh↗
DOE OSTI2021

Mixed Precision Fermi-Operator Expansion on Tensor Cores from a Machine Learning Perspective

Here we present a second-order recursive Fermi-operator expansion scheme using mixed precision floating point operations to perform electronic structure calculations using tensor core units. A performance of over 100 teraFLOPs is achieved for half-precision floating point operations on Nvidia’s A100 tensor core units. The second-order recursive Fermi-operator scheme is formulated in terms of a generalized, differentiable deep neural network structure, which solves the quantum mechanical electronic structure problem. We demonstrate how this network can be accelerated by optimizing the weight and bias values to substantially reduce the number of layers required for convergence. We also show how this machine learning approach can be used to optimize the coefficients of the recursive Fermi-operator expansion to accurately represent the fractional occupation numbers of the electronic states at finite temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Quantum algorithm for the linear Vlasov equation with collisions

The Vlasov equation is a nonlinear partial differential equation that provides a first-principles description of the dynamics of plasmas. Its linear limit is routinely used in plasma physics to investigate plasma oscillations and stability. In this paper, we present a quantum algorithm that simulates the linearized Vlasov equation with and without collisions, in the one-dimensional electrostatic limit. Rather than solving this equation in its native spatial and velocity phase space, we adopt an efficient representation in the dual space yielded by a Fourier-Hermite expansion. For a given simulation time, the Fourier-Hermite representation is exponentially more compact, thus yielding a classical algorithm that can match the performance of a previously proposed quantum algorithm for this problem. Further, this representation results in a system of linear ordinary differential equations (ODEs) which can be solved with well-developed quantum algorithms: a Hamiltonian simulation in the collisionless case, and quantum ODE solvers in the collisional case. In particular, we demonstrate that a quadratic speedup in system size is attainable.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Thermophysical properties of high-density, sintered monoliths of yttrium dihydride in the range 373–773 K

Yttrium dihydride is a promising nuclear reactor moderator for high-temperature, thermal micro-reactors due to its ability to retain hydrogen to high temperatures while having a relatively low impact on neutron economy. However, it is difficult to fabricate yttrium dihydride in high-density, near net-shape monoliths for moderator applications due to challenges associated with the hydrogen absorption process. Here, high-density monoliths of yttrium dihydride were prepared by powder metallurgical methods. The lattice strain and thermal expansion coefficient were measured using neutron diffraction of powders of directly-hydrided yttrium, while the molar heat capacity and thermal diffusivity of sintered yttrium dihydride were measured using differential scanning calorimetry (DSC) and laser flash analysis (LFA), respectively. The molar heat capacity of yttrium dihydride was also calculated using density functional theory (DFT) for comparison. These parameters were used to then calculate the thermal conductivity and resistivity of yttrium dihydride as a function of temperature. The thermophysical properties of materials produced by both methods were observed to be consistent with the values from literature for yttrium dihydride. Due to the novelty of producing yttrium dihydride by powder metallurgical methods, this result indicated that the sintered monoliths were of high quality and that powder metallurgy is a viable method for large-scale production of yttrium dihydride monoliths for nuclear reactor moderator applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Solving differential‐algebraic equations in power system dynamic analysis with quantum computing

Abstract Power system dynamics are generally modeled by high dimensional non‐linear differential‐algebraic equations (DAEs) given a large number of components forming the network. These DAEs' complexity can grow exponentially due to the increasing penetration of distributed energy resources, whereas their computation time becomes sensitive due to the increasing interconnection of the power grid with other energy systems. This paper demonstrates the use of quantum computing algorithms to solve DAEs for power system dynamic analysis. We leverage a symbolic programming framework to equivalently convert the power system's DAEs into ordinary differential equations (ODEs) using index reduction methods and then encode their data into qubits using amplitude encoding. The system non‐linearity is captured by Hamiltonian simulation with truncated Taylor expansion so that state variables can be updated by a quantum linear equation solver. Our results show that quantum computing can solve the power system's DAEs accurately with a computational complexity polynomial in the logarithm of the system dimension. We also illustrate the use of recent advanced tools in scientific machine learning for implementing complex computing concepts, that is, Taylor expansion, DAEs/ODEs transformation, and quantum computing solver with abstract representation for power engineering applications.

computational complexity↗
DOE OSTI2026

Hierarchical Gaussian Random Field Sampling for Multilevel Markov Chain Monte Carlo: Coupling Stochastic Partial Differential Equation and the Karhunen–Loève Decomposition

This work introduces structure preserving hierarchical decompositions for sampling Gaussian random fields (GRFs) within the context of multilevel Bayesian inference in high-dimensional space. Existing scalable hierarchical sampling methods, such as those based on stochastic partial differential equations (SPDEs), often reduce the dimensionality of the sample space at the cost of accuracy of inference. Other approaches, such that those based on Karhunen-Loève (KL) expansions, offer sample space dimensionality reduction but sacrifice GRF representation accuracy and ergodicity of the Markov chain Monte Carlo (MCMC) sampler and are computationally expensive for high-dimensional problems. The proposed method integrates the dimensionality reduction capabilities of KL expansions with the scalability of SPDE-based sampling, thereby providing a robust, unified framework for high-dimensional uncertainty quantification (UQ) that is scalable and accurate, preserves ergodicity, and offers dimensionality reduction of the sample space. The hierarchy in our multilevel algorithm is derived from the geometric multigrid hierarchy. By constructing a hierarchical decomposition that maintains the covariance structure across the levels in the hierarchy, the approach enables efficient coarse-to-fine sampling while ensuring that all samples are drawn from the desired distribution. The effectiveness of the proposed method is demonstrated on a benchmark subsurface flow problem, demonstrating its effectiveness in improving computational efficiency and statistical accuracy. Furthermore, our proposed technique is more efficient and accurate and displays better convergence properties than existing methods for high-dimensional Bayesian inference problems.

Gaussian random fields↗
DOE OSTI2024

cppTPSA/pyTPSA: a C++/Python package for truncated power series algebra

The truncated power series algebra (TPSA), also referred to as differential algebra (DA), is a well-established and widely used method in particle accelerator physics and astronomy. The most straightforward usage of TPSA/DA is to calculate the Taylor expansion of a given function at a specific point up to order ?. In recent years, as the application of TPSA/TA has been extended to other fields, a reusable implementation of TPSA/DA as a modern C++ library or other high level programming language like Python has become desirable. The cppTPSA package implements TPSA/DA in C++11 and provides developers a convenient library with which to build advanced TPSA/DA-based methods. A Python 3 library, pyTPSA, has also been developed based on the C++ lib.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Strong coupling expansion of free energy and BPS Wilson loop in $$ \mathcal{N} $$ = 2 superconformal models with fundamental hypermultiplets

As a continuation of the study (in arXiv:2102.07696 and arXiv:2104.12625 ) of strong-coupling expansion of non-planar corrections in \( \mathcal{N} \) = 2 4d superconformal models we consider two special theories with gauge groups SU( N ) and Sp(2 N ). They contain N -independent numbers of hypermultiplets in rank 2 antisymmetric and fundamental representations and are planar-equivalent to the corresponding \( \mathcal{N} \) = 4 SYM theories. These \( \mathcal{N} \) = 2 theories can be realised on a system of N D3-branes with a finite number of D7-branes and O7-plane; the dual string theories should be particular orientifolds of AdS 5 × S 5 superstring. Starting with the localization matrix model representation for the \( \mathcal{N} \) = 2 partition function on S 4 we find exact differential relations between the 1 /N terms in the corresponding free energy F and the \( \frac{1}{2} \) -BPS Wilson loop expectation value \( \left\langle \mathcal{W}\right\rangle \) and also compute their large ’t Hooft coupling ( λ » 1) expansions. The structure of these expansions is different from the previously studied models without fundamental hypermultiplets. In the more tractable Sp(2 N ) case we find an exact resummed expression for the leading strong coupling terms at each order in the 1 /N expansion. We also determine the exponentially suppressed at large λ contributions to the non-planar corrections to F and \( \left\langle \mathcal{W}\right\rangle \) and comment on their resurgence properties. We discuss dual string theory interpretation of these strong coupling expansions.

1/N expansion↗
DOE OSTI2024

Variational inference of effective range parameters for 3 He− 4 He scattering

We use two different methods, Monte Carlo sampling and variational inference (VI), to perform a Bayesian calibration of the effective-range parameters in 3 He– 4 He elastic scattering. The parameters are calibrated to data from a recent set of 3 He– 4 He elastic scattering differential cross section measurements. Analysis of these data for E lab ≤ 4.3 MeV yields a unimodal posterior for which both methods obtain the same structure. However, the effective-range expansion amplitude does not account for the 7/2 − state of 7 Be so, even after calibration, the description of data at the upper end of this energy range is poor. The data up to E lab = 2.6 MeV can be well described, but calibration to this lower-energy subset of the data yields a bimodal posterior. After adapting VI to treat such a multi-modal posterior we find good agreement between the VI results and those obtained with parallel-tempered Monte Carlo sampling.

effective field theory↗
DOE OSTI2019

Structural Health Monitoring of Epoxy Bond between Dissimilar Materials

Structures composed of adhesively bonded materials face many challenges when subjected to thermal loading, as adherend material(s) behave differently and can induce stresses in the glue bond. Current methods to test bond strength are limited to destructive tests, which increase costs to produce adhesively bonded structures. Strain gages are proposed to monitor the expansion profile of adhesive bonds as structures undergo thermal loading. Because resulting signals are DC in nature, no spectral quantities can be observed. Principle component analysis (PCA) is proposed to differentiate between damaged and undamaged structures. Training data are taken for various damage states and the minimum Mahalanobis distance is calculated to categorize testing data into damage state. The results indicate the potential for a strain-gage based monitoring system with PCA based decision-making, with further research necessary prior to implementation of the system.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Variations to the z-Expansion of the Form Factor Describing the Decay of B Mesons

We examine the decay rate of the particle decay B 0 → D -ℓ +νℓ using data collected from the Belle Collaboration. We studied three parameterizations of the form factor which describe the differential decay rate, the Caprini, Lellouch, and Neubert (CLN) parametrization, the Boyd, Grinstein, and Lebed (BGL) parametrization, and the Bourrely, Caprini, and Lellouch (BCL) parameterization. The form factor is a function of the hadronic recoil variable w, and each parameterization contains unique free parameters which are the focus of this work. We test the extrapolations of the form factor by fitting many different subsets of the low w data and then compare the prediction of the fit to the high w data using a χ 2 -metric. By only fitting the low w data we are able to examine the stability of extrapolations which will be informative for lattice simulations.

Simons, Daniel↗
DOE OSTI2025

The chromatin remodeler ADNP regulates neurodevelopmental disorder risk genes and neocortical neurogenesis

Although chromatin remodelers are among the most important risk genes associated with neurodevelopmental disorders (NDDs), the roles of these complexes during brain development are in many cases unclear. Here, we focused on the recently discovered ChAHP chromatin remodeling complex. The zinc finger and homeodomain transcription factor ADNP is a core subunit of this complex, and de novoADNPmutations lead to intellectual disability and autism spectrum disorder. However, germlineAdnpknockout mice were previously shown to exhibit early embryonic lethality, obscuring subsequent roles for the ChAHP complex in neurogenesis. To circumvent this early developmental arrest, we generated a conditionalAdnpmutant allele. Using single-cell transcriptomics, cut&run-seq, and histological approaches, we show that during neocortical development, Adnp orchestrates the production of late-born, upper-layer neurons through a two-step process. First, Adnp is required to sustain progenitor proliferation specifically during the developmental window for upper-layer cortical neurogenesis. Accordingly, we found that Adnp recruits the ChAHP subunit Chd4 to genes associated with progenitor proliferation. Second, in postmitotic differentiated neurons, we define a network of risk genes linked to NDDs that are regulated by Adnp and Chd4. Taken together, these data demonstrate that ChAHP is critical for driving the expansion of upper-layer cortical neurons and for regulating neuronal gene expression programs, suggesting that these processes may potentially contribute to NDD etiology.

Science & Technology - Other Topics↗
DOE OSTI2022

The Land–Sea Connection: Insights Into the Plant Lineage from a Green Algal Perspective

The colonization of land by plants generated opportunities for the rise of new heterotrophic life forms, including humankind. A unique event underpinned this massive change to earth ecosystems—the advent of eukaryotic green algae. Today, an abundant marine green algal group, the prasinophytes, alongside prasinodermophytes and nonmarine chlorophyte algae, is facilitating insights into plant developments. Genome-level data allow identification of conserved proteins and protein families with extensive modifications, losses, or gains and expansion patterns that connect to niche specialization and diversification. Here, we contextualize attributes according to Viridiplantae evolutionary relationships, starting with orthologous protein families, and then focusing on key elements with marked differentiation, resulting in patchy distributions across green algae and plants. We place attention on peptidoglycan biosynthesis, important for plastid division and walls; phytochrome photosensors that are master regulators in plants; and carbohydrate-active enzymes, essential to all manner of carbohydratebiotransformations. Together with advances in algal model systems, these areas are ripe for discovering molecular roles and innovations within and across plant and algal lineages.

Plant Sciences↗
DOE OSTI2020

Construction of quasisymmetric stellarators using a direct coordinate approach

In this work, optimized stellarator configurations and their analytical properties are obtained using a near-axis expansion approach. Such configurations are associated with good confinement as the guiding center particle trajectories and neoclassical transport are isomorphic to those in a tokamak. This makes them appealing as fusion reactor candidates. Using a direct coordinate approach, where the magnetic field and flux surface functions are found explicitly in terms of the position vector at successive orders in the distance to the axis, the set of ordinary differential equations for first and second order quasisymmetry is derived. Examples of quasi-axisymmetric shapes are constructed using a pseudospectral numerical method. Finally, the direct coordinate approach is used to independently verify two hypotheses commonly associated with quasisymmetric magnetic fields, namely that the number of equations exceeds the number of parameters at third order in the expansion and that the near-axis expansion does not prohibit exact quasisymmetry from being achieved on a single flux surface.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Impact of three-body forces on elastic nucleon-nucleus scattering observables

In a previous series of papers we investigated the domain of applicability of chiral potentials to the construction of a microscopic optical potential (OP) for elastic nucleon-nucleus scattering. The OP was derived at the first order of the spectator expansion of the Watson multiple scattering theory and its final expression was a folding integral between the nucleon-nucleon ( N N ) t matrix and the nuclear density of the target. In the calculations N N and three-nucleon ( 3 N ) chiral interactions were used for the target density and only the N N interaction for the N N t matrix. The purpose of this study is to achieve another step towards the calculation of a more consistent OP introducing the 3 N force also in the dynamic part of the OP. The full treatment of the 3 N interaction is beyond our present capabilities. Thus, here it is approximated with a density dependent N N interaction obtained after the averaging over the Fermi sphere. In practice, in our model the 3 N force acts as a medium correction of the bare N N interaction used to calculate the t matrix. Even if the 3 N force is treated in an approximate way, this method naturally extends our previous model of the OP and allows a direct comparison of our present and previous results. We consider as case studies the elastic scattering of nucleons off C 12 and O 16 . We present results for the differential cross section and the spin observables for different values of the projectile energy. From the comparison with the experimental data and with the results of our previous model we assess the importance of the 3 N interaction in the dynamic part of the OP. Conclusions: Our analysis indicates that the contribution of the 3 N force in the t matrix is small for the differential cross section and it is sizable for the spin observables, in particular, for the analyzing power. We find that the two-pion exchange term is the major contributor to the 3 N force. A chiral expansion order-by-order analysis of the scattering observables confirms the convergence of our results at the next-to-next-to-next-to-leading-order, as already established in our previous work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Stability and Conservation properties of Hermite-based approximations of the Vlasov-Poisson System

Spectral approximation based on Hermite-Fourier expansion of the Vlasov-Poisson model for a collisionless plasma in the electro-static limit is provided by adding high-order artificial collision operators of Lenard-Bernstein type. These differential operators are suitably designed in order to preserve the physically-meaningful invariants (number of particles, momentum, energy). In view of time-discretization, stability results in appropriate norms are presented. In this study, necessary conditions link the magnitude of the artificial collision term, the number of spectral modes of the discretization, as well as the time-step. The analysis, carried out in full for the Hermite discretization of a simple linear problem in one-dimension, is then partly extended to cover the complete nonlinear Vlasov-Poisson model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Supramolecular Metal‐Organic Framework Electrocatalysts With Hydration‐Adaptive Gallery Expansion and Linker‐Mediated Distal Ni‐Co Cooperation Enable Framework‐Retentive Oxygen Evolution

Atomic‑level tailoring of electronic communication between spatially separated metal sites offers a route to accelerate multielectron electrocatalysis. We report Ni-TPTC, Co-TPTC, and heterobimetallic Ni-Co-TPTC supramolecular metal-organic frameworks (SMOFs) for the oxygen evolution reaction (OER) built from a terphenyl‑tetracarboxylate (TPTC) linker. Single-crystal X-ray diffraction of heterobimetallic Ni–Co–TPTC reveals trans-bis-aqua octahedral chains assembled into a π-stacked, hydrogen-bonded lattice and confirms retention of the parent architecture, while powder X-ray diffraction supports an isostructural Co analog. In 1.0 M KOH, Ni-Co-TPTC reaches 20 mA cm −2 at 350 mV and maintains operation at ∼60 mA cm −2 for 45 h with modest decay of the initial current. Time‑dependent ex situ diffraction shows dominant framework reflections with low‑angle shifts consistent with gallery dilation (d‑spacing ∼7.7 → ∼9.2 Å) during early operation, while Co K‑edge X‑ray absorption and microscopy reveal Co‑rich oxide/oxyhydroxide‑like domains at longer times that correlate with decay. X‑ray photoelectron spectroscopy, quantified by the Remote Binding‑Energy Differential, tracks composition‑dependent Ni-Co polarization, and DFT free‑energy analysis suggests that a model Ni-Co environment lowers the Co‑centered potential‑limiting step by ∼0.24 eV relative to the Co‑only framework. Furthermore, these results suggest that framework‑retentive expansion and distal Ni-Co coupling can drive OER activity before gradual deligation and oxide formation mark longer‑time degradation.

Supramolecular metal-organic frameworks (SMOFs)↗