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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Quantum state preparation by adiabatic evolution with custom gates

Quantum state preparation by adiabatic evolution is currently rendered ineffective by the long implementation times of the underlying quantum circuits, comparable to the decoherence time of present and near-term quantum devices. These implementation times can be significantly reduced by realizing these circuits with custom gates. Using classical computing, we model the output of a realistic two-qubit processor implementing the adiabatic evolution of a two-spin system by means of custom gates. This modeled output is then compared with the results of quantum simulations solving the same problem on IBM Quantum (IBMQ) systems. Additionally, when used to emulate the behavior of the IBMQ quantum circuit, our realistic model yields state fidelities ranging from 65% to 85%, similar to the actual performance of a diverse set of IBMQ devices. When we reduced the implementation time by using custom gates, however, the loss of fidelity was reduced by at least a factor of 4, allowing us to accurately extract the energy of the target state. This improvement is enough to render adiabatic evolution useful for quantum state preparation for small systems or as a preconditioner for other state preparation methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Eigenstate entanglement scaling for critical interacting spin chains

With increasing subsystem size and energy, bipartite entanglement entropies of energy eigenstates cross over from the groundstate scaling to a volume law. In previous work, we pointed out that, when strong or weak eigenstate thermalization (ETH) applies, the entanglement entropies of all or, respectively, almost all eigenstates follow a single crossover function. The crossover functions are determined by the subsystem entropy of thermal states and assume universal scaling forms in quantum-critical regimes. This was demonstrated by field-theoretical arguments and the analysis of large systems of non-interacting fermions and bosons. Here, we substantiate such scaling properties for integrable and non-integrable interacting spin-1/2 chains at criticality using exact diagonalization. In particular, we analyze XXZ and transverse-field Ising models with and without next-nearest-neighbor interactions. Indeed, the crossover of thermal subsystem entropies can be described by a universal scaling function following from conformal field theory. Furthermore, we analyze the validity of ETH for entanglement in these models. Even for the relatively small system sizes that can be simulated, the distributions of eigenstate entanglement entropies are sharply peaked around the subsystem entropies of the corresponding thermal ensembles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Avoiding ergodicity problems in lattice discretizations of the Hubbard model

The Hubbard model arises naturally when electron-electron interactions are added to the tight-binding descriptions of many condensed matter systems. For instance, the two-dimensional Hubbard model on the honeycomb lattice is central to the ab initio description of the electronic structure of carbon nanomaterials, such as graphene. Such low-dimensional Hubbard models are advantageously studied with Markov chain Monte Carlo methods, such as hybrid Monte Carlo (HMC). HMC is the standard algorithm of the lattice gauge theory community, as it is well suited to theories of dynamical fermions. As HMC performs continuous, global updates of the lattice degrees of freedom, it provides superior scaling with system size relative to local updating methods. A potential drawback of HMC is its susceptibility to ergodicity problems due to so-called exceptional configurations, for which the fermion operator cannot be inverted. Recently, ergodicity problems were found in some formulations of HMC simulations of the Hubbard model. Here, we address this issue directly and clarify under what conditions ergodicity is maintained or violated in HMC simulations of the Hubbard model. We study different lattice formulations of the fermion operator and provide explicit, representative calculations for small systems, often comparing to exact results. Here, we show that a fermion operator can be found which is both computationally convenient and free of ergodicity problems.

First-principles calculations↗
DOE OSTI2022

Impact of multiplicity fluctuations on entropy scaling across system size

The initial state is one of the greatest uncertainties in heavy-ion collisions. A model-agnostic approach is taken in the phenomenological Trento framework which constrains parameters using Bayesian analysis. However, the color-glass condensate (CGC) effective theory predicts initial energy densities that lie outside the recent Bayesian analyses due, in part, to the assumption in Trento of event-by-event multiplicity fluctuations following a Γ distribution. We compare the Trento-preferred √T A T B scaling to CGC-like T A T B scaling coupled with log-normal fluctuations in AuAu and dAu collisions and find there is a significant impact on the multiplicity distributions and on the eccentricities, which may affect the extraction of viscosity in small systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Adaptive basis sets for practical quantum computing

Electronic structure calculations on small systems such as H 2 , H 2 O, LiH, and BeH 2 with chemical accuracy are still a challenge for the current generation of noisy intermediate-scale quantum (NISQ) devices. One of the reasons is that due to the device limitations, only minimal basis sets are commonly applied in quantum chemical calculations, which allows one to keep the number of qubits employed in the calculations at a minimum. However, the use of minimal basis sets leads to very large errors in the computed molecular energies as well as potential energy surface shapes. One way to increase the accuracy of electronic structure calculations is through the development of small basis sets better suited for quantum computing. In this work, we show that the use of adaptive basis sets, in which exponents and contraction coefficients depend on molecular structure, provides an easy way to dramatically improve the accuracy of quantum chemical calculations without the need to increase the basis set size and thus the number of qubits utilized in quantum circuits. As a proof of principle, we optimize an adaptive minimal basis set for quantum computing calculations on an H 2 molecule, in which exponents and contraction coefficients depend on the H—H distance, and apply it to the generation of H 2 potential energy surface on IBM-Q quantum devices. The adaptive minimal basis set reaches the accuracy of the double-zeta basis sets, thus allowing one to perform double-zeta quality calculations on quantum devices without the need to utilize twice as many qubits in simulations. This approach can be extended to other molecular systems and larger basis sets in a straightforward manner.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Probing scrambling and operator size distributions using random mixed states and local measurements

The dynamical spreading of quantum information through a many-body system, typically called scrambling, is a complex process that has proven to be essential to describe many properties of out-of-equilibrium quantum systems. Scrambling can, in principle, be fully characterized via the use of out-of-time-ordered correlation functions, which are notoriously hard to access experimentally. In this work, we put forward an alternative toolbox of measurement protocols to experimentally probe scrambling by accessing properties of the operator size probability distribution, which tracks the size of the support of observables in a many-body system over time. Our measurement protocols require the preparation of separable mixed states together with local operations and measurements, and combine the tools of randomized operations, a modern development of near-term quantum algorithms, with the use of mixed states, a standard tool in NMR experiments. We demonstrate how to efficiently probe the probability-generating function of the operator distribution and discuss the challenges associated with obtaining the moments of the operator distribution. We further show that manipulating the initial state of the protocol allows us to directly obtain the individual elements of the distribution for small system sizes. Published by the American Physical Society 2024

Blocher, Philip Daniel (ORCID:0000000163027567)↗
DOE OSTI2023

Multigrid Reduction in Time for Chaotic Dynamical Systems

As CPU clock speeds have stagnated and high performance computers continue to have ever higher core counts, increased parallelism is needed to take advantage of these new architectures. Traditional serial time-marching schemes can be a significant bottleneck, as many types of simulations require large numbers of time-steps which must be computed sequentially. Parallel-in-time schemes, such as the Multigrid Reduction in Time (MGRIT) method, remedy this by parallelizing across time-steps and have shown promising results for parabolic problems. However, chaotic problems have proved more difficult, since chaotic initial value problems (IVPs) are inherently ill-conditioned. MGRIT relies on a hierarchy of successively coarser time-grids to iteratively correct the solution on the finest time-grid, but due to the nature of chaotic systems, small inaccuracies on the coarser levels can be greatly magnified and lead to poor coarse-grid corrections. Here we introduce a modified MGRIT algorithm based on an existing quadratically converging nonlinear extension to the multigrid Full Approximation Scheme (FAS), as well as a novel time-coarsening scheme. Together, these approaches better capture long-term chaotic behavior on coarse-grids and greatly improve convergence of MGRIT for chaotic IVPs. Further, we introduce a novel low-memory variant of the algorithm for solving chaotic PDEs with MGRIT which not only solves the IVP, but also provides estimates for the unstable Lyapunov vectors of the system. Finally, we provide supporting numerical results for the Lorenz system and demonstrate parallel speedup for the chaotic Kuramoto–Sivashinsky PDE over a significantly longer time-domain than in previous works.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Investigation of Frozen Chemistry for Molten Salt Reactors (MSRs)

Understanding accident progression and the potential/conditions for fission product release from fuel is necessary to evaluate safety for any nuclear reactor system. Molten Salt Reactors (MSRs) under development need such analysis to support safety evaluations. Fission product chemistry specific to MSR concepts is a critical area that introduces distinct considerations relative to the current state-of-knowledge in reactor safety, primarily developed for water-moderated nuclear reactor systems. In Light Water Reactor (LWR) systems, it is necessary to capture the chemical interaction of fission products with the reactor evironment, containment and confinement systems. The overall effects at this point are relatively well understood for the purposes of performing safety evaluations. A key insight from LWR studies is that fission product chemical behavior can be reasonably captured by modeling approaches where the chemistry is "frozen". These modeling approaches assume that radionuclide reaction and speciation can be represented by chemical classes, each with characteristic transport behavior that is invariant under a broad range of thermochemical conditions. However, radionuclides can exhibit a range of behavior in the liquid salt-melt phase of the coolant used in MSRs. Radionuclides, salt, and the metal containment surfaces (i.e. pipes) can co-exist in dynamic equilibrium that could evolve with small system mass changes. A detailed investigation to the degree the equilibrium state can dynamically evolve with changes in the conditions of the molten salt mixture has not been previously conducted. It is currently not well understood where frozen chemistry assumptions are valid. Expanding the state-of-knowledge in this regard is relevant to better assessing the range of chemical effects that should be incorporated as part of MSR safety assessments. This investigation used the Oak Ridge Isotope GENeration (ORIGEN) module of the Standardized Computer-Analysis for Licensing Evaluation (SCALE) code to generate simulated radionuclide inventories for the MSR Experiment (MSRE) and then modeled reactor chemical speciation using the Molten Salt Thermodynamic Database – Thermochemical (MSTDB-TC) coupled with Thermochimica. The effect of composition variation during decay of fission product inventory in a molten salt over a period of 500 days prolonged post- at multiple temperatures was studied. Mass fractions for fluorine and berilium were varied in order to probe the effects of free fluorine control. Finally, speciation of fluoride reactors were showed by comparing MSRE readionuclide inventories with a FLiBe based molten salt breeder reactor (MSBR). The results showed that fission product mass change has little effect on phase mass changes and vapor pressures for fluoride species, but differ with varying carrier and fuel salt compositions. However, iodine species were found to have a vapor pressure not only dependent on temperature, but also the free fluorine potential, releasing iodine when the free fluorine potential is equal to the iodine inventory. This observation, however, arose under free fluorine potentials that are very unlikely to be realized in typical molten salt mixtures. Despite this observation, temperature was found to be the dominant parameter that drove phase change and fission product species vapor pressure. The results indicate that the current frozen chemistry approach is adequate for MSR analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

The role of the Kozai-Lidov mechanism in black hole binary mergers in galactic centers

In order to understand the rate of merger of stellar mass black hole binaries (BHBs) by gravitational wave (GW) emission it is important to determine the major pathways to merger. We use numerical simulations to explore the evolution of BHBs inside the radius of influence of supermassive black holes (SMBHs) in galactic centers. In this region, the evolution of binaries is dominated by perturbations from the central SMBH. In particular, as first pointed out by Antonini and Perets, the Kozai–Lidov mechanism trades relative inclination of the BHB to the SMBH for eccentricity of the BHB, and for some orientations can bring the BHB to an eccentricity near unity. At very high eccentricities, GW emission from the BHB can become efficient, causing the members of the BHB to coalesce. We use a novel combination of two N-body codes to follow this evolution. We are required to simulate small systems to follow the behavior accurately. We have completed 400 simulations that range from ∼300 stars around a 10{sup 3} M{sub ⊙} black hole to ∼4500 stars around a 10{sup 4} M{sub ⊙} black hole. These simulations are the first to follow the internal orbit of a binary near an SMBH while also following the changes to its external orbit self-consistently. We find that this mechanism could produce mergers at a maximum rate per volume of ∼100 Gpc{sup −3} yr{sup −1} or considerably less if the inclination oscillations of the binary remain constant as the BHB inclination to the SMBH changes, or if the binary black hole fraction is small.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2016

Use of a Small Unmanned Aircraft System for Autonomous Fire Spotting at the Great Dismal Swamp

This paper describes the results of a set of experiments and analyses conducted to evaluate the capability of small unmanned aircraft systems (sUAS) to spot nascent fires in the Great Dismal Swamp (GDS) National Wildlife Refuge. This work is the result of a partnership between the National Aeronautics and Space Administration and the US Fish and Wildlife service specifically to investigate sUAS usage for fire-spotting. The objectives of the current effort were to: 1) Determine suitability and utility of low-cost Small Unmanned Aircraft Systems (sUAS) to detect nascent fires at GDS; 2) Identify and assess the necessary National Airspace System (NAS) integration issues; and 3) Provide information to GDS and the community on system requirements and concepts-of-operation (CONOPS) for conducting fire detection/support mission in the National Airspace and (4) Identify potential applications of intelligent autonomy that would enable or benefit this high-value mission. In addition, data on the ability of various low-cost sensors to detect smoke plumes and fire hot spots was generated during the experiments as well as identifying a path towards a future practical mission utility by using sUAS in beyond visual-line-of-sight operation in the National Airspace System (NAS).

Logan, Michael J.↗
DOE OSTI2013

Computing the partition function, ensemble averages, and density of states for lattice spin systems by sampling the mean

An algorithm to approximately calculate the partition function (and subsequently ensemble averages) and density of states of lattice spin systems through non-Monte-Carlo random sampling is developed. This algorithm (called the sampling-the-mean algorithm) can be applied to models where the up or down spins at lattice nodes interact to change the spin states of other lattice nodes, especially non-Ising-like models with long-range interactions such as the biological model considered here. Because it is based on the Central Limit Theorem of probability, the sampling-the-mean algorithm also gives estimates of the error in the partition function, ensemble averages, and density of states. Easily implemented parallelization strategies and error minimizing sampling strategies are discussed. The sampling-the-mean method works especially well for relatively small systems, systems with a density of energy states that contains sharp spikes or oscillations, or systems with little a priori knowledge of the density of states.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Dynamical crossover between the infinite-volume and empty-lattice limits of ultra-cold fermions in 1D optical lattices

Unlike typical condensed-matter systems, ultra-cold atoms loaded into optical lattices allow separate control of both the particle number and system size. As a consequence, there are two distinct "thermodynamic” limits that can be defined for these systems: i) ’’infinite-volume limit” at constant finite density, and ii) "empty-lattice limit” at constant particle number. To probe the difference between these two limits and their crossover, we consider a partially occupied lattice and study the transport into the unoccupied region of non-interacting fermions and fermions interacting at the mean-field level. In the infinite-volume limit, a finite steady-state current emerges. On the other hand, in the empty-lattice limit there is no finite steady-state current. By changing the initial filling, we find a smooth crossover between the two limits. Our predictions may be verified using available experimental tools and demonstrate a fundamental difference between isolated small systems such as ultra-cold atoms and conventional condensed-matter systems.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2011

Simulation of Relativistic Shocks and Associated Radiation from Turbulent Magnetic Fields

Using our new 3-D relativistic particle-in-cell (PIC) code, we investigated long-term particle acceleration associated with a relativistic electron-positron jet propagating in an unmagnetized ambient electron-positron plasma. The simulations were performed using a much longer simulation system than our previous simulations in order to investigate the full nonlinear stage of the Weibel instability and its particle acceleration mechanism. Cold jet electrons are thermalized and ambient electrons are accelerated in the resulting shocks. Acceleration of ambient electrons leads to a maximum ambient electron density three times larger than the original value as predicted by hydrodynamic compression. Behind the bow shock, in the jet shock, strong electromagnetic fields are generated. These fields may lead to time dependent afterglow emission. In order to go beyond the standard synchrotron model used in astrophysical objects we have used PIC simulations and calculated radiation based on first principles. We calculated radiation from electrons propagating in a uniform parallel magnetic field to verify the technique. We also used the technique to calculate emission from electrons based on simulations with a small system. We obtain spectra which are consistent with those generated from electrons propagating in turbulent magnetic fields. This turbulent magnetic field is similar to the magnetic field generated at an early nonlinear stage of the Weibel instability. A fully developed shock within a larger system may generate a jitter/synchrotron spectrum.

Nishikawa, K.-I.↗
DOE OSTI2018

Identifying structural changes with unsupervised machine learning methods

In this work, unsupervised machine learning methods are used to identify structural changes using the melting point transition in classical molecular dynamics simulations as an example application of the approach. Dimensionality reduction and clustering methods are applied to instantaneous radial distributions of atomic configurations from classical molecular dynamics simulations of metallic systems over a large temperature range. Principal component analysis is used to dramatically reduce the dimensionality of the feature space across the samples using an orthogonal linear transformation that preserves the statistical variance of the data under the condition that the new feature space is linearly independent. From there, k-means clustering is used to partition the samples into solid and liquid phases through a criterion motivated by the geometry of the reduced feature space of the samples, allowing for an estimation of the melting point transition. This pattern criterion is conceptually similar to how humans interpret the data but with far greater throughput, as the shapes of the radial distributions are different for each phase and easily distinguishable by humans. The transition temperature estimates derived from this machine learning approach produce comparable results to other methods on similarly small system sizes. These results show that machine learning approaches can be applied to structural changes in physical systems.

42 ENGINEERING↗
DOE OSTI2022

Multicomponent gas mixture parametric CFD study of condensation heat transfer in small modular reactor system safety

Safety is always the primary concern for designing and analyzing nuclear reactor systems. The requirements for the safety margin for advanced small modular reactor (SMR) systems are targeted even higher than the conventional commercial large-scale nuclear reactors incorporating the passive and inherent safety systems. The SMR systems are designed with the condensation passive containment cooling system (PCCS), which plays a critical role in removing reactor heat during a steam release accident case. However, the presence of non-condensable gas (NCG), like air, reduces the heat transfer performance. This physics phenomenon becomes multifactorial for nuclear reactor containment during a fuel failure accident case that releases hydrogen gas. Besides, the mixture component of steam-air-hydrogen varies in reactor accident cases, which need simulation and validation keeping parameters of importance. Reviews showed that previous studies for SMR’s PCCCS did not cover the condensation heat transfer (CHT) in the presence of multicomponent NCG mixture parametric computational fluid dynamics (CFD) simulation and validation, making a research gap in the SMR design safety. A comprehensive CHT parametric CFD study was performed for SMR PCCS to fill this research gap. This study used experimental data as simulation 3D physics domain inlet and outlet boundary conditions. However, the wall boundary conditions were constant temperature, curve-fit, and annular coolant for verifying the turbulence models. Parametric simulations were performed, verified, and optimized for steam-NCGs mixtures. The multicomponent gases, multiphase mixtures, and fluid film condensation models were applied with associated turbulence models. The results of the parametric study were evaluated for realistic reactor conditions. Results showed that parametric study provided critical insight about the dependency of multicomponent gas mixture parameters that supports reactor safety design, analysis, and licensing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Aqueous organic flow batteries for sustainable energy storage

Aqueous Organic Redox Flow Batteries (RFBs) have the potential to address the large-scale need for storing electrical energy from intermittent sources like solar- and wind-based generation. Unlike metal-based redox systems, small organic molecules present the prospect of achieving sustainability, by being synthesizable from abundantly available carbon dioxide, water, nitrogen, sulfur, and renewable energy. This mini-review focuses on the progress and challenges in designing water-based RFBs based on small organic molecules that can address the requirements of large-scale energy storage. Further, much of the recent research in this area involves discovering new molecular architectures via computational screening, understanding degradation, and cell configurations to address the techno-economic challenges of extraordinary electrochemical durability, recyclability, low cost of precursor materials, and good solubility. Redox materials for the positive side of the cell are notably few. Future research must continue to focus on these techno-economic challenges through rapid materials discovery.

25 ENERGY STORAGE↗
DOE OSTI2014

Multi-layer Potfit: An accurate potential representation for efficient high-dimensional quantum dynamics

The multi-layer multi-configuration time-dependent Hartree method (ML-MCTDH) is a highly efficient scheme for studying the dynamics of high-dimensional quantum systems. Its use is greatly facilitated if the Hamiltonian of the system possesses a particular structure through which the multi-dimensional matrix elements can be computed efficiently. In the field of quantum molecular dynamics, the effective interaction between the atoms is often described by potential energy surfaces (PES), and it is necessary to fit such PES into the desired structure. For high-dimensional systems, the current approaches for this fitting process either lead to fits that are too large to be practical, or their accuracy is difficult to predict and control. This article introduces multi-layer Potfit (MLPF), a novel fitting scheme that results in a PES representation in the hierarchical tensor (HT) format. The scheme is based on the hierarchical singular value decomposition, which can yield a near-optimal fit and give strict bounds for the obtained accuracy. Here, a recursive scheme for using the HT-format PES within ML-MCTDH is derived, and theoretical estimates as well as a computational example show that the use of MLPF can reduce the numerical effort for ML-MCTDH by orders of magnitude, compared to the traditionally used POTFIT representation of the PES. Moreover, it is shown that MLPF is especially beneficial for high-accuracy PES representations, and it turns out that MLPF leads to computational savings already for comparatively small systems with just four modes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗