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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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NASA NTRS2020

The Inner Solar System's Habitability Through Time

Earth, Mars, and Venus, irradiated by an evolving Sun, have had fascinating but diverging histories of habitability. Although only Earth’s surface is considered to be habitable today, all three planets might have simultaneously been habitable early in their histories to microbial life. We consider how physical processes that have operated similarly or differently on these planets determined the creation and evolution of their atmospheres and surfaces over time. These include the geophysical and geochemical processes that determined the style of their interior dynamics and the presence or absence of a magnetic field; the surface-atmosphere exchange processes that acted as a source or sink for atmospheric mass and composition; the Sun-planet interactions that controlled escape of gases to space; and the atmospheric processes that interacted with these to determine climate and habitability. The divergent evolutions of the three planets provide an invaluable context for thinking about the search for life outside the Solar System.

Anthony D. Del Genio↗
DOE OSTI2020

Rapid evolution of aerosol particles and their optical properties downwind of wildfires in the western US

Abstract. During the first phase of the Biomass Burn Operational Project (BBOP) field campaign, conducted in the Pacific Northwest, the DOE G-1 aircraft was used to follow the time evolution of wildfire smoke from near the point of emission to locations 2–3.5 h downwind. In nine flights we made repeated transects of wildfire plumes at varying downwind distances and could thereby follow the plume's time evolution. On average there was little change in dilution-normalized aerosol mass concentration as a function of downwind distance. This consistency hides a dynamic system in which primary aerosol particles are evaporating and secondary ones condensing. Organic aerosol is oxidized as a result. On all transects more than 90 % of aerosol is organic. In freshly emitted smoke aerosol, NH4+ is approximately equivalent to NO3. After 2 h of daytime aging, NH4+ increased and is approximately equivalent to the sum of Cl, SO42, and NO3. Particle size increased with downwind distance, causing particles to be more efficient scatters. Averaged over nine flights, mass scattering efficiency (MSE) increased in ∼ 2 h by 56 % and doubled in one flight. Mechanisms for redistributing mass from small to large particles are discussed. Coagulation is effective at moving aerosol from the Aitken to accumulation modes but yields only a minor increase in MSE. As absorption remained nearly constant with age, the time evolution of single scatter albedo was controlled by age-dependent scattering. Near-fire aerosol had a single scatter albedo (SSA) of 0.8–0.9. After 1 to 2 h of aging SSAs were typically 0.9 and greater. Assuming global-average surface and atmospheric conditions, the observed age dependence in SSA would change the direct radiative effect of a wildfire plume from near zero near the fire to a cooling effect downwind.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Quantum algorithms for open lattice field theory

Certain aspects of some unitary quantum systems are well described by evolution via a non-Hermitian effective Hamiltonian, as in the Wigner-Weisskopf theory for spontaneous decay. Conversely, any non-Hermitian Hamiltonian evolution can be accommodated in a corresponding unitary system + environment model via a generalization of Wigner-Weisskopf theory. This demonstrates the physical relevance of novel features such as exceptional points in quantum dynamics, and opens up avenues for studying many-body systems in the complex plane of coupling constants. In the case of lattice field theory, sparsity lends these channels the promise of efficient simulation on standardized quantum hardware. We thus consider quantum operations that correspond to Suzuki-Lie-Trotter approximation of lattice field theories undergoing nonunitary time evolution, with potential applicability to studies of spin or gauge models at finite chemical potential, with topological terms, to quantum phase transitions—a range of models with sign problems. We develop non-Hermitian quantum circuits and explore their promise on a benchmark, the quantum one-dimensional Ising model with complex longitudinal magnetic field, showing that observables can probe the Lee-Yang edge singularity. The development of attractors past critical points in the space of complex couplings indicates a potential for study on near-term noisy hardware.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Shearing approach to gauge-invariant Trotterization

Universal quantum simulations of gauge field theories are exposed to the risk of gauge symmetry violations when it is not known how to compile the desired operations exactly using the available gate set. In this article, we show how time evolution can be compiled in an Abelian gauge theory—if only approximately—without compromising gauge invariance, by graphically motivating a block-diagonalization procedure. When gauge-invariant interactions are associated with a “spatial network” in the space of discrete quantum numbers, it is seen that cyclically shearing the spatial network converts simultaneous updates to many quantum numbers into conditional updates of a single quantum number; ultimately, this eliminates any need to pass through (and acquire overlap onto) unphysical intermediate configurations. Shearing is explicitly applied to gauge-matter and magnetic interactions of lattice quantum electrodynamics. The features that make shearing successful at preserving Abelian gauge symmetry may also be found in non-Abelian theories, bringing one closer to gauge-invariant simulations of quantum chromodynamics.

Gauge theories↗
DOE OSTI2023

Crack Growth Rate at Oxygen Electrode/Electrolyte Interface in Solid Oxide Electrolysis Cells Predicted by Experiment Coupled Multiphysics Modeling

Solid oxide electrolysis cell (SOEC) is a very efficient hydrogen production technology, but the cell degradation is a serious limiting factor for its long-term implementation. Oxygen electrode (OE) delamination is reported to be the critical degradation mechanism. In this study, we present a methodology to understand the delamination failure of the OE due to chemical stress in a better perspective. Several OE configurations were tested: baseline strontium-doped lanthanum cobalt iron oxide (LSCF) single layer design and tantalum-doped strontium cobalt oxide (SCT) - LSCF bilayer designs with different SCT loadings. An electro-chemo-mechanical model is developed to associate the electrochemical behavior of the cell with solid mechanics for calculating crack growth of the cell during long term test. The bilayer configuration with SCT 20 wt% has better performance as it survived in the long-term life test with the least crack length. This study implies that an additional nano-coating of SCT over the OE have improved the species transport and oxygen evolution with reduced chemical stress. As the operating current density decreases, it takes longer time for the cell to reach the delamination with the same critical crack length of 6.5 μ m (∼93% of the electrode/electrolyte interface length). Finally, it was concluded that chemical stress plays a significant role in interface delamination failure, however it may not be the only source of stresses at the interface.

08 HYDROGEN↗
NASA NTRS1995

Investigation of the basic physics of high efficiency semiconductor hot carrier solar cell

The main purpose of this research program is to investigate potential semiconductor materials and their multi-band-gap MQW (multiple quantum wells) structures for high efficiency solar cells for aerospace and commercial applications. The absorption and PL (photoluminescence) spectra, the carrier dynamics, and band structures have been investigated for semiconductors of InP, GaP, GaInP, and InGaAsP/InP MQW structures, and for semiconductors of GaAs and AlGaAs by previous measurements. The barrier potential design criteria for achieving maximum energy conversion efficiency, and the resonant tunneling time as a function of barrier width in high efficiency MQW solar cell structures have also been investigated in the first two years. Based on previous carrier dynamics measurements and the time-dependent short circuit current density calculations, an InAs/InGaAs - InGaAs/GaAs - GaAs/AlGaAs MQW solar cell structure with 15 bandgaps has been designed. The absorption and PL spectra in InGaAsP/InP bulk and MQW structures were measured at room temperature and 77 K with different pump wavelength and intensity, to search for resonant states that may affect the solar cell activities. Time-resolved IR absorption for InGaAsP/InP bulk and MQW structures has been measured by femtosecond visible-pump and IR-probe absorption spectroscopy. This, with the absorption and PL measurements, will be helpful to understand the basic physics and device performance in multi-bandgap InAs/InGaAs - InGaAs/InP - InP/InGaP MQW solar cells. In particular, the lifetime of the photoexcited hot electrons is an important parameter for the device operation of InGaAsP/InP MQW solar cells working in the resonant tunneling conditions. Lastly, time evolution of the hot electron relaxation in GaAs has been measured in the temperature range of 4 K through 288 K using femtosecond pump-IR-probe absorption technique. The temperature dependence of the hot electron relaxation time in the X valley has been measured.

Alfano, R. R.↗
DOE OSTI2025

Strategies for simulating the time evolution of Hamiltonian lattice field theories

Simulating the time evolution of quantum field theories given some Hamiltonian H requires developing algorithms for implementing the unitary operator e -iHt . A variety of techniques exist that accomplish this task, with the most common technique used so far being Trotterization, which is a special case of the application of a product formula. However, other techniques exist that promise better asymptotic scaling in certain parameters of the theory being simulated, the most efficient of which are based on the concept of block encoding. In this work we study the performance of such algorithms in simulating lattice field theories. We derive and compare the asymptotic gate complexities of several commonly used simulation techniques in application to Hamiltonian lattice field theories. Using the scalar $\hat{φ}$ 4 theory as a test, we also perform numerical studies and compare the gate costs required by product formulas and signal-processing-based techniques to simulate time evolution. For the latter, we use the linear combination of unitaries (LCU) construction augmented with the quantum Fourier transform circuit to switch between the field and momentum eigenbases, which leads to immediate order-of-magnitude improvement in the cost of preparing the block encoding. Further, this paper also includes a pedagogical review of the techniques used, in particular product formulas, LCU, qubitization, quantum signal processing, as well as the technique for simulating geometrically-local Hamiltonians developed by Haah, Hastings, Kothari, and Low.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Toward active disruption avoidance via real-time estimation of the safe operating region and disruption proximity in tokamaks

This paper describes a real-time capable algorithm for identifying the safe operating region around a tokamak operating point. The region is defined by a convex set of linear constraints, from which the distance of a point from a disruptive boundary can be calculated. The disruptivity of points is calculated from an empirical machine learning predictor that generates the likelihood of disruption. While the likelihood generated by such empirical models can be compared to a threshold to trigger a disruption mitigation system, the safe operating region calculation enables active optimization of the operating point to maintain a safe margin from disruptive boundaries. The proposed algorithm is tested using a random forest disruption predictor fit on data from DIII-D. The safe operating region identification algorithm is applied to historical data from DIII-D showing the evolution of disruptive boundaries and the potential impact of optimization of the operating point. Real-time relevant execution times are made possible by parallelizing many of the calculation steps and implementing the algorithm on a graphics processing unit. Lastly, a real-time capable algorithm for optimizing the target operating point within the identified constraints is also proposed and simulated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1987

Space Station evolution

The Space Station that will be launched and made operational in the early 1990s should be viewed as a beginning, a facility that will evolve with the passing of time to better meet the needs and requirements of a diverse set of users. Evolution takes several forms, ranging from simple growth through addition of infrastructure elements to upgrading of system capability through inclusion of advanced technologies. Much of the early considerations of Space Station evolution focused on physical growth. However, a series of recent workshops have revealed that the more likely mode of Space Station evolution will not be through growth but rather through a process known as 'branching'.

Black, David C.↗
DOE OSTI2022

A deep learning-based direct forecasting of CO 2 plume migration

Accurate and timely forecasts of CO 2 plume evolution in geological reservoirs are crucial for CO 2 migration detection, leakage risk assessment, and operation decision support. Conventional forecasting usually adopts a two-step strategy, first calibrating reservoir model parameters against observations using iterative inverse modeling (or history matching) and then applying the calibrated model for predictions. This method impedes real-time forecasts due to the heavy computational demand in inverse modeling and may suffer from poor prediction accuracy because of the limited observation data. In this work, we propose a deep learning-based latent space mapping framework to forecast CO 2 plume migration directly by avoiding the inverse modeling. We first use the convolutional autoencoder to map the high-dimensional complex plume extents onto low-dimensional latent space. Next, we use neural networks to learn the relationship between the observation variables and the prediction latent variables. And then for given observation data, we infer the prediction values directly. This one-step direct forecasting is computationally efficient which requires a few number of parallelizable reservoir simulations and it can provide accurate predictions with limited observations by learning the observation-prediction relationship in the reduced dimension. Therefore, our proposed method enables an in-time forecast of dynamic CO 2 plume distributions. In this work, we demonstrate the effectiveness and accuracy of our method in predicting the CO 2 plume migration using four metrics such as plume area, centroid movement distance, and plume spreading in the primary and secondary directions. And the spatio-temporal evolution patterns of plume migration under diverse geological complexities are also accurately quantified.

15 GEOTHERMAL ENERGY↗
NASA NTRS1990

Low order dynamical models for mixing layers

The goal of this project was to investigate the feasibility of developing useful low order dynamical systems to allow one to determine cheaply the effect of various initial conditions on the evolution of mixing layers. A mathematically rigorous approach for a time evolving base flow as found in a mixing layer seems to be the singular value decomposition of the linear operator transforming some initial perturbations into the solution at a given later time. Unfortunately, this is very costly, if at all feasible, and only deals with the linear evolution of a disturbance. A different approach based on weakly nonlinear analysis was attempted, but numerous difficulties were encountered. Several formulations were proposed which may be ill-posed. The reasons for this possible failure of the attempted approach is related to the fundamental limitations of weakly nonlinear analysis. The clarification of these issues is attempted in this report.

Riahi, D. N.↗
DOE OSTI2024

TChem-atm v1.0

SAND2024-11300O TChem-atm is a software library that was developed to solve complex kinetic models for atmospheric chemistry applications. TChem-atm interface employs a hierarchical parallelism design to exploit the massive parallelism available from modern computing platforms. It also supports gas atmospheric chemistry applications, e.g., the energy exascale earth system model. TChem can be used as a box model or coupled with a climate model to compute the time evolution of gas tracer species. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Safta, Cosmin↗
NASA NTRS1990

Numerical simulation of particle-wave interaction in boundary layers

The effects of wall injection and particle motion on the spatial stability of two-dimensional plane channel flow are investigated. For this purpose, an accurate Navier-Stokes solver to simulate the space-time evolution of disturbances in three-dimensional flows has been developed. The code is operational on the NASA Langley CRAY2 and can be ported to any other supercomputer. The code has been tested extensively in tracking the spatial evolution of two-dimensional disturbances in plane channel flow and provided excellent agreement with the linear theory including at the inflow/outflow boundaries. Preliminary calculations have been performed to investigate the effects of stationary and moving sources of vortical disturbances simulating a particle traveling in the flow field. Results suggest that even at very low amplitudes, vortical disturbances act as amplifiers on the Tollmien-Schlichting waves promoting rapid instability. It is also found that slow moving particles are more dangerous than both stationary and fast moving particles for the same disturbance levels.

Biringen, S.↗
NASA NTRS2024

In-depth Analysis of LISA Pathfinder Performance Results: Time Evolution, Noise Projection, Physical Models, and Implications for LISA

We present an in-depth analysis of the LISA Pathfinder differential acceleration performance over the entire course of its science operations, spanning approximately 500 days. We find: (1) The evolution of the Brownian noise that dominates the acceleration amplitude spectral density (ASD), for frequencies f≳1 mHz, is consistent with the decaying pressure due to the outgassing of a single gaseous species. (2) Between f=36 μHz and 1 mHz, the acceleration ASD shows a 1/f tail in excess of the Brownian noise of almost constant amplitude, with ≃20% fluctuations over a period of a few days, with no particular time pattern over the course of the mission. (3) At the lowest considered frequency of f=18 μHz, the ASD significantly deviates from the 1/f behavior, because of temperature fluctuations that appear to modulate a quasistatic pressure gradient, sustained by the asymmetries of the outgassing pattern. We also present the results of a projection of the observed acceleration noise on the potential sources for which we had either a direct correlation measurement or a quantitative estimate from dedicated experiments. These sources account for approximately 40% of the noise power in the 1/f tail. Finally, we analyze the possible sources of the remaining unexplained fraction and identify the possible measures that may be taken to keep those under control in LISA.

M Armano↗
DOE OSTI2023

Simultaneous Measurements of Noncommuting Observables: Positive Transformations and Instrumental Lie Groups

We formulate a general program for describing and analyzing continuous, differential weak, simultaneous measurements of noncommuting observables, which focuses on describing the measuring instrument autonomously, without states. The Kraus operators of such measuring processes are time-ordered products of fundamental differential positive transformations, which generate nonunitary transformation groups that we call instrumental Lie groups. The temporal evolution of the instrument is equivalent to the diffusion of a Kraus-operator distribution function, defined relative to the invariant measure of the instrumental Lie group. This diffusion can be analyzed using Wiener path integration, stochastic differential equations, or a Fokker-Planck-Kolmogorov equation. This way of considering instrument evolution we call the Instrument Manifold Program. We relate the Instrument Manifold Program to state-based stochastic master equations. We then explain how the Instrument Manifold Program can be used to describe instrument evolution in terms of a universal cover that we call the universal instrumental Lie group, which is independent not just of states, but also of Hilbert space. The universal instrument is generically infinite dimensional, in which case the instrument’s evolution is chaotic. Special simultaneous measurements have a finite-dimensional universal instrument, in which case the instrument is considered principal, and it can be analyzed within the differential geometry of the universal instrumental Lie group. Principal instruments belong at the foundation of quantum mechanics. We consider the three most fundamental examples: measurement of a single observable, position and momentum, and the three components of angular momentum. As these measurements are performed continuously, they converge to strong simultaneous measurements. For a single observable, this results in the standard decay of coherence between inequivalent irreducible representations. For the latter two cases, it leads to a collapse within each irreducible representation onto the classical or spherical phase space, with the phase space located at the boundary of these instrumental Lie groups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2014

Evolution and Implementation of the NASA Robotic Conjunction Assessment Risk Analysis Concept of Operations

Reacting to potential on-orbit collision risk in an operational environment requires timely and accurate communication and exchange of data, information, and analysis to ensure informed decision-making for safety of flight and responsible use of the shared space environment. To accomplish this mission, it is imperative that all stakeholders effectively manage resources: devoting necessary and potentially intensive resource commitment to responding to high-risk conjunction events and preventing unnecessary expenditure of resources on events of low collision risk. After 10 years of operational experience, the NASA Robotic Conjunction Assessment Risk Analysis (CARA) is modifying its Concept of Operations (CONOPS) to ensure this alignment of collision risk and resource management. This evolution manifests itself in the approach to characterizing, reporting, and refining of collision risk. Implementation of this updated CONOPS is expected to have a demonstrated improvement on the efficacy of JSpOC, CARA, and owner/operator resources.

operations↗
DOE OSTI2026

An efficient explicit implementation of a near-optimal quantum algorithm for simulating linear dissipative differential equations

We propose an efficient block-encoding technique for the implementation of the Linear Combination of Hamiltonian Simulations (LCHS) for simulating dissipative initial-value problems. This algorithm approximates a target nonunitary operator as a weighted sum of Hamiltonian evolutions, thereby emulating a dissipative problem by mixing various time scales. We introduce an efficient encoding of the LCHS into a quantum circuit based on a simple coordinate transformation that turns the dependence on the summation index into a trigonometric function. Classically, this method is equivalent to the use of a highly accurate Fejér-Clenshaw-Curtis quadrature formula. Quantumly, this significantly simplifies block-encoding of a dissipative problem and allows one to perform an exponential number of Hamiltonian simulations by a single Quantum Signal Processing (QSP) circuit. The resulting LCHS circuit has high success probability and the selector scales logarithmically with the number of terms in the LCHS sum and linearly with time. Careful analysis of error convergence proves that this method is more efficient than other LCHS circuits that have recently appeared in the literature. We verify the quantum circuit and its scaling by simulating it on a digital emulator of fault-tolerant quantum computers and, as a test problem, solve the advection-diffusion equation. The proposed algorithm can be used for simulating a wide class of nonunitary initial-value problems including the Liouville equation with added dissipation and linear embeddings of nonlinear systems, such as the Koopman-von Neumann and Carleman embeddings.

Novikau, I [Lawrence Livermore National Laboratory↗
DOE OSTI2022

Learning two-phase microstructure evolution using neural operators and autoencoder architectures

Abstract Phase-field modeling is an effective but computationally expensive method for capturing the mesoscale morphological and microstructure evolution in materials. Hence, fast and generalizable surrogate models are needed to alleviate the cost of computationally taxing processes such as in optimization and design of materials. The intrinsic discontinuous nature of the physical phenomena incurred by the presence of sharp phase boundaries makes the training of the surrogate model cumbersome. We develop a framework that integrates a convolutional autoencoder architecture with a deep neural operator (DeepONet) to learn the dynamic evolution of a two-phase mixture and accelerate time-to-solution in predicting the microstructure evolution. We utilize the convolutional autoencoder to provide a compact representation of the microstructure data in a low-dimensional latent space. After DeepONet is trained in the latent space, it can be used to replace the high-fidelity phase-field numerical solver in interpolation tasks or to accelerate the numerical solver in extrapolation tasks.

36 MATERIALS SCIENCE↗