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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 433 records · Page 24

Apparent fine tunings for field theories with broken space-time symmetries

We exhibit a class of effective field theories that have hierarchically small Wilson coefficients for operators that are not protected by symmetries but are not finely tuned. These theories possess bounded target spaces and vacua that break space-time symmetries. We give a physical interpretation of these theories as generalized solids with open boundary conditions. We show that these theories realize unusual RG flows where higher dimensional (seemingly irrelevant) operators become relevant even at weak coupling. Finally, we present an example of a field theory whose vacuum energy relaxes to a hierarchically small value compared to the UV cut-off.

Physics↗

On Nth roots of positive operators

A bounded operator A on a Hilbert space H was positive. These operators were symmetric, and as such constitute a natural generalization of nonnegative real diagonal matrices. The following result is thus both well known and not surprising: A positive operator has a unique positive square root (under operator composition).

Brown, D. R.↗

Interaction of the surfaces of the moon and Mercury with their exospheric atmospheres

A model of atmosphere-surface interactions on the moon and on Mercury is presented. This model rejects the traditional assumption that the atmospheric particle source is a 'saturated' absorbed surface layer of gas and instead assumes that interaction is with solid atoms bound in a lattice structure so that most collisions with the light atmospheric particles are free-free rather than free-bound. The energy accommodation per collision for He and H is dominated by first-order interaction terms and is generally less than 0.1 per collision. It follows that estimated thermal escape is drastically reduced for the light atoms on both bodies. Thus the model requires much reduced solar wind collection efficiencies for protons and alpha particles. Some peculiarities of the Mercury He and H atmospheres might possibly be explained by the nature of the gas-surface coupling.

Shemansky, D. E.↗

An approach to CMG steering using feedback linearization

This paper presents an approach for controlling spacecraft equipped with control moment gyroscopes. A technique from feedback linearization theory is used to transform the original nonlinear problem to an equivalent linear form without approximating assumptions. In this form, the spacecraft dynamics appear linearly, and are decoupled from redundancy in the system of gyroscopes. A general approach to distributing control effort among the available actuators is described which includes provisions for redistribution of rotors, explicit bounds in gimbal rates, and guaranteed operation at or near singular configurations. A particular algorithm is developed for systems of double-gimbal devices, and demonstrated in two examples for which existing approaches fail to give adequate performance.

Dzielski, John↗

Approach to control moment gyroscope steering using feedback linearization

This paper presents an approach for controlling spacecraft equipped with control moment gyroscopes. A technique from feedback linearization theory is used to transform the original nonlinear problem to an equivalent linear form without approximating assumptions. In this form, the spacecraft dynamics appear linearly, and are decoupled from redundancy in the system of gyroscopes. A general approach to distributing control effort among the available actuators is described which includes provisions for redistribution of rotors, explicit bounds in gimbal rates, and guaranteed operation at or near singular configurations. A particular algorithm is developed for systems of double-gimbal devices, and demonstrated in two examples for which existing approaches fail to give adequate performance.

Dzielski, John↗

Statistical-mechanical selection of the shapes of disk galaxies

A new method is proposed for selecting steady state shapes of disk galaxies as 'most probable states' of a large number of stars, given only the total energy and total angular momentum. A partial differential equation is derived for the mean gravitational potential; it is closely related to the 'sinh-Poisson' equation for the mean-field description of a line vortex system or electrostatic guiding-center plasma. A 'water bag' approximation to the distribution function for bound stars renders the equation analytically tractable, but accurate solution of it may require numerical integration, in view of its general nonlinearity.

Montgomery, David↗

Uncertainty Evaluation of Computational Model Used to Support the Integrated Powerhead Demonstration Project

NASA and the U.S. Air Force are working on a joint project to develop a new hydrogen-fueled, full-flow, staged combustion rocket engine. The initial testing and modeling work for the Integrated Powerhead Demonstrator (IPD) project is being performed by NASA Marshall and Stennis Space Centers. A key factor in the testing of this engine is the ability to predict and measure the transient fluid flow during engine start and shutdown phases of operation. A model built by NASA Marshall in the ROCket Engine Transient Simulation (ROCETS) program is used to predict transient engine fluid flows. The model is initially calibrated to data from previous tests on the Stennis E1 test stand. The model is then used to predict the next run. Data from this run can then be used to recalibrate the model providing a tool to guide the test program in incremental steps to reduce the risk to the prototype engine. In this paper, they define this type of model as a calibrated model. This paper proposes a method to estimate the uncertainty of a model calibrated to a set of experimental test data. The method is similar to that used in the calibration of experiment instrumentation. For the IPD example used in this paper, the model uncertainty is determined for both LOX and LH flow rates using previous data. The successful use of this model is then demonstrated to predict another similar test run within the uncertainty bounds. The paper summarizes the uncertainty methodology when a model is continually recalibrated with new test data. The methodology is general and can be applied to other calibrated models.

Steele, W. G.↗

Dynamic Stability Testing of the Mars Science Laboratory Entry Capsule

Results from a 26 shot ballistic range test of the Mars Science Laboratory (MSL) entry capsule are presented. The supersonic pitch damping properties of the MSL capsule were characterized between Mach 1.35 and Mach 3.5 and total angles-of-attack from 0 to 30 degrees. In flight, the MSL entry capsule will utilize a radial center-of-gravity offset to produce a non-zero trim angle-of-attack. This offset trim angle will produce lift, enabling the capsule to fly a guided entry and reducing the landing footprint dimensions to within 10 km of the desired landing site. A lifting configuration could not be tested at the ballistic range used for this test as the models would swerve into the range walls, possibly damaging cameras, the coordinate reference system or other facility assets. Ballistic (non-lifting) data was extracted and will be implemented in a conservative fashion to ensure that the dynamic stability characteristics of the flight vehicle are bounded. A comparison between the MSL pitch damping results and the dynamic model of the Mars Exploration Rover capsule shows generally close agreement with no significant differences in damping characteristics due to the change in backshell geometry. Dynamic moments are also compared to the MSL reaction control system (RCS) control authority to show the controller has sufficient margin to easily damp any dynamic stability effects.

Schroenenberger, Mark↗

Feature learning and generalization in deep networks with orthogonal weights

Fully-connected deep neural networks with weights initialized from independent Gaussian distributions can be tuned to criticality, which prevents the exponential growth or decay of signals propagating through the network. However, such networks still exhibit fluctuations that grow linearly with the depth of the network, which may impair the training of networks with width comparable to depth. We show analytically that rectangular networks with tanh activations and weights initialized from the ensemble of orthogonal matrices have corresponding preactivation fluctuations which are independent of depth, to leading order in inverse width. Moreover, we demonstrate numerically that, at initialization, all correlators involving the neural tangent kernel (NTK) and its descendants at leading order in inverse width—which govern the evolution of observables during training—saturate at a depth of ~20, rather than growing without bound as in the case of Gaussian initializations. We speculate that this structure preserves finite-width feature learning while reducing overall noise, thus improving both generalization and training speed in deep networks with depth comparable to width. We provide some experimental justification by relating empirical measurements of the NTK to the superior performance of deep non-linear orthogonal networks trained under full-batch gradient descent on the MNIST and CIFAR-10 classification tasks.

97 MATHEMATICS AND COMPUTING↗

WHAMII - An enumeration and insertion procedure with binomial bounds for the stochastic time-constrained traveling salesman problem

This paper presents an algorithm (WHAMII) designed to solve the Artificial Intelligence Design Challenge at the 1987 AIAA Guidance, Navigation and Control Conference. The problem under consideration is a stochastic generalization of the traveling salesman problem in which travel costs can incur a penalty with a given probability. The variability in travel costs leads to a probability constraint with respect to violating the budget allocation. Given the small size of the problem (eleven cities), an approach is considered that combines partial tour enumeration with a heuristic city insertion procedure. For computational efficiency during both the enumeration and insertion procedures, precalculated binomial probabilities are used to determine an upper bound on the actual probability of violating the budget constraint for each tour. The actual probability is calculated for the final best tour, and additional insertions are attempted until the actual probability exceeds the bound.

Dahl, Roy W.↗

Diagnostics of Mixed-State Topological Order and Breakdown of Quantum Memory

Topological quantum memory can protect information against local errors up to finite error thresholds. Such thresholds are usually determined based on the success of decoding algorithms rather than the intrinsic properties of the mixed states describing corrupted memories. Here we provide an intrinsic characterization of the breakdown of topological quantum memory, which both gives a bound on the performance of decoding algorithms and provides examples of topologically distinct mixed states. We employ three information-theoretical quantities that can be regarded as generalizations of the diagnostics of ground-state topological order, and serve as a definition for topological order in error-corrupted mixed states. We consider the topological contribution to entanglement negativity and two other metrics based on quantum relative entropy and coherent information. In the concrete example of the two-dimensional (2D) Toric code with local bit-flip and phase errors, we map three quantities to observables in 2D classical spin models and analytically show they all undergo a transition at the same error threshold. This threshold is an upper bound on that achieved in any decoding algorithm and is indeed saturated by that in the optimal decoding algorithm for the Toric code. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Reduced Order Modeling conditioned on monitored features for response and error bounds estimation in engineered systems

Reduced Order Models (ROMs) form essential tools across engineering domains by virtue of their function as surrogates for computationally intensive digital twinning simulators. Although purely data-driven methods are available for ROM construction, schemes that allow to retain a portion of the physics tend to enhance the interpretability and generalization of ROMs. However, physics-based techniques can adversely scale when dealing with nonlinear systems that feature parametric dependencies. This study introduces a generative physics-based ROM that is suited for nonlinear systems with parametric dependencies and is additionally able to provide numerical error bounds associated with the respective estimates. A main contribution of this work is the conditioning of these parametric ROMs to features that can be derived from monitoring measurements, feasibly in an online fashion. This is contrary to most existing ROM schemes, which remain restricted to the prescription of the physics-based, and usually a priori unknown, system parameters. Our work utilizes conditional Variational Autoencoders to continuously map the required reduction bases to a feature vector extracted from limited output measurements, while additionally allowing for a probabilistic assessment of the ROM-estimated Quantities of Interest. An auxiliary task using a neural network-based parametrization of suitable probability distributions is introduced to re-establish the link with physical model parameters. We verify the proposed scheme on a series of simulated case studies incorporating effects of geometric and material nonlinearity under parametric dependencies related to system properties and input load characteristics.

Conditional VAEs↗

Quantum error correction from complexity in Brownian SYK

We study the robustness of quantum error correction in a one-parameter ensemble of codes generated by the Brownian SYK model, where the parameter quantifies the encoding complexity. The robustness of error correction by a quantum code is upper bounded by the “mutual purity” of a certain entangled state between the code subspace and environment in the isometric extension of the error channel, where the mutual purity of a density matrix ρAB is the difference $\mathcal{F}$ p ($A : B$) ≡ $\mathrm{T}$r $p^{2}_{AB}$ - $\mathrm{T}$r $p^{2}_{A}$ $\mathrm{T}$r $p^{2}_{B}$. We show that when the encoding complexity is small, the mutual purity is O(1) for the erasure of a small number of qubits (i.e., the encoding is fragile). However, this quantity decays exponentially, becoming O(1/N) for O(log N) encoding complexity. Further, at polynomial encoding complexity, the mutual purity saturates to a plateau of O(e -N ). We also find a hierarchy of complexity scales associated to a tower of subleading contributions to the mutual purity that quantitatively, but not qualitatively, adjust our error correction bound as encoding complexity increases. In the AdS/CFT context, our results suggest that any portion of the entanglement wedge of a general boundary subregion A with sufficiently high encoding complexity is robustly protected against low-rank errors acting on A with no prior access to the encoding map. From the bulk point of view, we expect such bulk degrees of freedom to be causally inaccessible from the region A despite being encoded in it.

1/N expansion↗

Photovoltaic Inverter Failure Mechanism Estimation Using Unsupervised Machine Learning and Reliability Assessment

This article introduces a data-driven approach to assessing failure mechanisms and reliability degradation in outdoor photovoltaic (PV) string inverters. The manufacturer's stated PV inverter lifetime can vary due to the impact of operating site conditions. To address limitations in degradation estimation through accelerated testing, condition monitoring, or degradation modeling, we propose a machine learning (ML) oriented approach. Utilizing data from a 1.4 MW PV power plant operational since 2016, with 46 string PV inverters tied to the grid, we employ the unsupervised one-class support vector machine ML technique to analyze inverter and sensor data, capable of classifying humidity cycling and temperature fluctuations as dominant failure mechanisms. Utilizing the anomaly alert relationship and alert details specific to the inverter, the level of PV inverter output is considered as its availability or available reliability. Subsequently, a continuous Markov model is applied to six-month alert data, revealing an average stated reliability of 20% after 20 years of continuous operation. These results support recommendations for time-bound preventive measures to enhance PV inverter reliability under diverse outdoor conditions. Furthermore, the approach provides a nondestructive, top–down, and generalized method for analyzing any commercial PV inverter exposed to outdoor conditions, contingent on the availability of relevant data.

14 SOLAR ENERGY↗

Emergent pair density wave order across a Lifshitz transition

We numerically investigate the telltale signs of pair-density-wave order (PDW) in the Kondo-Heisenberg chain by focusing on the momentum resolved spectrum in different parameter regimes. Density matrix renormalization group calculations reveal that this phase is characterized by a dispersion with two minima and four Fermi points, indicating the emergence of an effective next-nearest-neighbor hopping that arises as a second-order effect to avoid magnetic frustration. The pairs appear in the spectrum as in-gap bound states with weight concentrated in the hole pockets. The low-energy physics can be understood by means of a generalized t−J model with next-nearest-neighbor hopping. Our results offer a guide for searching for experimental signatures, and for other models that can realize PDW physics.

Yang, Luhang [University of Tennessee Knoxville]↗

Three-body Coulomb systems using generalized angular-momentum S states

An expansion of the three-body Coulomb potential in generalized angular-momentum eigenfunctions developed earlier by one of the authors is used to compute energy eigenvalues and eigenfunctions of bound S states of three-body Coulomb systems. The results for He, H(-), e(-)e(+)e(-), and pmu(-)p are compared with the results of other computational approaches.

Whitten, R. C.↗

Phosphine absorption in the 5-micron window of Jupiter

Since the original suggestion by Gillett et al. (1969) it has generally been assumed that the region of partial transparency near 5 micron in Jupiter's atmosphere (the 5-micron window) is bounded by the nu sub 4 NH3 at 6.1 micron and the nu sub 3 CH4 band at 3.3 micron. New measurements of Jupiter and of laboratory phosphine (PH3) samples show that PH3 is a significant contributor to the continuum opacity in the window and in fact defines its short-wavelength limit. This has important implications for the use of 5-micron observations as a means to probe the deep atmospheric structure of Jupiter. The abundance of PH3 which results from a comparison of Jovian and laboratory spectra is about 3 to 5 cm-am. This is five to eight times less than that found by Larson et al. (1977) in the same spectral region, but is in good agreement with the result of Tokunaga et al. (1979) from 10-micron observations.

Beer, R.↗