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At least 1,477 records · Page 82

Out-of-distribution generalization for learning quantum dynamics

Generalization bounds are a critical tool to assess the training data requirements of Quantum Machine Learning (QML). Recent work has established guarantees for in-distribution generalization of quantum neural networks (QNNs), where training and testing data are drawn from the same data distribution. However, there are currently no results on out-of-distribution generalization in QML, where we require a trained model to perform well even on data drawn from a different distribution to the training distribution. Here, we prove out-of-distribution generalization for the task of learning an unknown unitary. In particular, we show that one can learn the action of a unitary on entangled states having trained only product states. Since product states can be prepared using only single-qubit gates, this advances the prospects of learning quantum dynamics on near term quantum hardware, and further opens up new methods for both the classical and quantum compilation of quantum circuits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system structural components

The objective is the development of several modular structural analysis packages capable of predicting the probabilistic response distribution for key structural variables such as maximum stress, natural frequencies, transient response, etc. The structural analysis packages are to include stochastic modeling of loads, material properties, geometry (tolerances), and boundary conditions. The solution is to be in terms of the cumulative probability of exceedance distribution (CDF) and confidence bounds. Two methods of probability modeling are to be included as well as three types of structural models - probabilistic finite-element method (PFEM); probabilistic approximate analysis methods (PAAM); and probabilistic boundary element methods (PBEM). The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Method (PSAM) tools will estimate structural safety and reliability, while providing the engineer with information on the confidence that should be given to the predicted behavior. Perhaps most critically, the PSAM results will directly provide information on the sensitivity of the design response to those variables which are seen to be uncertain.

Cruse, T. A.↗

Probabilistic Structural Analysis Methods for select space propulsion system structural components (PSAM)

The objective is the development of several modular structural analysis packages capable of predicting the probabilistic response distribution for key structural variables such as maximum stress, natural frequencies, transient response, etc. The structural analysis packages are to include stochastic modeling of loads, material properties, geometry (tolerances), and boundary conditions. The solution is to be in terms of the cumulative probability of exceedance distribution (CDF) and confidence bounds. Two methods of probability modeling are to be included as well as three types of structural models - probabilistic finite-element method (PFEM); probabilistic approximate analysis methods (PAAM); and probabilistic boundary element methods (PBEM). The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Method (PSAM) tools will estimate structural safety and reliability, while providing the engineer with information on the confidence that should be given to the predicted behavior. Perhaps most critically, the PSAM results will directly provide information on the sensitivity of the design response to those variables which are seen to be uncertain.

Cruse, T. A.↗

Low-Noise Rotorcraft Blades

Blades of helicopter rotors, tilt rotors, and like reshaped to reduce noise, according to proposal. Planform features combination of rearward and forward sweep. Forward sweep over large outer portion of blade constitutes primary noise-reduction feature. Relieves some of compressive effect in tip region, with consequent reduction of noise from compressive sources. Performance at high advance ratio improved. Cabin vibration and loading noise reduced by load-averaging effect of double-sweep planform. Aft-swept section provides balancing of aerodynamic and other dynamic forces on blade along 1/4-chord line of straight inboard section and along projection of line to outermost blade radius. Possible for hub-hinge forces and moments to remain within practical bounds. Provides stabilizing blade forces and moments to counteract any instability caused by forward sweep.

Brooks, Thomas F.↗

OARE flight maneuvers and calibration measurements on STS-58

The Orbital Acceleration Research Experiment (OARE), which has flown on STS-40, STS-50, and STS-58, contains a three axis accelerometer with a single, nonpendulous, electrostatically suspended proofmass which can resolve accelerations to the nano-g level. The experiment also contains a full calibration station to permit in situ bias and scale factor calibration. This on-orbit calibration capability eliminates the large uncertainty of ground-based calibrations encountered with accelerometers flown in the past on the orbiter, thus providing absolute acceleration measurement accuracy heretofore unachievable. This is the first time accelerometer scale factor measurements have been performed on orbit. A detailed analysis of the calibration process is given along with results of the calibration factors from the on-orbit OARE flight measurements on STS-58. In addition, the analysis of OARE flight maneuver data used to validate the scale factor measurements in the sensor's most sensitive range is also presented. Estimates on calibration uncertainties are discussed. This provides bounds on the STS-58 absolute acceleration measurements for future applications.

Blanchard, Robert C.↗

Polynomial range estimation as a troubled-cell indicator for high-order methods

Two troubled-cell indicators based on polynomial range estimation methods are used to flag cells that may violate positivity constraints. One method uses interval extension, and the second uses the range enclosure property of the Bernstein polynomial basis. Furthermore, both methods reduce compute time for the positivity preserver by limiting its application to a subset of cells. The Bernstein polynomial method remains effective as the problem dimensionality increases. Interval extension applied to the internal energy equation permits the use of the troubled-cell indicators for rational functions, though performance suffers compared to directly applying the indicators to polynomial functions.

42 ENGINEERING↗

Weighted relaxation for multigrid reduction in time

Current trends in computer architectures now mean that faster computation speed must come primarily from increased concurrency, not faster clock speeds, which are stagnating. Thus, this situation creates bottlenecks for serial algorithms, including the well-known bottleneck for sequential time-integration, where each individual time-value (i.e., time-step) is computed sequentially. One approach to alleviate this and achieve parallelism in time is with multigrid. Here, in this work, we consider multigrid-reduction-in-time (MGRIT), a multilevel method applied to the time dimension that computes multiple time-steps in parallel. Like all multigrid methods, MGRIT relies on the complementary relationship between relaxation on a fine-grid and a correction from the coarse grid to solve the problem. All current MGRIT implementations are based on unweighted-Jacobi relaxation; here we introduce the concept of weighted relaxation to MGRIT. We derive new convergence bounds for weighted relaxation, and use this analysis to guide the selection of relaxation weights. Numerical results then demonstrate that by choosing appropriate non-unitary relaxation weights, one can achieve faster convergence rates and lower iteration counts for MGRIT when compared with unweighted relaxation. In most cases, weighted relaxation yields a 10%–20% saving in iterations, which is significant when using large high-performance computers. For A-stable integration schemes, results also illustrate that under-relaxation can restore convergence in some cases where unweighted relaxation is not convergent.

97 MATHEMATICS AND COMPUTING↗

Novel Segregated Solid Propulsion System with Separately Stored Fuel and Oxidizer

Abstract The development and experimentation of a solid propulsion concept consisting of separate hydrogen‐rich solid propellant and solid oxidizer grains is presented. This system consists of an extremely fuel‐rich solid propellant, which, once ignited, undergoes a self‐sustaining decomposition to release fuel‐rich product gases, which are particularly rich in hydrogen gas. These relatively high‐temperature gases subsequently react with a solid oxidizer grain stored downstream. Progress in high‐nitrogen materials has allowed for the synthesis of fuel‐rich compounds that can store significant amounts of hydrogen, with little or no bound oxygen. With these new developments in propellant chemistry, a unique segregated propulsion system has been developed, creating an all‐solid propulsion system that combusts analogously to a reverse hybrid rocket system. Because of the physical separation of fuel and oxidizer, a higher level of safety is achieved which concurrently allows for the utilization of higher energy ingredients without the penalty of higher sensitivity. Theoretical performance calculations and experimental data have shown the potential for this system to compete with existing composite rocket propellants while having significant benefits in terms of safety, toxicity, and mission space. This paper presents a detailed overview of the conception, development, and testing of this propulsion system.

42 ENGINEERING↗

The first field application of a low-cost MPC for grid-interactive K-12 schools: Lessons-learned and savings assessment

K-12 schools are the largest energy consumers in the public sector, with their HVAC energy consumption representing the largest portion of their total energy use. While transitioning these schools to grid-interactive HVAC system operation through advanced controls offers significant financial and environmental benefits, and model predictive control (MPC) has been identified as a promising solution to achieve that, very few MPCs are affordable and have been deployed in K-12 schools. This situation raises concerns about the unclear real-world benefits of MPC technology among facility managers and industries. To address this gap, this paper presents a low-cost MPC solution that requires minimal control infrastructure costs and a unique field demonstration at a K-12 school, conducted for both cooling and heating seasons. This work adopted a previously developed MPC and extended it for use in the school application. The MPC aims to coordinate multiple packaged units to eliminate unnecessary peaks and shift cooling or heating loads in response to grid signals based on load conditions, while maintaining thermostat temperatures within school-defined bounds. Throughout the field tests, the MPC achieved a 24% reduction in peak demand during the cooling season and shifted cooling or heating loads by up to 16% in response to the school's utility tariff, considering load conditions, while also allowing end-users to override thermostat setpoints. Further, the paper also discusses the limitations of this study and future research directions for better performance of the MPC at K-12 schools.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Recent Advances in Nuclear Forensic Chemistry

Nuclear forensics is a rapidly growing field with a widespread impact on global nonproliferation. From the beginning, nuclear forensic capabilities have been inextricably bound to existing limitations within chemistry and materials science. As nuclear forensics has continued to develop as a unique field of research, new advances in chemistry have revolutionized our ability to rapidly and quantitatively analyze radioactive materials for attribution. In particular, microanalytical techniques originally developed for nanoscience, such as micro-XRF, SIMS, and SEM-EDX, have enabled spatially resolved chemical analyses to be performed with only nanograms of material. Such techniques have redefined the paradigm for pre- and postdetonation nuclear forensics, as large quantities of material are no longer necessary for full characterization and attribution. This Review explains how modern nuclear forensic techniques have developed from their origins in chemistry and provides real-world examples of how these techniques have been used to characterize radioactive materials, including fallout from nuclear detonations such as the 1945 Trinity test.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Generating Synthetic Time Series Photovoltaic Data with Real-World Physical Challenges and Noise for Use in Algorithm Test and Validation

The PV Fleet Data Initiative and other projects seek the develop algorithms for automated analysis of PV time series data for extraction of statistical information and other parameters of the data such as degradation rates, soiling loss information, tracker performance, clipping or curtailment, system availability and other valuable information. While there is a vast body of PV data available for application of said extraction algorithms it is difficult to validate these algorithms because the true parameters to be extracted are not known. There has been a wide use of synthetic data in the literature for algorithm validation but this synthetic data is typically very bounded by the problem or topic at hand. The PV Fleet Data Initiative project has demonstrated that real time series PV data almost always includes a host of data quality and physical problems that, in reality, any automated PV abstraction algorithm must handle appropriately. For this reason, this work describes the development of a complex synthetic PV times series data set that includes data quality and physical problems that have been experienced in real world PV data. The various quality and physical problems are documented in the synthetic data so that users can test the validity of various PV extraction algorithms as well as develop new algorithms to solve problems this data set can support.

14 SOLAR ENERGY↗

Robust Design Optimization via Failure Domain Bounding

This paper extends and applies the strategies recently developed by the authors for handling constraints under uncertainty to robust design optimization. For the scope of this paper, robust optimization is a methodology aimed at problems for which some parameters are uncertain and are only known to belong to some uncertainty set. This set can be described by either a deterministic or a probabilistic model. In the methodology developed herein, optimization-based strategies are used to bound the constraint violation region using hyper-spheres and hyper-rectangles. By comparing the resulting bounding sets with any given uncertainty model, it can be determined whether the constraints are satisfied for all members of the uncertainty model (i.e., constraints are feasible) or not (i.e., constraints are infeasible). If constraints are infeasible and a probabilistic uncertainty model is available, upper bounds to the probability of constraint violation can be efficiently calculated. The tools developed enable approximating not only the set of designs that make the constraints feasible but also, when required, the set of designs for which the probability of constraint violation is below a prescribed admissible value. When constraint feasibility is possible, several design criteria can be used to shape the uncertainty model of performance metrics of interest. Worst-case, least-second-moment, and reliability-based design criteria are considered herein. Since the problem formulation is generic and the tools derived only require standard optimization algorithms for their implementation, these strategies are easily applicable to a broad range of engineering problems.

Crespo, Luis G.↗

Elastic-Plastic Nonlinear Response of a Space Shuttle External Tank Stringer: Thermal and Mechanical Loadings - Part 2

Elastic-plastic, large-deflection nonlinear thermo-mechanical stress analyses are performed for the Space Shuttle external tank s intertank stringers. Detailed threedimensional finite element models are developed and used to investigate the stringer s elastic-plastic response for different thermal and mechanical loading events from assembly through flight. Assembly strains caused by initial installation on an intertank panel are accounted for in the analyses. Thermal loading due to tanking was determined to be the bounding loading event. The cryogenic shrinkage caused by tanking resulted in a rotation of the intertank chord flange towards the center of the intertank, which in turn loaded the intertank stringer feet. The analyses suggest that the strain levels near the first three fasteners remain sufficiently high that a failure may occur. The analyses also confirmed that the installation of radius blocks on the stringer feet ends results in an increase in the stringer capability.

Knight, Norman F., Jr.↗

Molecularly Functionalized Electrodes for Efficient Electrochemical Water Remediation

Here, the development and investigation of materials that leverage unique interfacial effects on electronic structure and redox chemistry are likely to play an outstanding role in advanced technologies for wastewater treatment. Here, the use of surface functionalization of metal oxides with a Ru(II)poly(pyridyl) complex was reported as a way to create hybrid assemblies with optimized electrochemical performance for water remediation, superior to those that could be achieved with the molecular catalyst or metal-oxide electrodes used individually. Mechanistic analysis demonstrated that the molecularly functionalized electrodes could suppress the formation of hydroxyl radicals (i. e., the dominant remediation pathway for bare metal-oxide electrodes), allowing the water remediation to proceed through the highly oxidizing Ru 3+ ions in the surface-bound complexes. Furthermore, the underlying metal-oxide substrates played a crucial role in altering the electronic structure and electrochemical properties of the surface-bound catalyst, such that the competing side reaction (i. e., water splitting) was largely inhibited.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CsO x Nanostructures on Au(111): Morphology- and Size-dependent Activity for the Water–Gas Shift Reaction

Alkali oxides are typically used as promoters of heterogeneous catalysts for the water–gas shift (WGS; H 2 O + CO → H 2 + CO 2 ) reaction. On Au(111), CsO x exhibits diverse nanostructures at varying coverages, as revealed by scanning tunneling microscopy. Clusters of cesium oxide (Cs 2 O 2 ) nucleate at elbow sites of the Au(111) herringbone when θ Cs is less than 0.1 ML. Subsequently, these clusters transform into two-dimensional (2D) islands (Cs 2 O, Cs 2 O 2 , CsO 2 ) as the cesium coverage increases (θ Cs > 0.1 ML). Both types of CsO x nanostructures enable the WGS process on Au(111). The highest activity was seen for the cesium oxide clusters which facilitated the partial dissociation of water and binding of CO. The CO ads and OH ads groups were not strongly bound and probably reacted to yield a short-lived HOCO intermediate that led to gaseous H 2 and CO 2 . The 2D islands of CsO x also enabled the WGS but their efficiency was reduced due to the formation of cesium hydroxide compounds (limiting mobility of OH groups) and the generation of CO 3 and C species (blocking of active centers). The fact that the performance of the CsO x /Au(111) catalysts changed dramatically with variations in the chemical properties of the CsO x nanostructures indicates that the alkali oxide was an integral part of the active phase, playing a central role in the activation and conversion of the reactants. To attach the label of “promoter” to CsO x is a simplification that does not help in the design and optimization of catalysts for C1 chemistry. In conclusion, to achieve a rational design, one must consider the structural and chemical properties of the alkali oxide.

36 MATERIALS SCIENCE↗

Poly(vinylferrocene) as an Ionomer and Sulfur-Confining Additive for Lithium–Sulfur Batteries

Lithium-sulfur (Li-S) batteries are promising owing to their high energy density, environmental benignity, and low cost. Most of the commonly used binders in Li-S battery cathodes are inert and have no significant effect on the challenges of sulfur as a cathode material, such as the polysulfide shuttle effect, low ionic/electronic conductivity, and a sluggish redox reaction. In this work, we demonstrate the use of poly(vinylferrocene) (PvFc) as a binder additive that can effectively increase the ionic conductivity of the cathode and act as a sulfide confining agent. Electrochemical tests performed with PvFc as part of the binder mixture used to cast the cathodes demonstrate an increase in rate capability and cycle life when compared to the baseline samples. Ionic conductivity measurements and X-ray photoelectron spectroscopy suggest that the π-cation molecular interaction between the cyclopentadienyl rings from ferrocene and Li + act like an ion couple with ferrocene acting as a static, covalently bound acceptor of Li + ions that enhances their mobility through the cathode. This coupled with the affinity between the ferrocenyl cations and the Li salt anions, which provides more distribution of counterions for Li + movement and improves accessibility to the cathode S reservoir, make PvFc a promising ionomer for Li-S batteries. In addition, the π-cation bonds between cyclopentadienyl and lithium polysulfides produce a sulfide confining effect that mitigates capacity fade through polysulfide dissolution. Furthermore, this work demonstrates an expansion in the utility of PvFc as a component in Li-ion batteries, which so far is mostly limited to use as an active material in organometallic batteries.

25 ENERGY STORAGE↗

How spin relaxes and dephases in bulk halide perovskites

Abstract Spintronics in halide perovskites has drawn significant attention in recent years, due to their highly tunable spin-orbit fields and intriguing interplay with lattice symmetry. Here, we perform first-principles calculations to determine the spin relaxation time ( T 1 ) and ensemble spin dephasing time ( $${T}_{2}^{*}$$ T 2 * ) in a prototype halide perovskite, CsPbBr 3 . To accurately capture spin dephasing in external magnetic fields we determine the Landé g -factor from first principles and take it into account in our calculations. These allow us to predict intrinsic spin lifetimes as an upper bound for experiments, identify the dominant spin relaxation pathways, and evaluate the dependence on temperature, external fields, carrier density, and impurities. We find that the Fröhlich interaction that dominates carrier relaxation contributes negligibly to spin relaxation, consistent with the spin-conserving nature of this interaction. Our theoretical approach may lead to new strategies to optimize spin and carrier transport properties.

74 ATOMIC AND MOLECULAR PHYSICS↗