SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
With a view to applying the generator coordinate method to large configuration spaces, we propose a simple approximate formula to compute diabatic many-body matrix elements without having to evaluate two-body interaction matrix elements. Here, the method is illustrated with two analytically solvable Hamiltonians based on the harmonic oscillator.
Some calculations of parton distributions from first principles only give access to a limited range of Fourier modes of the function to reconstruct. We present a physically motivated procedure to regularize the inverse integral problem using a Gaussian process as a Bayesian prior. We propose to fix the hyperparameters of the prior in a meaningful physical fashion, offering a simple implementation, great numerical efficiency, and allowing us to understand and keep control easily of the uncertainty of the reconstruction.
Physical properties of liquids and glasses are controlled not only by the short-range order (SRO) in the nearest-neighbor atoms but also by the medium-range order (MRO) observed for atoms beyond the nearest neighbors. In this article the nature of the MRO as the descriptor of point-to-set atomic correlation is discussed focusing on simple liquids, such as metallic liquids. Through the results of x-ray diffraction and simulation with classical potentials we show that the third peak of the pair-distribution function, which describes the MRO, shows a distinct change in temperature dependence at the glass transition, whereas the first peak, which represents the SRO, changes smoothly through the glass transition. Finally, the result suggests that the glass transition is induced by the freezing of the MRO rather than that of the SRO, implying a major role of the MRO on the viscosity of supercooled liquid.
The spatial atomic correlations in liquids and glasses extend often significantly beyond the nearest neighbors. Such correlations, called the medium-range order (MRO), affect many physical properties, but their nature is not well understood. In this article the variation of the MRO with temperature is calculated based upon the concept of the atomic-level pressure, focusing on simple liquids, such as metallic liquids. It is shown that the structural coherence length that characterizes MRO follows the Curie-Weiss law with a negative Curie temperature as observed by experiment and simulation. It is also shown that the glass transition is induced by freezing of the MRO, rather than the freezing of the nearest-neighbor shell. The implications of these results are discussed.
A simplistic model of atomic dynamics in liquid, based on the concept of dynamic fluctuations in local atomic connectivity, is proposed to elucidate the temperature variation of the viscosity of a material in its liquid phase. Within the simplifications and hypothesis made to define the model, it is possible to explain the crossover from a simple liquid to a cooperative liquid and covariance of viscosity near the glass transition temperature. The model is a mechanical analog of the Drude model for the electric transport in metal.
The de Gennes narrowing phenomenon is frequently observed by neutron or x-ray scattering measurements of the dynamics of complex systems, such as liquids, proteins, colloids, and polymers. The characteristic slowing down of dynamics in the vicinity of the maximum of the total scattering intensity is commonly attributed to enhanced cooperativity. In this Letter, we present an alternative view on its origin through the examination of the time-dependent pair correlation function, the van Hove correlation function, for a model liquid in two, three, and four dimensions. We find that the relaxation time increases monotonically with distance and the dependence on distance varies with dimension. We propose a heuristic explanation of this dependence based on a simple geometrical model. Furthermore, this finding sheds new light on the interpretation of the de Gennes narrowing phenomenon and the α-relaxation time.
we report that despite there being an infinite variety of types of flow, most rheological studies focus on a single type such as simple shear. Using discrete element simulations, we explore bulk granular systems in a wide range of flow types at large strains and characterize invariants of the stress tensor for different inertial numbers and interparticle friction coefficients. We identify a strong dependence on the type of flow, which grows with increasing inertial number or friction. Standard models of yielding, repurposed to describe the dependence of the stress on flow type in steady-state flow and at finite rates, are compared with data.
Work-function Φ measures the work needed for an electron to escape a solid. For simple metals, it is almost exclusively the result of the surface dipole created by spill-out of electrons from bulk into the vacuum as shown in the seminal work by Lang and Kohn [Phys. Rev. B 3, 1215 (1971)] using a jellium model. Despite a half century of intense efforts, however, such understanding has not been extended past metals. Here we present a universal model for Φ which contains a previously unrecognized bulk contribution Φ I [Phys. Rev. Lett. 121, 196802 (2018)]. By incorporating Φ I into the jellium model, we find that it dictates the dipole due to charge spill out and provides a description which applies to a wide range of materials, ranging from metals, semiconductors, to insulators.
In order to maintain a constant monochromatic synchrotron X-ray beam height for all energies, the separation between the crystals of a double-crystal monochromator is typically adjusted, via translation of the second crystal, while X-ray energy is varied, via rotation of the crystal pair. The ability to accurately translate the second crystal requires precise knowledge of the separation between the two crystals and, when present, crystal miscuts. Here, a simple method for calibrating the crystal gap from measured variation in the X-ray beam height that eliminates error in the fixed beam offset is provided.
One often observes small but measurable differences in the diffraction data measured from different crystals of a single protein. These differences might reflect structural differences in the protein and may reveal the natural dynamism of the molecule in solution. Partitioning these mixed-state data into single-state clusters is a critical step that could extract information about the dynamic behavior of proteins from hundreds or thousands of single-crystal data sets. Mixed-state data can be obtained deliberately (through intentional perturbation) or inadvertently (while attempting to measure highly redundant single-crystal data). To the extent that different states adopt different molecular structures, one expects to observe differences in the crystals; each of the polystates will create a polymorph of the crystals. After mixed-state diffraction data have been measured, deliberately or inadvertently, the challenge is to sort the data into clusters that may represent relevant biological polystates. Here, this problem is addressed using a simple multi-factor clustering approach that classifies each data set using independent observables, thereby assigning each data set to the correct location in conformational space. This procedure is illustrated using two independent observables, unit-cell parameters and intensities, to cluster mixed-state data from chymotrypsinogen (ChTg) crystals. It is observed that the data populate an arc of the reaction trajectory as ChTg is converted into chymotrypsin.
With the development of wide band-gap (WBG) technology, the switching speed of power semiconductor devices increases, which makes circuits more sensitive to parasitics. For three-level active neutral point clamped (3L-ANPC) converters, the over-voltage caused by additional non-active switch loop can be an issue. This paper analyzes the multiple commutation loops in 3L-ANPC converter and summarizes the impact factors of the device over-voltage. The nonlinearity of the output capacitance of the device can significantly influence the over-voltage. A simple control without introducing additional hardware circuit or complex software algorithm is proposed to attenuate the effect of the nonlinear output capacitance. Multi-pulse test is conducted for a 3L-ANPC converter built with silicon carbide (SiC) MOSFETs. With the proposed control, the testing results show that the peak drain-source voltage of both active and non-active switches is reduced by more than 20% compared to the conventional control.
A model for the spatial coherence function of a partially coherent light produced at the output of a step-index multimode fiber excited with a spatially coherent broadband source is developed. The field is reflected as a sum of coherent and partially coherent parts, the former being a fully developed speckle and the latter is described by a “Jinc” degree of coherence and uniform intensity over the core of the fiber. The model correctly incorporates all available experimental data, including global degree of coherence, and is intuitive and simple.
We present a new method for online selection of the penalty parameter for the alternating direction method of multipliers (ADMM) algorithm. ADMM is a widely used method for solving a range of optimization problems, including those that arise in signal and image processing. In its standard form, ADMM includes a scalar hyperparameter, known as the penalty parameter, which usually has to be tuned to achieve satisfactory empirical convergence. In this work, we develop a framework for analyzing the ADMM algorithm applied to a quadratic problem as an affine fixed point iteration. Using this framework, we develop a new method for automatically tuning the penalty parameter by detecting when it has become too large or small. We analyze this and several other methods with respect to their theoretical properties, i.e., robustness to problem transformations, and empirical performance on several optimization problems. Our proposed algorithm is based on a theoretical framework with clear, explicit assumptions and approximations, is theoretically covariant/invariant to problem transformations, is simple to implement, and exhibits competitive empirical performance.
We present a simple physical model that explains the device operation of a three-terminal (3T) IBC Si bottom cell platform that enables an efficient 3T tandem. If the IBC cell has two p-n junctions and one high-low junction (bipolar transistor), the two p-n junctions strongly interact via minority carrier diffusion in the base. In a two-BSF junction and one p-n junction IBC platform (single emitter), the BSF terminals interact via ohmic majority carrier current in the base. This interaction creates wide 'generating' power islands in the 2D current J 1 J 2 plane. The area and shape of these islands are determined by dissipative losses in the wafer base and in the cell contacts. Both positive and negative terminal currents are allowed for 3T operation, thus enabling both the top and bottom cells to operate at their full light currents. This opens new possibilities for 3T use in modules.
This paper describes simple and efficient machine learning (ML) methods for efficiently detecting multiple types of power system events captured by PMUs scarcely placed in a large power grid. It uses a single feature from each PMU based on a rectangle area enclosing the event in a given data window. This single feature is sufficient to enable commonly used ML models to detect different types of events quickly and accurately. The feature is used by five ML models on four different data-window sizes. The results indicated a tradeoff between the execution speed and detection accuracy in variety of data-window size choices. Here, the proposed method is insensitive to most data quality issues typical for data from field PMUs, and thus it does not require major data cleansing efforts prior to feature extraction.
Real-time monitoring of heat loads in cryogenic systems is critical for many applications, particularly high field magnets. In this work, we demonstrated that by monitoring changes in the capacitance of local probes consisting of thin metal strips with a porous glass fiber dielectric, boiling helium from as little as 0.1 J of deposited heat can be located by an analysis of the response speed and amplitude in nearby probes. We further implemented stray-capacitance monitoring of a magnet's metal support structures, a more global probe of the magnet volumes, in three high temperature superconducting Bi-2212 magnet types. Global structural stray-capacitance monitoring was evaluated for a single racetrack coil, a common coil dipole, and a canted cosine theta winding, showing a quench response comparable to voltage signals without inductive effects. The response of the local and global probes was compared in the single racetrack coil with well-known quench properties. Monitoring the cool-down of the common coil dipole demonstrated the added benefit of the global stray-capacitance as a liquid level monitor. This simple method of monitoring the capacitance has proven to be a versatile and robust technique for monitoring and locating heat.
In this article, we propose a simple yet effective approach, called point adversarial self mining (PASM), to improve the recognition accuracy in facial expression recognition (FER). Unlike previous works focusing on designing specific architectures or loss functions to solve this problem, PASM boosts the network capability by simulating human learning processes: providing updated learning materials and guidance from more capable teachers. Specifically, to generate new learning materials, PASM leverages a point adversarial attack method and a trained teacher network to locate the most informative position related to the target task, generating harder learning samples to refine the network. The searched position is highly adaptive since it considers both the statistical information of each sample and the teacher network capability. Other than being provided new learning materials, the student network also receives guidance from the teacher network. After the student network finishes training, the student network changes its role and acts as a teacher, generating new learning materials and providing stronger guidance to train a better student network. Here, the adaptive learning materials generation and teacher/student update can be conducted more than one time, improving the network capability iteratively. Extensive experimental results validate the efficacy of our method over the existing state of the arts for FER.
We numerically investigate the bandwidth and collimation characteristics of ultrasound beams generated by a simple collimated ultrasound beam source that consists of a piezoelectric disk operated near its radial mode resonances. We simulate the ultrasound beam generated in a fluid medium as a function of the excitation frequency for two cases: (1) free piezoelectric disk that corresponds to zero-traction along the lateral edge and (2) fixed piezoelectric disk that corresponds to zero-displacement along the lateral edge. We present and discuss the physical mechanism underpinning the frequency-dependent collimation and bandwidth properties of the ultrasound beams. We observe that the collimated beam generated by the free disk repeatedly lengthens/shortens and also extends/retracts sidelobes with increasing frequency. Alternatively, fixing the piezoelectric disk results in a consistent beam profile shape across a broad range of frequencies. This facilitates generating broadband signals such as a Gaussian pulse or chirp, which are common in ultrasound imaging. Thus, the fixed piezoelectric disk finds application as a collimated ultrasound beam source in a wide range of applications including medical ultrasound imaging, scanning acoustic microscopy, sonar detection, and other nondestructive ultrasound inspection techniques.