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An approach for calculating tunneling amplitudes from a nonlocalized initial state is presented. Generalizing the matching conditions and equations of motion to allow for complex momentum permits a description of tunneling in the presence of so-called classical motion. Possible applications of the method are presented.
This paper investigates the unnotched tensile properties of two-dimensional triaxial braid reinforced composites from both an experimental and analytical viewpoint. The materials are graphite fibers in an epoxy matrix. Three different reinforcing fiber architectures were considered. Specimens were cut from resin transfer molded (RTM) composite panels made from each braid. There were considerable differences in the observed elastic constants from different size strain gage and extensometer readings. Larger strain gages gave more consistent results and correlated better with the extensometer readings. Experimental strains correlated reasonably well with analytical predictions in the longitudinal, zero degree, fiber direction but not in the transverse direction. Tensile strength results were not always predictable even in reinforcing directions. Minor changes in braid geometry led to disproportionate strength variations. The unit cell structure of the triaxial braid was discussed with the assistence of computer analysis of the microgeometry. Photomicrographs of the braid geometry were used to improve upon the computer graphics representations of unit cells. These unit cells were used to predict the elastic moduli with various degrees of sophistication. The simple and the complex analyses were generally in agreement but none adequately matched the experimental results for all the braids.
This paper investigates the unnotched tensile properties of two-dimensional (2D) triaxial braid-reinforced composites both experimentally and analytically. The materials are graphite fibers in an epoxy matrix. Three different reinforcing fiber architectures were considered. There were considerable differences in the observed elastic constants from different size strain gage and extensometer readings. Larger strain gages gave more consistent results and correlated better with the extensometer readings. Experimental strains correlated reasonably well with analytical predictions in the longitudinal, 0 deg, fiber direction but not in the transverse direction. Tensile strength results were not always predictable even in reinforcing directions. Minor changes in braid geometry led to disproportionate strength variations. The unit cell structure of the triaxial braid was discussed with the assistance of computer analysis of the microgeometry. Photomicrographs of braid geometry were used to improve upon the computer graphics representations of unit cells. These unit cells were used to predict the elastic moduli with various degrees of sophistication. The simple and the complex analyses were generally in agreement, but none adequately matched the experimental results for all the braids.
The unnotched tensile properties of 2-D triaxial braid reinforced composites from both an experimental and an analytical viewpoint are studied. The materials are graphite fibers in an epoxy matrix. Three different reinforcing fiber architectures were considered. Specimens were cut from resin transfer molded (RTM) composite panels made from each braid. There were considerable differences in the observed elastic constants from different size strain gage and extensometer reading. Larger strain gages gave more consistent results and correlated better with the extensometer reading. Experimental strains correlated reasonably well with analytical predictions in the longitudinal, 0 degrees, fiber direction but not in the transverse direction. Tensile strength results were not always predictable even in reinforcing directions. Minor changes in braid geometry led to disproportionate strength variations. The unit cell structure of the triaxial braid was discussed with the assistance of computer analysis of the microgeometry. Photomicrographs of braid geometry were used to improve upon the computer graphics representations of unit cells. These unit cells were used to predict the elastic moduli with various degrees of sophistication. The simple and the complex analyses were generally in agreement but none adequately matched the experimental results for all the braids.
This dissertation evaluates receiver-based methods for mitigating the effects due to nonlinear bandlimited signal distortion present in high data rate satellite channels. The effects of the nonlinear bandlimited distortion is illustrated for digitally modulated signals. A lucid development of the low-pass Volterra discrete time model for a nonlinear communication channel is presented. In addition, finite-state machine models are explicitly developed for a nonlinear bandlimited satellite channel. A nonlinear fixed equalizer based on Volterra series has previously been studied for compensation of noiseless signal distortion due to a nonlinear satellite channel. This dissertation studies adaptive Volterra equalizers on a downlink-limited nonlinear bandlimited satellite channel. We employ as figure of merits performance in the mean-square error and probability of error senses. In addition, a receiver consisting of a fractionally-spaced equalizer (FSE) followed by a Volterra equalizer (FSE-Volterra) is found to give improvement beyond that gained by the Volterra equalizer. Significant probability of error performance improvement is found for multilevel modulation schemes. Also, it is found that probability of error improvement is more significant for modulation schemes, constant amplitude and multilevel, which require higher signal to noise ratios (i.e., higher modulation orders) for reliable operation. The maximum likelihood sequence detection (MLSD) receiver for a nonlinear satellite channel, a bank of matched filters followed by a Viterbi detector, serves as a probability of error lower bound for the Volterra and FSE-Volterra equalizers. However, this receiver has not been evaluated for a specific satellite channel. In this work, an MLSD receiver is evaluated for a specific downlink-limited satellite channel. Because of the bank of matched filters, the MLSD receiver may be high in complexity. Consequently, the probability of error performance of a more practical suboptimal MLSD receiver, requiring only a single receive filter, is evaluated.
The linear bicharacteristic scheme (LBS) was originally developed to improve unsteady solutions in computational acoustics and aeroacoustics. The LBS has previously been extended to treat lossy materials for one-dimensional problems. It is a classical leapfrog algorithm, but is combined with upwind bias in the spatial derivatives. This approach preserves the time-reversibility of the leapfrog algorithm, which results in no dissipation, and it permits more flexibility by the ability to adopt a characteristic based method. The use of characteristic variables allows the LBS to include the Perfectly Matched Layer boundary condition with no added storage or complexity. The LBS offers a central storage approach with lower dispersion than the Yee algorithm, plus it generalizes much easier to nonuniform grids. It has previously been applied to two and three-dimensional free-space electromagnetic propagation and scattering problems. This paper extends the LBS to the two-dimensional case. Results are presented for point source radiation problems, and the FDTD algorithm is chosen as a convenient reference for comparison.
The Orion European Service Module - Structural Test Article (E-STA) underwent sine vibration testing in 2016 using the Mechanical Vibration Facility (MVF) multi-axis shaker system at NASA Glenn Research Center’s (GRC) Plum Brook Station (PBS) Space Power Facility (SPF). The main objective was to verify the structural integrity of the European Service Module (ESM) under sine sweep dynamic qualification vibration testing. A secondary objective was to perform a fixed-base modal survey, while E-STA was still mounted to MVF, in order to achieve a test correlate the finite element model (FEM). To facilitate the E-STA system level correlation effort, a building block test approach was implemented. Modal tests were performed on two major subassemblies, the crew module/launch abort structure (CM/LAS) and the crew module adapter (CMA) mass simulators. These subassembly FEMs were individually correlated and then integrated into the E-STA FEM prior to the start of the E-STA sine vibration test. This paper summarizes the modal testing and model correlation efforts of both of these subassemblies and how the building block approach assisted in the overall correlation of the E-STA FEM. This paper will also cover modeling practices that should be avoided, recommended instrumentation positioning on complex structures, and the importance of the FEM geometrically matching CAD in sufficient detail in order to adequately replicate internal load paths. The goal of this paper is to inform the reader of the hard earned lessons learned and pitfalls to avoid when applying a building block test approach.
Deep generative neural networks have enabled modeling complex distributions, but incorporating physics knowledge into the neural networks is still challenging and is at the core of current physics-based machine learning research. To this end, we propose a physics generative neural network (PhysGNN), a new class of generative neural networks for learning unknown distributions in a physical system described by partial differential equations (PDE). PhysGNN couples PDE systems with generative neural networks. It is a fully differentiable model that allows back-propagation of gradients through both numerical PDE solvers and generative neural networks, and is trained by minimizing the discrete Wasserstein distance between generated and observed probability distributions of the PDE outputs using the stochastic gradient descent method. Moreover, PhysGNN does not require adversarial training like standard generative neural networks, which offers better stability than adversarial training. We show that PhysGNN can learn complex distributions in stochastic inverse problems, where conventional methods such as maximum likelihood estimation and momentum matching methods may be inapplicable when little knowledge is known about the form of unknown distributions or the physical model is too complex. Furthermore, our method allows physics-based generative neural network training for learning complex distributions in the context of differential equations.
CRISPR-Cas systems have become ubiquitous for genome editing in eukaryotic as well as bacterial systems. Cas9 forms a complex with a guide RNA (gRNA) and searches DNA for a matching sequence (target site) next to a protospacer adjacent motif (PAM). Once found, Cas9 cuts the DNA. Cas9 is revolutionary for the ability to change the RNA sequence and target a new site easily. However, while algorithms have been developed to predict gRNA-specific Cas9 activity, a fundamental biological understanding of gRNA-specific activity is lacking. Here, the number of PAM sites in the genome is effectively a large pool of inhibitory substrates, competing with the target site for the Cas9/gRNA complex. We demonstrate that increasing the number of non-target sites for a given gRNA reduces on-target activity in a dose-dependent manner. Furthermore, we show that the use of Cas9 mutants with increased PAM specificity toward a smaller subset of PAMs (or smaller pool of competitive substrates) improves cutting rates, while increased PAM promiscuity decreases cutting rates. Decreasing the potential search space by increasing PAM specificity provides a path toward improving on-target activity for slower high-fidelity Cas9 variants. Engineering improved PAM specificity to reduce the competitive search space offers an alternative strategy to engineer Cas9 variants with increased specificity and maintained on-target activity.
The in-depth understanding of the reported photoelectrochemical properties of the layered carbon nitride, poly(triazine imide)/LiCl (PTI/LiCl), has been limited by the apparent disorder of the Li/H atoms within its framework. To understand and resolve the current structural ambiguities, an optimized one-step flux synthesis (470 °C, 36 h, LiCl/KCl flux) was used to prepare PTI/LiCl and deuterated-PTI/LiCl in high purity. Its structure was characterized by a combination of neutron/X-ray diffraction and transmission electron microscopy. The range of possible Li/H atomic configurations was enumerated for the first time and, combined with total energy calculations, reveals a more complex energetic landscape than previously considered. Experimental data were fitted against all possible structural models, exhibiting the most consistency with a new orthorhombic model (Sp. Grp. Ama2) that also has the lowest total energy. In addition, a new Cu(I)-containing PTI (PTI/CuCl) was prepared with the more strongly scattering Cu(I) cations in place of Li, and most closely matching with the partially-disorder structure in Cmc2 1 . Thus, a complex configurational landscape of PTI is revealed to consist of a number of ordered crystalline structures that are new potential synthetic targets, such as with the use of metal-exchange reactions.
The current instrumentation for observing the complex flow fields in and around wind plants struggles to match the fidelity of existing simulation tools. As a result, these measurement limitations create a hurdle for validating and assessing the quality of the wind plant numerical models. This roadmap for instrumentation development recommendations was created to offer guidance on narrowing the gap between measurement and simulation fidelity. A process was established to identify where gaps in instrumentation exist for wind energy test campaigns by analyzing the capabilities of instrumentation for capturing the various important phenomena at the necessary resolution for both the science goal and validation objectives. To this end, a multi-disciplinary team of experts on instrumentation, wind energy, and atmospheric science was assembled to identify these significant instrumentation needs. A recommendation for instrumentation to be developed is provided, and the framework developed through this process is expected to be useful to the design of future test campaigns. The mapping tools developed for this process will be distributed as part of a future International Energy Agency Wind Technology Collaboration Program task on instrumentation development.
Accurate electronic-noise simulation is essential for low-energy physics in liquid-argon TPCs. More realistic noise modeling allows us to better tune reconstruction algorithms and more reliably assess and optimize signal-detection thresholds. We present a data-driven noise simulation framework developed for the ICEBERG test stand for DUNE that generates synthetic noise waveforms that reproduce both (i) the measured per-channel magnitude of the Fast Fourier Transform (FFT) and (ii) frequency-dependent channel-to-channel correlations observed in ICEBERG noise data. Using a dedicated noise-only dataset, we build a compact noise model containing per-channel FFT-magnitude targets together with a small set of band-wise cross-wire color matrices. White noise is generated in the frequency domain by drawing circular-symmetric complex Gaussian coefficients with random phases and scaling them to match the measured FFT-magnitude targets, and cross-wire correlations are subsequently imposed using the stored color matrices. The model and algorithm were integrated into the LArSoft + Wire-Cell Toolkit simulation chain and validated by comparing waveform structure, frequency-domain spectra, and band-limited correlation matrices from simulated noise and ICEBERG data. This approach can be extended to other LArTPC operating conditions.
CaptureFOAM provides utilities for fast and accurate direct air capture (DAC) contactor simulations, based on the OpenFOAM framework. At the core, CaptureFOAM is a suite of mass transfer and chemistry models built upon the OpenFOAM thin film model, which allows coarser mesh resolution and less constrictive time step requirements when compared to a traditional volume of fluid approach. This allows CaptureFOAM to conduct device-scale simulations for complex geometries including commercial packing materials and novel contactor shapes, matching experimental results in a wide variety of applications.
Near-IR photometry and spectroscopy of 5145 Pholus reveals that the visual to IR colors are unusually red and appear to show evidence for complex organic solids and/or ices on the surface. No compelling match is found with any present measurements of single-component ice or tholin samples.
This study provides the engineering science underpinnings for improved characterization and quantification of the interplay of gases with kerogen and minerals in shale. Natural nanoporous media such as shale (i.e., mudstone) often present with low permeability and dual porosity, making them difficult to characterize given the complex structural and chemical features across multiple scales. These structures give nanoporous solids a large surface area for gas to sorb. In oil and gas applications, full understanding of these media and their sorption characteristics are critical for evaluating gas reserves, flow, and storage for enhanced recovery and CO 2 sequestration potential. Other applications include CO 2 capture from industrial plants, hydrogen storage on sorbent surfaces, and heterogeneous catalysis in ammonia synthesis. Therefore, high-resolution experimental procedures are demanded to better understand the gas–solid behavior. In this study, CT imaging was applied on the sub-millimeter scale to shale samples (Eagle Ford and Wolfcamp) to improve quantitative agreement between CT-derived and pulse decay (mass balance) derived results. Improved CT imaging formulations are presented that better match mass balance results, highlighting the significance of gas sorption in complex nanoporous media. The proposed CT routine implemented on the Eagle Ford sample demonstrated a 17% error reduction (22% to 5%) when compared to the conventional CT procedure. These observations are consistent in the Wolfcamp sample, emphasizing the reliability of this technique for broader implementation of digital adsorption studies in nanoporous geomaterials.
Strings constructed from three-terminal tandem (3TT) solar cells offer the performance benefits of voltage-matching (which reduces sensitivity to spectral variation), but without the subcell voltage isolation required by four-terminal cells. However, the circuitry for a 3TT string can become complex, making circuit analysis more challenging. Here, we illustrate the essential features of “homogenous” voltage-matched (VM) 3TT strings, for which all 3TT cells in the string are nominally identical (with the same design/doping sequence, such that they can be fabricated on the same manufacturing line). Several representative VM string configurations are explicitly considered, and used to describe the general construction of string I(V) curves. End losses intrinsic to these strings are discussed in detail, along with mitigation strategies to minimize their impact. Our analysis agrees with experimental results for eight-cell strings constructed from GaInP/GaAs 3TT devices.
Epitaxial growth of complex oxides on large-area wafers, such as sapphire and silicon, represents a key step toward scalable oxide device production. Solid phase epitaxy allows the synthesis of γ-Al 2 O 3 on α-Al 2 O 3 and provides a template with a matched lattice constant and appropriate cubic symmetry for subsequent heteroepitaxial growth of perovskite complex oxides. Nb-doped SrTiO 3 thin films were deposited epitaxially on (111)-oriented γ-Al 2 O 3 intermediate layers on (0001) c-axis-oriented sapphire α-Al 2 O 3 crystals using pulsed laser deposition. The Nb:SrTiO 3 thin films with a thickness of 53 nm, grown at 700 °C on γ-Al 2 O 3 , reached fully relaxed lattice parameters and were epitaxially oriented with respect to the substrate. Nb:SrTiO 3 layers deposited using identical deposition conditions directly on α-Al 2 O 3 , without the γ-Al 2 O 3 intermediate layer, were polycrystalline. The sheet conductivity of Nb:SrTiO 3 grown on γ-Al 2 O 3 /α-Al 2 O 3 is more than ten times higher than that of Nb:SrTiO 3 grown directly on α-Al 2 O 3 without the γ-Al 2 O 3 layer. The results point to new directions for the integration of (111)-oriented pseudocubic perovskite complex oxides and the integration of epitaxial complex oxides over larger areas using α-Al 2 O 3 single-crystal substrates.
Abstract We consider variants of a recently developed Newton-CG algorithm for nonconvex problems (Royer, C. W. & Wright, S. J. (2018) Complexity analysis of second-order line-search algorithms for smooth nonconvex optimization. SIAM J. Optim., 28, 1448–1477) in which inexact estimates of the gradient and the Hessian information are used for various steps. Under certain conditions on the inexactness measures, we derive iteration complexity bounds for achieving $\epsilon $-approximate second-order optimality that match best-known lower bounds. Our inexactness condition on the gradient is adaptive, allowing for crude accuracy in regions with large gradients. We describe two variants of our approach, one in which the step size along the computed search direction is chosen adaptively, and another in which the step size is pre-defined. To obtain second-order optimality, our algorithms will make use of a negative curvature direction on some steps. These directions can be obtained, with high probability, using the randomized Lanczos algorithm. In this sense, all of our results hold with high probability over the run of the algorithm. We evaluate the performance of our proposed algorithms empirically on several machine learning models. Our approach is a first attempt to introduce inexact Hessian and/or gradient information into the Newton-CG algorithm of Royer & Wright (2018, Complexity analysis of second-order line-search algorithms for smooth nonconvex optimization. SIAM J. Optim., 28, 1448–1477).