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A self-similar model for the flow evolution in a turbulent mixing layer is presented. The model is dependent on the interaction between vortex pairing, unstable collective excitation, and turbulent diffusion. An integrable nonlinear equation governing the flow expansion is derived from the model.
Laminated continuous fiber polymeric composites are capable of sustaining substantial load induced microstructural damage prior to component failure. Because this damage eventually leads to catastrophic failure, it is essential to capture the mechanics of progressive damage in any cogent life prediction model. For the past several years the authors have been developing one solution approach to this problem. In this approach the mechanics of matrix cracking and delamination are accounted for via locally averaged internal variables which account for the kinematics of microcracking. Damage progression is predicted by using phenomenologically based damage evolution laws which depend on the load history. The result is a nonlinear and path dependent constitutive model which has previously been implemented to a finite element computer code for analysis of structural components. Using an appropriate failure model, this algorithm can be used to predict component life. In this paper the model will be utilized to demonstrate the ability to predict the load path dependence of the damage and stresses in plates subjected to fatigue loading.
The fidelity of climate projections is often undermined by biases in climate models due to their simplification or misrepresentation of unresolved climate processes. While various bias correction methods have been developed to post-process model outputs to match observations, existing approaches usually focus on limited, low-order statistics, or break either the spatiotemporal consistency of the target variable, or its dependency upon model resolved dynamics. We develop a Regularized Adversarial Domain Adaptation (RADA) methodology to overcome these deficiencies, and enhance efficient identification and correction of climate model biases. Instead of pre-assuming the spatiotemporal characteristics of model biases, we apply discriminative neural networks to distinguish historical climate simulation samples and observation samples. The evidences based on which the discriminative neural networks make distinctions are applied to train the domain adaptation neural networks to bias correct climate simulations. We regularize the domain adaptation neural networks using cycle-consistent statistical and dynamical constraints. An application to daily precipitation projection over the contiguous United States shows that our methodology can correct all the considered moments of daily precipitation at approximately $1^\circ$ resolution, ensures spatiotemporal consistency and inter-field correlations, and can discriminate between different dynamical conditions. Our methodology offers a powerful tool for disentangling model parameterization biases from their interactions with the chaotic evolution of climate dynamics, opening a novel avenue toward big-data enhanced climate predictions.
Methane is photolyzed by the solar UV in the stratosphere of Saturn. Subsequent photochemistry leads to the production of acetylene (C2H2) and diacetylene (C4H2). These species are produced where it is relatively warm (T is greater than or equal to 140 K), but the tropopause temperature of Saturn (approximately 80 K) is low enough that these two species may freeze out to their respective ices. Numerical models which include both photochemistry and condensation loss make predictions about the mixing ratios of these species and haze production rates. These models are dependent upon knowing reaction pathways and their associated kinetic reaction rate constants and vapor pressures. How uncertainties in the chemistry and improvements in the vapor pressures affect model predictions for Saturn are discussed.
Studies of size effects on thermal conductivity typically necessitate the fabrication of a comprehensive film thickness series. In this Letter, we demonstrate how material fabricated in a wedged geometry can enable similar, yet higher-throughput measurements to accelerate experimental analysis. Frequency domain thermoreflectance (FDTR) is used to simultaneously determine the thermal conductivity and thickness of a wedged silicon film for thicknesses between 100 nm and 17 μm by considering these features as fitting parameters in a thermal model. FDTR-deduced thicknesses are compared to values obtained from cross-sectional scanning electron microscopy, and corresponding thermal conductivity measurements are compared against several thickness-dependent analytical models based upon solutions to the Boltzmann transport equation. Our results demonstrate how the insight gained from a series of thin films can be obtained via fabrication of a single sample.
A general model for time-dependent breakdown in metal-oxide-silicon (MOS) structures is developed and related to experimental measurements on samples deliberately contaminated with Na. A statistical method is used for measuring the breakdown probability as a function of log time and applied field. It is shown that three time regions of breakdown can be explained respectively in terms of silicon surface defects, ion emission from the metal interface, and lateral ion diffusion at the silicon interface.
The objective of this work is to construct and evaluate subgrid-scale models that depend on both the strain rate and the vorticity. This will be accomplished by first assuming that the subgrid-scale stress is a function of the strain and rotation rate tensors. Extensions of the Caley-Hamilton theorem can then be used to write the assumed functional dependence explicitly in the form of a tensor polynomial involving products of the strain and rotation rates. Finally, use of this explicit expression as a subgrid-scale model will be evaluated using direct numerical simulation data for homogeneous, isotropic turbulence.
The basic concept of some stationary models and the way in which these models are used for and in how far they influence the determination of stellar and wind parameters of massive hot stars are discussed. However, as follows directly from the assumption of stationarity, these models are inherently incapable of describing a number of additional observational features, which immediately show that the nonstationary aspects of the wind must be of significant importance. A number of these features are discussed: the soft X-ray emission; the discrete absorption components; the temporal variability of the wind lines, where the blue edges are varying most significantly while the red emission part remains relatively constant; the electron scattering wings of recombination lines in Wolf-Rayet stars; the black troughs in saturated P-Cygni profiles; the variability of optical lines; and the nonthermal radio emission observed in massive stars. The basic picture resulting from the present dynamical models is discussed.
The 3D Virtual Astromaterials Samples (3DVAS) collection is a multi-year funded project to create a digital database of sixty Apollo Lunar and Antarctic Meteorite samples following non-destructive documentation conservation protocols. After initial image processing, the photos are evaluated and processed using unique structure-from-motion photogrammetric techniques in a high performance modelling software designed to create a 3D model from 2D images: Agisoft Photoscan Pro. Agisoft Photoscan Pro uses image processing algorithms and techniques originating in computer vision to resolve 3D models for accurate and detailed visualization of a subject. The software provides a stepwise process that is tailored per model based on spatial and specular reflectance properties, for example. The process includes: photo alignment, creation of a dense point cloud, mesh, and finally texture. Photo alignment is dependent on model properties. The 3DVAS process requires a special rotation platform with calibrated photogrammetric targets, specific distance rotation protocols, and a contrasting background for alignment and scale accuracy. As a result of the photographic process, alignment will complete with two mirrored hemispheres that, in a sense, represent the 2D images overlapping to create a 3D model. Each dense point cloud is analyzed with provided statistical measures in a gradual selection process to eliminate outliers. The point cloud is reduced to include only data valuable to the final model. When a precise dense point cloud is achieved, a mesh and texture are applied. Each model is scaled with scale bar accuracies within 100 microns. Each sample has its own intimate process for modelling; there is no standard for the parameters required in the final creation of a high resolution model. By processing multiple samples, a skill is gained in practice to allow a close definition of the original sample and will result in the most detailed version of the sample shell. This process completes one-fifth of the 3DVAS protocol for providing accurate digital documentation. Each model shell is merged with X-ray Computed Tomography data to create a full volumetric sample. All 3DVAS data will be served on NASA's Astromaterials Acquisition and Curation website with an early subset of data available in 2019 and the 3D Virtual Astromaterials Samples Collection launch in 2020.
The importance of interstellar neutrals in understanding and modelling the global interaction of the solar wind with the local interstellar medium is becoming increasingly apparent. Unfortunately the self-consistent inclusion of a neutral interstellar component into time-dependent, dynamical models is formidably difficult due to the extremely large mean free paths associated with the neutrals and the creation of essentially different neutral distributions from different interaction regions of the solar wind and LISM. In full generality, one has to address the problem by treating the neutrals kinetically with the appropriate extinction and creation source terms. In this paper, a limited set of simulations will be presented in which the solar wind and interstellar plasma is described as a 2D fully compressible time-dependent fluid while the interstellar neutral distribution is derived by solving the appropriate Boltzmann equation directly.
The T(e) variation in the high-latitude ionosphere at altitudes between 120 and 800 km has been modeled for solar maximum, winter solstice, and strong magnetic activity conditions. The calculated electron temperatures are consistent with the plasma densities and ion temperatures computed from a time-dependent ionospheric model. Heating rates for both solar EUV and auroral precipitation were included. In general, the predicted UT variation of the electron temperature that results from the displacement between the magnetic and geographic poles is only a few hundred degrees. However, in sunlit trough regions, T(e) hot spots develop, and these hot spots show a marked UT variation, by as much as 2500 K. The dominant parameter controlling the T(e) variation above 200 km is the magnetospheric heat flux into the ionosphere, which is essentially unknown. For realistic values of the magnetospheric heat flux, the maximum electron temperature ranges from 5000 to 10,000 K at 800 km. A magnetospheric heat flux is particularly effective in enhancing trough electron temperatures. In general, the electron heat flux at high altitudes is uniquely related to the electron temperature and gradient, except on auroral field lines where thermoelectric heat flow is important.
The results from studies on polar wind ion heating due to kinetic ion beam instabilities and the effects of such ion heating on the outflow of O(+) in the polar wind are presented and discussed. First, the linear instabilities associated with an O(+) and H(+) polar wind plasma in the presence of O(+) and H(+) beams for a range of O(+)/H(+) beam densities, T(sub e)/T(sub i), and ion beam speeds were examined. Then, nonlinear heating of the polar wind ions was studied, using numerical simulations. The O(+) and H(+) polar wind ions were modeled by isotropic Maxwellian distributions, and the electrons, O(+) beams, and H(+) beams were modeled by drifting Maxwellian distributions. The effects of the kinetic ion heating on the outflow of the polar wind ions were examined from the ionosphere, using a time-dependent hydrodynamic model. A numerical code to solve the O(+) and H(+) continuity and momentum equations in a flux tube from ionospheric to magnetospheric altitudes were developed. The effects of ion heating were included by allowing for the altitudinal variation of the ion temperatures in the momentum equation. The ion temperature profiles were specified based on the ion heating characteristics found from previous kinetic simulations. It was assumed that heating occurred above 1500 km and increased to a saturated value of temperature that was obtained directly from the kinetic simulation study. The characteristics of the dynamical polar wind without ion heating were studied, and a flux tube on closed field lines that suddenly became open at t = 0 was simulated. Then, the effects of ion heating were included. To gain some physical insight, two limiting cases were considered: preferential H(+) heating and preferential O(+) heating. How O(+) heating can lead to enhanced polar wind O(+) fluxes in the polar magnetosphere is shown.
Current global atmospheric reanalysis products such as ERA-5, MERRA-2, and JRA-55 provide estimates of land surface states and fluxes, including soil moisture, soil temperature, snow mass, latent and sensible heat fluxes, and runoff. These land surface estimates are based on land surface process models and, depending on the reanalysis product, on precipitation observations or the assimilation of land surface observations of soil moisture and snow conditions from satellites and in situ networks. The land models used in the current global atmospheric reanalysis systems are generally focused on water and energy balance processes, with prescribed static land cover and prescribed climatological vegetation conditions. That is, current global atmospheric reanalysis products do not reflect changes in land use or land cover, nor do they provide dynamic estimates of the land carbon cycle. These and other gaps, including the omission of anthropogenic processes such as irrigation in the land model, need to be addressed in the development of the next generation Earth system reanalysis systems. This presentation provides an overview of the state-of-the-art and future developments of land surface estimates in global reanalysis systems.
We discuss open heavy flavor (D-meson) and quarkonium (J/ψ) production in high multiplicity proton-proton (p+p) and proton-nucleus (p+A) collisions at the LHC in the impact parameter dependent saturation model. A key ingredient in our calculations is the fluctuations of the gluon saturation scale at large-x at each impact parameter, reflecting rare parton configurations inside the projectile and target. Such initial state fluctuations have been used to describe the multiplicity distribution of D-meson and J/ψ production yield at mid rapidity in small collision systems at the LHC. In these proceedings, we examine the rapidity dependence of J/ψ production and emphasize its importance in constraining initial state models of high multiplicity events in small systems.
Cookoff experiments of powdered and pressed TATB-based plastic bonded explosives (PBXs) have been modeled using a pressure-dependent universal cookoff model (UCM) in combination with a micromechanics pressurization (MMP) model described in a companion paper. The MMP model is based on the accumulation of decomposition gases at nucleation sites that load the surrounding TATB crystals and binder. This is the first cookoff model to use an analytical mechanics solution for compressibility and thermal expansion to describe internal pressurization caused by both temperature and decomposition occurring within closed-pore explosives. This approach produces more accurate predictions of ignition time and pressurization within high-density explosives than simple equation-of-state models. The current paper gives details of the reaction chemistry, model parameters, predicted uncertainty, and validation using experiments from multiple laboratories with errors less than 6 %. The UCM/MMP model framework gives more accurate thermal ignition predictions for high density explosives that are initially impermeable to decomposition gases.
A summary of the conceptual models to be used in representing slit (ST) and engineered trenches (ET) in PORFLOW (ACRi 2018) simulations as part of the performance assessment (PA) of the E-Area Low Level Waste Facility (ELLWF) is presented. Key details that are discussed include: model geometries, spatially dependent hydro-stratigraphic representations, model dimensionality, and boundary conditions (i.e., infiltration rates, cover overhangs, subsidence). Accounting for differences in the percent of non-crushable materials, eighteen unique models, defined by seven hydro-stratigraphic groupings, will be used to represent slit and engineered trenches.
The approach for the method development assumes that, for a thermally loaded structure, the overall strain history is defined by linear elastic analysis. The local stress history at a fatigue critical location is then determined from a one dimensional material behavior model and the local strain and temperature conditions. Three material models are currently being evaluated to assess their ability to predict relevant high temperature cyclic material response characteristics. They are: a time independent classical plasticity and creep representation, a time dependent viscoplastic model capable of predicting combined creep and plasticity effects, and an approximate elastic analysis approach that uses a series of stress-strain curves and a cyclic hardening model to determine reverse plasticity.
High power multiple quantum well AlGaAs diode laser master oscillator - power amplifier (MOPA) systems were examined both experimentally and theoretically. For two pass operation, it was found that powers in excess of 0.3 W per 100 micrometers of facet length were achievable while maintaining diffraction-limited beam quality. Internal electrical-to-optical conversion efficiencies as high as 25 percent were observed at an internal amplifier gain of 9 dB. Theoretical modeling of multiple quantum well amplifiers was done using appropriate rate equations and a heuristic model of the carrier density dependent gain. The model gave a qualitative agreement with the experimental results. In addition, the model allowed exploration of a wider design space for the amplifiers. The model predicted that internal electrical-to-optical conversion efficiencies in excess of 50 percent should be achievable with careful system design. The model predicted that no global optimum design exists, but gain, efficiency, and optical confinement (coupling efficiency) can be mutually adjusted to meet a specific system requirement. A three quantum well, low optical confinement amplifier was fabricated using molecular beam epitaxial growth. Coherent beam combining of two high power amplifiers injected from a common master oscillator was also examined. Coherent beam combining with an efficiency of 93 percent resulted in a single beam having diffraction-limited characteristics. This beam combining efficiency is a world record result for such a system. Interferometric observations of the output of the amplifier indicated that spatial mode matching was a significant factor in the less than perfect beam combining. Finally, the system issues of arrays of amplifiers in a coherent beam combining system were investigated. Based upon experimentally observed parameters coherent beam combining could result in a megawatt-scale coherent beam with a 10 percent electrical-to-optical conversion efficiency.