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At least 865 records · Page 48

Interplay Between Crustal‐Scale Thrusting, High Metamorphic Heating Rates, and the Development of Inverted Thermal‐Metamorphic Gradients: Numerical Models and Examples From the Caledonides of Northern Scotland

Abstract Understanding the processes that produce high prograde metamorphic heating rates and the development of inverted metamorphic sequences in collisional thrust belts remains a fundamental challenge for tectonics and metamorphic petrology. New 2D finite element models of crustal‐scale thrusts with variable slip rates (10, 20, 35, 50 km Myr −1 ) are used to examine how thrust sheet emplacement contributes to these processes. In the models, average prograde heating rates of 31–118 °C Myr −1 are observed in the footwall, with maximum transient heating rates of ∼167 °C Myr −1 occurring at the highest slip rate. Also, thrust sheet emplacement produces an inverted thermal gradient in the model footwall. At slip rates of 10 km Myr −1 , heating magnitudes >200 °C are observed >7 km structurally beneath the thrust plane. At slip rates of 20–50 km Myr −1 , models produce thermal penetration depths of 4–5 km for similar heating magnitudes. Petrologically determined heating rates for thrust footwalls in the Scandian orogenic wedge of northern Scotland mostly yield rates consistent with model results (10–230 °C Myr −1 ). The model‐derived magnitude of inverted thermal gradients is also similar to those indicated in texturally determined deformation temperature transects across the Scandian orogenic wedge (100 °C–180 °C). Combined, these results indicate that high heating rates can be produced by fault slip at typical plate velocities. Additionally, this implies that crustal‐scale thrusts are likely to produce inverted metamorphic sequences in most systems, provided that P‐T conditions during slip allow for metamorphic or recrystallization processes that would preserve evidence for such features.

Thigpen, J. Ryan↗

Temperature-plant pigment-optical relations in a recurrent offshore mesoscale eddy near Point Conception, California

The temperature-plant pigment-optical structure of a mesoscale anticyclonic eddy consistently found in shipboard surveys and satellite-sensed data several hundred kilometers southwest of Point Conception, CA, is described on three different time scales (100-day mesoscale, annual, and several-year). The satellite coastal zone color scanner (CZCS) ocean color imagery detected the near-surface chlorophyll structure of the eddy, but in situ optical and plant pigment data suggest that such imagery does not provide a good estimate of the integrated chlorophyll field of the eddy. The temperature and plant pigment boundaries of the eddy, as determined from two-dimensional gradients of advanced very high resolution radiometer (AVHRR) and CZCS imagery, do not coincide spatially. This and in situ temperature, plant pigment, and optical structure provide additional evidence that some eddy systems in the California Current are not isolated vortex systems but rather continuously entrain waters of nonlocal origin laterally into their upper layers. Within the California Current a ratio of AVHRR/CZCS data is useful for separating inshore from oceanic water masses and following their surface entrainment by offshore vortices. The historical 28-year California Cooperative Oceanic Fisheries Investigations data for the Point Conception region of the California Current and remotely sensed data over this region show that the Point Conception eddy is a recurrent feature in the offshore California Current. Moreover, the available data provide evidence that a large number of warm-core mesoscale eddies occur simultaneously in a transition zone between coastal and oceanic regimes, that these features recur at preferred locations within the transition zone, and that this family of eddies should impose a significant offshore boundary condition on the flow of the California Current.

Simpson, James J.↗

A New View of the Dynamics of Reynolds Stress Generation in Turbulent Boundary Layers

The structure of a numerically simulated turbulent boundary layer over a flat plate at Re(theta) = 670 was studied using the invariants of the velocity gradient tensor (Q and R) and a related scalar quantity, the cubic discriminant (D = 27R(exp 2)/4 + Q(exp 3)). These invariants have previously been used to study the properties of the small-scale motions responsible for the dissipation of turbulent kinetic energy. In addition, these scalar quantities allow the local flow patterns to be unambiguously classified according to the terminology proposed by Chong et al. The use of the discriminant as a marker of coherent motions reveals complex, large-scale flow structures that are shown to be associated with the generation of Reynolds shear stress -u'v'(bar). These motions are characterized by high spatial gradients of the discriminant and are believed to be an important part of the mechanism that sustains turbulence in the near-wall region.

Cantwell, Brian J.↗

A review of quasi-coherent structures in a numerically simulated turbulent boundary layer

Preliminary results of a comprehensive study of the structural aspects of a numerically simulated number turbulent boundary layer are presented. A direct Navier-Stokes simulation of a flat-plate, zero pressure gradient boundary layer at Re0 = 670 was used. Most of the known nonrandom, coherent features of turbulent boundary layers are confirmed in the simulation, and several new aspects of their spatial character are reported. The spatial relationships between many of the various structures are described, forming the basis for a more complete kinematical picture of boundary layer physics than has been previously known. In particular, the importance of vortex structures of various forms to the generation of Reynolds shear stress is investigated.

Robinson, S. K.↗

Carbon-sequestration gradient insulation composites

The massive use of carbon-sequestration building materials promises a potential global carbon sink in decarbonizing the building industry. Renewable biogenic materials from abundant agriculture waste for building practice have been around over thousands of years. However, in addition to their flammability and moisture problems, addressing their low thermal and structural performance is also becoming indispensable and urgent when it comes to environmentally sustainable and energy-efficient buildings. Here, we report a nature-inspired biogenic gradient insulation composite with an optimized silica concentration of 30 wt %, a density of 0.246 g/cm 3 , and a porosity of 86%. The gradient hybrid composite exhibits a thermal conductivity of 28.2 mW m -1 K -1 , which is the lowest achieved under optimal preparation conditions. Here, it also shows a flexural modulus of 590 MPa for the aerogel-rich layer without surface modification, and it demonstrates superior fire retardancy and superhydrophobicity after surface treatment.

36 MATERIALS SCIENCE↗

From Molecules to Solids: A vdW-DF-C09 Case Study of the Mercury Dihalides

The mercury dihalides show a remarkable diversity in the structural preferences in their minimum energy structure types, spanning molecular to strongly bound ionic solids. A challenge in the development of density functional methods for extended systems is to arrive at strategies that serve equally well such a broad range of bonding modes or structural preferences. The chemical bonding and the stabilities of mercury dihalides and the general utility and reliability of the van der Waals density functional with C09 exchange (vdW-DF-C09) in predicting or describing the energetics and structural preferences in these metal dihalides is examined. Here, we show that, in contrast with the uncorrected generalized gradient approximation of the Perdew-Burke-Erzenhoff (PBE) exchange-correlation functional, qualitative and quantitative patterns in the bonding of the mercury dihalide solids are well reproduced with vdW-DF-C09 for the full series of HgX 2 systems for X = F, Cl, Br, and I. The possible existence of a low-temperature cotunnite polymorph for HgF 2 and PbF 2 is posited.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Classifying and analyzing small-angle scattering data using weighted k nearest neighbors machine learning techniques

A consistent challenge for both new and expert practitioners of small-angle scattering (SAS) lies in determining how to analyze the data, given the limited information content of said data and the large number of models that can be employed. Machine learning (ML) methods are powerful tools for classifying data that have found diverse applications in many fields of science. Here, ML methods are applied to the problem of classifying SAS data for the most appropriate model to use for data analysis. The approach employed is built around the method of weighted k nearest neighbors (wKNN), and utilizes a subset of the models implemented in the SasView package (https://www.sasview.org/) for generating a well defined set of training and testing data. The prediction rate of the wKNN method implemented here using a subset of SasView models is reasonably good for many of the models, but has difficulty with others, notably those based on spherical structures. A novel expansion of the wKNN method was also developed, which uses Gaussian processes to produce local surrogate models for the classification, and this significantly improves the classification accuracy. Further, by integrating a stochastic gradient descent method during post-processing, it is possible to leverage the local surrogate model both to classify the SAS data with high accuracy and to predict the structural parameters that best describe the data. The linking of data classification and model fitting has the potential to facilitate the translation of measured data into results for both novice and expert practitioners of SAS.

97 MATHEMATICS AND COMPUTING↗

MULTI-LEADER: MULTI-source LEarning-Accelerated Design of high-Efficiency multi-stage compRessor (Final Technical Report)

The objective of MULTI-LEADER is to cut design costs by 80% while generating more energy-efficient designs of multi-stage compressors by developing and implementing novel machine learning (ML) techniques, which enable faster and fewer design iterations, improved solver performance, and concurrent multi-disciplinary design. Current industrial practices for the design of multi-stage compressors involve simulation-based design optimization with successive levels of model fidelity, iteratively evaluated between distinct disciplines, one stage at a time to tackle the high dimensional design variations. This project addresses these key design challenges: (1) concurrent optimization of multiple stages under many non-linear constraints; (2) multitude of evaluation of high-fidelity and expensive solvers and their gradients during optimization convergence in high-dimensional design; (3) multi-disciplinary design to maximize aerodynamic performance while guaranteeing structural integrity and additive manufacturability; (4) utilization of multiple fidelity of solvers with disparate parameterization and modeling assumptions. MULTI-LEADER achieved more than 5x speed up in detailed design of more energy-efficient compressors via these machine learning (ML) innovations: (i) rapid design surrogates by multi-source learning from diverse fidelities across multiple disciplines, (ii) physics-constrained data-augmented modeling for improved empiricism, (iii) generative manifold embedding for high dimensional concurrent design without gradient information; (iv) budget-constrained fidelity-adaptive sampling towards fewer design iterations.

33 ADVANCED PROPULSION SYSTEMS↗

3D Quantification of Elemental Gradients within Heterostructured Particles of Battery Cathodes

Heterogenous architectures with elemental gradients tailored within particles have been pursued to combat the instabilities limiting Ni-rich cathode materials for lithium-ion batteries. The growth of different compositional layers is accomplished during the synthesis of hydroxide precursors. However, the extent to which these concentration gradients are modified during high-temperature reactions is difficult to establish in their intact, spherical form. Here, we show the entire three-dimensional structure of a secondary particle can be resolved nondestructively with differential X-ray absorption spectroscopy (XAS) through transmission X-ray microscopy (TXM). The relationship between particle location and elemental content was fully quantified, with high statistical significance, for heterostructures possessing different compositional gradients in the precursors with 90:5:5 Ni:Mn:Co core compositions. Reduced elemental heterogeneity was observed after high-temperature synthesis, but gradients remained. In conclusion, the methodology presented should be used to guide synthesis while assuring that gains in electrochemical performance are linked to precise elemental distributions at the nanoscale.

25 ENERGY STORAGE↗

High resolution magnetic resonance imaging of the calcaneus: age-related changes in trabecular structure and comparison with dual X-ray absorptiometry measurements

A high-resolution magnetic resonance imaging (MRI) protocol, together with specialized image processing techniques, was applied to the quantitative measurement of age-related changes in calcaneal trabecular structure. The reproducibility of the technique was assessed and the annual rates of change for several trabecular structure parameters were measured. The MR-derived trabecular parameters were compared with calcaneal bone mineral density (BMD), measured by dual X-ray absorptiometry (DXA) in the same subjects. Sagittal MR images were acquired at 1.5 T in 23 healthy women (mean age: 49.3 +/- 16.6 [SD]), using a three-dimensional gradient echo sequence. Image analysis procedures included internal gray-scale calibration, bone and marrow segmentation, and run-length methods. Three trabecular structure parameters, apparent bone volume (ABV/TV), intercept thickness (I.Th), and intercept separation (I.Sp) were calculated from the MR images. The short- and long-term precision errors (mean %CV) of these measured parameters were in the ranges 1-2% and 3-6%, respectively. Linear regression of the trabecular structure parameters vs. age showed significant correlation: ABV/TV (r2 = 33.7%, P < 0.0037), I.Th (r2 = 26.6%, P < 0.0118), I.Sp (r2 = 28.9%, P < 0.0081). These trends with age were also expressed as annual rates of change: ABV/TV (-0.52%/year), I.Th (-0.33%/year), and I.Sp (0.59%/year). Linear regression analysis also showed significant correlation between the MR-derived trabecular structure parameters and calcaneal BMD values. Although a larger group of subjects is needed to better define the age-related changes in trabecular structure parameters and their relation to BMD, these preliminary results demonstrate that high-resolution MRI may potentially be useful for the quantitative assessment of trabecular structure.

NASA Discipline Number 26-10↗

Exploring Gradient-Based Multi-directional Controls in GANs

Generative Adversarial Networks (GANs) have been widely applied in modeling diverse image distributions. However, despite its impressive applications, the structure of the latent space in GANs largely remains as a black-box, leaving its controllable generation an open problem, especially when spurious correlations between different semantic attributes exist in the image distributions. To address this problem, previous methods typically learn linear directions or individual channels that control semantic attributes in the image space. However, they often suffer from imperfect disentanglement, or are unable to obtain multi-directional controls. Furthermore, in this work, in light of the above challenges, we propose a novel approach that discovers nonlinear controls, which enables multi-directional manipulation as well as effective disentanglement, based on gradient information in the learned GAN latent space. More specifically, we first learn interpolation directions by following the gradients from classification networks trained separately on the attributes, and then navigate the latent space by exclusively controlling channels activated for the target attribute in the learned directions. Empirically, with small training data, our approach is able to gain fine-grained controls over a diverse set of bi-directional and multi-directional attributes, and we showcase its ability to achieve disentanglement significantly better than state-of-the-art methods both qualitatively and quantitatively.

97 MATHEMATICS AND COMPUTING↗

Modeling Arctic boundary layer cloud streets at grey-zone resolutions

To better understand how model resolution affects the formation of Arctic boundary layer clouds, we investigated the influence of grid spacing on simulating cloud streets that occurred near Utqiagvik (formerly Barrow), Alaska on 2 May 2013 and were observed by the Moderate Resolution Imaging Spectroradiometer (MODIS). The Weather Research and Forecasting model was used to simulate the clouds using nested domains with increasingly fine resolution ranging from a horizontal grid spacing of 27 km in the boundary-layer-parameterized mesoscale domain to a grid spacing of 0.111 km in the large-eddy-permitting domain. We investigated the model-simulated mesoscale environment, horizontal and vertical cloud structures, boundary layer stability, and cloud properties, all of which were subsequently used to interpret the observed roll-cloud case. Increasing model resolution led to a transition from a more buoyant boundary layer to a more shear-driven turbulent boundary layer. The clouds were stratiform-like in the mesoscale domain, but as the model resolution increased, roll-like structures, aligned along the wind field, appeared with ever smaller wavelengths. A stronger vertical water vapor gradient occurred above the cloud layers with decreasing grid spacing. With fixed model grid spacing at 0.333 km, changing the model configuration from a boundary layer parameterization to a large-eddy-permitting scheme produced a more shear-driven and less unstable environment, a stronger vertical water vapor gradient below the cloud layers, and the wavelengths of the rolls decreased slightly. In this study, only the large-eddy-permitting simulation with gird spacing of 0.111 km was sufficient to model the observed roll clouds.

Lai, Hui-Wen↗

Collisionless relativistic magnetic reconnection driven by electron vortices in laser-plasma interaction

Magnetic reconnection (MR) is a fundamental process in space and laboratory plasmas. The appearance of high power lasers opens a new way to investigate MR under the relativistic condition. In this paper, relativistic collisionless MR driven by two ultra-intense lasers and a pair of asymmetric targets is studied numerically via the kinetic simulations. The static magnetic fields produced by the electron vortex structures with opposite magnetic polarities approach each other driven by the magnetic pressure and the density gradient. The antiparallel magnetic fields annihilate accompanied with the topological variation and the corresponding magnetic field energy is being dissipated to the kinetic energy of the nonthermal charged particles. Besides the outflows along the current sheet, a fast particle bunch is accelerated perpendicularly contributed by the displacement current.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Toward Machine Learning-Driven Mass Spectrometric Identification of Trichothecenes in the Absence of Standard Reference Materials

While a significant body of work exists on the detection of commonly known trichothecene toxins, biological, environmental, and other transformational processes can generate many under-characterized and unknown modified trichothecenes. Lacking both analytical reference standards and associated mass spectral databases, identification of these modified compounds reflects both a challenge and a critical gap from forensic and public health perspectives. Here we report here the application of machine learning (ML) techniques toward identification of discriminative fragment ions from mass spectrometric data that can be exploited to detect evidence of type A and B trichothecenes. The goal of this work is to establish a new method for the identification of unknown, though structurally similar trichothecenes, by leveraging objective ML techniques. Discriminative fragments derived from a series of gradient-boosted machine learners are then used to develop ML-driven precursor ion scan (PIS) methods on a triple quadrupole mass spectrometer (QQQ) for screening of “unknown unknown” trichothecenes. Specifically, we apply the PIS method to a laboratory-synthesized trichothecene, a first step in demonstrating the power of alternative, machine learning-driven mass spectrometric methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamics of Bottlebrush Polymers in Solution by Neutron Spin Echo Spectroscopy

In this work, we present dynamical and morphological studies on poly(dimethylsiloxane) (PDMS)-based bottlebrush polymers in solution. A combination of small-angle neutron scattering (SANS), pulsed field gradient nuclear magnetic resonance (PFG NMR), and neutron spin echo (NSE) spectroscopy was used to identify structural changes inherent in changing the side-chain length while keeping the backbone constant. These morphological changes are mirrored in the diffusion coefficient determined by PFG NMR, resulting in two coefficients for the elongated and one for the more spherical sample. Faster motions are tracked by NSE using the advantage of time- and length-scale resolutions with the diffusion coefficient predetermined by PFG NMR. Hereby, the sample with short side chains relaxes like wormlike micelles considering the longitudinal direction, whereas the dynamics along the radial extension shows a much stronger Q-dependence as known from any theory. The dynamical behavior within the blob region, covered with the more spherical sample, follows the predictions of Zimm as well as of Zilman and Granek (ZG).

36 MATERIALS SCIENCE↗

Mix and match—a versatile equilibrium approach for hybrid colloidal synthesis

Colloidal synthesis is a powerful bottom-up approach for programmed self-assembly which holds promise for both research and industry. While diverse, each synthetic process is typically restricted to a specific chemistry. Many applications however require composite materials, whereas a chemical equilibrium can typically only match one material but not the other. Here, a scalable general approach is presented, alleviating the dependency on a specific chemical reaction, by resorting to a mechanical equilibrium; an isopycnic density-gradient-step is tailored to form clusters with prescribed composition. Valence control is demonstrated, making dimers, trimers, and tetramers with purity as high as 96%. The measured kinetics shows a scaleable throughput. The density gradient step plays a dual role of both filtering out undesired products and concentrating the target structures. The “Mix-and-Match” approach is general, and applies to a broad range of colloidal matter: diverse material compositions (plastics, glasses, and emulsions); a range of colloidal interactions (van der Waals, Coulomb, and DNA hybridization); and a spectrum of sizes (nanoscale to multiple micrometers). Lastly, the strength of the method is displayed by producing a monodisperse suspension from a highly polydisperse emulsion. The ability to combine colloids into architectures of hybrid materials has applications in pharmaceuticals, cosmetics, and photonics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cryogenic aspects of a 20 MW class low-temperature superconducting generator for the renewables industry

In this paper we give a progress update on the cryogenic design for cooling a 20 MW class, partially superconducting generator with stationary field coils for offshore wind renewables industry [1-2]. This is a continuation of an earlier program on a 10 MW system dating back ten years. Whereas this new power rating increase leads to a radial diameter expansion of the superconducting field coils from 4 to > 9.5 m, it maintains the axial length. We show the design based on this scaled up with enlarged diameter. The field coil size increase asks for higher cooling power that leads to a bigger cold box size to accommodate the cryocoolers. In the design, as many as 8 cryocoolers can be accessed and serviced from the nacelle that houses the main cryogenic components. A typical thermal load balance sheet with all components is given and compared against the available cryocooler cooling power at different operating conditions. Due to the cryocoolers’ local point of contact cooling within the nacelle, the temperature gradient of the thermal shield that fully encloses the cold mass with its embedded field coils needs to be balanced out to minimize the heat burden on the field coils. This requires additional analytical efforts and implementation of further design features. The extended nacelle houses the cold box with its cryogenic infrastructure. The interface for the envisaged cryogenic pushbutton closed-loop circulating system remains invisible, requires no handling of cryogenic liquids and is hermetically closed. The field coil diameter increase also leads to a greater initial helium gas storage volume. In addition, it requires higher initial room temperature fill pressure within the toroidal helium vapor storage tanks and in cooling tubes connecting to the cryocoolers. The toroidal helium gas tanks are thermally coupled with the thermal shield so that helium convection inside the storage tank can improve heat transfer and reduce the temperature gradient of the thermal shield. Besides those heat transfer challenges, additional mechanical strain within this large structure is exerted on the torque tubes during initial cooldown and when energizing field coils. Some of those design challenges are quite unexpected, leading to novel workarounds in order to maintain the chosen cooling strategy. Finally, we assess those design limitations in view of further cryogenic scalability with emphasis on manufacturability and assembly.

cryogenics↗

Peatland microbial community responses to plant functional group and drought are depth-dependent

Peatlands store one-third of Earth's soil carbon, the stability of which is uncertain due to climate change-driven shifts in hydrology and vegetation, and consequent impacts on microbial communities that mediate decomposition. Peatland carbon cycling varies over steep physicochemical gradients characterizing vertical peat profiles. However, it is unclear how drought-mediated changes in plant functional groups (PFGs) and water table (WT) levels affect microbial communities at different depths. We combined a multiyear mesocosm experiment with community sequencing across a 70-cm depth gradient, to test the hypotheses that vascular PFGs (Ericaceae vs. sedges) and WT (high vs. low) structure peatland microbial communities in depth-dependent ways. Several key results emerged. (i) Both fungal and prokaryote (bacteria and archaea) community structure shifted with WT and PFG manipulation, but fungi were much more sensitive to PFG whereas prokaryotes were much more sensitive to WT. (ii) PFG effects were largely driven by Ericaceae, although sedge effects were evident in specific cases (e.g., methanotrophs). (iii) Treatment effects varied with depth: the influence of PFG was strongest in shallow peat (0-10, 10-20 cm), whereas WT effects were strongest at the surface and middle depths (0-10, 30-40 cm), and all treatment effects waned in the deepest peat (60-70 cm). Furthermore, our results underline the depth-dependent and taxon-specific ways that plant communities and hydrologic variability shape peatland microbial communities, pointing to the importance of understanding how these factors integrate across soil profiles when examining peatland responses to climate change.

59 BASIC BIOLOGICAL SCIENCES↗