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At least 919 records · Page 51

Analysis of shell-type structures subjected to time-dependent mechanical and thermal loading

The development of a general mathematical model and solution methodologies for analyzing structural response of thin, metallic shell-like structures under dynamic and/or static thermomechanical loads is examined. In the mathematical model, geometric as well as material-type of nonlinearities are considered. Traditional as well as novel approaches are reported and detailed applications are presented in the appendices. The emphasis for the mathematical model, the related solution schemes, and the applications, is on thermal viscoelastic and viscoplastic phenomena, which can predict creep and ratchetting.

Simitses, George J.↗

New Representation of Bearings in LS-DYNA

Non-linear, dynamic, finite element analysis is used in various engineering disciplines to evaluate high-speed, dynamic impact and vibration events. Some of these applications require connecting rotating to stationary components. For example, bird impacts on rotating aircraft engine fan blades are a common analysis performed using this type of analysis tool. Traditionally, rotating machines utilize some type of bearing to allow rotation in one degree of freedom while offering constraints in the other degrees of freedom. Most times, bearings are modeled simply as linear springs with rotation. This is a simplification that is not necessarily accurate under the conditions of high-velocity, high-energy, dynamic events such as impact problems. For this reason, it is desirable to utilize a more realistic non-linear force-deflection characteristic of real bearings to model the interaction between rotating and non-rotating components during dynamic events. The present work describes a rolling element bearing model developed for use in non-linear, dynamic finite element analysis. This rolling element bearing model has been implemented in LS-DYNA as a new element, *ELEMENT_BEARING.

bearings↗

Distributed Sensing of a Cantilever Beam and Plate Using a Fiber Optic Sensing System

As the capabilities of Fiber Optic Sensing Systems continue to improve, their application to real-time distributed sensing for structural analysis and control of flexible systems is increasingly feasible. This paper will report experimental results on the use of a Fiber Optic Sensing System for static and dynamic shape estimation of a cantilever beam and plate. Demonstrating the use of this sensor technology in benchtop experiments is the first step in effectively incorporating fiber optic sensors in the Integrated Adaptive Wing Technology Maturation aeroelastic half-span wind tunnel model for real-time shape sensing and feedback for drag optimization, maneuver load alleviation, gust load alleviation, and flutter suppression control laws. The effectiveness of the sensing system will be analyzed and the application of these results to aeroelasticity experimentation will be discussed.

Heaney, Patrick S.↗

Mammalian complex III heme dynamics studied with pump-probe spectroscopy and red light illuminations

The electronic or molecular mechanisms which initiate photobiomodulation (PBM) in cells are not yet fully understood. Porcine complex III (C-III) of the electron transport chain was characterized with transient absorption spectroscopy (TAS). Then we applied our recently developed continuous wave laser coupled TAS procedure (CW-TAS) to investigate the effect of red light irradiances on the heme dynamics of C-III in its c 1 reduced state. The time constants associated with the axial ligand photodissociation were found to be 3.3 ± 0.3 ps for the oxidized state and 4.9 ± 0.4 ps for the c 1 reduced state. The analysis of the CW-TAS procedure yielded no significant changes in the C-III heme dynamics. We rule out the possibility of 635 nm CW light at 4.7 mW/cm 2 inducing a PBM effect on the heme dynamic of C-III, specifically with the photodissociation of its axial ligand.

59 BASIC BIOLOGICAL SCIENCES↗

DAGSENS: Directed Acyclic Graph Based Direct and Adjoint Transient Sensitivity Analysis for Event-Driven Objective Functions

We present DAGSENS, a new theory for parametric transient sensitivity analysis of Differential Algebraic Equation systems (DAEs), such as SPICE-level circuits. The key ideas behind DAGSENS are, (1) to represent the entire sequence of computations, starting from DAE parameters, all the way up to the objective function whose sensitivity is needed, as a Directed Acyclic Graph (DAG) called the "sensitivity DAG", and (2) to compute the required sensitivities efficiently (with time complexity linear in the size of the sensitivity DAG) by leveraging dynamic programming techniques to traverse the DAG. DAGSENS is simple, elegant, and easy-to-understand compared to existing sensitivity analysis approaches; for example, in DAGSENS, one can switch between direct and adjoint transient sensitivities just by changing the direction of DAG traversal (i.e., topological order vs. reverse topological order). Also, DAGSENS is significantly more powerful than existing sensitivity analysis approaches because it allows one to compute the sensitivities of a much more general class of objective functions, including those defined based on "events" that occur during a transient simulation (e.g., a node voltage crossing a particular threshold, a phase-locked loop (PLL) achieving lock, a signal reaching its maximum/minimum value during a transient run, etc.). In this paper, we apply DAGSENS to compute the sensitivities of important event-driven performance metrics in several real-world electronic and biological applications, including high-speed communication (featuring sub-systems such as I/0 links and PLLs), statistical cell library characterization, and gene expression in Drosophila embryos.

42 ENGINEERING↗

Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers

We report the first congruent integration of HPC, AI, and multiscale modeling (MSM) for solving a mainstream biomechanical problem of thrombogenesis involving 6 million particles at record molecular-scale resolutions in space and at simulation rates of milliseconds per day. The two supercomputers, the IBM Summit-like AiMOS and our University’s SeaWulf, are used for scalability analysis of, and production runs with, the LAMMPS with our customization and AI augmentation and they attained optimal simulation speeds of 3,077 µs/day and 266 µs/day respectively. The long-time and large scales simulations enable the first study of the integrated platelet flowing, flipping, aggregating dynamics in one dynamically-coupled production run. The platelets’ angular and translational speeds, membrane particles’ speeds, and the membrane stress distributions are presented for the analysis of platelets’ aggregations.

Zhu, Yicong↗

In-Situ Blade Strain Measurements and Fatigue Analysis of a Cross-Flow Turbine Operating in a Tidal Flow

Cross-flow turbines (CFTs) are inherently unsteady devices with regards to operating principle and loading. By improving our understanding of the dynamic loading on these turbines, we hope to better inform CFT design, improve survivability, and reduce overall costs. The University of New Hampshire (UNH) and the National Renewable Energy Laboratory (NREL) collaborated on a project to instrument and test a four-bladed New Energy Corp. vertical axis cross-flow turbine in a real tidal flow. One blade from the 3.2 m diameter x 1.7 m height turbine was instrumented with eight full-bridge strain gauges along the span of the blade. The turbine was then deployed at the UNH-Atlantic Marine Energy Center (AMEC) Tidal Energy Test Site in Portsmouth, NH. Time-synchronized measurements of blade strain, inflow, thrust, rotational speed, and electrical output were obtained to characterize blade loading under various conditions. The blade strain was examined to assess the dynamic loading and conduct a fatigue analysis on the device.

blade strain↗

Computational fluid dynamics analysis of char conversion in Sandia’s pressurized entrained flow reactor

Design and analysis of practical reactors utilizing solid feedstocks rely on reaction rate parameters that are typically generated in lab-scale reactors. Evaluation of the reaction rate information often relies on assumptions of uniform temperature, velocity, and species distributions in the reactor, in lieu of detailed measurements that provide local information. This assumption might be a source of substantial error, since reactor designs can impose significant inhomogeneities, leading to data misinterpretation. Spatially resolved reactor simulations help understand the key processes within the reactor and support the identification of severe variations of temperature, velocity, and species distributions. In this work, Sandia’s pressurized entrained flow reactor is modeled to identify inhomogeneities in the reaction zone. Tracer particles are tracked through the reactor to estimate the residence times and burnout ratio of introduced coal char particles in gasifying environments. The results reveal a complex mixing environment for the cool gas and particles entering the reactor along the centerline and the main high-speed hot gas reactor flow. Furthermore, the computational fluid dynamics (CFD) results show that flow asymmetries are introduced through the use of a horizontal gas pre-heating section that connects to the vertical reactor tube. Computed particle temperatures and residence times in the reactor differ substantially from the idealized plug flow conditions typically evoked in interpreting experimental measurements. Furthermore, experimental measurements and CFD analysis of heat flow through porous refractory insulation suggest that for the investigated conditions (1350 °C, <20 atm), the thermal conductivity of the insulation does not increase substantially with increasing pressure.

47 OTHER INSTRUMENTATION↗

Delamination-Assisted Ultrafast Wrinkle Formation in a Freestanding Film

Freestanding films provide a versatile platform for materials engineering thanks to additional structural motifs not found in films with a substrate. A ubiquitous example is wrinkles, yet little is known about how they can develop over as fast as a few picoseconds due to a lack of experimental probes to visualize their dynamics in real time on the nanoscopic scale. Here, we use time-resolved electron diffraction to directly observe light-activated wrinkling formation in freestanding La 2/3 Ca 1/3 MnO 3 films. Via a “lock-in” analysis of oscillations in the diffraction peak position, intensity, and width, we quantitatively reconstructed how wrinkles develop on the time scale of lattice vibration. Contrary to the common assumption of fixed boundary conditions, we found that wrinkle development is associated with ultrafast delamination at the film boundaries. Finally, our work provides a generic protocol to quantify wrinkling dynamics in freestanding films and highlights the importance of the film–substrate interaction in determining the properties of freestanding structures.

36 MATERIALS SCIENCE↗

Observations and Numerical Modeling of the Jovian Ribbon

Multiple wavelength observations made by the Hubble Space Telescope in early 2007 show the presence of a wavy, high-contrast feature in Jupiter's atmosphere near 30 degrees North. The "Jovian Ribbon," best seen at 410 nanometers, irregularly undulates in latitude and is time-variable in appearance. A meridional intensity gradient algorithm was applied to the observations to track the Ribbon's contour. Spectral analysis of the contour revealed that the Ribbon's structure is a combination of several wavenumbers ranging from k equals 8-40. The Ribbon is a dynamic structure that has been observed to have spectral power for dominant wavenumbers which vary over a time period of one month. The presence of the Ribbon correlates with periods when the velocity of the westward jet at the same location is highest. We conducted numerical simulations to investigate the stability of westward jets of varying speed, vertical shear, and background static stability to different perturbations. A Ribbon-like morphology was best reproduced with a 35 per millisecond westward jet that decreases in amplitude for pressures greater than 700 hectopascals and a background static stability of N equals 0.005 per second perturbed by heat pulses constrained to latitudes south of 30 degrees North. Additionally, the simulated feature had wavenumbers that qualitatively matched observations and evolved throughout the simulation reproducing the Jovian Ribbon's dynamic structure.

Saturnian Ribbon↗

Efficient Jitter Analysis for Spacecraft

Typically in space missions, the science instruments require a specific degree of pointing accuracy as well as dynamical quietness. This dynamical quietness, which is needed to allow the instruments to make measurements (remote sensing applications) or perform other functions, is usually characterized in terms of jitter and stability specifications. In order to insure that the spacecraft meets the requirements of its instruments, several jitter analyses are performed throughout the design phase of the spacecraft and beyond as the models of the spacecraft, its components, and disturbances mature. Each such analysis involves the simulation of the spacecraft and instrument dynamical response to all known disturbance scenarios, followed by the computation of jitter values for each instrument based on the specified jitter time windows. The direct approach for computing jitter values by sweeping maxima and minima throughout the time history may be costly in the computational sense as the size and number of the time histories involved could be quite large. Keeping in mind that typical spacecraft simulation time histories may easily involve hundreds of thousands or millions of points, it is imperative that a jitter analysis algorithm be developed which is more efficient than the direct approach. This paper presents a vectorized algorithm for efficient computation of spacecraft jitter values. The algorithm identifies the extreme points in the time history, which are the points that may dominate the jitter values depending on the location of the jitter window along the time history. The span of influence of each extremum is then computed by the algorithm and used in an efficient and vectorized fashion to obtain the jitter values. The algorithm deals with the multiple jitter windows 2 sequentially, first computing jitter values for the smallest time window, then looping over the remaining time windows until all jitter values are computed. A numerical example is carried out to demonstrate the efficiency and feasibility of the proposed jitter analysis technique.

Maghami, Peiman G.↗

Time-Dependent Reliability Analysis of Nuclear Hybrid Energy Systems

This paper focuses on developing a framework for comprehensive time-dependent reliability analysis of a nuclear hybrid energy system (NHES) design. Subsystem interactions of this complex integrated system under stochastic electricity demand and load-following operation capabilities requires dynamic reliability assessment of the NHES in component, subsystem and system level. In order to capture the dynamic operational behavior of critical systems and components, a detailed thermal hydraulic model of the NHES is generated using Modelica and tested under different electricity demand histories generated using RAVEN. The physical data (e.g., valve position, flow rates, inlet outlet water temperatures) gathered from Modelica used to calculate time-dependent failure rates through fitting data into the piecewise Weibull distribution. Optimum maintenance interval is calculated, and maintenance cost estimates based on the calculated reliability metric is presented for the selected component. Component time-dependent failure rates fed into the subsystem reliability model built with non-Markovian Stochastic Petri Nets. The component and subsystem failure rates are calculated and updated in every hour to characterize the system behavior appropriately and to understand operational reliability of the NHES design in a given time.

Guler Yigitoglu, Askin↗

An Idealized Test of the Response of the Community Atmosphere Model to Near‐Grid‐Scale Forcing Across Hydrostatic Resolutions

Abstract A set of idealized experiments are developed using the Community Atmosphere Model (CAM) to understand the vertical velocity response to reductions in forcing scale that is known to occur when the horizontal resolution of the model is increased. The test consists of a set of rising bubble experiments, in which the horizontal radius of the bubble and the model grid spacing are simultaneously reduced. The test is performed with moisture, through incorporating moist physics routines of varying complexity, although convection schemes are not considered. Results confirm that the vertical velocity in CAM is to first‐order, proportional to the inverse of the horizontal forcing scale, which is consistent with a scale analysis of the dry equations of motion. In contrast, experiments in which the coupling time step between the moist physics routines and the dynamical core (i.e., the “physics” time step) are relaxed back to more conventional values results in severely damped vertical motion at high resolution, degrading the scaling. A set of aqua‐planet simulations using different physics time steps are found to be consistent with the results of the idealized experiments.

54 ENVIRONMENTAL SCIENCES↗

Altersbestimmung an thermalen Tiefenwässern im Oberjura des Molassebeckens mittels Krypton-Isotopen

81 Kr (half-life 229,000 years) is an ideal tracer for old groundwater. The Upper Jurassic rock in the deep Molasse Basin is an outstanding geothermal groundwater reservoir (with temperatures up to 140 °C). However, due to the complex groundwater evolution (ion and isotope exchange, gas flux, etc.), comprehensive hydrogeological studies completed to date, including 14 C–DIC and He isotopes, could not resolve the recharge dynamics and residence times. Nine geothermal wells were therefore sampled for 81 Kr/ 85 Kr employing the laser-based atom trap tracer analysis technique (ATTA). In the western and central basin, the results reveal predominant groundwater recharge during the last glacial period with one sample influenced by infiltration during the earlier glacial period. Recharge signatures and 81 Kr-model-ages fit very well to subglacial recharge with cross-formational flow through the sedimentary cover (600 to >3000 m deep). In the eastern basin, the results point to the Cromerian complex, indicating a slower flow system with less influence from recharge during glacial periods.

54 ENVIRONMENTAL SCIENCES↗

Solid state dewetting of thin plasmonic films under focused cw-laser irradiation

Elevated temperatures and large thermal gradients are a significant source of component failure in microelectronics, and is the limiting factor in heat-assisted magnetic recording (HAMR). Here, we have investigated the effect of solid-state dewetting in Au thin films, as a function of local temperature, film thickness, and substrate adhesion. In this work, a localised temperature rise is induced in thin (≤ 50 nm) polycrystalline Au films on SiO 2 substrates via focused continuous-wave laser irradiation at 488 nm. The magnitude and distribution of the total temperature rise is measured using CCD-based thermoreflectance. This also allows a sensitive measurement of the temperature at which dewetting occurs, showing that for thin (≤ 50 nm) Au films without adhesion layers, rapid dewetting can occur at temperatures as low as 50° C. The time decay of the reflected light from the illuminating laser is used to monitor locally the dynamics of solid state dewetting. TEM diffraction analysis shows significant changes in the microstructure and crystallographic texture of the films as far as 10 µm away from the illuminated area. The use of a thin metallic adhesion layer (such as Ti or Cr) is shown to significantly improve the adhesion of the Au to the substrate and reduce the tendency towards dewetting, but does not entirely protect it from changes to the crystallographic texture.

36 MATERIALS SCIENCE↗

Experimental Assessment of Mammalian Lipidome Complexity Using Multimodal 21 T FTICR Mass Spectrometry Imaging

Herein, we assess the complementarity and complexity of data that can be detected within mammalian lipidome mass spectrometry imaging (MSI) via matrix-assisted laser desorption ionization (MALDI) and nanospray desorption electrospray ionization (nano-DESI). We do so by employing 21 T Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) with absorption mode FT processing in both cases, allowing unmatched mass resolving power per unit time (≥613k at m/z 760, 1.536 s transients). While our results demonstrated that molecular coverage and dynamic range capabilities were greater in MALDI analysis, nano-DESI provided superior mass error, and all annotations for both modes had sub-ppm error. Taken together, these experiments highlight the coverage of 1676 lipids and serve as a functional guide for expected lipidome complexity within nano-DESI-MSI and MALDI-MSI. To further assess the lipidome complexity, mass splits (i.e., the difference in mass between neighboring peaks) within single pixels were collated across all pixels from each respective MSI experiment. The spatial localization of these mass splits was powerful in informing whether the observed mass splits were biological or artificial (e.g., matrix related). Mass splits down to 2.4 mDa were observed (i.e., sodium adduct ambiguity) in each experiment, and both modalities highlighted comparable degrees of lipidome complexity. Further, we highlight the persistence of certain mass splits (e.g., 8.9 mDa; double bond ambiguity) independent of ionization biases. Here, we also evaluate the need for ultrahigh mass resolving power for mass splits ≤4.6 mDa (potassium adduct ambiguity) at m/z > 1000, which may only be resolved by advanced FTICR-MS instrumentation.

21T-FTICR-MS↗

Strongly Correlated Ion Dynamics in Plastic Ionic Crystals and Polymerized Ionic Liquids

Understanding the mechanisms controlling ionic conductivity is critical for the development of the next generation of batteries and supercapacitors. This paper discusses the significant role played by ionic correlations in conductivity of concentrated ionic systems. Our studies of an organic ionic plastic crystal reveal that correlations in ions dynamics suppress conductivity by 25–100 times in comparison to the expected uncorrelated ionic conductivity estimated from the Nernst–Einstein relationship. Furthermore, additional analysis also demonstrates that ionic correlations suppress conductivity in polymerized ionic liquids and gel by ~10 times. Thus, ionic correlations, usually neglected in many studies, play a very important role in conductivity of concentrated ionic systems. These results cannot be explained by a diffusion of ion pairs because all these systems are essentially single ion conductors. In contrast, strongly correlated motions of mobile ions with the same charge (cation–cation or anion–anion correlations) are the major mechanism suppressing the ionic conductivity in these systems. Finally, on the basis of these results, we emphasize that charge transport rather than ion diffusion is critical for electrolyte performance and suggest the potential design of plastic crystals and polymer electrolytes with enhanced ionic conductivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time-series forecasting using manifold learning, radial basis function interpolation, and geometric harmonics

We address a three-tier numerical framework based on nonlinear manifold learning for the forecasting of high-dimensional time series, relaxing the “curse of dimensionality” related to the training phase of surrogate/machine learning models. At the first step, we embed the high-dimensional time series into a reduced low-dimensional space using nonlinear manifold learning (local linear embedding and parsimonious diffusion maps). Then, we construct reduced-order surrogate models on the manifold (here, for our illustrations, we used multivariate autoregressive and Gaussian process regression models) to forecast the embedded dynamics. Finally, we solve the pre-image problem, thus lifting the embedded time series back to the original high-dimensional space using radial basis function interpolation and geometric harmonics. The proposed numerical data-driven scheme can also be applied as a reduced-order model procedure for the numerical solution/propagation of the (transient) dynamics of partial differential equations (PDEs). In conclusion, we assess the performance of the proposed scheme via three different families of problems: (a) the forecasting of synthetic time series generated by three simplistic linear and weakly nonlinear stochastic models resembling electroencephalography signals, (b) the prediction/propagation of the solution profiles of a linear parabolic PDE and the Brusselator model (a set of two nonlinear parabolic PDEs), and (c) the forecasting of a real-world data set containing daily time series of ten key foreign exchange rates spanning the time period 3 September 2001–29 October 2020.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗