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At least 451 records · Page 25

A robust self-starting explicit computational methodology for structural dynamic applications - Architecture and representations

A robust self-starting explicit architecture for computational structural dynamics is described. The proposed methodology involves expressing the governing equations of motion in conservation form and temporal discretization is accomplished in the spirit of the Lax-Wendroff type formulations. The development of the basic methodology is shown. Discretization in space is accomplished by introducing stress-based representations and employing the classical Galerkin scheme. Numerical test model results are presented which validate the architecture.

Tamma, Kumar K.↗

Properties of thermospheric gravity waves on earth, Venus and Mars

A spectral model with spherical harmonics and Fourier components that can simulate atmospheric perturbations in the global geometry of a multiconstituent atmosphere is presented. The boundaries are the planetary surface where the transport velocities vanish and the exobase where molecular heat conduction and viscosity dominate. The time consuming integration of the conservation equations is reduced to computing the transfer function (TF) which describes the dynamic properties of the medium divorced from the complexities in the temporal and horizontal variations of the excitation source. Given the TF, the atmospheric response to a chosen source distribution is then obtained in short order. Theoretical studies are presented to illuminate some properties of gravity waves on earth, Venus and Mars.

Mayr, H. G.↗

Parallel Multiscale Algorithms for Astrophysical Fluid Dynamics Simulations

Our goal is to develop software libraries and applications for astrophysical fluid dynamics simulations in multidimensions that will enable us to resolve the large spatial and temporal variations that inevitably arise due to gravity, fronts and microphysical phenomena. The software must run efficiently on parallel computers and be general enough to allow the incorporation of a wide variety of physics. Cosmological structure formation with realistic gas physics is the primary application driver in this work. Accurate simulations of e.g. galaxy formation require a spatial dynamic range (i.e., ratio of system scale to smallest resolved feature) of 104 or more in three dimensions in arbitrary topologies. We take this as our technical requirement. We have achieved, and in fact, surpassed these goals.

Norman, Michael L.↗

Diagnostics of Laser Produced Plume Under Carbon Nanotube Growth Conditions

This paper presents diagnostic data obtained from the plume of a graphite composite target during carbon nanotube production by the double-pulse laser oven method. The insitu emission spectrum (300 to 650 nm) is recorded at different locations upstream of the target and at different delay times from the lasers (IR and green). Spectral features are identified as emissions from C2 (Swan System: a (sup 3)pi(sub g) - delta (sup 3)pi(sub u) and C3 (Comet Head System: A (sup 1)pi(sub u) - chi (sup 1)sigma(sub u) (sup +). Experimental spectra are compared with computed spectra to estimate vibrational temperatures of excited state C2 in the range of 2500 to 4000 kappa The temporal evolution of the 510 nm band of C2 is monitored for two target positions in various locations which shows confinement of the plume in the inner tube and increase in plume velocity with temperature. The excitation spectra of C2 are obtained by using a dye laser to pump the (0,1) transition of the Swan System and collecting the Laser Induced Fluorescence signal from C2 These are used to obtain "ground-state" rotational and vibrational temperatures which are close to the oven temperature. Images of the plume are also collected and are compared with the spectral measurements.

Arepalli, Sivaram↗

Computational AeroAcoustics for Fan Noise Prediction

An overview of the current state-of-the-art in computational aeroacoustics as applied to fan noise prediction at NASA Glenn is presented. Results from recent modeling efforts using three dimensional inviscid formulations in both frequency and time domains are summarized. In particular, the application of a frequency domain method, called LINFLUX, to the computation of rotor-stator interaction tone noise is reviewed and the influence of the background inviscid flow on the acoustic results is analyzed. It has been shown that the noise levels are very sensitive to the gradients of the mean flow near the surface and that the correct computation of these gradients for highly loaded airfoils is especially problematic using an inviscid formulation. The ongoing development of a finite difference time marching code that is based on a sixth order compact scheme is also reviewed. Preliminary results from the nonlinear computation of a gust-airfoil interaction model problem demonstrate the fidelity and accuracy of this approach. Spatial and temporal features of the code as well as its multi-block nature are discussed. Finally, latest results from an ongoing effort in the area of arbitrarily high order methods are reviewed and technical challenges associated with implementing correct high order boundary conditions are discussed and possible strategies for addressing these challenges ore outlined.

Envia, Ed↗

Effect of Off-Body Laser Discharge on Drag Reduction of Hemisphere Cylinder in Supersonic Flow

The interaction of an off-body laser discharge with a hemisphere cylinder in supersonic flow is investigated. The objectives are 1) experimental determination of the drag reduction and energetic efficiency of the laser discharge, and 2) assessment of the capability for accurate simulation of the interaction. The combined computational and experimental study comprises two phases. In the first phase, laser discharge in quiescent air was examined. The temporal behavior of the shock wave formed by the laser discharge was compared between experiment and simulation and good agreement is observed. In the second phase, the interaction of the laser discharge with a hemisphere cylinder was investigated numerically. Details of the pressure drag reduction and the physics of the interaction of the heated region with the bow shock are included. The drag reduction due to this interaction persisted for about five characteristic times where one characteristic time represents the time for the flow to move a distance equal to the hemisphere radius. The energetic efficiency of laser discharge for the case with 50 mJ energy absorbed by the gas is calculated as 3.22.

Kianvashrad, Nadia↗

The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) Project: A Review

The Southern Ocean serves as the primary gateway through which the intermediate, deep, and bottom waters of the ocean interact with the surface ocean (and thus the atmosphere), and it has a profound influence on the oceanic uptake of anthropogenic carbon and heat as well as nutrient resupply from the abyss to the surface. Yet it has been the least observed and understood region of the world ocean. The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) project was implemented in 2014 with a goal to help remedy this deficit in observations and understanding. The SOCCOM project is based on two major advances that have the potential to transform understanding of the Southern Ocean. The first is the development of new biogeochemical sensors mounted on autonomous profiling floats that allow sampling of ocean biogeochemistry in 3-dimensional space. Floats may detect processes with a temporal resolution that ranges from hours to years. The second is that the climate modeling community finally has the computational resources and physical understanding to develop fully coupled climate models that can represent crucial, mesoscale processes in the Southern Ocean, as well as corresponding models that assimilate observations to produce a state estimate. The observational component, based on deployment of profiling floats with oxygen, nitrate, pH and bio-optical sensors, is generating vast amounts of new biogeochemical data that provide a year-round view of the Southern Ocean from the surface to 2000 m. The modeling effort is applying these observations and enhancing our understanding of the current ocean, and reducing uncertainty in projections of future carbon and nutrient cycles and climate. After nine years of operation, including a project renewal in the sixth year, the SOCCOM project has deployed more than 260 profiling floats. These floats have collected over 27,000 vertical profiles throughout the Southern Ocean. A data-assimilating biogeochemical state estimate model has been implemented. Here, the design of the SOCCOM project is reviewed and the scientific results that have been obtained are described. The project’s capability to help meet the observing system priorities outlined for a notional UN Decade for Ocean Sciences Southern Ocean observing system is assessed.

Jorge L. Sarmiento↗

Analyzing inference workloads for spatiotemporal modeling

Ensuring power grid resiliency, forecasting climate conditions, and optimization of transportation infrastructure are some of the many application areas where data is collected in both space and time. Spatiotemporal modeling is about modeling those patterns for forecasting future trends and carrying out critical decision-making by leveraging machine learning/deep learning. Once trained offline, field deployment of trained models for near real-time inference could be challenging because performance can vary significantly depending on the environment, available compute resources and tolerance to ambiguity in results. Users deploying spatiotemporal models for solving complex problems can benefit from analytical studies considering a plethora of system adaptations to understand the associated performance-quality trade-offs. To facilitate the co-design of next-generation hardware architectures for field deployment of trained models, it is critical to characterize the workloads of these deep learning (DL) applications during inference and assess their computational patterns at different levels of the execution stack. In this paper, we develop several variants of deep learning applications that use spatiotemporal data from dynamical systems. We study the associated computational patterns for inference workloads at different levels, considering relevant models (Long short-term Memory, Convolutional Neural Network and Spatio-Temporal Graph Convolution Network), DL frameworks (Tensorflow and PyTorch), precision (FP16, FP32, AMP, INT16 and INT8), inference runtime (ONNX and AI Template), post-training quantization (TensorRT) and platforms (Nvidia DGX A100 and Sambanova SN10 RDU). Overall, our findings indicate that although there is potential in mixed-precision models and post-training quantization for spatiotemporal modeling, extracting efficiency from contemporary GPU systems might be challenging. Instead, co-designing custom accelerators by leveraging optimized High Level Synthesis frameworks (such as SODA High-Level Synthesizer for customized FPGA/ASIC targets) can make workload-specific adjustments to enhance the efficiency.

97 MATHEMATICS AND COMPUTING↗

Computing the Envelope for Stepwise Constant Resource Allocations

Estimating tight resource level is a fundamental problem in the construction of flexible plans with resource utilization. In this paper we describe an efficient algorithm that builds a resource envelope, the tightest possible such bound. The algorithm is based on transforming the temporal network of resource consuming and producing events into a flow network with noises equal to the events and edges equal to the necessary predecessor links between events. The incremental solution of a staged maximum flow problem on the network is then used to compute the time of occurrence and the height of each step of the resource envelope profile. The staged algorithm has the same computational complexity of solving a maximum flow problem on the entire flow network. This makes this method computationally feasible for use in the inner loop of search-based scheduling algorithms.

Muscettola, Nicola↗

Investigating the Numerical Stability of Using an Impedance Boundary Condition to Model Broadband Noise Scattering With Acoustic Liners

Reducing aircraft noise is a major objective in the field of computational aeroacoustics. When designing next generation quiet aircraft, it is important to be able to accurately and efficiently predict the acoustic scattering by an aircraft body from a given noise source. Acoustic liners are an effective tool for achieving aircraft noise reduction and are characterized by a frequency-dependent impedance value. Converted into the time-domain using Fourier transforms, an impedance boundary condition can be used to simulate the acoustic wave scattering by geometric bodies treated with acoustic liners. A Broadband Impedance Model will be discussed in which the liner impedance is specified along a wide range of frequencies. The liner impedance boundary condition will be derived and coupled with a time-domain boundary integral equation to model acoustic scattering by a flat plate consisting of both un-lined and lined surfaces. The scattering solution will be obtained iteratively using both spatial and temporal basis functions and the stability will be demonstrated through eigenvalue analysis. Stability will be assessed for its dependence on time step, spatial discretization, as well as temporal basis function order. Both second- and third-order Lagrange temporal basis functions are considered.

acoustics↗

Model for the computation of self-motion in biological systems

A technique is presented by which direction- and speed-tuned cells, such as those commonly found in the middle temporal region of the primate brain, can be utilized to analyze the patterns of retinal image motion that are generated during observer movement through the environment. The developed model determines heading by finding the peak response in a population of detectors or neurons each tuned to a particular heading direction. It is suggested that a complex interaction of multiple cell networks is required for the solution of the self-motion problem in the primate brain.

Perrone, John A.↗

DOME: Directional medical embedding vectors from Electronic Health Records

Motivation: The increasing availability of Electronic Health Record (EHR) systems has created enormous potential for translational research. Recent developments in representation learning techniques have led to effective large-scale representations of EHR concepts along with knowledge graphs that empower downstream EHR studies. However, most existing methods require training with patient-level data, limiting their abilities to expand the training with multi-institutional EHR data. On the other hand, scalable approaches that only require summary-level data do not incorporate temporal dependencies between concepts. Methods: We introduce a DirectiOnal Medical Embedding (DOME) algorithm to encode temporally directional relationships between medical concepts, using summary-level EHR data. Specifically, DOME first aggregates patient-level EHR data into an asymmetric co-occurrence matrix. Then it computes two Positive Pointwise Mutual Information (PPMI) matrices to correspondingly encode the pairwise prior and posterior dependencies between medical concepts. Following that, a joint matrix factorization is performed on the two PPMI matrices, which results in three vectors for each concept: a semantic embedding and two directional context embeddings. They collectively provide a comprehensive depiction of the temporal relationship between EHR concepts. Results: We highlight the advantages and translational potential of DOME through three sets of validation studies. First, DOME consistently improves existing direction-agnostic embedding vectors for disease risk prediction in several diseases, for example achieving a relative gain of 5.5% in the area under the receiver operating characteristic (AUROC) for lung cancer. Second, DOME excels in directional drug-disease relationship inference by successfully differentiating between drug side effects and indications, correspondingly achieving relative AUROC gain over the state-of-the-art methods by 10.8% and 6.6%. Finally, DOME effectively constructs directional knowledge graphs, which distinguish disease risk factors from comorbidities, thereby revealing disease progression trajectories. The source codes are provided at https://github.com/celehs/Directional-EHRembedding.

60 APPLIED LIFE SCIENCES↗

Development of a CFD Code for Analysis of Fluid Dynamic Forces in Seals

The aim is to develop a 3-D computational fluid dynamics (CFD) code for the analysis of fluid flow in cylindrical seals and evaluation of the dynamic forces on the seals. This code is expected to serve as a scientific tool for detailed flow analysis as well as a check for the accuracy of the 2D industrial codes. The features necessary in the CFD code are outlined. The initial focus was to develop or modify and implement new techniques and physical models. These include collocated grid formulation, rotating coordinate frames and moving grid formulation. Other advanced numerical techniques include higher order spatial and temporal differencing and an efficient linear equation solver. These techniques were implemented in a 2D flow solver for initial testing. Several benchmark test cases were computed using the 2D code, and the results of these were compared to analytical solutions or experimental data to check the accuracy. Tests presented here include planar wedge flow, flow due to an enclosed rotor, and flow in a 2D seal with a whirling rotor. Comparisons between numerical and experimental results for an annular seal and a 7-cavity labyrinth seal are also included.

Athavale, Mahesh M.↗

Multi-Domain Routing in Delay Tolerant Networks

The goal of Delay Tolerant Networking (DTN) is to provide the missing ingredient for the ever-growing collection of communicating nodes in our solar system to become a Solar System Internet (SSI). Great strides have been made in modeling particular types of DTNs, such as schedule- or discovery-based. Now, analogously to the Internet, these smaller DTNs can be considered routing domains which must be stitched together to form the overall SSI. In this paper, we propose a framework for cross-domain routing in DTNs as well as methodologies for detecting these sub-domains. Example time-varying networks are given to demonstrate the techniques proposed. A basic component is the mathematical theory of sheaves, which unifies the underlying model of DTN routing algorithms, by giving rise to routing sheaves – these can be defined for the dynamic and scheduled networks as noted above, and can also be used to define the interfaces between these domains in order to route across them. An immediate application would be routing across discovery-based networks connected by scheduled networks. These DTN subdomains remain elusive, however, and need to become well-defined and properly sized for tractable computability. In particular, a balance must be determined between areas that are too large (i.e. large matrix computations) versus areas that are too small (i.e. “many” single-noded domains). Moreover, the connections between the domains should, at least locally, be chosen to optimize data flow and connectivity: we address this in three ways. First, tools from persistent homology are given to understand underlying structures, reminiscent of hierarchies in the Internet Protocol (IP) addressing. Second, we construct a notion of temporal graph curvature based on network geometry to analyze flows induced by dynamical processes on these networks. Finally, Schrodinger Bridges, a tool arising from statistical physics, are proposed as a method of constructing flows on time-evolving networks with desirable properties such as speed, robustness, and load sensitivity. We construct an approach to temporal hypergraphs to simultaneously model unicast, multicast, and broadcast, using the language of scheme theory, and then consider DTN network coding as a way to achieve network-level computation and organization. The paper concludes with a discussion and ideas for future work.

Alan Hylton↗

Automated mesoscale winds derived from GOES multispectral imagery

An automated technique for extracting mesoscale winds from sequences of GOES VISSR image pairs was developed, tested and configured for quasi-real time/research applications on a computing system which gives mesoscale wind estimates at the highest spatial/temporal resolution possible from the VISSR imagery down to a wind vector separation of 10 km. Preprocessing of imagery using IR resampling, VIS edge preserving filtering, and reduced VIS resolution averaging improved height assignments and vector extraction for 10, 15, and 30 min imagery. An objective quality control system provides much greater than 99% accuracy in eliminating questionable wind estimates. Automated winds generally have better spatial coverage and density, and have random error estimates half as large as the manual winds. Dynamical analysis of cloud wind divergence revealed temporally consistent convergence centers on the meso beta scale that are highly correlated with on going and future developing convective storms. The entire system of computer codes was successfully vectorized for execution on an array processor resulting in job turnaround in less than one hour.

Wilson, G. S.↗

Initial results from the High Altitude Observatory white light coronagraph on Skylab - A progress report

Frequent periodic observations by the white-light coronagraph allow an examination of coronal variations over a broad range of temporal scales. Examples of the slowest and most rapid variations are presented. An example of extremely slow coronal variations is the gradual evolution - to a large equatorial streamer - in association with a marked decrease in solar activity, as the total magnetic flux in one hemisphere decreased. Another example is given of a long-lived quasi-stable coronal streamer, apparently associated with a stable filament channel; comparison of this streamer with coronal potential-magnetic-field computations show little correlation. Some results on coronal transients - the most rapid variations observed - are summarized. Characteristic masses and energies involved in mass-ejection transients, their temporal and spatial distributions, their associations with surface phenomena and possible interplanetary signatures, and their role in coronal evolution are briefly noted.

Macqueen, R. M.↗

Sub-100-fs energy transfer in coenzyme NADH is a coherent process assisted by a charge-transfer state

Excitation energy transfer (EET) is a key photoinduced process in biological chromophoric assemblies. Here we investigate the factors which can drive EET into efficient ultrafast sub-ps regimes. We demonstrate how a coherent transport of electronic population could facilitate this in water solvated NADH coenzyme and uncover the role of an intermediate dark charge-transfer state. High temporal resolution ultrafast optical spectroscopy gives a 54 ± 11 fs time constant for the EET process. Nonadiabatic quantum dynamical simulations computed through the time-evolution of multidimensional wavepackets suggest that the population transfer is mediated by photoexcited molecular vibrations due to strong coupling between the electronic states. The polar aqueous solvent environment leads to the active participation of a dark charge transfer state, accelerating the vibronically coherent EET process in favorably stacked conformers and solvent cavities. Our work demonstrates how the interplay of structural and environmental factors leads to diverse pathways for the EET process in flexible heterodimers and provides general insights relevant for coherent EET processes in stacked multichromophoric aggregates like DNA strands.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗