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Results for “cascaded information flow”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Reconfigurable Cascaded Thermal Neuristors for Neuromorphic Computing

While the complementary metal-oxide semiconductor (CMOS) technology is the mainstream for the hardware implementation of neural networks, an alternative route is explored based on a new class of spiking oscillators called “thermal neuristors”, which operate and interact solely via thermal processes. Utilizing the insulator-to-metal transition (IMT) in vanadium dioxide, a wide variety of reconfigurable electrical dynamics mirroring biological neurons is demonstrated. Notably, inhibitory functionality is achieved just in a single oxide device, and cascaded information flow is realized exclusively through thermal interactions. To elucidate the underlying mechanisms of the neuristors, a detailed theoretical model is developed, which accurately reflects the experimental results. In conclusion, this study establishes the foundation for scalable and energy-efficient thermal neural networks, fostering progress in brain-inspired computing.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Flow Reconstruction in A Transonic Turbine Cascade Using Physics-Informed Neural Networks (PINNS)

This paper investigates the application of Physics-Informed Neural Networks (PINNs) for the analysis of turbine blades in a transonic cascade. The 2-D flow field in a transonic turbine cascade is reconstructed in three ways: the traditional forward approach (PINN not trained on experimental data), by training the PINN using discrete sets of experimentally measured pressure at midspan, and in the inverse sense where no inlet or outlet pressure boundary conditions are applied. Comparisons between the PINN solutions to measured data are made. This is repeated for three different turbine blades with distinct loading characteristics. Good agreement is shown between a CFD calculation of the CMC7 blade, and the PINN model trained with all data. The PINN is trained utilizing all available data, half the available data, data from only the leading edge region, and data from only the trailing edge region. The forward problem results deviate the most from experimental data but show promise. Solutions from the assisted training cases show that the PINN can reconstruct the flow field with acceptable accuracy when trained on measurements along the entire blade. In the inverse case, it is shown that to simultaneously achieve acceptable errors for inlet Mach number and outlet isentropic Mach number, the PINN must be trained on the static pressure data along the entire blade.

Machine Learning↗
NASA NTRSDate not supplied

GT2024-128885: Flow Reconstruction in a Transonic Turbine Cascade using Physics-Informed Neural Networks (PINNs)

This presentation investigates the application of Physics-Informed Neural Networks (PINNs) for the analysis of turbine blades in a transonic cascade. PINNs are a machine learning method trained on losses calculated from reconstructed governing equations, assigned boundary/initial conditions, and measured data. We reconstruct the 2-D flow field in a transonic turbine cascade in two ways: the traditional forward approach (without training/experimental data) and by training the PINN using experimental data. We then compare the PINN solutions to measured data. This is repeated for three different turbine blades with distinct loading characteristics. The experimental data used for training is the static pressure measurements along the suction and pressure sides of each blade. The PINN is trained utilizing all available data, half the available data, data from only the leading edge region, and data from only the trailing edge region. It's shown that the PINN can reconstruct the flow field in all cases with acceptable errors. Cases where the PINN is trained on all the data, and even half the data, resulted in the lowest errors. The exit Mach number is inferred for each case and compared to the experimentally calculated value.

Machine Learning↗
NASA NTRS1997

Gas Dynamics, Characterization, and Calibration of Fast Flow Flight Cascade Impactor Quartz Crystal Microbalances (QCM) for Aerosol Measurements

During recent high altitude flights, we have tested the aerosol section of the fast flow flight cascade impactor quartz crystal microbalance (QCM) on loan to Howard University from NASA. The aerosol mass collected during these flights was disappointingly small. Increasing the flow through the QCM did not correct the problem. It was clear that the instrument was not being operated under proper conditions for aerosol collect ion primarily because the gas dynamics is not well understood. A laboratory study was therefore undertaken using two different fast flow QCM's in an attempt to establish the gas flow characteristics of the aerosol sections and its effect on particle collection, Some tests were made at low temperatures but most of the work reported here was carried out at room temperature. The QCM is a cascade type impactor originally designed by May (1945) and later modified by Anderson (1966) and Mercer et al (1970) for chemical gas analysis. The QCM has been used extensively for collecting and sizing stratospheric aerosol particles. In this paper all flow rates are given or corrected and referred to in terms of air at STP. All of the flow meters were kept at STP. Although there have been several calibration and evaluation studies of moderate flow cascade impactors of less than or equal to 1 L/rein., there is little experimental information on the gas flow characteristics for fast flow rates greater than 1 L/rein.

Grant, J.R.↗
DOE OSTI2020

Direct Observation of the Dynamics of Single-Cell Metabolic Activity during Microbial Diauxic Growth

Understanding how genetic information is realized as the behavior of individual cells is a long-term goal of biology but represents a significant technological challenge. In clonal microbial populations, variation in gene regulation is often interpreted as metabolic heterogeneity. This follows the central dogma of biology, in which information flows from DNA to RNA to protein and ultimately manifests as activity. At present, DNA and RNA can be characterized in single cells, but the abundance and activity of proteins cannot. Inferences about metabolic activity usually therefore rely on the assumption that transcription reflects activity. By tracking the atoms from which they build their biomass, we make direct observations of growth rate and substrate specialization in individual cells throughout a period of growth in a changing environment. This approach allows the flow of information from DNA to be constrained from the distal end of the regulatory cascade and will become an essential tool in the rapidly advancing field of single-cell metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Hydrologic connectivity and dynamics of solute transport in a mountain stream: Insights from a long-term tracer test and multiscale transport modeling informed by machine learning

The movement of solutes in a watershed is a complex process with multiple interactions and feedbacks across spatial and temporal scales. Modeling the dynamics of solute transport along diverse hydrologic pathways within watersheds – from hillslopes to stream channels and in and out of the hyporheic zones – is challenging but critically important, as these processes integrate and contribute to the biogeochemical functioning of the river corridor up to the river network scale. Here we use results from a long-term network-scale tracer test at the H.J. Andrews experimental forest in western Cascade Mountains, Oregon, USA to inform a multiscale framework for transport in stream corridors. The framework uses a Lagrangian-based subgrid model to represent the effects of hyporheic exchange flow and advective transport at stream network scales. The spatially and temporally resolved stream discharge needed for the transport model is imputed across the river system by an entity-aware long short-term memory network. Modeled concentrations show good agreements with the observations and exhibit power scaling laws indicative of a very wide range of timescales over which hyporheic exchange flow occurs. Our results demonstrate a data-informed modeling framework that links dynamical processes occurring at small scales to a network context to help understand how changes at reach scale cascade into network-scale effects, providing a useful tool for sustainable river basin management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Gaussian process hydrodynamics

Abstract We present a Gaussian process (GP) approach, called Gaussian process hydrodynamics (GPH) for approximating the solution to the Euler and Navier-Stokes (NS) equations. Similar to smoothed particle hydrodynamics (SPH), GPH is a Lagrangian particle-based approach that involves the tracking of a finite number of particles transported by a flow. However, these particles do not represent mollified particles of matter but carry discrete/partial information about the continuous flow. Closure is achieved by placing a divergence-free GP prior ξ on the velocity field and conditioning it on the vorticity at the particle locations. Known physics (e.g., the Richardson cascade and velocity increment power laws) is incorporated into the GP prior by using physics-informed additive kernels. This is equivalent to expressing ξ as a sum of independent GPs ξ l , which we call modes, acting at different scales (each mode ξ l self-activates to represent the formation of eddies at the corresponding scales). This approach enables a quantitative analysis of the Richardson cascade through the analysis of the activation of these modes, and enables us to analyze coarse-grain turbulence statistically rather than deterministically. Because GPH is formulated by using the vorticity equations, it does not require solving a pressure equation. By enforcing incompressibility and fluid-structure boundary conditions through the selection of a kernel, GPH requires significantly fewer particles than SPH. Because GPH has a natural probabilistic interpretation, the numerical results come with uncertainty estimates, enabling their incorporation into an uncertainty quantification (UQ) pipeline and adding/removing particles (quanta of information) in an adapted manner. The proposed approach is suitable for analysis because it inherits the complexity of state-of-the-art solvers for dense kernel matrices and results in a natural definition of turbulence as information loss. Numerical experiments support the importance of selecting physics-informed kernels and illustrate the major impact of such kernels on the accuracy and stability. Because the proposed approach uses a Bayesian interpretation, it naturally enables data assimilation and predictions and estimations by mixing simulation data and experimental data.

Mathematics↗
DOE OSTI2026

Representation and Impact of Water Head on Power System Planning and Operation

Representing water head information in power system model files, can provide a more realistic model of the system and thereby inform operation and planning personnel in the decision-making process. This article describes a procedure for modifying the power system model files (steady-state and dynamic) to represent water head information. Additionally, the impact of representing the water head on power system reliability studies including contingency analysis, cascading failure analysis and dynamic frequency response analysis has been investigated, using the modified power system models. This paper considers the detailed Western Electricity Coordination Council model during summer and winter conditions as the test system for the impact analysis. Results show that under reduced water head: 1) the number of critical voltage and branch flow violations increases; 2) chances of cascading failure and island formation increases; and 3) frequency nadir decreases as compared to those of the base cases where the water head information is not represented.

13 - HYDRO ENERGY↗
NASA NTRS1984

The boundary layer on compressor cascade blades

The flow field about an airfoil in a cascade at chord Reynolds number (R sub C) near 50,000. The program is experimental and combines laser Doppler anemometry (LDA) with flow visualization techniques in order to obtain detailed flow data (e.g., boundary layer profiles, points of separation and the transition zone) on a cascade of highly-loaded compressor blades. The information provided is to serve as benchmark data for the evaluation of current and future compressor cascade predictive models, in this way aiding in the compressor design process. The completed pressure surface mean velocity profiles, as well as two detailed near wake velocity profiles, all at a single incidence angle are provided.

Deutsch, S.↗
NASA NTRS1986

The boundary layer on compressor cascade blades

The purpose of NASA Research Grant NSG-3264 is to characterize the flowfield about an airfoil in a cascade at chord Reynolds number(R sub C)near 5 x 10 to the 5th power. The program is experimental and combines laser Doppler velocimeter (LDV) measurements with flow visualization techniques in order to obtain detailed flow data, e.g., boundary layer profiles, points of separation and the transition zone, on a cascade of highly-loaded compressor blades. The information provided by this study is to serve as benchmark data for the evaluation of current and future compressor cascade predictive models, in this way aiding in the compressor design process. Summarized is the research activity for the period 1 December 1985 through 1 June 1986. Progress made from 1 June 1979 through 1 December 1985 is presented. Detailed measurements have been completed at the initial cascade angle of 53 deg. (incidence angle 5 degrees). A three part study, based on that data, has been accepted as part of the 1986 Gas Turbine Conference and will be submitted for subsequent journal publication. Also presented are data for a second cascade angle of 45 deg (an incidence angle of 3 degrees).

Deutsch, S.↗
NASA NTRS1993

An efficient procedure for cascade aeroelastic stability determination using nonlinear, time-marching aerodynamic solvers

A numerical eigenvalue problem formulation and a practical calculation procedure for exact eigenvalues and corresponding eigenvectors are developed and applied to a nonlinear, two-dimensional, time-marching full potential solver for cascade aeroelastic stability analysis. This procedure is based on the Lanczos recursive method and it directly calculates stability information about a nonlinear steady state. It is compared to conventional approaches in the frequency and time domains developed earlier and is found to be 100-10.000 times more computationally efficient. Eigenvalue constellations and the flutter results for flow through a cascade SR5 propfan airfoil are presented.

Mahajan, Aparajit J.↗
NASA NTRS1989

Prediction of turbine rotor-stator interaction using Navier-Stokes methods

Flows in turbomachinery are generally complex and do not easily lend themselves to numerical computation. The flows are three-dimensional and inherently unsteady. Complicated blade geometries and flow phenomena such as separation and periodic transition from laminar to turbulent flow add to the numerical complexity. Nevertheless, the accurate numerical analysis of such flows is a problem of considerable interest and practical importance to the turbomachinery community. Much of the early work in turbomachinery flow prediction focussed on airfoil cascades. While such analyses of flows in isolated airfoil rows have helped improve understanding of the flow phenomena and have gained widespread acceptance in the industrial community as a design tool, they do not yield any information regarding the unsteady effects arising out of rotor-stator aerodynamic interaction. These interaction effects become increasingly important as the distance between successive stator and rotor rows is decreased. Thus, the need exists for analytical tools that treat the rotor and stator airfoils as a system and provide information regarding the magnitude and the impact of the unsteady effects. The focus a three-dimensional, time-accurate, thin-layer Navier-Stokes code that was recently developed to study rotor-stator interaction problems. A system of patched and overlaid grids that move relative to each other is used to discretize the flow field and the governing equations are integrated using a third-order upwind scheme set in an iterative, implicit framework. The code was used to simulate subsonic flow through an axial turbine configuration for which considerable experimental data exists. Grid refinement studies were also conducted as part of the code validation process. The current status of the research, along with planned future directions, are also discussed.

Madavan, Nateri K.↗
NASA NTRS1950

Attainable circulation about airfoils in cascade

From consideration of available information on boundary-layer behavior, a relation among profile thickness, maximum surface velocity, Reynolds number, velocity diagram, and solidity is established for a cascade of airfoils immersed in a two-dimensional incompressible fluid flow. Several cascades are computed to show the effect of various cascade design parameters on minimum required cascade solidity. Comparisons with experimentally determined blade performance show that the derived blade loadings are equal or higher for moderate flow deceleration and somewhat lower for large deceleration. Blades with completely laminar flow appear practical for impulse or reaction blading.

Goldstein, Arthur W↗
NASA NTRS2001

Segmented Domain Decomposition Multigrid For 3-D Turbomachinery Flows

A Segmented Domain Decomposition Multigrid (SDDMG) procedure was developed for three-dimensional viscous flow problems as they apply to turbomachinery flows. The procedure divides the computational domain into a coarse mesh comprised of uniformly spaced cells. To resolve smaller length scales such as the viscous layer near a surface, segments of the coarse mesh are subdivided into a finer mesh. This is repeated until adequate resolution of the smallest relevant length scale is obtained. Multigrid is used to communicate information between the different grid levels. To test the procedure, simulation results will be presented for a compressor and turbine cascade. These simulations are intended to show the ability of the present method to generate grid independent solutions. Comparisons with data will also be presented. These comparisons will further demonstrate the usefulness of the present work for they allow an estimate of the accuracy of the flow modeling equations independent of error attributed to numerical discretization.

Celestina, M. L.↗
NASA NTRS2012

Variable-Speed Power-Turbine Research at Glenn Research Center

The main rotors of the NASA Large Civil Tilt-Rotor (LCTR) notional vehicle operate over a wide speed-range, from 100 percent at takeoff to 54 percent at cruise. The variable-speed power turbine (VSPT) offers one approach by which to effect this speed variation. VSPT aerodynamics challenges include high work factors at cruise, wide (40 to 60 ) incidence-angle variations in blade and vane rows over the speed range, and operation at low Reynolds numbers. Rotordynamics challenges include potential responsiveness to shaft modes within the 50 percent VSPT speed-range. A research effort underway at NASA Glenn Research Center, intended to address these key aerodynamic and rotordynamic challenges, is described. Conceptual design and 3-D multistage RANS and URANS analyses, conducted internally and under contract, provide expected VSPT sizing, stage-count, performance and operability information, and maps for system studies. Initial steps toward experimental testing of incidence-tolerant blading in a transonic linear cascade are described, and progress toward development/improvement of a simulation capability for multistage turbines with low Reynolds number transitional flow is summarized. Preliminary rotordynamics analyses indicate that viable concept engines with 50 percent VSPT shaft-speed range. Assessments of potential paths toward VSPT component-level testing are summarized.

Welch, Gerard E.↗
NASA NTRS2020

Watershed Modeling with Remotely Sensed Big Data: MODIS Leaf Area Index Improves Hydrology and Water Quality Predictions

Traditional watershed modeling often overlooks the role of vegetation dynamics. There is also little quantitative evidence to suggest that increased physical realism of vegetation dynamics in process-based models improves hydrology and water quality predictions simultaneously. In this study, we applied a modified Soil and Water Assessment Tool (SWAT) to quantify the extent of improvements that the assimilation of remotely sensed Leaf Area Index (LAI) would convey to streamflow, soil moisture, and nitrate load simulations across a 16,860 km2 agricultural watershedin the midwestern United States. We modified the SWAT source code to automatically override the model’s built-in semiempirical LAI with spatially distributed and temporally continuous estimates from Moderate Resolution Imaging Spectroradiometer (MODIS). Compared to a “basic” traditional model with limited spatial information, our LAI assimilation model (i) significantly improved daily streamflow simulations during medium-to-low flow conditions, (ii) provided realistic spatial distributions of growing season soil moisture, and (iii) substantially reproduced the long-term observed variability of daily nitrate loads. Further analysis revealed that the overestimation or underestimation of LAI imparted a proportional cascading effect on how the model partitions hydrologic fluxes and nutrient pools. As such, assimilation of MODIS LAI data corrected the model’sLAI overestimation tendency, which led to a proportionally increased rootzone soil moisture and decreased plant nitrogen uptake. With these new findings, our study fills the existing knowledge gap regarding vegetation dynamics in watershed modeling and confirms that assimilation of MODIS LAI data in watershed models can effectively improve both hydrology and water quality predictions.

Adnan Rajib↗
NASA NTRS1974

Three-dimensional flow in transonic axial compressor blade rows

Recent developments in the three-dimensional aerodynamic theory of inviscid flow in transonic axial compressors are reviewed. Emphasis is placed on the newly completed lifting surface theory of a transonic ducted rotor. The relationship between the lifting surface theory and axisymmetric through-theories of turbomachines is illustrated; a few examples of the additional information obtainable from the new theory are then given. Quasi-two-dimensional cascade theory can also be extracted from the present analysis and the relevance of cascade theory to the actual three-dimensional problem assessed. Details are reported elsewhere, but some of the qualitative conclusions are discussed here. Even moderate departure from uniform spanwise loading of the rotor blades, for example, leads to a rather profound influence of the downstream wakes, suggesting the need for considerable care in applying cascade data on a direct quasi-two-dimensional basis.

Mccune, J. E.↗
NASA NTRS2009

Experimental Study of the Effects of Periodic Unsteady Wakes on Flow Separation in Low Pressure Turbines

The present study, which is the first of a series of investigations of low pressure turbine (LPT) boundary layer aerodynamics, is aimed at providing detailed unsteady boundary layer flow information to understand the underlying physics of the inception, onset, and extent of the separation zone. A detailed experimental study on the behavior of the separation zone on the suction surface of a highly loaded LPT-blade under periodic unsteady wake flow is presented. Experimental investigations were performed on a large-scale, high-subsonic unsteady turbine cascade research facility with an integrated wake generator and test section unit. Blade Pak B geometry was used in the cascade. The wakes were generated by continuously moving cylindrical bars device. Boundary layer investigations were performed using hot wire anemometry at Reynolds number of 110,000, based on the blade suction surface length and the exit velocity, for one steady and two unsteady inlet flow conditions, with the corresponding passing frequencies, wake velocities, and turbulence intensities. The reduced frequencies cover the entire operation range of LP-turbines. In addition to the unsteady boundary layer measurements, blade surface pressure measurements were performed at Re = 50,000, 75,000, 100,000, 110,000, and 125,000. For each Reynolds number, surface pressure measurements are carried out at one steady and two periodic unsteady inlet flow conditions. Detailed unsteady boundary layer measurement identifies the onset and extension of the separation zone as well as its behavior under unsteady wake flow. The results, presented in ensemble-averaged and contour plot forms, help to understand the physics of the separation phenomenon under periodic unsteady wake flow.

Ozturk, Burak↗