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NASA NTRS2018

Stochastic Reduced Order Models with Python (SROMPy)

Stochastic Reduced Order Models with Python (SROMPy) is a software package developed to enable user-friendly utilization of the stochastic reduced order model (SROM) approach for uncertainty quantification. A SROM is a low dimensional, discrete approximation to a random quantity that enables efficient and non-intrusive stochastic computations. With SROMPy, a user can easily generate a SROM to approximate a random variable or vector described by several different types of probability distributions using the Python programming language. Once a SROM is constructed, the software can be used to propagate uncertainty through a user-defined computational model to estimate statistics of a given quantity of interest. This report is meant to introduce the SROMPy module and brie y demonstrate its capabilities. A simple example of a spring-mass system with a random input is included to illustrate the practicality of the SROM approach to uncertainty quantification and relative ease of applying it with SROMPy. The example includes a comparison with a solution obtained using classical Monte Carlo simulation, demonstrating the similarities and advantages of using the SROM approach.

Warner, James E.↗

NASA NTRS2015

Comparison of High-Order and Low-Order Methods for Large-Eddy Simulation of a Compressible Shear Layer

The objective of this work is to compare a high-order solver with a low-order solver for performing large-eddy simulations (LES) of a compressible mixing layer. The high-order method is the Wave-Resolving LES (WRLES) solver employing a Dispersion Relation Preserving (DRP) scheme. The low-order solver is the Wind-US code, which employs the second-order Roe Physical scheme. Both solvers are used to perform LES of the turbulent mixing between two supersonic streams at a convective Mach number of 0.46. The high-order and low-order methods are evaluated at two different levels of grid resolution. For a fine grid resolution, the low-order method produces a very similar solution to the high-order method. At this fine resolution the effects of numerical scheme, subgrid scale modeling, and filtering were found to be negligible. Both methods predict turbulent stresses that are in reasonable agreement with experimental data. However, when the grid resolution is coarsened, the difference between the two solvers becomes apparent. The low-order method deviates from experimental results when the resolution is no longer adequate. The high-order DRP solution shows minimal grid dependence. The effects of subgrid scale modeling and spatial filtering were found to be negligible at both resolutions. For the high-order solver on the fine mesh, a parametric study of the spanwise width was conducted to determine its effect on solution accuracy. An insufficient spanwise width was found to impose an artificial spanwise mode and limit the resolved spanwise modes. We estimate that the spanwise depth needs to be 2.5 times larger than the largest coherent structures to capture the largest spanwise mode and accurately predict turbulent mixing.

large eddy simulations↗

NASA NTRS2006

Dielectronic Recombination In Active Galactic Nuclei

XMM-Newton and Chandra observations of active galactic nuclei (AGN) show rich spectra of X-ray absorption lines. These observations have detected a broad unresolved transition array (UTA) between approx. 15-17 A. This is attributed to inner-shell photoexcitation of M-shell iron ions. Modeling these UTA features is currently limited by uncertainties in the low-temperature dielectronic recombination (DR) data for M-shell iron. In order to resolve this issue, and to provide reliable iron M-shell DR data for plasma modeling, we are carrying out a series of laboratory measurements using the heavy-ion Test Storage Ring (TSR) at the Max-Plank-Institute for Nuclear Physics in Heidelberg, Germany. Currently, laboratory measurements of low temperature DR can only be performed at storage rings. We use the DR data obtained at TSR, to calculate rate coefficients for plasma modeling and to benchmark theoretical DR calculations. Here we report our recent experimental results for DR of Fe XIV forming Fe XIII.

Lukic, D. V.↗

NASA NTRS2015

Low Order Wavefront Sensing and Control for WFIRST-AFTA Coronagraph

To maintain the required WFIRST Coronagraph performance in a realistic space environment, a low order wavefront sensing and control (LOWFS/C) subsystem is necessary. The LOWFS/C use s the rejected stellar light from coronagraph to sense and suppress the telescope pointing drift and jitter as well as the low order wavefront errors due to changes in thermal loading of the telescope and the rest of the observatory. In this paper we will present an overview of the low order wavefront sensing and control subsystem for the WFIRST -AFTA Coronagraph. We will describe LOWFS/C's Zernike wavefront sensor concept and WFIRST LOWFS/C control design. We will present an overview of our analysis and modeling results on the Zernike wavefront sensor, the line -of-sight jitter suppression loop performance, as well as the low order wavefront error correction with the coronagraph's deformable mirror. In this paper we will also report the LOWFS/C testbed design and the preliminary in-air test results, which show a very promising performance of the Zernike wavefront sensor and FSM feedback loop.

exoplanets↗

NASA NTRS1998

High-Density Plasma Reactors: Simulations for Design

The development of improved and more efficient plasma reactors is a costly process for the semiconductor industry. Until five years ago, the Industry made most of its advancements through a trial and error approach. More recently, the role of computational modeling in the design process has increased. Both conventional computational fluid dynamics (CFD) techniques like Navier-Stokes solvers as well as particle simulation methods are used to model plasma reactor flowfields. However, since high-density plasma reactors generally operate at low gas pressures on the order of 1 to 10 mTorr, a particle simulation may be necessary because of the failure of CFD techniques to model rarefaction effects. The direct simulation Monte Carlo method is the most widely accepted and employed particle simulation tool and has previously been used to investigate plasma reactor flowfields. A plasma DSMC code is currently under development at NASA Ames Research Center with its foundation as the object-oriented parallel Cornell DSMC code, MONACO. The present investigation is a follow up of a neutral flow investigation of the effects of process parameters as well as reactor design on etch rate and etch rate uniformity. The previous work concentrated on silicon etch of a chlorine flow in a configuration typical of electron cyclotron resonance (ECR) or helical resonator type reactors. The effects of the plasma on the dissociation chemistry were modeled by making assumptions about the electron temperature and number density. The electrons or ions themselves were not simulated.The present work extends these results by simulating the charged species.The electromagnetic fields are calculated such that power deposition is modeled self-consistently. Electron impact reactions are modeled along with mechanisms for charge exchange. An bipolar diffusion assumption is made whereby electrons remain tied to the ions. However, the velocities of tile electrons are allowed to be modified during collisions and are not confined to a Maxwellian distribution. The interaction between the neutral flow and plasma is examined, and results for etch rate uniformity from the previous research and the present plasma simulations are compared.

Hash, David B.↗

NASA NTRS1994

Correlations in cosmic density fields

A method is proposed to place constraints on the functional form of the high-order correlation functions zeta(sub n) that arise in cosmic density fields at large scales. This technique is based on a mass-in-cell statistic and a difference of mass in partitions of a cell. The relationship between these measures is sensitive to the formal structure of the zeta(sub n) as well as their amplitudes. This relationship is quantified in several theoretical models of structure, based on the hierarchical clustering paradigm. The results lead to a test for specific types of hierarchical clustering that is sensitive to correlations of all orders. The method is applied to examples of simulated large-scaled structure dominated by cold dark matter. In the preliminary study, the hierarchical paradigm appears to be a realistic approximation over a broad range of the scales. Furthermore, there is evidence that graphs of low-order vertices are dominant. On the basis of simulated data a phenomological model is specified that gives a good representation of clustering from linear scales to the strongly clustered regime (zeta(sub 2) approximately 500).

Bromley, B. C.↗

NASA NTRS2010

Enceladus Plume Density Modeling and Reconstruction for Cassini Attitude Control System

In 2005, Cassini detected jets composed mostly of water, spouting from a set of nearly parallel rifts in the crust of Enceladus, an icy moon of Saturn. During an Enceladus flyby, either reaction wheels or attitude control thrusters on the Cassini spacecraft are used to overcome the external torque imparted on Cassini due to Enceladus plume or jets, as well as to slew the spacecraft in order to meet the pointing needs of the on-board science instruments. If the estimated imparted torque is larger than it can be controlled by the reaction wheel control system, thrusters are used to control the spacecraft. Having an engineering model that can predict and simulate the external torque imparted on Cassini spacecraft due to the plume density during all projected low-altitude Enceladus flybys is important. Equally important is being able to reconstruct the plume density after each flyby in order to calibrate the model. This paper describes an engineering model of the Enceladus plume density, as a function of the flyby altitude, developed for the Cassini Attitude and Articulation Control Subsystem, and novel methodologies that use guidance, navigation, and control data to estimate the external torque imparted on the spacecraft due to the Enceladus plume and jets. The plume density is determined accordingly. The methodologies described have already been used to reconstruct the plume density for three low-altitude Enceladus flybys of Cassini in 2008 and will continue to be used on all remaining low-altitude Enceladus flybys in Cassini's extended missions.

Sarani, Siamak↗

NASA NTRS1992

HDL to verification logic translator

The increasingly higher number of transistors possible in VLSI circuits compounds the difficulty in insuring correct designs. As the number of possible test cases required to exhaustively simulate a circuit design explodes, a better method is required to confirm the absence of design faults. Formal verification methods provide a way to prove, using logic, that a circuit structure correctly implements its specification. Before verification is accepted by VLSI design engineers, the stand alone verification tools that are in use in the research community must be integrated with the CAD tools used by the designers. One problem facing the acceptance of formal verification into circuit design methodology is that the structural circuit descriptions used by the designers are not appropriate for verification work and those required for verification lack some of the features needed for design. We offer a solution to this dilemma: an automatic translation from the designers' HDL models into definitions for the higher-ordered logic (HOL) verification system. The translated definitions become the low level basis of circuit verification which in turn increases the designer's confidence in the correctness of higher level behavioral models.

Gambles, J. W.↗

NASA NTRS1984

Long-lifetime Martian orbit selection using a time-dependent model of the Martian atmosphere

A mathematical model of the time-dependent Martian atmosphere has been developed in order to accurately calculate the effects of aerodynamic drag on a low altitude satellite. The time-dependent properties of the model include solar activity effects, dust storm effects, seasonal and diurnal variations, and annual motion effects. Position effects are accounted for through Martian latitude and longitude. Expected values of mass density, temperature, scale height, and the estimated standard deviation of the mass density are provided. An example of the use of the model in selecting an orbit for the Mars Geochemical/Climatology Orbiter is given.

Culp, R. D.↗

NASA NTRS2001

Dynamic regulation of heart rate during acute hypotension: new insight into baroreflex function

To examine the dynamic properties of baroreflex function, we measured beat-to-beat changes in arterial blood pressure (ABP) and heart rate (HR) during acute hypotension induced by thigh cuff deflation in 10 healthy subjects under supine resting conditions and during progressive lower body negative pressure (LBNP). The quantitative, temporal relationship between ABP and HR was fitted by a second-order autoregressive (AR) model. The frequency response was evaluated by transfer function analysis. Results: HR changes during acute hypotension appear to be controlled by an ABP error signal between baseline and induced hypotension. The quantitative relationship between changes in ABP and HR is characterized by a second-order AR model with a pure time delay of 0.75 s containing low-pass filter properties. During LBNP, the change in HR/change in ABP during induced hypotension significantly decreased, as did the numerator coefficients of the AR model and transfer function gain. Conclusions: 1) Beat-to-beat HR responses to dynamic changes in ABP may be controlled by an error signal rather than directional changes in pressure, suggesting a "set point" mechanism in short-term ABP control. 2) The quantitative relationship between dynamic changes in ABP and HR can be described by a second-order AR model with a pure time delay. 3) The ability of the baroreflex to evoke a HR response to transient changes in pressure was reduced during LBNP, which was due primarily to a reduction of the static gain of the baroreflex.

Clinical Trial↗

NASA NTRS2013

Thermal Modeling in Support of the Edison Demonstration of Smallsat Networks Project

NASA's Edison program is intending to launch a swarm of at least 8 small satellites in 2013. This swarm of 1.5U Cubesats, the Edison Demonstration of Smallsat Networks (EDSN) project, will demonstrate intra-swarm communications and multi-point in-situ space physics data acquisition. In support of the design and testing of the EDSN satellites, a geometrically accurate thermal model has been constructed. Due to the low duty cycle of most components, no significant overheating issues were found. The predicted mininum temperatures of the external antennas are low enough, however, that some mitigation may be in order. The development and application of the model will be discussed in detail.

Coker, Robert F.↗

NASA NTRS2013

Thermal Modeling in Support of the Edison Demonstration of Smallsat Networks Project

Coker, Robert↗

NASA NTRSDate not supplied

Multiscale Modeling of Reconstructed Tricalcium Silicate using NASA Multiscale Analysis Tool

To study microstructure characteristics of cementitious materials hydrated in space; previously, cement binder formations were processed under microgravity conditions and was further compared against ground-based experiments. For accurate estimation of process-structure-property linkage, particularly on samples hydrated in the microgravity environment, it is desired to have a high-fidelity volumetric representation of the microstructure. However, owing to small sample size and high porosity of the space-returned samples, conventional experimental characterization techniques are not viable. Hence, a deep learning-based reconstruction algorithm was employed to obtain high fidelity 3D volumes from sparse high resolution 2D Scanning Electron Microscopy (SEM) images, as inputs to micromechanics-based modeling. This machine learning-based reconstruction methodology validated against low-order statistical descriptors, captured the microstructural topology of both sample types (ground, 1g and microgravity, μg). Due to the lack of gravity, hydration products of the samples processed in space differed from those processed-on ground. Such AI-generated virtual samples were analyzed in a multiscale recursive micromechanics approach using the NASA Multiscale Analysis Tool (NASMAT). Here, we present a methodology to rapidly integrate and evaluate these AI-generated volumes in NASMAT. The synthesized microstructural volumes are directly employed as Representative Volume Elements (RVEs) to preserve the fidelity (1 pixel = 0.54 m). Invariably, analysis of such largescale problems (5123 voxels) requires huge amount of computational resources. By taking advantage of the NASMAT architecture, we also focused on systematic multiscale integration of these AI-reconstructed virtual volumes to reduce the computational demands. In this work, this methodology is demonstrated on the ground-based, 1g samples. The estimated stiffness value of 15.90 GPa is comparable to experimentally obtained modulus of hydrated tricalcium silicate sample. The workflow presented here paves the way for utilizing the NASMAT tool to perform multiscale analyses of other multi-phase material systems using either 3D virtual datasets synthesized using AI or obtained via micro-CT.

Machine Learning↗

NASA NTRS1989

A multiloop, digital flutter suppression control law synthesis case study

A methodology for obtaining a digital low-order, multiloop, robust control law for aeroelastic application from a full-state Linear Quadratic Gaussian design is presented. As part of the design methodology, the multivariable system robustness at the plant input and output is evaluated using singular value properties and improved using constrained optimization procedures. To validate the methodology, a digital flutter suppression system has been designed for the full-span Active Flexible Wing (AFW) wind-tunnel model as part of a collaborative effort between the NASA Langley Research Center and Rockwell International. Preliminary results for a low-order discrete, symmetric flutter suppression system design that significantly improved the AFW model stability are provided and the experiences gained during the design process are discussed.

Mukhopadhyay, Vivek↗

NASA NTRS1992

Experimental dehydration of natural obsidian and estimation of DH2O at low water contents

Water diffusion experiments were carried out by dehydrating rhyolitic obsidian from Valles Caldera (New Mexico, USA) at 510-980 degrees C. The starting glass wafers contained approximately 0.114 wt% total water, lower than any glasses previously investigated for water diffusion. Weight loss due to dehydration was measured as a function of experiment duration, which permits determination of mean bulk water diffusivity, mean Dw. These diffusivities are in the range of 2.6 to 18 X 10(-14) m2/s and can be fit with the following Arrhenius equation: ln mean Dw (m2/s) = -(25.10 +/- 1.29) - (46,480 +/- 11,400) (J/mol) / RT, except for two replicate runs at 510 degrees C which give mean Dw values much lower than that defined by the above equation. When interpreted according to a model of water speciation in which molecular H2O is the diffusing species with concentration-independent diffusivity while OH units do not contribute to the transport but react to provide H2O, the data (except for the 510 degrees C data) are in agreement with extrapolation from previous results and hence extend the previous data base and provide a test of the applicability of the model to very low water contents. Mean bulk water diffusivities are about two orders of magnitude less than molecular H2O diffusivities because the fraction of molecular H2O out of total water is very small at 0.114 wt% total water and less. The 510 degrees C experimental results can be interpreted as due to slow kinetics of OH to H2O interconversion at low temperatures.

NASA Program Exobiology↗

NASA NTRS1973

Optimal space communications techniques

The design, development, and analysis are reported of a digital phase-locked loop (DPLL) for FM demodulation and threshold extension. One of the features of the developed DPLL is its synchronous, real time operation. The sampling frequency is constant and all the required arithmetic and logic operations are performed within one sampling period, generating an output sequence which is converted to analog form and filtered. An equation relating the sampling frequency to the carrier frequency must be satisfied to guarantee proper DPLL operation. The synchronous operation enables a time-shared operation of one DPLL to demodulate several FM signals simultaneously. In order to obtain information about the DPLL performance at low input signal-to-noise ratios, a model of an input noise spike was introduced, and the DPLL equation was solved using a digital computer. The spike model was successful in finding a second order DPLL which yielded a five db threshold extension beyond that of a first order DPLL.

Schilling, D. L.↗

NASA NTRSDate not supplied

Multifidelity Optimization with Transonic Flutter Constraints

This work considers static and dynamic aeroelastic optimization of a cantilevered platewing in transonic flow. Low- and high-fidelity aeroelastic predictions are fed into a standard trust region model management scheme in order to efficiently solve this expensive optimization problem with multifidelity methods. Differences in fidelity are entirely driven by different aerodynamic solvers: linear panel methods for the low-fidelity method, and inviscid CFD-based solvers for the high-fidelity response. The optimization problem utilizes shape, sizing, and trim variables to satisfy stress, trim, and flutter constraints, and is solved across a range of subsonic and transonic Mach numbers. The multifidelity method is able to provide a speed-up for all cases considered here, despite sizable inaccuracies in the low-fidelity response for transonic flows.

Bret K Stanford↗

NASA NTRS2005

Reduced-Order Modeling of a Heaving Airfoil

A reduced-order model of a flapping airfoil is developed using Proper Orthogonal Decomposition (POD). The proper basis functions, developed from snapshots of full Navier-Stokes simulations, are used for a Galerkin projection of the governing equations. The resulting coupled, nonlinear ordinary di.erential equations have a low dimension because the first few basis members capture most of the energy of the flow. The reduced-order model is used to simulate heaving motions that are both similar to and different from the motion(s) used to generate the basis functions, and the errors in the model are quantified. Several methods are used to generate mode sets that can be used over a range of heaving parameters, including snapshots from one, two, and multiple Navier-Stokes simulations. As snapshots from additional simulations are added to the decomposition, the mode sets become richer and can simulate a wider range of parameter space, at some computational cost. Whereas the POD method is fully applicable in three dimensions, the simulation technique based on a body-fixed and body-fitted grid suffers large overhead when extended to three dimensions. To reduce the overhead, an embedding technique is discussed which embeds the solid wing into a fixed Cartesian grid. The wing, which can now have multiple pieces and also be flexible, is represented by a distribution of body forces. This distribution is determined to give exactly the flow around a flapping wing.

Haj-Hariri, H.↗