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NASA NTRS1980

Supersonic flow over three-dimensional ablated nosetips using an unsteady implicit numerical procedure

The three-dimensional supersonic flow over passive, that is, nonablating, indented nosetips of reentry vehicles is determined using an unsteady implicit numerical algorithm which solves either the inviscid Euler equations or the 'thin-layer' Navier-Stokes equations. A nonorthogonal independent variable transformation is used to map the distorted physical domain, containing multiple zones of embedded subsonic flow and separated flow regions into a rectangular computational volume at whose boundaries the required permeable or impermeable boundary conditions are simulated. Use of the implicit algorithm results in faster convergence to the steady state because of a larger allowable time step over conventional explicit schemes. The numerical results obtained compare favorably with existing numerical solutions and experimental data for simple spheres which validates the program. Results are also presented for analytically defined indented bodies for both laminar and turbulent flow conditions that demonstrate the program's capability for computing such flows.

Kutler, P.↗

NASA NTRS1984

Simulation of transonic separated airfoil flow by finite difference viscous-inviscid interaction

A finite difference viscous inviscid interaction program has been developed for simulating the separated transonic flow about lifting airfoils, including the wake. In contrast to most interaction programs, this code combines a finite difference boundary layer algorithm with the inviscid program. The recently developed finite difference boundary layer code efficiently simulates attached and reversed compressible boundary layer and wake flows. New viscous inviscid interaction algorithms were also developed to couple the boundary layer code with the inviscid transonic full potential program. Transonic cases with shock induced and trailing edge separation are computed and compared with experimental and Navier-Stokes results.

Vandalsem, W. R.↗

NASA NTRS1985

Estimation of dynamic rotor loads for the rotor systems research aircraft: Methodology development and validation

The Rotor Systems Research Aircraft uses load cells to isolate the rotor/transmission systm from the fuselage. A mathematical model relating applied rotor loads and inertial loads of the rotor/transmission system to the load cell response is required to allow the load cells to be used to estimate rotor loads from flight data. Such a model is derived analytically by applying a force and moment balance to the isolated rotor/transmission system. The model is tested by comparing its estimated values of applied rotor loads with measured values obtained from a ground based shake test. Discrepancies in the comparison are used to isolate sources of unmodeled external loads. Once the structure of the mathematical model has been validated by comparison with experimental data, the parameters must be identified. Since the parameters may vary with flight condition it is desirable to identify the parameters directly from the flight data. A Maximum Likelihood identification algorithm is derived for this purpose and tested using a computer simulation of load cell data. The identification is found to converge within 10 samples. The rapid convergence facilitates tracking of time varying parameters of the load cell model in flight.

Duval, R. W.↗

NASA NTRS1984

Furthur development of the dynamic gas temperature measurement system

Candidate concepts capable of generating dynamic temperatures were identified and analyzed for use in verifying experimentally the frequency response of the dynamic gas temperature measurement system. A rotating wheel concept and one other concept will be selected for this purpose. Modifications to the data reduction code algorithms developed were identified and evaluated to reduce substantially the data reduction execution time. These modifications will be incorporated in a new data reduction program to be written in FORTRAN IV.

Elmore, D. L.↗

NASA NTRS1992

A comparison of upwind schemes for computation of three-dimensional hypersonic real-gas flows

The method of Suresh and Liou (1992) is extended, and the resulting explicit noniterative upwind finite-volume algorithm is applied to the integration of 3D parabolized Navier-Stokes equations to model 3D hypersonic real-gas flowfields. The solver is second-order accurate in the marching direction and employs flux-limiters to make the algorithm second-order accurate, with total variation diminishing in the cross-flow direction. The algorithm is used to compute hypersonic flow over a yawed cone and over the Ames All-Body Hypersonic Vehicle. The solutions obtained agree well with other computational results and with experimental data.

Gerbsch, R. A.↗

NASA NTRS1996

Design of Robust Adaptive Unbalance Response Controllers for Rotors with Magnetic Bearings

Experimental results have recently demonstrated that an adaptive open loop control strategy can be highly effective in the suppression of unbalance induced vibration on rotors supported in active magnetic bearings. This algorithm, however, relies upon a predetermined gain matrix. Typically, this matrix is determined by an optimal control formulation resulting in the choice of the pseudo-inverse of the nominal influence coefficient matrix as the gain matrix. This solution may result in problems with stability and performance robustness since the estimated influence coefficient matrix is not equal to the actual influence coefficient matrix. Recently, analysis tools have been developed to examine the robustness of this control algorithm with respect to structured uncertainty. Herein, these tools are extended to produce a design procedure for determining the adaptive law's gain matrix. The resulting control algorithm has a guaranteed convergence rate and steady state performance in spite of the uncertainty in the rotor system. Several examples are presented which demonstrate the effectiveness of this approach and its advantages over the standard optimal control formulation.

Knospe, Carl R.↗

NASA NTRS1998

Automatic Vortex Core Detection

An eigenvector method for vortex identification has been applied to recent numerical and experimental studies in external flow aerodynamics. This paper shows that it is an effective way to extract and visualize features such as vortex cores, spiral vortex breakdowns, and vortex bursts. The algorithm has also been incorporated in a finite element flow solver to guide an automatic mesh refinement program. Results show that this approach can resolve small scale vortical structures in helicopter rotor simulations which are not captured on coarse meshes.

Kenwright, David↗

NASA NTRSDate not supplied

Space Flown Rodent Liver RNA Sequencing Data for Machine Learning in Space Biology Research

High-throughput nucleic acid sequencing (DNA-seq, RNA-seq) has become widespread in biomedical research due to the growing availability and affordability of these assays. Data analysis has been accelerated in recent years by the adoption of artificial intelligence (AI) and machine learning (ML) techniques by biomedical researchers. In space biology research, RNAseq datasets from space-flown experimental samples are critical for characterizing the gene expression aberrations associated with exposure to spaceflight stressors. However, space biological experiments tend to be very low sample size, so identifying proper AI/ML algorithms for sequencing data analysis is an ongoing challenge since these algorithms typically require large sample size. The NASA Science Mission Directorate (SMD) has started the “Benchmark Initiative for AI/ML”, focused on creating datasets meant for three main applications: 1) scientific benchmarking, which finds the best algorithm for a specific problem; 2) application benchmarking, which measures algorithm performance against a set of parameters; and 3) system benchmarking, which evaluates performance of hardware and software architecture. These scientific benchmarks consist of an AI-ready dataset and a reference implementation on a specific scientific question. In this work, we focused on generating standardized datasets to allow the scientific community to benchmark AI/ML algorithms in the domain of space biology. We present here a standardized, AI-ready, publicly available benchmark dataset for space biology RNA-seq data as a collaboration between the NASA AI4LS (Artificial Intelligence for Life Sciences) working group. and NASA’s SMD. This dataset consists of space-flown and ground control mouse liver found in the NASA GeneLab omics database. However, to amplify the small sample number (n=112 samples) for ML purposes, we employ Gaussian noise and a generative adversarial network to extend this dataset to 6,000 synthetic samples, matching the original gene expression characteristics.

James Casaletto↗

NASA NTRS2022

Hybrid Model Based Approaches for Systems Health Management and Prognostics

This is a previously approved and published presentation. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Present achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. In principle, data-driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data-driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety-critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Prognostics↗

NASA NTRS2003

Computational And Experimental Studies Of Three-Dimensional Flame Spread Over Liquid Fuel Pools

Schiller, Ross, and Sirignano (1996) studied ignition and flame spread above liquid fuels initially below the flashpoint temperature by using a two-dimensional computational fluid dynamics code that solves the coupled equations of both the gas and the liquid phases. Pulsating flame spread was attributed to the establishment of a gas-phase recirculation cell that forms just ahead of the flame leading edge because of the opposing effect of buoyancy-driven flow in the gas phase and the thermocapillary-driven flow in the liquid phase. Schiller and Sirignano (1996) extended the same study to include flame spread with forced opposed flow in the gas phase. A transitional flow velocity was found above which an originally uniform spreading flame pulsates. The same type of gas-phase recirculation cell caused by the combination of forced opposed flow, buoyancy-driven flow, and thermocapillary-driven concurrent flow was responsible for the pulsating flame spread. Ross and Miller (1998) and Miller and Ross (1998) performed experimental work that corroborates the computational findings of Schiller, Ross, and Sirignano (1996) and Schiller and Sirignano (1996). Cai, Liu, and Sirignano (2002) developed a more comprehensive three-dimensional model and computer code for the flame spread problem. Many improvements in modeling and numerical algorithms were incorporated in the three-dimensional model. Pools of finite width and length were studied in air channels of prescribed height and width. Significant three-dimensional effects around and along the pool edge were observed. The same three-dimensional code is used to study the detailed effects of pool depth, pool width, opposed air flow velocity, and different levels of air oxygen concentration (Cai, Liu, and Sirignano, 2003). Significant three-dimensional effects showing an unsteady wavy flame front for cases of wide pool width are found for the first time in computation, after being noted previously by experimental observers (Ross and Miller, 1999). Regions of uniform and pulsating flame spread are mapped for the flow conditions of pool depth, opposed flow velocity, initial pool temperature, and air oxygen concentration under both normal and microgravity conditions. Details can be found in Cai et al. (2002, 2003). Experimental results recently performed at NASA Glenn of flame spread across a wide, shallow pool as a function of liquid temperature are also presented here.

Ross, Howard D.↗

NASA NTRS1985

A multistage time-stepping scheme for the Navier-Stokes equations

A class of explicit multistage time-stepping schemes is used to construct an algorithm for solving the compressible Navier-Stokes equations. Flexibility in treating arbitrary geometries is obtained with a finite-volume formulation. Numerical efficiency is achieved by employing techniques for accelerating convergence to steady state. Computer processing is enhanced through vectorization of the algorithm. The scheme is evaluated by solving laminar and turbulent flows over a flat plate and an NACA 0012 airfoil. Numerical results are compared with theoretical solutions or other numerical solutions and/or experimental data.

Swanson, R. C.↗

NASA NTRS1985

A multistage time-stepping scheme for the Navier-Stokes equations

Swanson, R. C.↗

NASA NTRS1986

A multistage time-stepping scheme for the thin-layer Navier-Stokes equations

A finite-volume scheme for numerical integration of the Euler equations was extended to allow solution of the thin-layer Navier-Stokes equations in two and three dimensions. The extended algorithm, which is based on a class of four-stage Runge-Kutta time-stepping schemes, was made numerically efficient through the following convergence acceleration technique: (1) local time stepping, (2) enthalpy damping, and (3) residual smoothing. Also, the high degree of vectorization possible with the algorithm has yielded an efficient program for vector processors. The scheme was evaluated by solving laminar and turbulent flows. Numerical results have compared well with either theoretical or other numerical solutions and/or experimental data.

Swanson, R. C., Jr.↗

NASA NTRS1992

Ionospheric gravity wave measurements with the USU dynasonde

A method for the measurement of ionospheric Gravity Wave (GW) using the USU Dynasonde is outlined. This method consists of a series of individual procedures, which includes functions for data acquisition, adaptive scaling, polarization discrimination, interpolation and extrapolation, digital filtering, windowing, spectrum analysis, GW detection, and graphics display. Concepts of system theory are applied to treat the ionosphere as a system. An adaptive ionogram scaling method was developed for automatically extracting ionogram echo traces from noisy raw sounding data. The method uses the well known Least Mean Square (LMS) algorithm to form a stochastic optimal estimate of the echo trace which is then used to control a moving window. The window tracks the echo trace, simultaneously eliminating the noise and interference. Experimental results show that the proposed method functions as designed. Case studies which extract GW from ionosonde measurements were carried out using the techniques described. Geophysically significant events were detected and the resultant processed results are illustrated graphically. This method was also developed for real time implementation in mind.

Berkey, Frank T.↗

NASA NTRS1990

Myths and legends in learning classification rules

This paper is a discussion of machine learning theory on empirically learning classification rules. The paper proposes six myths in the machine learning community that address issues of bias, learning as search, computational learning theory, Occam's razor, 'universal' learning algorithms, and interactive learnings. Some of the problems raised are also addressed from a Bayesian perspective. The paper concludes by suggesting questions that machine learning researchers should be addressing both theoretically and experimentally.

Buntine, Wray↗

NASA NTRS1992

Implementation of input command shaping to reduce vibration in flexible space structures

Viewgraphs on implementation of input command shaping to reduce vibration in flexible space structures are presented. Goals of the research are to explore theory of input command shaping to find an efficient algorithm for flexible space structures; to characterize Middeck Active Control Experiment (MACE) test article; and to implement input shaper on the MACE structure and interpret results. Background on input shaping, simulation results, experimental results, and future work are included.

Chang, Kenneth W.↗

NASA NTRS1999

A Study of Quality of Service Communication for High-Speed Packet-Switching Computer Sub-Networks

In this thesis, we analyze various factors that affect quality of service (QoS) communication in high-speed, packet-switching sub-networks. We hypothesize that sub-network-wide bandwidth reservation and guaranteed CPU processing power at endpoint systems for handling data traffic are indispensable to achieving hard end-to-end quality of service. Different bandwidth reservation strategies, traffic characterization schemes, and scheduling algorithms affect the network resources and CPU usage as well as the extent that QoS can be achieved. In order to analyze those factors, we design and implement a communication layer. Our experimental analysis supports our research hypothesis. The Resource ReSerVation Protocol (RSVP) is designed to realize resource reservation. Our analysis of RSVP shows that using RSVP solely is insufficient to provide hard end-to-end quality of service in a high-speed sub-network. Analysis of the IEEE 802.lp protocol also supports the research hypothesis.

Cui, Zhenqian↗

NASA NTRS2003

Numerical Models of Human Circulatory System under Altered Gravity: Brain Circulation

A computational fluid dynamics (CFD) approach is presented to model the blood flow through the human circulatory system under altered gravity conditions. Models required for CFD simulation relevant to major hemodynamic issues are introduced such as non-Newtonian flow models governed by red blood cells, a model for arterial wall motion due to fluid-wall interactions, a vascular bed model for outflow boundary conditions, and a model for auto-regulation mechanism. The three-dimensional unsteady incompressible Navier-Stokes equations coupled with these models are solved iteratively using the pseudocompressibility method and dual time stepping. Moving wall boundary conditions from the first-order fluid-wall interaction model are used to study the influence of arterial wall distensibility on flow patterns and wall shear stresses during the heart pulse. A vascular bed modeling utilizing the analogy with electric circuits is coupled with an auto-regulation algorithm for multiple outflow boundaries. For the treatment of complex geometry, a chimera overset grid technique is adopted to obtain connectivity between arterial branches. For code validation, computed results are compared with experimental data for steady and unsteady non-Newtonian flows. Good agreement is obtained for both cases. In sin-type Gravity Benchmark Problems, gravity source terms are added to the Navier-Stokes equations to study the effect of gravitational variation on the human circulatory system. This computational approach is then applied to localized blood flows through a realistic carotid bifurcation and two Circle of Willis models, one using an idealized geometry and the other model using an anatomical data set. A three- dimensional anatomical Circle of Willis configuration is reconstructed from human-specific magnetic resonance images using an image segmentation method. The blood flow through these Circle of Willis models is simulated to provide means for studying gravitational effects on the brain circulation under auto-regulation.

Kim, Chang Sung↗