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NASA NTRS1993

Updating finite element dynamic models using an element-by-element sensitivity methodology

A sensitivity-based methodology for improving the finite element model of a given structure using test modal data and a few sensors is presented. The proposed method searches for both the location and sources of the mass and stiffness errors and does not interfere with the theory behind the finite element model while correcting these errors. The updating algorithm is derived from the unconstrained minimization of the squared L sub 2 norms of the modal dynamic residuals via an iterative two-step staggered procedure. At each iteration, the measured mode shapes are first expanded assuming that the model is error free, then the model parameters are corrected assuming that the expanded mode shapes are exact. The numerical algorithm is implemented in an element-by-element fashion and is capable of 'zooming' on the detected error locations. Several simulation examples which demonstate the potential of the proposed methodology are discussed.

Farhat, Charbel↗

NASA NTRS2011

Negative Stress Margins - Are They Real?

Advances in modeling and simulation, new finite element software, modeling engines and powerful computers are providing opportunities to interrogate designs in a very different manner and in a more detailed approach than ever before. Margins of safety are also often evaluated using local stresses for various design concepts and design parameters quickly once analysis models are defined and developed. This paper suggests that not all the negative margins of safety evaluated are real. The structural areas where negative margins are frequently encountered are often near stress concentrations, point loads and load discontinuities, near locations of stress singularities, in areas having large gradients but with insufficient mesh density, in areas with modeling issues and modeling errors, and in areas with connections and interfaces, in two-dimensional (2D) and three-dimensional (3D) transitions, bolts and bolt modeling, and boundary conditions. Now, more than ever, structural analysts need to examine and interrogate their analysis results and perform basic sanity checks to determine if these negative margins are real.

Raju, Ivatury S.↗

NASA NTRS2011

Negative stress margins – are they real?

Raju, Ivatury S.↗

NASA NTRS1993

A comparison of refined models for flexible subassemblies

Interactions between structure response and control of large flexible space systems have challenged current modeling techniques and have prompted development of new techniques for model improvement. Due to the geometric complexity of envisioned large flexible space structures, finite element models (FEM's) will be used to predict the dynamic characteristics of structural components. It is widely accepted that these models must be experimentally 'validated' before their acceptance as the basis for final design analysis. However, predictions of modal properties (natural frequencies, mode shapes, and damping ratios) are often in error when compared to those obtained from Experimental Modal Analysis (EMA). Recent research efforts have resulted in the development of algorithmic approaches for model improvement, also referred to as system or structure identification.

Smith, Suzanne Weaver↗

NASA NTRS2012

RxGen General Optical Model Prescription Generator

RxGen is a prescription generator for JPL's in-house optical modeling software package called MACOS (Modeling and Analysis for Controlled Optical Systems), which is an expert optical analysis software package focusing on modeling optics on dynamic structures, deformable optics, and controlled optics. The objectives of RxGen are to simplify and automate MACOS prescription generations, reducing errors associated with creating such optical prescriptions, and improving user efficiency without requiring MACOS proficiency. RxGen uses MATLAB (a high-level language and interactive environment developed by MathWorks) as the development and deployment platform, but RxGen can easily be ported to another optical modeling/analysis platform. Running RxGen within the modeling environment has the huge benefit that variations in optical models can be made an integral part of the modeling state. For instance, optical prescription parameters determined as external functional dependencies, optical variations by controlling the in-/exclusion of optical components like sub-systems, and/or controlling the state of all components. Combining the mentioned capabilities and flexibilities with RxGen's optical abstraction layer completely eliminates the hindering aspects for requiring proficiency in writing/editing MACOS prescriptions, allowing users to focus on the modeling aspects of optical systems, i.e., increasing productivity and efficiency. RxGen provides significant enhancements to MACOS and delivers a framework for fast prototyping as well as for developing very complex controlled optical systems.

Sigrist, Norbert↗

NASA NTRS1977

Prediction of pilot reserve attention capacity during air-to-air target tracking

Reserve attention capacity of a pilot was calculated using a pilot model that allocates exclusive model attention according to the ranking of task urgency functions whose variables are tracking error and error rate. The modeled task consisted of tracking a maneuvering target aircraft both vertically and horizontally, and when possible, performing a diverting side task which was simulated by the precise positioning of an electrical stylus and modeled as a task of constant urgency in the attention allocation algorithm. The urgency of the single loop vertical task is simply the magnitude of the vertical tracking error, while the multiloop horizontal task requires a nonlinear urgency measure of error and error rate terms. Comparison of model results with flight simulation data verified the computed model statistics of tracking error of both axes, lateral and longitudinal stick amplitude and rate, and side task episodes. Full data for the simulation tracking statistics as well as the explicit equations and structure of the urgency function multiaxis pilot model are presented.

Onstott, E. D.↗

NASA NTRSDate not supplied

Precision in Assembled Discrete Lattice Space Structures for Next-Generation ISAM Applications

Robust autonomous robotic assembly of large-scale space structures has been a long-term and challenging goal to enable higher quality in-space communication and science instrumentation. For optical observatory support structures and antenna structures, the challenge is the strict dimensional precision requirements (generally RMS surface error) driven by the operational radiation wavelength. Early theoretical work in the area linked RMS surface error of a reflector support truss plate to the natural passive dynamic mode frequencies of the structure, as well as to the error distribution in dimensions of constituent structural elements. Prior robotic truss assembly demonstrations focused on designing ultra-high precision structural elements, joints, and robotic actuators. Recently, an alternative space structure assembly strategy based on a programmable matter approach (NASA ARMADAS) was demonstrated. This approach uses lattice building blocks (voxels) that are reversibly, mechanically joined into a bulk lattice structure by robots that locomote in and on the structure itself. Such a system can achieve high-level autonomy with low computation, robustly assemble utilizing inexpensive and imprecise robots, and efficiently build structures several orders of magnitude larger than the assembly robots. However, for instrumentation support structure applications, the resulting precision of these building block-based lattice structures is not well studied. Since they are demonstrated with many more assembly units than prior art trusses, it is unclear whether the same precision design approaches apply. In this work, we study in simulation the effects of voxel geometry, error in distribution, assembly resolution (module size), and assembly geometry on the error of both beam and plate lattice structures. While average RMS error of a plate increases with plate size, increasing plate thickness quickly collapses RMS error towards a limit that is on the order of the error of the constituent parts. We validate our models against previously published precision measurements of built systems. Results from this study will guide manufacturing precision requirements, as well as designs, for future robotically assembled structural applications and establish feasibility for different applications.

Christine E Gregg↗

NASA NTRS1984

Fitting aerodynamic forces in the Laplace domain: An application of a nonlinear nongradient technique to multilevel constrained optimization

A technique which employs both linear and nonlinear methods in a multilevel optimization structure to best approximate generalized unsteady aerodynamic forces for arbitrary motion is described. Optimum selection of free parameters is made in a rational function approximation of the aerodynamic forces in the Laplace domain such that a best fit is obtained, in a least squares sense, to tabular data for purely oscillatory motion. The multilevel structure and the corresponding formulation of the objective models are presented which separate the reduction of the fit error into linear and nonlinear problems, thus enabling the use of linear methods where practical. Certain equality and inequality constraints that may be imposed are identified; a brief description of the nongradient, nonlinear optimizer which is used is given; and results which illustrate application of the method are presented.

Tiffany, S. H.↗

NASA NTRS1986

Space Station dynamic modeling, control and simulation

Dynamic disturbances of many orders of magnitude greater than those of conventional spacecraft will be routine for the Space Station. Accurate knowledge of inflight structural dynamics and disturbances will be lacking. System identification will reduce uncertainties. To deal with the remaining model errors and time-varying elements, adaptive control may be required. Dynamic models for two Space Station configurations are derived. A direct model reference adaptive control algorithm is synthesized and evaluated with respect to the station model parameter errors and plant dynamics truncations. Both the rigid body and the flexible modes are treated. Simulation results show that convergence of the adaptive algorithm can be achieved in 100 to about 300 seconds with reasonable performance even during Shuttle hard docking operations in which station mass and inertia are instantaneously changed by more than 100 percent.

Ih, C.-H. C.↗

NASA NTRS1989

Model reduction for flexible spacecraft with clustered natural frequencies

Two approaches to the problem of model reduction for flexible spacecraft that have proved very useful are balancing and model truncation. Furthermore, it is well known that a model representation of a lightly damped flexible structure with widely spaced natural frequencies is approximately balanced. Consequently, reduction in either coordinate system gives similar results for this case. It is important to note, however, that flexible space structures typically have clusters of closely spaced frequencies. In such cases, reduction in model coordinates can give large errors, while the error obtained using balancing is generally much smaller. A new reduction procedure which combines the best features of model and balanced reduction is therefore developed. It is more efficient than balanced reduction of the full system, as it only involves balancing those subsystems of close modes that are highly correlated, yet is shown to yield results which are essentially as good.

Williams, T. W. C.↗

NASA NTRS1999

TRMM Field Campaigns: Objectives and Status Report

The Tropical Rainfall Measuring Mission (TRMM) satellite has been sending valuable data since launch in November 1997. Some of the key goals of the joint NASA (US) and NASDA (Japan) mission are: (1) to estimate the four-dimensional diabatic heating in the tropical and subtropical atmosphere, (2) understand the role of latent heating in driving tropical and extratropical circulations, (3) obtain monthly area-averaged estimates of rainfall over the data-sparse oceans, and (4) estimate the relative contribution of convective and stratiform precipitation over different regions during different seasons. The overarching scientific objective is to understand and improve estimates of rainfall and latent heating profiles throughout the global tropics. This requires observations for fundamental understanding of cloud dynamics and microphysics, as well as for validation, testing assumptions and error estimates of cloud-resolving models, forward radiative transfer models, algorithms used to estimate rainfall statistics and vertical structure of precipitation from surface-based radar, and from satellites. Field experiments designed to contribute to this understanding have been conducted in Texas and the South China Sea in spring of 1998, Florida in summer of 1998, and interior Brazil in (boreal) winter 1999. In summer 1999, a major oceanic campaign will be based at Kwajalein Atoll. Some early results will be highlighted, noting some significant contrasts between oceanic and continental convective systems.

Zipser, Edward I.↗

NASA NTRS2001

Convective Systems Observed and Simulated During TRMM Field Campaigns

Recently completed TRMM field campaigns (TEFLUN1998, SCSMEX-1998, TRMM.LBA-1999, and KWAJEX 1999) have obtained direct measurements of microphysical data associated with convective systems from various geographical locations. These TRMM field experiments were designed to contribute to fundamental understanding of cloud dynamics and microphysics, as well as for validation,, testing assumptions and error estimates of cloud-resolving models, forward radiative transfer models, algorithms used to estimate rainfall statistics and vertical structure of precipitation and latent heating from both surface-based radar and satellites.

Tao, Wei-Kuo↗

NASA NTRS1996

Validation of an Experimentally Derived Uncertainty Model

The results show that uncertainty models can be obtained directly from system identification data by using a minimum norm model validation approach. The error between the test data and an analytical nominal model is modeled as a combination of unstructured additive and structured input multiplicative uncertainty. Robust controllers which use the experimentally derived uncertainty model show significant stability and performance improvements over controllers designed with assumed ad hoc uncertainty levels. Use of the identified uncertainty model also allowed a strong correlation between design predictions and experimental results.

Lim, K. B.↗

NASA NTRSDate not supplied

Aeroheating Predictions for a Hypersonic, Turbulent Near-Wake

The accuracy of heating predictions using various turbulence models is examined for an axisymmetric near-wake at Mach 6. The CFD predictions are compared with experimental data collected under AGARD Working Group 18 on the wake of a 70-degree sphere-cone. The impact of grid resolution and discretization error is estimated, which allows a comparison of stacked-block and conventional structured meshes. The accuracy of steady Reynolds-averaged Navier-Stokes (RANS) models is contrasted with that of a hybrid RANS/Large-Eddy Simulation model. The predictions are made with three different CFD codes (LAURA, FUN3D, and HyperSolve), to demonstrate the code-to-code variation in the results. Steady SST models capture the qualitative nature of the heating in the wake, including the increasing peak heating with increasing Reynolds number. Spalart-Allmaras models, including SA-Catris, under-predicted the peak heating in the wake. Hybrid RANS/LES models improve upon the SA results but have their own modeling difficulties near the shear layer impingement. These results are generally consistent across solvers and grid topologies.

RANS↗

NASA NTRSDate not supplied

Aeroheating Predictions for a Hypersonic, Turbulent Near-Wake

RANS↗

NASA NTRS2015

Calibration of Predictor Models Using Multiple Validation Experiments

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

Crespo, Luis G.↗

NASA NTRS1999

Data Assimilation Into a Coupled Ocean Atmosphere Model: Application to the 1997-1998 El Nino

As part of JPL's ocean data assimilation effort to study ocean circulation and seasonal-interannual climate variability, sea level anomaly observed by TOPEX altimeter, together with sea surface temperature and wind stress data, are assimilated into a simple coupled ocean atmosphere model of the tropical Pacific. Model-data consistency is examined. Impact of the assimilation (as initialization) on El Nino Southern Oscillation (ENSO) forecasts is evaluated. The coupled model consists of a shallow water component with two baroclinic modes, an Ekman shear layer, a simplified mixed-layer temperature equation, and a statistical atmosphere based on dominant correlations between historical surface temperature and wind stress anomaly data. The adjoins method is used to fit the coupled model to the data over various six-month periods from late 1996 to early 1998 by optimally adjusting the initial state, model parameters, and basis functions of the statistical atmosphere. On average, the coupled model can be fitted to the data to approximately within the data and representation errors (5 cm, 0.5 C, and 10 sq m/sq m for sea level, surface temperature, and pseudo wind stress anomalies, respectively). The estimated fields resemble observed spatio-temporal structure reasonably well. Hindcasts/forecasts of the 1997/1998 El Nino initialized from forced estimated ocean states and parameters are much more realistic than those simply initialized from ocean states (see figure below). In particular, the ability of the model to produce significant warming beyond the initial state is dramatically improved. Parameter estimation, which compensates for some model errors, is found to be important to obtaining better fits of the model to data and to improving forecasts.

Lee, Tong↗

NASA NTRS1995

Effects of Target Fragmentation on Evaluation of LET Spectra From Space Radiation in Low-Earth Orbit (LEO) Environment: Impact on SEU Predictions

Recent improvements in the radiation transport code HZETRN/BRYNTRN and galactic cosmic ray environmental model have provided an opportunity to investigate the effects of target fragmentation on estimates of single event upset (SEU) rates for spacecraft memory devices. Since target fragments are mostly of very low energy, an SEU prediction model has been derived in terms of particle energy rather than linear energy transfer (LET) to account for nonlinear relationship between range and energy. Predictions are made for SEU rates observed on two Shuttle flights, each at low and high inclination orbit. Corrections due to track structure effects are made for both high energy ions with track structure larger than device sensitive volume and for low energy ions with dense track where charge recombination is important. Results indicate contributions from target fragments are relatively important at large shield depths (or any thick structure material) and at low inclination orbit. Consequently, a more consistent set of predictions for upset rates observed in these two flights is reached when compared to an earlier analysis with CREME model. It is also observed that the errors produced by assuming linear relationship in range and energy in the earlier analysis have fortuitously canceled out the errors for not considering target fragmentation and track structure effects.

Shinn, J. L.↗