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NASA NTRS2018

Dynamic Adjustment of Simulation Parameters for Efficient Vehicle Prognostics

Model-based diagnostics and prognostics rely on state estimation and uncertainty management algorithms to produce useful information for system operators and maintainers. This information enables more informed operational decisions, condition-based maintenance, and overall mission safety assurance. Typically, uncertainty is associated with vehicle state-of-health estimation and prediction results because of modeling errors, internal or external sources of noise, and sensor inaccuracy. Probabilistic uncertainty management methods including Sequential Monte Carlo simulation are commonly used to reason about state-of-health estimates and predictions in the presence of these sources of uncertainty. However, such algorithms can be computationally expensive as they require a very large number of samples to obtain a sufficiently accurate quantification of the end of life probability distribution. As a result, highly mobile autonomous systems that leverage the prognostic results for mission-level replanning are often constrained in their processing capability because of these computationally expensive simulation approaches. Therefore, in this paper, we investigate algorithmic methods for dynamically adjusting simulation time step as well as number of samples to achieve highly efficient prognostic results while maintaining results accuracy. Results obtained from simulated flight experiments of an electric unmanned aerial vehicle are presented to verify the efficacy of such algorithms.

Prognostics↗

NASA NTRS2024

Interpretable Machine Learning for Molecular Biosignatures: a Novel Single-Sample Feature Importance Method That Is Sensitive To Statistical Interactions

Isotope ratio mass spectrometry (IRMS) of volatiles (e.g., CO 2 ) promises to be a powerful tool for potential biosignature detection for future missions to ocean worlds (OW) such as Europa and Enceladus. Machine learning (ML) methods for IRMS data could enable science autonomy by onboard prediction of seawater chemistry and biosignature presence. However, ML models are likely to be complex and involve statistical interactions between features (variables), which can make predictions seem opaque and enigmatic. For ML predictions as significant as extraterrestrial biosignatures, we must place extraordinary confidence in models. It is therefore essential that these models make interpretable predictions (i.e., human-understandable) and include false-prediction diagnostics. We achieve high accuracy and interpretability in ML biosignature and seawater chemistry models for OW through a nearest-neighbors feature selection tool that detects statistical interactions between predictors, constructs interaction networks for visualization of selected features working together to make a prediction, and reports single-sample feature importance scores for false-detection diagnostics. Here we develop a novel single-sample nearest-neighbors projected distance regression(ssNPDR) feature selection method that improves upon existing single-sample algorithms through the inclusion of statistical interactions while providing false-prediction diagnostics for ML models.

geochemistry↗

NASA NTRS1998

Estimation of 3-D Cloud Effects on TOMS Satellite Retrieval of Surface UV Irradiance

To improve surface UV irradiance retrieval from the Total Ozone Mapping Spectrometer (TOMS) we simulate errors of the TOMS cloud correction algorithm for summertime broken cloud conditions. Cloud scenes (50 km by 50 km) are modeled by a normal random (Gaussian) field with a fixed lower boundary and conservative scattering. The model relates stochastic field characteristics with the cloud amount, mean cloud diameter and aspect ratio. Clouds are embedded into Rayleigh atmosphere with standard ozone profile. Radiative transfer calculations of the radiance at the top of the atmosphere and irradiance at the surface were performed using 3-D Monte Carlo (MC) code. The results are averaged over the satellite field of view on the surface (50 km by 50 km) and compared with TOMS predicted surface irradiance for the same scene reflectance. The TOMS algorithm assumes horizontally homogeneous Cl-type cloud between 3 km and 5.5 km. The effective optical depth is determined by fitting observed (MC) radiance at 380 nm. Having the same radiance at the satellite the homogeneous and broken cloud models predict different average irradiances at the surface. This is due to the differences in Bidirectional Reflection Distribution Function (BRDF) for homogeneous and broken cloud scenes with the same hemispherical albedo. For typical TOMS observational geometry at mid-latitudes the simulated single pixels errors may be as large as +/- 20%. Qualitatively these errors are due to the dominance of the non-horizontal cloud surfaces, which are not accounted for in the homogeneous cloud model. However, due to high variability of the real cloud shapes and types it is unclear how these single pixel errors would affect TOMS time-integrated UV exposure over extended periods (weeks to months) for different regions.

Krotkov, Nickolay A.↗

NASA NTRS1994

The future of time and frequency dissemination

I will try to extrapolate the changes in the dissemination of time and frequency information that have taken place during the last 25 years to predict the future developments both in the methods of disseminating time and frequency and in the kinds of customers we will be asked to serve. Two important developments are likely to play pivotal roles in driving the evolution of dissemination. The first is the commercial availability of very high quality clocks -- devices whose performance may eventually rival that of the current generation of primary frequency standards. The widespread use of these devices may blur the traditional distinction between client and server, and may replace it with a more symmetrical interchange of data among peers. The second is the increasing demand for digital time and frequency information driven by the increasing sophistication of everything from traffic lights to electric power meters. The needs of these individual users may not tax the state of the art of primary frequency standards in principle, but their large numbers and wide geographical distribution present a technological challenge that is difficult to meet at a reasonable price using existing methods. Some of these problems may be solved (or at least addressed) using developments in communications and consumer electronics such as the increasing use of fiber-optic telephone circuits and the increasing bandwidth and sophistication of the cable network used to transmit television pictures. To be useful, these advances in hardware must stimulate parallel advances in software algorithms and methods. These advances are more difficult to predict with great confidence, but the developments of the last few years will be examined to provide some indications of the future.

Levine, Judah↗

NASA NTRS2006

A COTS-Based Attitude Dependent Contact Scheduling System

The mission architecture of the Gamma-ray Large Area Space Telescope (GLAST) requires a sophisticated ground system component for scheduling the downlink of science data. Contacts between the ````````````````` satellite and the Tracking and Data Relay Satellite System (TDRSS) are restricted by the limited field-of-view of the science data downlink antenna. In addition, contacts must be scheduled when permitted by the satellite s complex and non-repeating attitude profile. Complicating the matter further, the long lead-time required to schedule TDRSS services, combined with the short duration of the downlink contact opportunities, mandates accurate GLAST orbit and attitude modeling. These circumstances require the development of a scheduling system that is capable of predictively and accurately modeling not only the orbital position of GLAST but also its attitude. This paper details the methods used in the design of a Commercial Off The Shelf (COTS)-based attitude-dependent. TDRSS contact Scheduling system that meets the unique scheduling requirements of the GLAST mission, and it suggests a COTS-based scheduling approach to support future missions. The scheduling system applies filtering and smoothing algorithms to telemetered GPS data to produce high-accuracy predictive GLAST orbit ephemerides. Next, bus pointing commands from the GLAST Science Support Center are used to model the complexities of the two dynamic science gathering attitude modes. Attitude-dependent view periods are then generated between GLAST and each of the supporting TDRSs. Numerous scheduling constraints are then applied to account for various mission specific resource limitations. Next, an optimization engine is used to produce an optimized TDRSS contact schedule request which is sent to TDRSS scheduling for confirmation. Lastly, the confirmed TDRSS contact schedule is rectified with an updated ephemeris and adjusted bus pointing commands to produce a final science downlink contact schedule.

DeGumbia, Jonathan D.↗

NASA NTRS2011

Algorithm for Determination of Orion Ascent Abort Mode Achievability

For human spaceflight missions, a launch vehicle failure poses the challenge of returning the crew safely to earth through environments that are often much more stressful than the nominal mission. Manned spaceflight vehicles require continuous abort capability throughout the ascent trajectory to protect the crew in the event of a failure of the launch vehicle. To provide continuous abort coverage during the ascent trajectory, different types of Orion abort modes have been developed. If a launch vehicle failure occurs, the crew must be able to quickly and accurately determine the appropriate abort mode to execute. Early in the ascent, while the Launch Abort System (LAS) is attached, abort mode selection is trivial, and any failures will result in a LAS abort. For failures after LAS jettison, the Service Module (SM) effectors are employed to perform abort maneuvers. Several different SM abort mode options are available depending on the current vehicle location and energy state. During this region of flight the selection of the abort mode that maximizes the survivability of the crew becomes non-trivial. To provide the most accurate and timely information to the crew and the onboard abort decision logic, on-board algorithms have been developed to propagate the abort trajectories based on the current launch vehicle performance and to predict the current abort capability of the Orion vehicle. This paper will provide an overview of the algorithm architecture for determining abort achievability as well as the scalar integration scheme that makes the onboard computation possible. Extension of the algorithm to assessing abort coverage impacts from Orion design modifications and launch vehicle trajectory modifications is also presented.

Tedesco, Mark B.↗

NASA NTRS1978

On several aspects and applications of the multigrid method for solving partial differential equations

Several aspects of multigrid methods are briefly described. The main subjects include the development of very efficient multigrid algorithms for systems of elliptic equations (Cauchy-Riemann, Stokes, Navier-Stokes), as well as the development of control and prediction tools (based on local mode Fourier analysis), used to analyze, check and improve these algorithms. Preliminary research on multigrid algorithms for time dependent parabolic equations is also described. Improvements in existing multigrid processes and algorithms for elliptic equations were studied.

Dinar, N.↗

NASA NTRS2008

Automated Generation and Assessment of Autonomous Systems Test Cases

This slide presentation reviews some of the issues concerning verification and validation testing of autonomous spacecraft routinely culminates in the exploration of anomalous or faulted mission-like scenarios using the work involved during the Dawn mission's tests as examples. Prioritizing which scenarios to develop usually comes down to focusing on the most vulnerable areas and ensuring the best return on investment of test time. Rules-of-thumb strategies often come into play, such as injecting applicable anomalies prior to, during, and after system state changes; or, creating cases that ensure good safety-net algorithm coverage. Although experience and judgment in test selection can lead to high levels of confidence about the majority of a system's autonomy, it's likely that important test cases are overlooked. One method to fill in potential test coverage gaps is to automatically generate and execute test cases using algorithms that ensure desirable properties about the coverage. For example, generate cases for all possible fault monitors, and across all state change boundaries. Of course, the scope of coverage is determined by the test environment capabilities, where a faster-than-real-time, high-fidelity, software-only simulation would allow the broadest coverage. Even real-time systems that can be replicated and run in parallel, and that have reliable set-up and operations features provide an excellent resource for automated testing. Making detailed predictions for the outcome of such tests can be difficult, and when algorithmic means are employed to produce hundreds or even thousands of cases, generating predicts individually is impractical, and generating predicts with tools requires executable models of the design and environment that themselves require a complete test program. Therefore, evaluating the results of large number of mission scenario tests poses special challenges. A good approach to address this problem is to automatically score the results based on a range of metrics. Although the specific means of scoring depends highly on the application, the use of formal scoring - metrics has high value in identifying and prioritizing anomalies, and in presenting an overall picture of the state of the test program. In this paper we present a case study based on automatic generation and assessment of faulted test runs for the Dawn mission, and discuss its role in optimizing the allocation of resources for completing the test program.

Testing challenges↗

NASA NTRS2004

Planetary Transmission Diagnostics

This report presents a methodology for detecting and diagnosing gear faults in the planetary stage of a helicopter transmission. This diagnostic technique is based on the constrained adaptive lifting algorithm. The lifting scheme, developed by Wim Sweldens of Bell Labs, is a time domain, prediction-error realization of the wavelet transform that allows for greater flexibility in the construction of wavelet bases. Classic lifting analyzes a given signal using wavelets derived from a single fundamental basis function. A number of researchers have proposed techniques for adding adaptivity to the lifting scheme, allowing the transform to choose from a set of fundamental bases the basis that best fits the signal. This characteristic is desirable for gear diagnostics as it allows the technique to tailor itself to a specific transmission by selecting a set of wavelets that best represent vibration signals obtained while the gearbox is operating under healthy-state conditions. However, constraints on certain basis characteristics are necessary to enhance the detection of local wave-form changes caused by certain types of gear damage. The proposed methodology analyzes individual tooth-mesh waveforms from a healthy-state gearbox vibration signal that was generated using the vibration separation (synchronous signal-averaging) algorithm. Each waveform is separated into analysis domains using zeros of its slope and curvature. The bases selected in each analysis domain are chosen to minimize the prediction error, and constrained to have the same-sign local slope and curvature as the original signal. The resulting set of bases is used to analyze future-state vibration signals and the lifting prediction error is inspected. The constraints allow the transform to effectively adapt to global amplitude changes, yielding small prediction errors. However, local wave-form changes associated with certain types of gear damage are poorly adapted, causing a significant change in the prediction error. The constrained adaptive lifting diagnostic algorithm is validated using data collected from the University of Maryland Transmission Test Rig and the results are discussed.

Lewicki, David G.↗

NASA NTRS2016

In Search of a Time Efficient Approach to Crack and Delamination Growth Predictions in Composites

Analysis benchmarking was used to assess the accuracy and time efficiency of algorithms suitable for automated delamination growth analysis. First, the Floating Node Method (FNM) was introduced and its combination with a simple exponential growth law (Paris Law) and Virtual Crack Closure technique (VCCT) was discussed. Implementation of the method into a user element (UEL) in Abaqus/Standard(Registered TradeMark) was also presented. For the assessment of growth prediction capabilities, an existing benchmark case based on the Double Cantilever Beam (DCB) specimen was briefly summarized. Additionally, the development of new benchmark cases based on the Mixed-Mode Bending (MMB) specimen to assess the growth prediction capabilities under mixed-mode I/II conditions was discussed in detail. A comparison was presented, in which the benchmark cases were used to assess the existing low-cycle fatigue analysis tool in Abaqus/Standard(Registered TradeMark) in comparison to the FNM-VCCT fatigue growth analysis implementation. The low-cycle fatigue analysis tool in Abaqus/Standard(Registered TradeMark) was able to yield results that were in good agreement with the DCB benchmark example. Results for the MMB benchmark cases, however, only captured the trend correctly. The user element (FNM-VCCT) always yielded results that were in excellent agreement with all benchmark cases, at a fraction of the analysis time. The ability to assess the implementation of two methods in one finite element code illustrated the value of establishing benchmark solutions.

Krueger, Ronald↗

NASA NTRS1985

On the accuracy of modelling the dynamics of large space structures

Proposed space missions will require large scale, light weight, space based structural systems. Large space structure technology (LSST) systems will have to accommodate (among others): ocean data systems; electronic mail systems; large multibeam antenna systems; and, space based solar power systems. The structures are to be delivered into orbit by the space shuttle. Because of their inherent size, modelling techniques and scaling algorithms must be developed so that system performance can be predicted accurately prior to launch and assembly. When the size and weight-to-area ratio of proposed LSST systems dictate that the entire system be considered flexible, there are two basic modeling methods which can be used. The first is a continuum approach, a mathematical formulation for predicting the motion of a general orbiting flexible body, in which elastic deformations are considered small compared with characteristic body dimensions. This approach is based on an a priori knowledge of the frequencies and shape functions of all modes included within the system model. Alternatively, finite element techniques can be used to model the entire structure as a system of lumped masses connected by a series of (restoring) springs and possibly dampers. In addition, a computational algorithm was developed to evaluate the coefficients of the various coupling terms in the equations of motion as applied to the finite element model of the Hoop/Column.

Diarra, C. M.↗

NASA NTRS1985

On the accuracy of modelling the dynamics of large space structures

Proposed space missions will require large scale, light weight, space based structural systems. Large space structure technology (LSST) systems will have to accommodate (among others): ocean data systems; electronic mail systems; large multibeam antenna systems; and, space based solar power systems. The structures are to be delivered into orbit by the Space Shuttle. Because of their inherent size, modelling techniques and scaling algorithms must be developed so that system performance can be predicted accurately prior to launch and assembly. When the size and weight-to-area ratio of proposed LSST systems dictate that the entire system be considered flexible, there are two basic modelling methods which can be used. The first is a continuum approach, a mathematical formulation for predicting the motion of a general orbiting flexible body, in which elastic deformations are considered small compared with characteristic body dimensions. This approach is based on an a priori knowledge of the frequencies and shape functions of all modes included within the system model. Alternatively, finite element techniques can be used to model the entire structure as a system of lumped masses connected by a series of (restoring) springs and possibly dampers. In addition, a computational algorithm was developed to evaluate the coefficients of the various coupling terms in the equations of motion as applied to the finite element model of the Hoop/Column.

Diarra, C. M.↗

NASA NTRS2010

Multivariate Methods for Prediction of Geologic Sample Composition with Laser-Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy (LIBS) uses pulses of laser light to ablate a material from the surface of a sample and produce an expanding plasma. The optical emission from the plasma produces a spectrum which can be used to classify target materials and estimate their composition. The ChemCam instrument on the Mars Science Laboratory (MSL) mission will use LIBS to rapidly analyze targets remotely, allowing more resource- and time-intensive in-situ analyses to be reserved for targets of particular interest. ChemCam will also be used to analyze samples that are not reachable by the rover's in-situ instruments. Due to these tactical and scientific roles, it is important that ChemCam-derived sample compositions are as accurate as possible. We have compared the results of partial least squares (PLS), multilayer perceptron (MLP) artificial neural networks (ANNs), and cascade correlation (CC) ANNs to determine which technique yields better estimates of quantitative element abundances in rock and mineral samples. The number of hidden nodes in the MLP ANNs was optimized using a genetic algorithm. The influence of two data preprocessing techniques were also investigated: genetic algorithm feature selection and averaging the spectra for each training sample prior to training the PLS and ANN algorithms. We used a ChemCam-like laboratory stand-off LIBS system to collect spectra of 30 pressed powder geostandards and a diverse suite of 196 geologic slab samples of known bulk composition. We tested the performance of PLS and ANNs on a subset of these samples, choosing to focus on silicate rocks and minerals with a loss on ignition of less than 2 percent. This resulted in a set of 22 pressed powder geostandards and 80 geologic samples. Four of the geostandards were used as a validation set and 18 were used as the training set for the algorithms. We found that PLS typically resulted in the lowest average absolute error in its predictions, but that the optimized MLP ANN and the CC ANN often gave results comparable to PLS. Averaging the spectra for each training sample and/or using feature selection to choose a small subset of wavelengths to use for predictions gave mixed results, with degraded performance in some cases and similar or slightly improved performance in other cases. However, training time was significantly reduced for both PLS and ANN methods by implementing feature selection, making this a potentially appealing method for initial, rapid-turn-around analyses necessary for Chemcam's tactical role on MSL. Choice of training samples has a strong influence on the accuracy of predictions. We are currently investigating the use of clustering algorithms (e.g. k-means, neural gas, etc.) to identify training sets that are spectrally similar to the unknown samples that are being predicted, and therefore result in improved predictions

Morris, Richard↗

NASA NTRS1988

On the Wiener-Masani algorithm for finding the generating function of multivariate stochastic processes

The algorithms developed by Wiener and Masani (1957 and 1958) and Masani (1960) for the characterization of a class of multivariate stationary stochastic processes are investigated analytically. The algorithms permit the determination of (1) the generating function, (2) the prediction-error matrix, and (3) an autoregressive representation of the linear least-squares predictor. A number of theorems and lemmas are proved, and it is shown that the range of validity of the algorithms can be extended significantly beyond that given by Wiener and Masani.

Miamee, A. G.↗

NASA NTRS1990

Adaptive state estimation for control of flexible structures

This paper proposes a new approach of obtaining adaptive state estimation of a system in the presence of unknown system disturbances and measurement noise. In the beginning, a non-optimal Kalman filter with arbitrary initial guess for the process and measurement noises is implemented. At the same time, an adaptive transversal predictor (ATP) based on the recursive least-squares (RLS) algorithm is used to yield optimal one- to p- step-ahead output predictions using the previous input/output data. Referring to these optimal predictions the Kalman filter gain is updated and the performance of the state estimation is thus improved. If forgetting factor is implemented in the recursive least-squares algorithm, this method is also capable of dealing with the situation when the noise statistics are slowly time-varying. This feature makes this new approach especially suitable for the control of flexible structures. A numerical example demonstrates the feasibility of this real time adaptive state estimation method.

Chen, Chung-Wen↗

NASA NTRS2012

Prognostics Approach for Power MOSFET Under Thermal-Stress

The prognostic technique for a power MOSFET presented in this paper is based on accelerated aging of MOSFET IRF520Npbf in a TO-220 package. The methodology utilizes thermal and power cycling to accelerate the life of the devices. The major failure mechanism for the stress conditions is dieattachment degradation, typical for discrete devices with leadfree solder die attachment. It has been determined that dieattach degradation results in an increase in ON-state resistance due to its dependence on junction temperature. Increasing resistance, thus, can be used as a precursor of failure for the die-attach failure mechanism under thermal stress. A feature based on normalized ON-resistance is computed from in-situ measurements of the electro-thermal response. An Extended Kalman filter is used as a model-based prognostics techniques based on the Bayesian tracking framework. The proposed prognostics technique reports on preliminary work that serves as a case study on the prediction of remaining life of power MOSFETs and builds upon the work presented in [1]. The algorithm considered in this study had been used as prognostics algorithm in different applications and is regarded as suitable candidate for component level prognostics. This work attempts to further the validation of such algorithm by presenting it with real degradation data including measurements from real sensors, which include all the complications (noise, bias, etc.) that are regularly not captured on simulated degradation data. The algorithm is developed and tested on the accelerated aging test timescale. In real world operation, the timescale of the degradation process and therefore the RUL predictions will be considerable larger. It is hypothesized that even though the timescale will be larger, it remains constant through the degradation process and the algorithm and model would still apply under the slower degradation process. By using accelerated aging data with actual device measurements and real sensors (no simulated behavior), we are attempting to assess how such algorithm behaves under realistic conditions.

Power MOSFET PHM↗

NASA NTRS1992

SPEEDES - A multiple-synchronization environment for parallel discrete-event simulation

Synchronous Parallel Environment for Emulation and Discrete-Event Simulation (SPEEDES) is a unified parallel simulation environment. It supports multiple-synchronization protocols without requiring users to recompile their code. When a SPEEDES simulation runs on one node, all the extra parallel overhead is removed automatically at run time. When the same executable runs in parallel, the user preselects the synchronization algorithm from a list of options. SPEEDES currently runs on UNIX networks and on the California Institute of Technology/Jet Propulsion Laboratory Mark III Hypercube. SPEEDES also supports interactive simulations. Featured in the SPEEDES environment is a new parallel synchronization approach called Breathing Time Buckets. This algorithm uses some of the conservative techniques found in Time Bucket synchronization, along with the optimism that characterizes the Time Warp approach. A mathematical model derived from first principles predicts the performance of Breathing Time Buckets. Along with the Breathing Time Buckets algorithm, this paper discusses the rules for processing events in SPEEDES, describes the implementation of various other synchronization protocols supported by SPEEDES, describes some new ones for the future, discusses interactive simulations, and then gives some performance results.

Steinman, Jeff S.↗

NASA NTRS1975

The use of ERTS imagery for lake classification

The feasibility of using photographic representations of the ERTS imagery to classify lakes in the State of Wisconsin as to their trophic level was studied. Densitometric readings in band 5 of ERTS 70 mm imagery were taken for all the lakes in Wisconsin greater than 100 acres (approximately 1000 lakes). An algorithm has been developed from ground truth measurements to predict from satellite imagery an indicator of trophic status.

Scarpace, F. L.↗