Statistical and machine learning-based durability-testing strategies for energy storage
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The current focus in the ongoing development of autonomous driving systems (ADS) for heavy duty vehicles is that of vehicle operational safety. To this end, developers and researchers alike are working towards a complete understanding of the operating environments and conditions that autonomous vehicles are subject to during their mission. This understanding is critical to the testing and validation phases of the development of autonomous vehicles and allows for the identification of both the nominal and edge case scenarios encountered by these systems. Previous work by the authors saw the development of a comprehensive scenario generation framework to identify an operating domain specification (ODS), or external and internal conditions an autonomous driving system can expect to encounter on its mission to form critical scenario groups for autonomous vehicle testing and validating using statistical patterns, clustering, and correlation. Continuing this prior work, this paper focuses on the generation of test cases based on the critical scenarios identified that can be used to prioritize either the most common nominal driving scenarios or the least common severe driving scenarios. These test cases can then be used validate, through simulation or real-world testing, the operating design domain (ODD) for a generalized driving mission and built upon to identify spatial and temporal impacts on the driving mission of an autonomous vehicle.
The seal configuration tester (SCT) developed at the Stennis Space Center (SSC) was designed to replicate the intended application of different seat and seal materials in a high pressure oxygen system and assess the wearibility of those materials. Statistical models were used to test the reliability of the SCT in its intended application, and the tests showed very consistent measurements over time, indicating that the device was working as intended. Other statistical designs were used to test different O-ring materials in a high-pressure oxygen system. Those tests indicated that the SCT could be used to rank the performance of O-ring materials in certain environments. The results indicated that some cheaper materials performed as well as, if not better than, other more expensive materials. Different lubrications were integrated in the testing as well and had a significant impact on the performance of the materials. Testing of seat materials is the next stage of this project. An augmentation grant (JAG) was obtained to further this experimental testing at the Stennis Space Center. This part of the project is ongoing at this time and therefore there are no significant accomplishments with respect to seat materials as of yet.
This communication extends a statistical analysis of forced-descent decompression sickness at altitude in exercising subjects (J Appl Physiol 1994; 76:2726-2734) with a data subset having an additional explanatory variable, rate of ascent. The original explanatory variables for risk-function analysis were environmental pressure of the altitude, duration of exposure, and duration of pure-O2 breathing before exposure; the best fit was consistent with the idea that instantaneous risk increases linearly as altitude exposure continues. Use of the new explanatory variable improved the fit of the smaller data subset, as indicated by log likelihood. Also, with ascent rate accounted for, replacement of the term for linear accrual of instantaneous risk by a term for rise and then decay made a highly significant improvement upon the original model (log likelihood increased by 37 log units). The authors conclude that a more representative data set and removal of the variability attributable to ascent rate allowed the rise-and-decay mechanism, which is expected from theory and observations, to become manifest.
In order to obtain the most benefit from building a structure with composite laminates, the strength of the laminate must be known. Based on the "weakest link" theory, the lower strength numbers obtained from testing are the ones to be used for design and analysis. The strength value to be used is determined by a statistical analysis of the test data, and is known as an allowable. MIL-HDBK- 17 outlines procedures to follow for determining these allowables. There are two types of statistically determined allowables, A- Basis and B-Basis. A-Basis is defined as a strength value at which only 1 in 100 specimens will fail with a 95% confidence level. B-Basis is a strength value at which only 10 in 100 specimens will fail with a 95% confidence level. As more specimens are tested a higher value of strength can be used as a valid allowable. Composites are highly process dependent and show much strength variation with environment, so it is critical to test materials and environments that are representative of hardware. Either using data obtained from a previous test series, or extrapolation to a certain temperature is highly discouraged.
Consideration is given to alternate vibroacoustic test plans for sortie and free flyer Shuttle payloads. Statistical decision models for nine test plans provide a viable method of evaluating the cost effectiveness of alternate vibroacoustic test plans and the associated test levels. The methodology is a major step toward the development of a useful tool for the quantitative tailoring of vibroacoustic test programs to sortie and free flyer payloads. A broader application of the methodology is now possible by the use of the OCTAVE computer code.
A simple, graphical framework is presented for robust statistical evaluation of results obtained from N-Version testing of a series of RANS CFD codes. The solutions were obtained by a variety of code developers and users for the June 2001 Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic configuration used for the computational tests is the DLR-F4 wing-body combination previously tested in several European wind tunnels and for which a previous N-Version test had been conducted. The statistical framework is used to evaluate code results for (1) a single cruise design point, (2) drag polars and (3) drag rise. The paper concludes with a discussion of the meaning of the results, especially with respect to predictability, Validation, and reporting of solutions.
Flying qualities criteria for Single Pilot Instrument Flight Rule (SPIFR) operations were investigated. The ARA aircraft was modified and adapted for SPIFR operations. Aircraft configurations to be flight-tested were chosen and matched on the ARA in-flight simulator, implementing modern control theory algorithms. Mission planning and experimental matrix design were completed. Microprocessor software for the onboard data acquisition system was debugged and flight-tested. Flight-path reconstruction procedure and the associated FORTRAN program were developed. Algorithms associated with the statistical analysis of flight test results and the SPIFR flying qualities criteria deduction are discussed.
An extensive data base of flow angularity repeatability measurements from four NTF check standard model tests is analyzed for statistical consistency and to characterize the results for prediction of angle-of-attack uncertainty for customer tests. A procedure for quality assurance for flow angularity measurements during customer tests is also presented. The efficacy of the procedure is tested using results from a customer test.
A technique is demonstrated for accelerated stress corrosion testing of high strength aluminum alloys. The method offers better precision and shorter exposure times than traditional pass fail procedures. The approach uses data from tension tests performed on replicate groups of smooth specimens after various lengths of exposure to static stress. The breaking strength measures degradation in the test specimen load carrying ability due to the environmental attack. Analysis of breaking load data by extreme value statistics enables the calculation of survival probabilities and a statistically defined threshold stress applicable to the specific test conditions. A fracture mechanics model is given which quantifies depth of attack in the stress corroded specimen by an effective flaw size calculated from the breaking stress and the material strength and fracture toughness properties. Comparisons are made with experimental results from three tempers of 7075 alloy plate tested by the breaking load method and by traditional tests of statistically loaded smooth tension bars and conventional precracked specimens.
Electrostatic Discharge (ESD) induced by the accumulation of charge in the space environment is known to cause spacecraft anomalies and failures. While it is critical to estimate the worst-case expected ESD, sensitive radar instruments can be impacted by high rates of occurrence of very small ESD. To estimate the correct extreme behavior, it is important to select the correct extreme value distribution for extrapolation of test results limited in time and sensitivity. Quantile-quantile (Q-Q) analysis is used to compare electron beam-induced ESD test data to several statistical distributions used in the published literature. The best-fit distribution is shown to vary from between tests on different materials; however, it is clear that power law distributions are not good approximations for low amplitude events. Q-Q analysis is a convenient graphical method for evaluating multiple theoretical extreme-value distributions simultaneously.
A ground winds test was conducted on the Skylab 2 spacecraft in a subsonic wind tunnel and the results were tape recorded for analysis. The data reduction system used to analyze the tapes for full scale, first and second mode bending moments, or acceleration plots versus dynamic pressure or wind velocity is explained. Portions of the Skylab 2 tape data were analyzed statistically in the form of power spectral densities, autocorrelations, and cross correlations to introduce a concept of using system response decay as a measure of linear system damping.
Test program, employing empirical, statistical and physical methods, determines service life and failure probabilities of electrochemical cells and batteries, and is applicable to testing mechanical, electrical, and chemical devices. Data obtained aids long-term performance prediction of battery or cell.
The Solar TErrestrial RElations Observatory (STEREO), the third mission in NASA's Solar Terrestrial Probes program, was launched in 2006 on a two year mission to study solar phenomena. STEREO consists of two nearly identical satellites, each carrying an Extreme Ultraviolet Imager (EUVI) telescope as part of the Sun Earth Connection Coronal and Heliospheric Investigation instrument suite. EUVI is a normal incidence, 98mm diameter, Ritchey-Chretien telescope designed to obtain wide field of view images of the Sun at short wavelengths (17.1-30.4nm) using a CCD detector. The telescope entrance aperture is divided into four quadrants by a mask near the secondary mirror spider veins. A mechanism that rotates another mask allows only one of these sub-apertures to accept light over an exposure. The EUVI contains no focus mechanism. Mechanical models predict a difference in telescope focus between ambient integration conditions and on-orbit operation. We describe an independent check of the ambient, ultraviolet, absolute focus setting of the EUVI telescopes after they were integrated with their respective spacecraft. A scanning Hartmann-like test design resulted from constraints implied by the EUVI aperture select mechanism. This inexpensive test was simultaneously coordinated with other NASA integration and test activities in a high-vibration, clean room environment. The total focus test error was required to be better than +/-0.05 mm. We describe the alignment and test procedure, sources of statistical and systematic error, and then the focus determination results using various algorithms. The results are consistent with other tests of focus alignment and indicate that the EUVI telescopes meet the ambient focus offset requirements. STEREO is functioning well on-orbit and the EUVI telescopes meet their on-orbit image quality requirements.
A receiver gain modulation circuit (RGMC) was developed that modulates the power gain of the output of a radiometer receiver with a test signal. As the radiometer receiver switches between calibration noise references, the test signal is mixed with the calibrated noise and thus produces an ensemble set of measurements from which ensemble statistical analysis can be used to extract statistical information about the test signal. The RGMC is an enabling technology of the ensemble detector. As a key component for achieving ensemble detection and analysis, the RGMC has broad aeronautical and space applications. The RGMC can be used to test and develop new calibration algorithms, for example, to detect gain anomalies, and/or correct for slow drifts that affect climate-quality measurements over an accelerated time scale. A generalized approach to analyzing radiometer system designs yields a mathematical treatment of noise reference measurements in calibration algorithms. By treating the measurements from the different noise references as ensemble samples of the receiver state, i.e. receiver gain, a quantitative description of the non-stationary properties of the underlying receiver fluctuations can be derived. Excellent agreement has been obtained between model calculations and radiometric measurements. The mathematical formulation is equivalent to modulating the gain of a stable receiver with an externally generated signal and is the basis for ensemble detection and analysis (EDA). The concept of generating ensemble data sets using an ensemble detector is similar to the ensemble data sets generated as part of ensemble empirical mode decomposition (EEMD) with exception of a key distinguishing factor. EEMD adds noise to the signal under study whereas EDA mixes the signal with calibrated noise. It is mixing with calibrated noise that permits the measurement of temporal-functional variability of uncertainty in the underlying process. The RGMC permits the evaluation of EDA by modulating the receiver gain using an external signal. Without the RGMC, samples of calibrated references from radiometers form an ensemble data set of the natural occurring fluctuations within a receiver. By driving the gain of an otherwise stable receiver with an external signal, the conceptual framework and generalization of the mathematics of EDA can be tested. A series of measurements was conducted to evaluate and characterize the performance of the RGMC. Test signals stepped the RGMC across its dynamic range of performance using a radiometer that sampled four noise references; analysis indicates that the RGMC successfully modulated the receiver gain with an external signal. Calibration algorithms applied to four noise references demonstrate the RGMC produced ensemble data sets of the external signal.
The considered research had the objective to design a statistical model that could perform an error analysis of curve fits of wind tunnel test data using analysis of variance and regression analysis techniques. Four related subproblems were defined, and by solving each of these a solution to the general research problem was obtained. The capabilities of the evolved true statistical model are considered. The least squares fit is used to determine the nature of the force, moment, and pressure data. The order of the curve fit is increased in order to delete the quadratic effect in the residuals. The analysis of variance is used to determine the magnitude and effect of the error factor associated with the experimental data.
A statistical summary of electrical characterization was performed on JANTX 1N5619 silicon diodes. Parameters are presented with test conditions, mean, standard deviation, lowest reading, 10% point, 90% point, and highest reading.
A statistical summary of the electrical characterization of diodes and transistors is presented. Each parameter is presented with test conditions, mean, standard deviation, lowest reading, 10% point (where 10% of all readings are equal to or less than the indicated reading), 90% point (where 90% of all readings are equal to or less than indicated reading) and the highest reading.