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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Spacecraft utility and the development of confidence intervals for criticality of anomalies

The concept of spacecraft utility, a measure of its performance in orbit, is discussed and its formulation is described. Performance is defined in terms of the malfunctions that occur and the criticality to the mission of these malfunctions. Different approaches to establishing average or expected values of criticality are discussed and confidence intervals are developed for parameters used in the computation of utility.

Williams, R. E.↗
NASA NTRS1983

Computing Graphical Confidence Bounds

Approximation for graphical confidence bounds is simple enough to run on programmable calculator. Approximation is used in lieu of numerical tables not always available, and exact calculations, which often require rather sizable computer resources. Approximation verified for collection of up to 50 data points. Method used to analyze tile-strength data on Space Shuttle thermal-protection system.

Mezzacappa, M. A.↗
NASA NTRS1988

Variance and bias confidence criteria for ERA modal parameter identification

For the ERA system identification algorithm, perturbation methods are used to develop expressions for variance and bias of the identified modal parameters. Based on the statistics of the measurement noise, the variance results serve as confidence criteria by indicating how likely the true parameters are to lie within any chosen interval about their identified values. This replaces the use of expensive and time-consuming Monte Carlo computer runs to obtain similar information. The bias estimates help guide the ERA user in his choice of which data points to use and how much data to use in order to obtain the best results, performing the trade-off between the bias and scatter. Also, when the uncertainty in the bias is sufficiently small, the bias information can be used to correct the ERA results. In addition, expressions for the variance and bias of the singular values serve as tools to help the ERA user decide the proper modal order.

Longman, Richard W.↗
NASA NTRS1988

Confidence set inference with a prior quadratic bound

In the uniqueness part of a geophysical inverse problem, the observer wants to predict all likely values of P unknown numerical properties z = (z sub 1,...,z sub p) of the earth from measurement of D other numerical properties y(0)=(y sub 1(0),...,y sub D(0)) knowledge of the statistical distribution of the random errors in y(0). The data space Y containing y(0) is D-dimensional, so when the model space X is infinite-dimensional the linear uniqueness problem usually is insoluble without prior information about the correct earth model x. If that information is a quadratic bound on x (e.g., energy or dissipation rate), Bayesian inference (BI) and stochastic inversion (SI) inject spurious structure into x, implied by neither the data nor the quadratic bound. Confidence set inference (CSI) provides an alternative inversion technique free of this objection. CSI is illustrated in the problem of estimating the geomagnetic field B at the core-mantle boundary (CMB) from components of B measured on or above the earth's surface. Neither the heat flow nor the energy bound is strong enough to permit estimation of B(r) at single points on the CMB, but the heat flow bound permits estimation of uniform averages of B(r) over discs on the CMB, and both bounds permit weighted disc-averages with continous weighting kernels. Both bounds also permit estimation of low-degree Gauss coefficients at the CMB. The heat flow bound resolves them up to degree 8 if the crustal field at satellite altitudes must be treated as a systematic error, but can resolve to degree 11 under the most favorable statistical treatment of the crust. These two limits produce circles of confusion on the CMB with diameters of 25 deg and 19 deg respectively.

Backus, George E.↗
NASA NTRS1992

Efficient Computation Of Confidence Intervals Of Parameters

Study focuses on obtaining efficient algorithm for estimation of confidence intervals of ML estimates. Four algorithms selected to solve associated constrained optimization problem. Hybrid algorithms, following search and gradient approaches, prove best.

Murphy, Patrick C.↗
NASA NTRS1993

Confidence bounds on structural reliability

Different approaches for quantifying physical, statistical, and model uncertainties associated with the distribution parameters which are aimed at determining structural reliability are described. Confidence intervals on the distribution parameters of the input random variables are estimated using four algorithms to evaluate uncertainty of the response. Design intervals are evaluated using either Monte Carlo simulation or an iterative approach. A first order approach can be used to compute a first approximation of the design interval, but its accuracy is not satisfactory. The regression approach which combines the iterative approach with Monte Carlo simulation is capable of providing good results if the performance function can be accurately represented using regression analysis. It is concluded that the design interval-based approach seems to be quite general and takes into account distribution and model uncertainties.

Mehta, S. R.↗
NASA NTRS1995

A Probabilistic Tool that Aids Logistics Engineers in the Establishment of High Confidence Repair Need-Dates at the NASA Shuttle Logistics Depot

The NASA Shuttle Logistics Depot (NSLD) is tasked with the responsibility for repair and manufacture of Line Replaceable Unit (LRU) hardware and components to support the Space Shuttle Orbiter. Due to shrinking budgets, cost effective repair of LRU's becomes a primary objective. To achieve this objective, is imperative that resources be assigned to those LRU's which have the greatest expectation of being needed as a spare. Forecasting the times at which spares are needed requires consideration of many significant factors including: failure rate, flight rate, spares availability, and desired level of support, among others. This paper summarizes the results of the research and development work that has been accomplished in producing an automated tool that assists in the assignment of effective repair start-times for LRU's at the NSLD. This system, called the Repair Start-time Assessment System (RSAS), uses probabilistic modeling technology to calculate a need date for a repair that considers the current repair pipeline status, as well as, serviceable spares and projections of future demands. The output from the system is a date for beginning the repair that has significantly greater confidence (in the sense that a desired probability of support is ensured) than times produced using other techniques. Since an important output of RSAS is the longest repair turn-around time that will ensure a desired probability of support, RSAS has the potential for being applied to operations at any repair depot where spares are on-hand and repair start-times are of interest. In addition, RSAS incorporates tenants of Just-in-Time (JIT) techniques in that the latest repair start-time (i.e., the latest time at which repair resources must be committed) may be calculated for every failed unit This could reduce the spares inventory for certain items, without significantly increasing the risk of unsatisfied demand.

Bullington, J. V.↗
NASA NTRS2007

Gaining Confidence in Navigating Rosetta at Mars Swing-By

The Mars swing-by in the early morning of the 25th of February 2007 was one of the most critical events the Rosetta mission has experienced so far on its way to the comet Churyumov-Gerasimenko. The closest approach took place at a distance of only 250 km from the planet s surface. Missing the optimal target would have translated into considerable fuel cost. In order to achieve confidence in operating through this highly critical mission phase, a navigation analysis exercise was carried out beforehand. This paper describes the purpose and the chosen approach for this preparatory Flight Dynamics activity. It presents and discusses results of the analysis. Emphasis is put on the question of what is needed to simulate a valuable data set representative for operations. The results of the navigation analysis are compared with real data obtained during swing-by operations.

Crammn, Ruediger↗
NASA NTRS2009

A Near-Term, High-Confidence Heavy Lift Launch Vehicle

The use of well understood, legacy elements of the Space Shuttle system could yield a near-term, high-confidence Heavy Lift Launch Vehicle that offers significant performance, reliability, schedule, risk, cost, and work force transition benefits. A side-mount Shuttle-Derived Vehicle (SDV) concept has been defined that has major improvements over previous Shuttle-C concepts. This SDV is shown to carry crew plus large logistics payloads to the ISS, support an operationally efficient and cost effective program of lunar exploration, and offer the potential to support commercial launch operations. This paper provides the latest data and estimates on the configurations, performance, concept of operations, reliability and safety, development schedule, risks, costs, and work force transition opportunities for this optimized side-mount SDV concept. The results presented in this paper have been based on established models and fully validated analysis tools used by the Space Shuttle Program, and are consistent with similar analysis tools commonly used throughout the aerospace industry. While these results serve as a factual basis for comparisons with other launch system architectures, no such comparisons are presented in this paper. The authors welcome comparisons between this optimized SDV and other Heavy Lift Launch Vehicle concepts.

Rothschild, William J.↗
NASA NTRS2010

PRA in Design: Increasing Confidence in Pre-Operational Assessments of Risks (Results of a Joint NASA/NRC Workshop)

In late 2009, the National Aeronautics and Space Administration (NASA) and the U.S. Nuclear Regulatory Commission (NRC) jointly organized a workshop to discuss technical issues associated with application of risk assessments to early phases of system design. The workshop, which was coordinated by the Idaho National Laboratory, involved invited presentations from a number of PRA experts in the aerospace and nuclear fields and subsequent discussion to address the following questions: (a) What technical issues limit decision-makers' confidence in PRA results, especially at a pre-operational phase of the system life cycle? (b) What is being done to address these issues'? (c) What more can be done ? The workshop resulted in participant observations and suggestions on several technical issues, including the pursuit of non-traditional approaches to risk assessment and the verification and validation of risk models. The workshop participants also identified several important non-technical issues, including risk communication with decision makers, and the integration of PRA into the overall design process.

Youngblood, Robert↗
NASA NTRS2017

Confidence Level Based Approach to Total Dose Specification for Spacecraft Electronics

A confidence level based approach to total dose radiation hardness assurance is presented for spacecraft electronics. It is applicable to both ionizing and displacement damage dose. Results are compared to the traditional approach that uses radiation design margin and advantages of the new approach are discussed.

Total Dose Distributions in Space↗
NASA NTRS2018

The Small Satellite Reliability Initiative: A Public-Private Effort Addressing SmallSat Mission Confidence

Presently, most CubeSat components and buses are generally not appropriate for missions where significant or indeterminate risk of failure is unacceptable. This has precluded their use in many cases where their attributes could otherwise enable or enhance mission objectives. However, in the future, CubeSats and SmallSats, which deviate from CubeSat form factors but often incorporate CubeSat components and subsystems, will address challenges that many presently consider to be beyond the platform's capabilities. This growing potential utility, combined with the limited volume of successful CubeSat flight heritage, is driving an interagency effort to improve small satellite mission confidence.

SmallSat↗
NASA NTRS2018

A Hybrid Method of Assurance Cases and Testing for Improved Confidence in Autonomous Space Systems

Autonomous systems react intelligently to their environments, making them capable of handling many possible conditions, but challenging to test. We are investigating a new test development method that aims to maximize the confidence to be achieved by combining Assurance Cases with High Throughput Testing (HTT). Assurance Cases, developed for safety-critical systems, are a rigorous argument that the system satisfies a property (e.g., the Mars rover will not tip over during a traverse). They integrate testing, analysis, and environmental and operational assumptions, from which the set of conditions that testing must cover is determined. In our method, information from the Assurance Case is used to determine the test coverage needed, and then input to HTT to generate the minimal test suites needed to provide that coverage.

Huntsberger, Terry↗
NASA NTRSDate not supplied

Algorithmic Classification of Raman Spectra Biosignatures: Improving Life Detection Confidence

“Agnostic” biosignatures – indicators of life (or the absence of life), independent of a particular biochemistry – are increasingly considered a high standard for life detection. The Ladder of Life Detection (2018) called for investigating how combinations of independent and different potential biosignatures affect confidence. To address this gap, statistical classification of elemental abundances, isotopic fractionation, and reflectance spectroscopy (VNIR) has been implemented. Raman spectroscopy, highly desirable due to its wide availability, has the potential to improve this predictive power. This work implemented biosignature classification algorithms on Raman data alone, in preparation for combination with the other data types. Raman spectroscopy data was collected from published databases and papers as part of a manually curated dataset of “indicative” and “non-indicative of life” samples. These currently include 61 non-indicative samples (meteorites, magnetite); 3 indicative living samples (bacteria); 20 indicative non-living samples (chalk, bone); and 12 indicative mixed (with non-indicative material) samples (soil, microbial mats). Laboratory work is ongoing to characterize additional samples, particularly a greater breadth of mixed systems. Spectra were interpolated, filtered with the Savitzsky-Golay filter, and de-noised. For a preliminary examination, agnostic features were manually extracted including mean intensity, number of peaks, and mean peak width. Different peak prominences and filtering polynomials were used to refine features. Classification algorithms were implemented: k-nearest neighbors (KNN), logistic regression (LR), linear support vector machines (SVM), random forest (RF), Gaussian naïve bayes (GNB). Lastly, Monte Carlo simulations on 1,000 50%-train-test-splits were used to validate classification performance and feature significance. The preliminary feature set achieved its highest AUC of 0.52 with LR, with no strongly discriminatory features. Work to improve feature extraction, such as through deep learning with back propagation, is planned. In future work, the Raman data will be combined with the other data types, and potentially new data types such as enantiomeric excess. This project was partially supported through the NASA Ames Project EXcellence (APEX) incubator program.

Astrobiology↗
DOE OSTI2025

The Profiled Feldman-Cousins Method for Confidence Interval Construction for the Nova 3-Flavor Oscillation Analysis

The small interaction cross-section of neutrinos makes experimental neutrino physics particularly responsive to technological advancements. A significant development leveraged by the NOvA experiment is large-scale parallel processing, enabling novel computational approaches to longstanding experimental challenges. Central to managing the resulting high-throughput data is NOvA’s implementation of the Freight Train model, designed for efficient data production and handling.This dissertation details the methodology and execution of the NOvA 2024 3-Flavor Oscillation Analysis, supported by a comprehensive dataset spanning ten years. It emphasizes frequentist results refined through the Feldman-Cousins (FC) technique, specifically addressing confidence interval corrections in parameter estimation. The computational intensity associated with Feldman-Cousins arises from extensive Monte Carlo simulations, which were substantially mitigated through parallel computing on the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC), employing the MPI framework.To further enhance computational efficiency, an Importance Sampling method is introduced and evaluated, demonstrating significant potential to reduce complexity, particularly in exploring extreme parameter space regions. This thesis presents both the successful application of advanced computational resources and the development of sophisticated statistical techniques, aiming to enhance the precision and scope of neutrino oscillation analyses.

Dye ajdye11190@gmail.com, Andrew Joseph [Mississip↗