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NASA NTRS2011

NASA Tech Briefs, April 2011

Topics covered include: Amperometric Solid Electrolyte Oxygen Microsensors with Easy Batch Fabrication; Two-Axis Direct Fluid Shear Stress Sensor for Aerodynamic Applications; Target Assembly to Check Boresight Alignment of Active Sensors; Virtual Sensor Test Instrumentation; Evaluation of the Reflection Coefficient of Microstrip Elements for Reflectarray Antennas; Miniaturized Ka-Band Dual-Channel Radar; Continuous-Integration Laser Energy Lidar Monitor; Miniaturized Airborne Imaging Central Server System; Radiation-Tolerant, SpaceWire-Compatible Switching Fabric; Small Microprocessor for ASIC or FPGA Implementation; Source-Coupled, N-Channel, JFET-Based Digital Logic Gate Structure Using Resistive Level Shifters; High-Voltage-Input Level Translator Using Standard CMOS; Monitoring Digital Closed-Loop Feedback Systems; MASCOT - MATLAB Stability and Control Toolbox; MIRO Continuum Calibration for Asteroid Mode; GOATS Image Projection Component; Coded Modulation in C and MATLAB; Low-Dead-Volume Inlet for Vacuum Chamber; Thermal Control Method for High-Current Wire Bundles by Injecting a Thermally Conductive Filler; Method for Selective Cleaning of Mold Release from Composite Honeycomb Surfaces; Infrared-Bolometer Arrays with Reflective Backshorts; Commercialization of LARC (trade mark) -SI Polyimide Technology; Novel Low-Density Ablators Containing Hyperbranched Poly(azomethine)s; Carbon Nanotubes on Titanium Substrates for Stray Light Suppression; Monolithic, High-Speed Fiber-Optic Switching Array for Lidar; Grid-Tied Photovoltaic Power System; Spectroelectrochemical Instrument Measures TOC; A Miniaturized Video System for Monitoring Drosophila Behavior; Hydrofocusing Bioreactor Produces Anti-Cancer Alkaloids; Creep Measurement Video Extensometer; Radius of Curvature Measurement of Large Optics Using Interferometry and Laser Tracker n-B-pi-p Superlattice Infrared Detector; Safe Onboard Guidance and Control Under Probabilistic Uncertainty; General Tool for Evaluating High-Contrast Coronagraphic Telescope Performance Error Budgets; Hidden Statistics of Schroedinger Equation; Optimal Padding for the Two-Dimensional Fast Fourier Transform; Spatial Query for Planetary Data; Higher Order Mode Coupling in Feed Waveguide of a Planar Slot Array Antenna; Evolutionary Computational Methods for Identifying Emergent Behavior in Autonomous Systems; Sampling Theorem in Terms of the Bandwidth and Sampling Interval; Meteoroid/Orbital Debris Shield Engineering Development Practice and Procedure; Self-Balancing, Optical-Center-Pivot, Fast-Steering Mirror; Wireless Orbiter Hang-Angle Inclinometer System; and Internal Electrostatic Discharge Monitor - IESDM.

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NASA NTRS1990

Ceramics Analysis and Reliability Evaluation of Structures (CARES). Users and programmers manual

This manual describes how to use the Ceramics Analysis and Reliability Evaluation of Structures (CARES) computer program. The primary function of the code is to calculate the fast fracture reliability or failure probability of macroscopically isotropic ceramic components. These components may be subjected to complex thermomechanical loadings, such as those found in heat engine applications. The program uses results from MSC/NASTRAN or ANSYS finite element analysis programs to evaluate component reliability due to inherent surface and/or volume type flaws. CARES utilizes the Batdorf model and the two-parameter Weibull cumulative distribution function to describe the effect of multiaxial stress states on material strength. The principle of independent action (PIA) and the Weibull normal stress averaging models are also included. Weibull material strength parameters, the Batdorf crack density coefficient, and other related statistical quantities are estimated from four-point bend bar or unifrom uniaxial tensile specimen fracture strength data. Parameter estimation can be performed for single or multiple failure modes by using the least-square analysis or the maximum likelihood method. Kolmogorov-Smirnov and Anderson-Darling goodness-of-fit tests, ninety percent confidence intervals on the Weibull parameters, and Kanofsky-Srinivasan ninety percent confidence band values are also provided. The probabilistic fast-fracture theories used in CARES, along with the input and output for CARES, are described. Example problems to demonstrate various feature of the program are also included. This manual describes the MSC/NASTRAN version of the CARES program.

Nemeth, Noel N.↗

NASA NTRS1993

Probabilistic simulation of multi-scale composite behavior

A methodology is developed to computationally assess the probabilistic composite material properties at all composite scale levels due to the uncertainties in the constituent (fiber and matrix) properties and in the fabrication process variables. The methodology is computationally efficient for simulating the probability distributions of material properties. The sensitivity of the probabilistic composite material property to each random variable is determined. This information can be used to reduce undesirable uncertainties in material properties at the macro scale of the composite by reducing the uncertainties in the most influential random variables at the micro scale. This methodology was implemented into the computer code PICAN (Probabilistic Integrated Composite ANalyzer). The accuracy and efficiency of this methodology are demonstrated by simulating the uncertainties in the material properties of a typical laminate and comparing the results with the Monte Carlo simulation method. The experimental data of composite material properties at all scales fall within the scatters predicted by PICAN.

Liaw, D. G.↗

NASA NTRS2013

Statistical Analyses of Raw Material Data for MTM45-1/CF7442A-36% RW: CMH Cure Cycle

This report describes statistical characterization of physical properties of the composite material system MTM45-1/CF7442A, which has been tested and is currently being considered for use on spacecraft structures. This composite system is made of 6K plain weave graphite fibers in a highly toughened resin system. This report summarizes the distribution types and statistical details of the tests and the conditions for the experimental data generated. These distributions will be used in multivariate regression analyses to help determine material and design allowables for similar material systems and to establish a procedure for other material systems. Additionally, these distributions will be used in future probabilistic analyses of spacecraft structures. The specific properties that are characterized are the ultimate strength, modulus, and Poisson􀂶s ratio by using a commercially available statistical package. Results are displayed using graphical and semigraphical methods and are included in the accompanying appendixes.

Coroneos, Rula↗

NASA NTRS2019

Risk Estimation of Threatening Asteroids

When faced with the question of designing an asteroid deflection mission or with the decision of launching it, significant uncertainties are present in the asteroid’s physical properties, and its orbit solution. The success of the deflection mission relies heavily on these aspects. For example, a heavier than expected asteroid will reduce the imparted deflection DV. So will a larger porosity value by reducing the beta factor [1]. Here, we present a new capability that estimates asteroid impact risk under consideration of these uncertainties. The new method samples the uncertainty space along multiple dimensions, performs a predetermined deflection, propagates the deflected samples to the Earth, models the impact damage, and estimates the overall risk outcome. The work builds on the Probabilistic Asteroid Impact Risk (PAIR) assessment tool [2] by including orbital uncertainty and deflection capabilities. We demonstrate this risk estimation approach for threatening asteroids using the example of the fictitious impactor 2019 PDC. Such analysis provides a quantitative basis for the work of decision makers and disaster managers. It may further find application in areas such as mitigation mission planning where projected post-mitigation risk can be compared to premitigation levels as a means of cost-benefit analysis formitigation options.

Rumpf, Clemens↗

NASA NTRS2019

Blind Validation Study of Parametric Cost Estimation Tool SEER-H for NASA Space Missions

One of the primary parametric cost modeling tools used by NASA and the aerospace industry to estimate the development and production cost of future spacecraft hardware is SEER-H by Galorath. To date, no independent validation of this tool for cost estimation of space missions has been reported in the literature. In the present validation study, cost estimators used SEER-H to estimate the cost of twelve different past NASA science missions. The estimators were prevented from knowing the actual cost of the missions in an effort to minimize cognitive biases. The point estimates of SEER-H had an average error of 23%, median error of -0.3%, and a standard deviation of 43%. Nine of the twelve mission's actual costs fell within the 80% confidence interval of SEER's probabilistic estimates. Several factors independent of SEER that may have affected the accuracy of the results have been identified and are discussed; these include: uncertainty in the technical data used for the estimates, the methods used to estimate uncertainty in spacecraft component mass and numbers of prototypes, and the experience of the estimators.

SEER-H↗

NASA NTRS2020

Behavior modeling for cybersecurity

In this paper, we elaborate on the key actors within the context of the cyber world at the Jet Propulsion Laboratory and use Bayesian Belief Networks to represent the causal and probabilistic relationships between the various elements that affect an actor and the likelihood of exploits and adverse consequences that can occur due to an exploit. We assess the effectiveness of each of the mitigative methods and the sensitivity of the system to each of the aggravating as well as mitigative factors. We use a combination of objective incident data and Subject Matter Expert knowledge as input to these models.

King, James↗

NASA NTRS2021

Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations

The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean prediction and analysis. The increasing coverage of in situ Argo profile data allows for an increasingly accurate analysis of the mixed layer depth (MLD) variability associated with deviations from the seasonal climatology. However, sampling rates are not sufficient to fully resolve subseasonal (<90 day) MLD variability. Yet, many multivariate observations-based analyses include implicit modeled subseasonal MLD variability. One analysis method is optimal interpolation of in situ data, but the interior analysis can be improved by leveraging surface data with regression or variational approaches. Here, we demonstrate how machine learning methods and satellite sea surface temperature, salinity, and height facilitate MLD estimation in a pilot study of two regions: the mid-latitude southern Indian and the eastern equatorial Pacific Oceans. We construct multiple machine learning architectures to produce weekly 1/2° gridded MLD anomaly fields (relative to a monthly climatology) with uncertainty estimates. We test multiple traditional and probabilistic machine learning techniques to compare both accuracy and probabilistic calibration. We validate our methodology by applying it to ocean model simulations. We find that incorporating sea surface data through a machine learning model improves the performance of spatiotemporal MLD variability estimation compared to optimal interpolation of Argo observations alone. These preliminary results are a promising first step for the application of machine learning to MLD prediction.

Machine Learning↗

NASA NTRS1993

Probabilistic nonlinear finite element analysis of composite structures

A probabilistic finite element analysis procedure for laminated composite shells is developed. A total Lagrangian finite element formulation, employing a degenerated three-dimensional laminated composite shell element with the full Green-Lagrange strains and first-order shear deformable kinematics, is used. The first-order second-moment technique for probabilistic finite element analysis of random fields is employed, and results are presented in the form of mean and variance of the structural response. Reliability calculations are made by using the first-order reliability method combined with sensitivity derivatives from the finite element analysis. Both ply-level and micromechanics-level random variables are incorporated, the latter by means of the Aboudi micromechanics model. Two sample problems are solved to verify the accuracy of the procedures developed and to quantify the variability of certain material type/structure combinations. In general, the procedure is quite effective in determining the response statistics and reliability for linear and geometric nonlinear behavior of laminated composite shells.

Engelstad, S. P.↗

NASA NTRS1996

Structures Division 1994 Annual Report

The NASA Lewis Research Center Structures Division is an international leader and pioneer in developing new structural analysis, life prediction, and failure analysis related to rotating machinery and more specifically to hot section components in air-breathing aircraft engines and spacecraft propulsion systems. The research consists of both deterministic and probabilistic methodology. Studies include, but are not limited to, high-cycle and low-cycle fatigue as well as material creep. Studies of structural failure are at both the micro- and macrolevels. Nondestructive evaluation methods related to structural reliability are developed, applied, and evaluated. Materials from which structural components are made, studied, and tested are monolithics and metal-matrix, polymer-matrix, and ceramic-matrix composites. Aeroelastic models are developed and used to determine the cyclic loading and life of fan and turbine blades. Life models are developed and tested for bearings, seals, and other mechanical components, such as magnetic suspensions. Results of these studies are published in NASA technical papers and reference publication as well as in technical society journal articles. The results of the work of the Structures Division and the bibliography of its publications for calendar year 1994 are presented.

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NASA NTRS1997

Structures Division

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NASA NTRS2008

Figures of Merit for Control Verification

This paper proposes a methodology for evaluating a controller's ability to satisfy a set of closed-loop specifications when the plant has an arbitrary functional dependency on uncertain parameters. Control verification metrics applicable to deterministic and probabilistic uncertainty models are proposed. These metrics, which result from sizing the largest uncertainty set of a given class for which the specifications are satisfied, enable systematic assessment of competing control alternatives regardless of the methods used to derive them. A particularly attractive feature of the tools derived is that their efficiency and accuracy do not depend on the robustness of the controller. This is in sharp contrast to Monte Carlo based methods where the number of simulations required to accurately approximate the failure probability grows exponentially with its closeness to zero. This framework allows for the integration of complex, high-fidelity simulations of the integrated system and only requires standard optimization algorithms for its implementation.

Crespo, Luis G.↗

NASA NTRS1995

Model checking

Automatic formal verification methods for finite-state systems, also known as model-checking, successfully reduce labor costs since they are mostly automatic. Model checkers explicitly or implicitly enumerate the reachable state space of a system, whose behavior is described implicitly, perhaps by a program or a collection of finite automata. Simple properties, such as mutual exclusion or absence of deadlock, can be checked by inspecting individual states. More complex properties, such as lack of starvation, require search for cycles in the state graph with particular properties. Specifications to be checked may consist of built-in properties, such as deadlock or 'unspecified receptions' of messages, another program or implicit description, to be compared with a simulation, bisimulation, or language inclusion relation, or an assertion in one of several temporal logics. Finite-state verification tools are beginning to have a significant impact in commercial designs. There are many success stories of verification tools finding bugs in protocols or hardware controllers. In some cases, these tools have been incorporated into design methodology. Research in finite-state verification has been advancing rapidly, and is showing no signs of slowing down. Recent results include probabilistic algorithms for verification, exploitation of symmetry and independent events, and the use symbolic representations for Boolean functions and systems of linear inequalities. One of the most exciting areas for further research is the combination of model-checking with theorem-proving methods.

Dill, David L.↗

NASA NTRS2019

Inclusion of Radiation Environment Variability for Reliability Estimates for SiC Power MOSFETs

Variability of the solar energetic particle environment is investigated for single-event-burnout reliability of silicon-carbide power metal-oxide-semiconductor field effect transistors. A probabilistic assessment of failure evaluates the benefits of de-rating voltage, shielding, and mission length. The Prediction of Solar particle Yields for Characterizing Integrating Circuits code is used to calculate a cumulative density function for the fluence of the environment. The lethal ion method is then used to determine what proportion of the environment will cause single-event-burnout. The operating voltage determines the lowest linear-energy-transfer particle that will cause single-event-burnout and that should be included in the environment distribution. The shielding and mission length also determine the final environment distribution of the mission fluence. Through calculating the reliability for different operating voltages, shielding, and mission length for a specific device, it is shown that shielding thickness and operating voltage have a large effect on reliability and can be traded off during the design.

Heavy ion↗

NASA NTRS2017

Probabilistic Forecasting of Surface Ozone with a Novel Statistical Approach

The recent change in the Environmental Protection Agency's surface ozone regulation, lowering the surface ozone daily maximum 8-h average (MDA8) exceedance threshold from 75 to 70 ppbv, poses significant challenges to U.S. air quality (AQ) forecasters responsible for ozone MDA8 forecasts. The forecasters, supplied by only a few AQ model products, end up relying heavily on self-developed tools. To help U.S. AQ forecasters, this study explores a surface ozone MDA8 forecasting tool that is based solely on statistical methods and standard meteorological variables from the numerical weather prediction (NWP) models. The model combines the self-organizing map (SOM), which is a clustering technique, with a step wise weighted quadratic regression using meteorological variables as predictors for ozone MDA8. The SOM method identifies different weather regimes, to distinguish between various modes of ozone variability, and groups them according to similarity. In this way, when a regression is developed for a specific regime, data from the other regimes are also used, with weights that are based on their similarity to this specific regime. This approach, regression in SOM (REGiS), yields a distinct model for each regime taking into account both the training cases for that regime and other similar training cases. To produce probabilistic MDA8 ozone forecasts, REGiS weighs and combines all of the developed regression models on the basis of the weather patterns predicted by an NWP model. REGiS is evaluated over the San Joaquin Valley in California and the northeastern plains of Colorado. The results suggest that the model performs best when trained and adjusted separately for an individual AQ station and its corresponding meteorological site.

Ozone variables↗

NASA NTRS1990

Performability analysis using semi-Markov reward processes

Beaudry (1978) proposed a simple method of computing the distribution of performability in a Markov reward process. Two extensions of Beaudry's approach are presented. The method is generalized to a semi-Markov reward process by removing the restriction requiring the association of zero reward to absorbing states only. The algorithm proceeds by replacing zero-reward nonabsorbing states by a probabilistic switch; it is therefore related to the elimination of vanishing states from the reachability graph of a generalized stochastic Petri net and to the elimination of fast transient states in a decomposition approach to stiff Markov chains. The use of the approach is illustrated with three applications.

Ciardo, Gianfranco↗

NASA NTRS2020

Subseasonal-to-Seasonal Hindcast Skill Assessment of Ridging Events Related to Drought Over the Western United States

Persistent atmospheric ridging events centered near the western United States are associated with widespread precipitation deficits and meteorological drought. Due to the relatively low skill of- dynamical models in forecasting precipitation on subseasonal‐to‐seasonal (S2S) time scales across this region, forecasts of ridging are explored in this study as a potential bridge for early warning drought prediction. To assess skill, we evaluate deterministic and probabilistic S2S hindcasts (out to 6 week lead time) of ridging events and geopotential height anomalies over the western United States in five ensemble hindcast systems. Prediction skill for ridging events is shown to be highly variable across models. For some models, longer‐time‐averaged patterns of geopotential height anomalies across the first 6 weeks can be skillfully simulated, when evaluated probabilistically against climatology. The most skillful models show modest skill in forecasting above normal ridging occurrences at lead times of Weeks 3–4 and Weeks 5–6,with some sensitivity to the specific ridge location and method for determining skill. Using the European Centre for Medium‐Range Weather Forecasts (ECMWF) model as a case study, longer lead time forecast busts are shown to often occur under extended periods of highly active La Nina‐like tropical convection. Model errors at simulating these tropical convection features may have a disproportionately large impact and degrade downstream forecasts over the western United States. Despite the documented model shortcomings, our results highlight an opportunity to target skillful ridging forecasts from dynamical models for improving early warning drought forecasting at S2S lead times.

S2S↗

NASA NTRSDate not supplied

Toward an IMU-Based Space Suit Motion Capture System

Spacesuits are complex engineering systems that sustain human health and enable performance outside Earth-like environments. These systems must support human mobility and physical workload demands while minimizing injury risk during extravehicular activity (EVA). Future EVA operations on the Lunar surface are expected to be more frequent and require higher physical workloads than previously during the ISS, Shuttle, and Apollo programs. To characterize the workloads and ergonomics needs a suit must support, the kinematics of the space suit must be measured during operationally-relevant tasks in ground analog environments. Kinematics capture of the suit is challenging for traditional optical motion capture (OMC) approaches due to marker occlusion, harsh lighting or environmental conditions, and tests with suit surrogates in outdoor field environments. To this end, engineers at NASA are developing the Augmented Suit Inverse Kinematics (ASIK) system, a complete motion capture method and inverse kinematics solver which relies solely on a network of wireless inertial measurement units (IMUs) attached to the major kinematic segments of the spacesuit. The ASIK modeling language allows for the simple inclusion of probabilistic priors such as suit size and shape or IMU poses. The ASIK system was tested in a 7-subject pilot study. Each subject donned NASA’s new prototype exploration spacesuit in the Active Response Gravity Offload System (ARGOS) facility at Johnson Space Center in Houston, TX. The suits were outfitted with 12 IMUs to estimate lower body and trunk kinematics. The suits were also outfitted with a set of reflective OMC markers, and traditional OMC data was collected and processed. Characterization of the ASIK-derived suit joint angles’ accuracy against an optical motion capture datum will be presented. Discussion of these results, as well as discussion of system calibration and nuances of mathematical observability, will be included.

IMU↗