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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Analysis of tipping-curve measurements performed at the DSS-13 beam-waveguide antenna at 32.0 and 8.45 GigaHertz

This article reports on the analysis of the Ka-band Antenna Performance Experiment tipping-curve data acquired at the DSS-13 research and development beam-waveguide (BWG) antenna. By measuring the operating system temperatures as the antenna is moved form zenith to low-elevation angles and fitting a model to the data, one can obtain information on how well the overall temperature model behaves at zenith and approximate the contribution due to the atmosphere. The atmospheric contribution estimated from the data can be expressed in the form of (1) atmospheric noise temperatures that can provide weather statistic information and be compared against those estimated from other methods and (2) the atmospheric loss factor used to refer efficiency measurements to zero atmosphere. This article reports on an analysis performed on a set of 68 8.4-GHz and 67 32-GHz tipping-curve data sets acquired between December 1993 and May 1995 and compares the results with those inferred from a surface model using input meteorological data and from water vapor radiometer (WVR) data. The general results are that, for a selected subset of tip curves, (1) the BWG tipping-curve atmospheric temperatures are in good agreement with those determined from WVR data (the average difference is 0.06 +/- 0.64 K at 32 GHz) and (2) the surface model average values are biased 3.6 K below those of the BWG and WVR at 32 GHz.

Morabito, D. D.↗
NASA NTRS1973

Short and long periodic atmospheric variations between 25 and 200 km

Previously collected data on atmospheric pressure, density, temperature and winds between 25 and 200 km from sources including Meteorological Rocket Network data, ROBIN falling sphere data, grenade release and pitot tube data, meteor winds, chemical release winds, satellite data, and others were analyzed by a daily difference method and results on the distribution statistics, magnitude, and spatial structure of gravity wave and planetary wave atmospheric variations are presented. Time structure of the gravity wave variations were determined by the analysis of residuals from harmonic analysis of time series data. Planetary wave contributions in the 25-85 km range were discovered and found to have significant height and latitudinal variation. Long period planetary waves, and seasonal variations were also computed by harmonic analysis. Revised height variations of the gravity wave contributions in the 25 to 85 km height range were computed. An engineering method and design values for gravity wave magnitudes and wave lengths are given to be used for such tasks as evaluating the effects on the dynamical heating, stability and control of spacecraft such as the space shuttle vehicle in launch or reentry trajectories.

Justus, C. G.↗
NASA NTRS1985

Circuit analysis method for thin-film solar cell modules

The design of a thin-film solar cell module is dependent on the probability of occurrence of pinhole shunt defects. Using known or assumed defect density data, dichotomous population statistics can be used to calculate the number of defects expected in a module. Probability theory is then used to assign the defective cells to individual strings in a selected series-parallel circuit design. Iterative numerical calculation is used to calcuate I-V curves using cell test values or assumed defective cell values as inputs. Good and shunted cell I-V curves are added to determine the module output power and I-V curve. Different levels of shunt resistance can be selected to model different defect levels.

Burger, D. R.↗
NASA NTRS1998

T wave alternans as a predictor of recurrent ventricular tachyarrhythmias in ICD recipients: prospective comparison with conventional risk markers

INTRODUCTION: The current standard for arrhythmic risk stratification is electrophysiologic (EP) testing, which, due to its invasive nature, is limited to patients already known to be at high risk. A number of noninvasive tests, such as determination of left ventricular ejection fraction (LVEF) or heart rate variability, have been evaluated as additional risk stratifiers. Microvolt T wave alternans (TWA) is a promising new risk marker. Prospective evaluation of noninvasive risk markers in low- or moderate-risk populations requires studies involving very large numbers of patients, and in such studies, documentation of the occurrence of ventricular tachyarrhythmias is difficult. In the present study, we identified a high-risk population, recipients of an implantable cardioverter defibrillator (ICD), and prospectively compared microvolt TWA with invasive EP testing and other risk markers with respect to their ability to predict recurrence of ventricular tachyarrhythmias as documented by ICD electrograms. METHODS AND RESULTS: Ninety-five patients with a history of ventricular tachyarrhythmias undergoing implantation of an ICD underwent EP testing, assessment of TWA, as well as determination of LVEF, baroreflex sensitivity, signal-averaged ECG, analysis of 24-hour Holter monitoring, and QT dispersion from the 12-lead surface ECG. The endpoint of the study was first appropriate ICD therapy for electrogram-documented ventricular fibrillation or tachycardia during follow-up. Kaplan-Meier survival analysis revealed that TWA (P < 0.006) and LVEF (P < 0.04) were the only significant univariate risk stratifiers. EP testing was not statistically significant (P < 0.2). Multivariate Cox regression analysis revealed that TWA was the only statistically significant independent risk factor. CONCLUSIONS: Measurement of microvolt TWA compared favorably with both invasive EP testing and other currently used noninvasive risk assessment methods in predicting recurrence of ventricular tachyarrhythmias in ICD recipients. This study suggests that TWA might also be a powerful tool for risk stratification in low- or moderate-risk patients, and needs to be prospectively evaluated in such populations.

Non-NASA Center↗
DOE OSTI2025

Rapid characterization and failure analysis of 6276 rooftop-harvested photovoltaic connectors

Photovoltaic (PV) connectors, which link modules in series and connect PV strings in parallel, have increasingly been recognized as a primary contributor to PV system failures and a source of numerous fire incidents. However, publicly available data on the rates and types of connector failures are scarce, primarily due to the proprietary nature of the information and the need for comprehensive analysis. This study represents the first large-scale investigation of harvested PV connectors, drawing from a dataset of 6276 connectors from residential rooftop solar systems across the United States. The outcome of this work is twofold: 1) we have established a rapid characterization method for large populations of harvested connectors, incorporating visual inspection, resistance measurements, and X-ray imaging; and 2) the analysis made possible by our rapid-processing method has revealed, for a population of connector models provided by a single rooftop installer, failure statistics and insights for various connector makes and models, installation practices, operating currents, and internal component displacements. This research identifies common failure modes that could be considered in future connector designs standards, and operations and maintenance practices, to ultimately improve the reliability of this vital component of PV infrastructure.

MC4↗
NASA NTRS1990

Pressure Gauges Monitor Leakage Past Seals

Method devised to measure leakage of gas past each of two sets of primary and secondary seals into common volume from which aggregate flow measured. Although method applicable only to specific combination of flow configuration and thermal conditions, it serves as example of more general approach involving use of statistical analysis to extract additional information from measurements.

Smith, Steven A.↗
NASA NTRS1990

Computational tools for multi-linked flexible structures

A software module which designs and tests controllers and filters in Kalman Estimator form, based on a polynomial state-space model is discussed. The user-friendly program employs an interactive graphics approach to simplify the design process. A variety of input methods are provided to test the effectiveness of the estimator. Utilities are provided which address important issues in filter design such as graphical analysis, statistical analysis, and calculation time. The program also provides the user with the ability to save filter parameters, inputs, and outputs for future use.

Lee, Gordon K. F.↗
NASA NTRS1994

Variability of measured sonic boom signatures

The topics discussed include the following: atmospheric turbulence; BOOMFILE Database description; BOOMFILE flight conditions; XB-70 Database descriptions; analysis progression; extended database; prediction method; overpressure variability dependence on flight conditions; loudness variability on flight conditions; sonic boom variability in repeat flights; and statistical distributions.

Elmer, K. R.↗
NASA NTRS2012

Did Geomagnetic Activity Challenge Electric Power Reliability During Solar Cycle 23? Evidence from the PJM Regional Transmission Organization in North America

During solar cycle 22, a very intense geomagnetic storm on 13 March 1989 contributed to the collapse of the Hydro-Quebec power system in Canada. This event clearly demonstrated that geomagnetic storms have the potential to lead to blackouts. This paper addresses whether geomagnetic activity challenged power system reliability during solar cycle 23. Operations by PJM Interconnection, LLC (hereafter PJM), a regional transmission organization in North America, are examined over the period 1 April 2002 through 30 April 2004. During this time PJM coordinated the movement of wholesale electricity in all or parts of Delaware, Maryland, New Jersey, Ohio, Pennsylvania, Virginia, West Virginia, and the District of Columbia in the United States. We examine the relationship between a proxy of geomagnetically induced currents (GICs) and a metric of challenged reliability. In this study, GICs are proxied using magnetometer data from a geomagnetic observatory located just outside the PJM control area. The metric of challenged reliability is the incidence of out-of-economic-merit order dispatching due to adverse reactive power conditions. The statistical methods employed make it possible to disentangle the effects of GICs on power system operations from purely terrestrial factors. The results of the analysis indicate that geomagnetic activity can significantly increase the likelihood that the system operator will dispatch generating units based on system stability considerations rather than economic merit.

storms↗
NASA NTRS1972

Determination of stability derivatives from flight data using a Newton-Raphson minimization technique

A modified Newton-Raphson or quasilinearization minimization technique for determining stability derivatives from flight data was developed and compared with simple-equations, analog-matching, least-squares, and Shinbrot methods of analysis. For the data analyzed, the solutions computed by using the estimates obtained from the Newton-Raphson technique fit the data and determined coefficients adequately. A further modification to include a priori information was found to be useful. A model statistically similar to the flight data was analyzed using the same methods (excluding analog matching), and the Newton-Raphson technique was found to yield superior estimates. An approximate Cramer-Rao bound was compared with the error covariance matrix of the model and was found to provide information about the reliability of the individual estimates obtained. The technique was successfully applied to data obtained from a light airplane, a large supersonic airplane, and a lifting body vehicle. It was shown that the reliability of the estimates of a given coefficient obtained from these vehicles depends upon the data analyzed.

Iliff, K. W.↗
NASA NTRS2015

Online Dectection and Modeling of Safety Boundaries for Aerospace Application Using Bayesian Statistics

The behavior of complex aerospace systems is governed by numerous parameters. For safety analysis it is important to understand how the system behaves with respect to these parameter values. In particular, understanding the boundaries between safe and unsafe regions is of major importance. In this paper, we describe a hierarchical Bayesian statistical modeling approach for the online detection and characterization of such boundaries. Our method for classification with active learning uses a particle filter-based model and a boundary-aware metric for best performance. From a library of candidate shapes incorporated with domain expert knowledge, the location and parameters of the boundaries are estimated using advanced Bayesian modeling techniques. The results of our boundary analysis are then provided in a form understandable by the domain expert. We illustrate our approach using a simulation model of a NASA neuro-adaptive flight control system, as well as a system for the detection of separation violations in the terminal airspace.

Statistics↗
NASA NTRS1999

Statistical physics and physiology: monofractal and multifractal approaches

Even under healthy, basal conditions, physiologic systems show erratic fluctuations resembling those found in dynamical systems driven away from a single equilibrium state. Do such "nonequilibrium" fluctuations simply reflect the fact that physiologic systems are being constantly perturbed by external and intrinsic noise? Or, do these fluctuations actually, contain useful, "hidden" information about the underlying nonequilibrium control mechanisms? We report some recent attempts to understand the dynamics of complex physiologic fluctuations by adapting and extending concepts and methods developed very recently in statistical physics. Specifically, we focus on interbeat interval variability as an important quantity to help elucidate possibly non-homeostatic physiologic variability because (i) the heart rate is under direct neuroautonomic control, (ii) interbeat interval variability is readily measured by noninvasive means, and (iii) analysis of these heart rate dynamics may provide important practical diagnostic and prognostic information not obtainable with current approaches. The analytic tools we discuss may be used on a wider range of physiologic signals. We first review recent progress using two analysis methods--detrended fluctuation analysis and wavelets--sufficient for quantifying monofractual structures. We then describe recent work that quantifies multifractal features of interbeat interval series, and the discovery that the multifractal structure of healthy subjects is different than that of diseased subjects.

NASA Discipline Cardiopulmonary↗
NASA NTRS2018

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a piloting an aircraft, where activities with distinct visual signatures might be things like communicating, navigating, and monitoring. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. The method is in some respects similar to recurrence analysis, but here we compare not individual fixations, but groups of fixations aggregated over a fixed time interval. The duration of this interval is a parameter that we will refer to as delta. We assume that the environment has been divided into a set of N different areas-of-interest (AOIs). For a given interval of time of duration delta, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector. These proportions can be converted to integer counts by multiplying by delta divided by the average fixation duration (another parameter that we fix at 280 milliseconds). We compare different intervals by computing the chi-square statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. The method has been applied to approximately 100 hours of eye movement data collected from pilots in a high-fidelity B747 flight simulator, and the results have been compared to synthetic data in which the each activity is represented as first-order Markov process with random probabilities assigned to the AOIs. Randomly-generated synthetic activities can require thousands of fixations to be discriminated with statistical significance, while the human data can be clustered using averaging windows of some 10's of seconds, suggesting that the actual activities are much more narrowly focused than random Markov models.

activity analysis↗
NASA NTRS2022

Introduction to Analysis Methods for Big Earth Data

Big Earth Data are too big to be tractable to simple data inspection. Thus, they typically require models to make sense of all the data. Useful models for Big Earth Data may be physical, statistical, or machine learning based. While physical models are ideal for understanding the data, they are not always feasible, particularly when our ability to observe at finer scales exceeds our ability to incorporate the physics. Statistical models are more generalized, but computationally intensive for many Earth Observation datasets. Machine Learning models generally scale well but are sometimes limited in the physical understanding they can offer. Hybrid models combine attributes—and advantages—of two or more of these types.

Christopher Lynnes↗
NASA NTRS1995

LES, DNS and RANS for the analysis of high-speed turbulent reacting flows

The purpose of this research is to continue our efforts in advancing the state of knowledge in large eddy simulation (LES), direct numerical simulation (DNS), and Reynolds averaged Navier Stokes (RANS) methods for the computational analysis of high-speed reacting turbulent flows. In the second phase of this work, covering the period 1 Aug. 1994 - 31 Jul. 1995, we have focused our efforts on two programs: (1) developments of explicit algebraic moment closures for statistical descriptions of compressible reacting flows and (2) development of Monte Carlo numerical methods for LES of chemically reacting flows.

Adumitroaie, V.↗
DOE OSTI2025

Highly Resolved Reference Projections of Building Energy Use for the Contiguous United States: Building Sector Energy Baselines, Projection Methods, and Results

This report describes one methodology of projecting energy consumption of the US residential and commercial building sectors using NREL's ResStock™ and ComStock™ as well as growth rates derived from EIA's Annual Energy Outlook (AEO). The impetus for this work is to provide an intermediate method for compiling demand-side sectoral energy projections that is suitable for grid-scale analysis, such as NREL's Standard Scenarios. ResStock and ComStock are physics-based and statistically representative building stock models of the US residential and commercial sector, respectively. Using the 2012 actual meteorological year (AMY) weather data, the sectoral energy baselines are simulated and then segmented along key dimensions (e.g., geography, dwelling/building type). The segmented results are then scaled using the corresponding annual growth rates derived from the 2021 AEO reference case to produce energy projections out to 2050. The compiled result is a demand-side grid model (dsgrid) data set suitable for use in NREL's large-scale grid models, such as the Regional Energy Deployment System (ReEDS). This simple projection method does not endogenously represent how the building stock could evolve through time. Most notably, it does not reflect large-scale electrification, for example, the conversion of space heating, water heating, clothes drying, and cooking from primary fossil fuels to electricity, as this is not part of AEO's reference case assumptions. Nonetheless this approach is more resolved and potentially extensible compared to the current method used by Standard Scenarios's reference case, which augments a sector's total load based on a single growth rate from AEO.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1988

Kuhn-Tucker optimization based reliability analysis for probabilistic finite elements

The fusion of probability finite element method (PFEM) and reliability analysis for fracture mechanics is considered. Reliability analysis with specific application to fracture mechanics is presented, and computational procedures are discussed. Explicit expressions for the optimization procedure with regard to fracture mechanics are given. The results show the PFEM is a very powerful tool in determining the second-moment statistics. The method can determine the probability of failure or fracture subject to randomness in load, material properties and crack length, orientation, and location.

Liu, W. K.↗
NASA NTRS2014

Challenges in Evaluating Relationships Between Quantitative Data (Carbon Dioxide) and Qualitative Data (Self-Reported Visual Changes)

Understanding the nuances in clinical data is critical in developing a successful data analysis plan. Carbon dioxide (CO2) data are collected on board the International Space Station (ISS) in a continuous stream. Clinical data on ISS are primarily collected via conversations between individual crewmembers and NASA Flight Surgeons during weekly Private Medical Conferences (PMC). Law, et.al, 20141 demonstrated a statistically significant association between weekly average CO2 levels on ISS and self-reported headaches over the reporting period from March 14, 2001 to May 31, 2012. The purpose of this analysis is to describe the evaluation of a possible association between visual changes and CO2 levels on ISS and to discuss challenges in developing an appropriate analysis plan. METHODS & PRELIMINARY RESULTS: A first analysis was conducted following the same study design as the published work on CO2 and self-reported headaches1; substituting self-reported changes in visual acuity in place of self-reported headaches. The analysis demonstrated no statistically significant association between visual impairment characterized by vision symptoms self-reported during PMCs and ISS average CO2 levels over ISS missions. Closer review of the PMC records showed that vision outcomes are not well-documented in terms of clinical severity, timing of onset, or timing of resolution, perhaps due to the incipient nature of vision changes. Vision has been monitored in ISS crewmembers, pre- and post-flight, using standard optometry evaluations. In-flight visual assessments were limited early in the ISS program, primarily consisting of self-perceived changes reported by crewmembers. Recently, on-orbit capabilities have greatly improved. Vision data ranges from self-reported post-flight changes in visual acuity, pre- to postflight changes identified during fundoscopic examination, and in-flight progression measured by advanced on-orbit clinical imaging capabilities at predetermined testing intervals. In contrast, CO2 data are recorded in a continuous stream over time; however, for the initial analysis this data was categorized into weekly averages.

Mendez, C. M.↗