Search NASA⌕ Search

SEARCH · Search NASA

Results for “Statistical sampling techniques”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3

Light beams and radiation patterns in random media

The purpose of this paper is to apply a numerical technique in solving problems involving light beams in a random medium. The technique starts by generating numerically sample media with prescribed statistical properties. Rays are then traced in these sample media, and the ray statistics are compiled. These statistics are utilized to find the mean square displacement and distribution of a beam. Problems on beam broadening and distortion of radiation patterns are considered. Fluctuations in wave amplitude and phase are also investigated. When possible, the numerical results are compared with the analytical results and experimental results.

Youakim, M. Y.↗

Maximizing Macromolecule Crystal Size for Neutron Diffraction Experiments

A challenge in neutron diffraction experiments is growing large (greater than 1 cu mm) macromolecule crystals. In taking up this challenge we have used statistical experiment design techniques to quickly identify crystallization conditions under which the largest crystals grow. These techniques provide the maximum information for minimal experimental effort, allowing optimal screening of crystallization variables in a simple experimental matrix, using the minimum amount of sample. Analysis of the results quickly tells the investigator what conditions are the most important for the crystallization. These can then be used to maximize the crystallization results in terms of reducing crystal numbers and providing large crystals of suitable habit. We have used these techniques to grow large crystals of Glucose isomerase. Glucose isomerase is an industrial enzyme used extensively in the food industry for the conversion of glucose to fructose. The aim of this study is the elucidation of the enzymatic mechanism at the molecular level. The accurate determination of hydrogen positions, which is critical for this, is a requirement that neutron diffraction is uniquely suited for. Preliminary neutron diffraction experiments with these crystals conducted at the Institute Laue-Langevin (Grenoble, France) reveal diffraction to beyond 2.5 angstrom. Macromolecular crystal growth is a process involving many parameters, and statistical experimental design is naturally suited to this field. These techniques are sample independent and provide an experimental strategy to maximize crystal volume and habit for neutron diffraction studies.

Judge, R. A.↗

Statistical evaluation of vibration analysis techniques

An evaluation methodology is presented for a selection of candidate vibration analysis techniques applicable to machinery representative of the environmental control and life support system of advanced spacecraft; illustrative results are given. Attention is given to the statistical analysis of small sample experiments, the quantification of detection performance for diverse techniques through the computation of probability of detection versus probability of false alarm, and the quantification of diagnostic performance.

Milner, G. Martin↗

A Monte Carlo investigation of thrust imbalance of solid rocket motor pairs

A technique is described for theoretical, statistical evaluation of the thrust imbalance of pairs of solid-propellant rocket motors (SRMs) firing in parallel. Sets of the significant variables, determined as a part of the research, are selected using a random sampling technique and the imbalance calculated for a large number of motor pairs. The performance model is upgraded to include the effects of statistical variations in the ovality and alignment of the motor case and mandrel. Effects of cross-correlations of variables are minimized by selecting for the most part completely independent input variables, over forty in number. The imbalance is evaluated in terms of six time - varying parameters as well as eleven single valued ones which themselves are subject to statistical analysis. A sample study of the thrust imbalance of 50 pairs of 146 in. dia. SRMs of the type to be used on the space shuttle is presented. The FORTRAN IV computer program of the analysis and complete instructions for its use are included. Performance computation time for one pair of SRMs is approximately 35 seconds on the IBM 370/155 using the FORTRAN H compiler.

Sforzini, R. H.↗

Monte Carlo techniques for solving transport problems

The Monte Carlo procedure is a model sampling technique. A model is established, and the behavior of sample units in this model is followed. A sufficient number of sample units are followed to obtain a statistical average or macroscopic quantities, which are the quantities of interest. This technique was used in crude form by Fermi in connection with the building of the first atomic pile. Later, Von Neumann and Ulam developed and used the Monte Carlo procedure extensively in developing the atomic bomb. Since then this technique has gained considerable use in nuclear reactor problems (refs. 1 and 2), and we at the Lewis Research Center have been extending it to thermal radiation (refs. 3 and 4), rarefied gas flows, and plasma flow problems (ref. 5). This technique, which requires a large number of sample histories to obtain solutions with small variances, is receiving greater use because of the development of the high-speed electronic computers.

SAMPLED DATA SYSTEM↗

New AFM Techniques for Investigating Molecular Growth Mechanisms of Protein Crystals

Atomic Force Microscopy (AFM) has emerged as a powerful technique for investigating protein crystal growth. Earlier AFM studies were among the first to demonstrate that these crystals grew by dislocation and 2D nucleation growth mechanisms [1]. These investigations were restricted to the micron range where only surface features, such as dislocation hillocks and 2D islands are visible. Most AFM instruments can scan at higher resolutions and have the potential to resolve individual protein molecules at nanometer ranges. Such scans are essential for determining the molecular packing arrangements on crystal faces and for probing the growth process at the molecular level. However, at this resolution the AFM tip influences the image produced, with the resulting image being a convolution of the tip shape and the surface morphology [2]. In most studies this problem is resolved by deconvoluting the image to obtain the true surface morphology. Although deconvolution routines work reasonably well for simple one- dimensional shapes, for complex surfaces this approach does not produce accurate results. In this study we devised a new approach which takes advantage of the precise molecular order of crystal surfaces, combined with the knowledge of individual molecular shapes from the crystallographic data of the protein and the AFM tip shape. This information is used to construct expected theoretical AFM images by convoluting the tip shape with the constructed crystal surface shape for a given surface packing arrangement. By comparing the images from actual AFM scans with the constructed ones for different possible surface packing arrangements, the correct packing arrangement can be conclusively determined. This approach was used in this study to determine the correct one from two possible packing arrangements on (I 10) faces of tetragonal lysozyme crystals. Another novel AFM technique was also devised to measure the dimension of individual growth units of the crystal faces. Measuring these units was not attempted before and most studies have assumed that the growth unit consisted of individual protein molecules. The linescan mode of AFM instruments allows the crystal surface to be scanned along a single line. By scanning across a growth step an image showing the motion of the step is obtained. Normally such an image shows a straight line for continuous and constant step velocity. In this study by increasing the scan rate and by decreasing the step velocity (by decreasing the supersaturation), we were able to capture images of individual growth events, shown by jump discontinuities in the step line. By suitable integration of the image the growth unit dimension in the scanned direction can be obtained. Since multiple units can be involved in the growth process it is necessary to collect a statistically relevant sample before drawing conclusions about the growth mechanism. This technique was successfully employed to obtain the dimensions of growth units for the (110) face, showing that they consisted of various aggregates corresponding to the 43 helices in the crystal structure.

Li, Huayu↗

Extensions of the space trajectories error analysis programs

A generalized covariance analysis technique which permits the study of the sensitivity of linear estimation algorithms to errors in a priori statistics has been developed and programed. Several sample cases are presented to illustrate the use of this technique. Modifications to the Simulated Trajectories Error Analysis Program (STEAP) to enable targeting a multiprobe mission of the Planetary Explorer type are discussed. The logic for the mini-probe targeting is presented. Finally, the initial phases of the conversion of the Viking mission Lander Trajectory Reconstruction (LTR) program for use on Venus missions is discussed. An integrator instability problem is discussed and a solution proposed.

Adams, G. L.↗

The Integrated Medical Model: Statistical Forecasting of Risks to Crew Health and Mission Success

The Integrated Medical Model (IMM) helps capture and use organizational knowledge across the space medicine, training, operations, engineering, and research domains. The IMM uses this domain knowledge in the context of a mission and crew profile to forecast crew health and mission success risks. The IMM is most helpful in comparing the risk of two or more mission profiles, not as a tool for predicting absolute risk. The process of building the IMM adheres to Probability Risk Assessment (PRA) techniques described in NASA Procedural Requirement (NPR) 8705.5, and uses current evidence-based information to establish a defensible position for making decisions that help ensure crew health and mission success. The IMM quantitatively describes the following input parameters: 1) medical conditions and likelihood, 2) mission duration, 3) vehicle environment, 4) crew attributes (e.g. age, sex), 5) crew activities (e.g. EVA's, Lunar excursions), 6) diagnosis and treatment protocols (e.g. medical equipment, consumables pharmaceuticals), and 7) Crew Medical Officer (CMO) training effectiveness. It is worth reiterating that the IMM uses the data sets above as inputs. Many other risk management efforts stop at determining only likelihood. The IMM is unique in that it models not only likelihood, but risk mitigations, as well as subsequent clinical outcomes based on those mitigations. Once the mathematical relationships among the above parameters are established, the IMM uses a Monte Carlo simulation technique (a random sampling of the inputs as described by their statistical distribution) to determine the probable outcomes. Because the IMM is a stochastic model (i.e. the input parameters are represented by various statistical distributions depending on the data type), when the mission is simulated 10-50,000 times with a given set of medical capabilities (risk mitigations), a prediction of the most probable outcomes can be generated. For each mission, the IMM tracks which conditions occurred and decrements the pharmaceuticals and supplies required to diagnose and treat these medical conditions. If supplies are depleted, then the medical condition goes untreated, and crew and mission risk increase. The IMM currently models approximately 30 medical conditions. By the end of FY2008, the IMM will be modeling over 100 medical conditions, approximately 60 of which have been recorded to have occurred during short and long space missions.

Fitts, M. A.↗

Preliminary design of an Earth-based debris detection system using current technology and existing installations

Assessment of debris hazard requires the determination of debris down to mm sizes for near-Earth orbits and near-stationary points. It is necessary to obtain reasonable orbits for a statistically significant sample of the debris population. Several ground-based techniques for detection are available. Radar detection was used to obtain information of existing debris population. Another technique is optical detection. The possibilities and application of optical detection with state-of-the-art instrumentation is studied.

Morgan, T. H.↗

Shuttle Hypervelocity Impact Database

With three missions outstanding, the Shuttle Hypervelocity Impact Database has nearly 3000 entries. The data is divided into tables for crew module windows, payload bay door radiators and thermal protection system regions, with window impacts compromising just over half the records. In general, the database provides dimensions of hypervelocity impact damage, a component level location (i.e., window number or radiator panel number) and the orbiter mission when the impact occurred. Additional detail on the type of particle that produced the damage site is provided when sampling data and definitive analysis results are available. Details and insights on the contents of the database including examples of descriptive statistics will be provided. Post flight impact damage inspection and sampling techniques that were employed during the different observation campaigns will also be discussed. Potential enhancements to the database structure and availability of the data for other researchers will be addressed in the Future Work section. A related database of returned surfaces from the International Space Station will also be introduced.

Hyde, James L.↗

Multiple-Beam Detection of Fast Transient Radio Sources

A method has been designed for using multiple independent stations to discriminate fast transient radio sources from local anomalies, such as antenna noise or radio frequency interference (RFI). This can improve the sensitivity of incoherent detection for geographically separated stations such as the very long baseline array (VLBA), the future square kilometer array (SKA), or any other coincident observations by multiple separated receivers. The transients are short, broadband pulses of radio energy, often just a few milliseconds long, emitted by a variety of exotic astronomical phenomena. They generally represent rare, high-energy events making them of great scientific value. For RFI-robust adaptive detection of transients, using multiple stations, a family of algorithms has been developed. The technique exploits the fact that the separated stations constitute statistically independent samples of the target. This can be used to adaptively ignore RFI events for superior sensitivity. If the antenna signals are independent and identically distributed (IID), then RFI events are simply outlier data points that can be removed through robust estimation such as a trimmed or Winsorized estimator. The alternative "trimmed" estimator is considered, which excises the strongest n signals from the list of short-beamed intensities. Because local RFI is independent at each antenna, this interference is unlikely to occur at many antennas on the same step. Trimming the strongest signals provides robustness to RFI that can theoretically outperform even the detection performance of the same number of antennas at a single site. This algorithm requires sorting the signals at each time step and dispersion measure, an operation that is computationally tractable for existing array sizes. An alternative uses the various stations to form an ensemble estimate of the conditional density function (CDF) evaluated at each time step. Both methods outperform standard detection strategies on a test sequence of VLBA data, and both are efficient enough for deployment in real-time, online transient detection applications.

Thompson, David R.↗

Graph Neural Networks for Parameterized Quantum Circuits Expressibility Estimation (Rev.1)

Parameterized quantum circuits (PQCs) are fundamental to quantum machine learning (QML), quantum optimization, and variational quantum algorithms (VQAs). The expressibility of PQCs is a measure that determines their capability to harness the full potential of the quantum state space. It is thus a crucial guidepost to know when selecting a particular PQC ansatz. However, the existing technique for expressibility computation through statistical estimation requires a large number of samples, which poses significant challenges due to time and computational resource constraints. This paper introduces a novel approach for expressibility estimation of PQCs using Graph Neural Networks (GNNs). We demonstrate the predictive power of our GNN model with a dataset consisting of 25,000 samples from the noiseless IBM QASM Simulator and 12,000 samples from three distinct noisy quantum backends. The model accurately estimates expressibility, with root mean square errors (RMSE) of 0.05 and 0.06 for the noiseless and noisy backends, respectively. We compare our model’s predictions with reference circuits from Sim et al. and IBM Qiskit’s hardwareefficient ansatz sets to further evaluate our model’s performance. Our experimental evaluation in noiseless and noisy scenarios reveals a close alignment with ground truth expressibility values, highlighting the model’s efficacy. Moreover, our model exhibits promising extrapolation capabilities, predicting expressibility values with low RMSE for out-of-range qubit circuits trained solely on only up to 5-qubit circuit sets. This work thus provides a reliable means of efficiently evaluating the expressibility of diverse PQCs on noiseless simulators and hardware.

97 MATHEMATICS AND COMPUTING↗

Characterizing the Uncertainty of Measurement of Traceable Isotope Ratios with Bayesian Statistical Techniques

Analytical techniques such as multicollector—inductively coupled plasma—mass spectrometry (MC-ICP-MS) are routinely employed at SRNL, other National Laboratories, and in academia to determine the precise isotopic composition of diverse natural and anthropogenic samples (e.g., rocks and nuclear materials). Quantifying and reporting uncertainty in such analyses, while regularly performed, have a rigorous statistical foundation. The Guide to the Expression of Uncertainty in Measurement 4 (GUM) outlines conventional techniques used to assess such uncertainty. As the accessibility and speed of statistical computing increase, there is a need to modernize conventional techniques. For example, Supplement 1 to the 3rd to the GUM suggests the use of approximation methods as an updated approach to the GUM.

McLarty, Ellis C.↗

Reduction of flow-measurement uncertainties in laser velocimeters with nonorthogonal channels

An analysis of certain geometrical limitations inherent in the application of laser velocimeters with nonorthogonal channels has led to the development of advanced-LDA-calibration and data-acquisition techniques that minimize systematic and statistical errors, respectively. The data-acquisition technique optimizes the number of velocity samples collected from three velocimeter channels as a function of local turbulence intensity, vector direction, and prescribed confidence interval. Linear velocity surveys and streamline traces measured in a turbulent flow field with a three-dimensional laser velocimeter are presented and the validity and accuracy of the theoretical analysis are discussed.

Snyder, P. K.↗

A deep x-ray survey of the Pleiades cluster and the B6-A3 main sequence stars in Orion

We have obtained deep ROSAT images of three regions within the Pleiades open cluster. We have detected 317 X-ray sources in these ROSAT PSPC images, 171 of which we associate with certain probable members of the Pleiades cluster. We detect nearly all Pleiades members with spectral types later than G0 and within 25 arcminutes of our three field centers where our sensitivity is highest. This has allowed us to derive for the first time the luminosity function for the G, K, and M dwarfs of an open cluster without the need to use statistical techniques to account for the presence of upper limits in the data sample. Because of our high X-ray detection frequency down to the faint limit of the optical catalog, we suspect that some of our unidentified X-ray sources are previously unknown, very low-mass members of the Pleiades. A large fraction of the Pleiades members detected with ROSAT have published rotational velocities. Plots of L(sub x)/L(sub bol) versus spectroscopic rotational velocity show tightly correlated 'saturation' type relations for stars with (B - V)(sub O) greater than 0.60. For each of several color ranges, X-ray luminosities rise rapidly with increasing rotation rate until v sin i approximately equals 15 km/s, and then remain essentially flat for rotation rates up to at least v sin i approximately equal to 100 km/s. The dispersion in rotation among low-mass stars in the Pleiades is by far the dominant contributor to the dispersion in L(subx) at a given mass. Only about 35 percent of the B.A. and early F stars in the Pleiades are detected as X-ray sources in our survey. There is no correlation between X-ray flux and rotation for these stars. The X-ray luminosity function for the early-type Pleiades stars appears to be bimodal, with only a few exceptions. We either detect these stars at fluxes in the range found for low-mass stars or we derive X-ray limits below the level found for most Pleiades dwarfs. The X-ray spectra for the early-type Pleiades stars detected by ROSAT are indistinguishable from the spectra of the low-mass Pleiades members. We believe that the simple explanation for this behavior is that the early-type Pleiades stars are not themselves intrinsic X-ray sources and that the X-ray sources and that the X-ray emission actually arises from low-mass companions to these stars.

Caillault, Jean-Pierre↗

A deep imaging survey of the Pleiades with ROSAT

We have obtained deep ROSAT images of three regions within the Pleiades open cluster. We have detected 317 X-ray sources in these ROSAT Position Sensitive Proportional Counter (PSPC) images, 171 of which we associate with certain or probable members of the Pleiades cluster. We detect nearly all Pleiades members with spectral types later than G0 and within 25 arcminutes of our three field centers where our sensitivity is highest. This has allowed us to derive for the first time the luminosity function for the G, K, amd M dwarfs of an open cluster without the need to use statistical techniques to account for the presence of upper limits in the data sample. Because of our high X-ray detection frequency down to the faint limit of the optical catalog, we suspect that some of our unidentified X-ray sources are previously unknown, very low-mass members of Pleiades. A large fraction of the Pleiades members detected with ROSAT have published rotational velocities. Plots of L(sub X)/L(sub Bol) versus spectroscopic rotational velocity show tightly correlated `saturation' type relations for stars with ((B - V)(sub 0)) greater than or equal to 0.60. For each of several color ranges, X-ray luminosities rise rapidly with increasing rotation rate until c sin i approximately equal to 15 km/sec, and then remains essentially flat for rotation rates up to at least v sin i approximately equal to 100 km/sec. The dispersion in rotation among low-mass stars in the Pleiades is by far the dominant contributor to the dispersion in L(sub X) at a given mass. Only about 35% of the B, A, and early F stars in the Pleiades are detected as X-ray sources in our survey. There is no correlation between X-ray flux and rotation for these stars. The X-ray luminosity function for the early-type Pleiades stars appears to be bimodal -- with only a few exceptions, we either detect these stars at fluxes in the range found for low-mass stars or we derive X-ray limits below the level found for most Pleiades dwarfs. The X-ray spectra for the early-type Pleiades stars detected by ROSAT are indistinguishable from the spectra of the low-mass Pleiades members. We believe that the simplest explanation for this behavior is that the early-type Pleiades stars are not themselves intrinsic X-ray sources and that the X-ray emission actually arises from low-mass companions to these stars.

Stauffer, J. R.↗

Analyzing and Predicting Effort Associated with Finding and Fixing Software Faults

Context: Software developers spend a significant amount of time fixing faults. However, not many papers have addressed the actual effort needed to fix software faults. Objective: The objective of this paper is twofold: (1) analysis of the effort needed to fix software faults and how it was affected by several factors and (2) prediction of the level of fix implementation effort based on the information provided in software change requests. Method: The work is based on data related to 1200 failures, extracted from the change tracking system of a large NASA mission. The analysis includes descriptive and inferential statistics. Predictions are made using three supervised machine learning algorithms and three sampling techniques aimed at addressing the imbalanced data problem. Results: Our results show that (1) 83% of the total fix implementation effort was associated with only 20% of failures. (2) Both safety critical failures and post-release failures required three times more effort to fix compared to non-critical and pre-release counterparts, respectively. (3) Failures with fixes spread across multiple components or across multiple types of software artifacts required more effort. The spread across artifacts was more costly than spread across components. (4) Surprisingly, some types of faults associated with later life-cycle activities did not require significant effort. (5) The level of fix implementation effort was predicted with 73% overall accuracy using the original, imbalanced data. Using oversampling techniques improved the overall accuracy up to 77%. More importantly, oversampling significantly improved the prediction of the high level effort, from 31% to around 85%. Conclusions: This paper shows the importance of tying software failures to changes made to fix all associated faults, in one or more software components and/or in one or more software artifacts, and the benefit of studying how the spread of faults and other factors affect the fix implementation effort.

software fix implementation effort↗

A statistical technique for determining rainfall over land employing Nimbus-6 ESMR measurements

Statistical analysis is performed by first sampling three categories of Nimbus 6 ESMR brightness temperatures (representing rain over land, wet land surfaces without rain, and dry land surfaces), then testing these populations for uniqueness. A classification algorithm to delineate rain over land is developed. It is found that synoptic-scale rainfall over land, where surface thermodynamic temperatures are greater than 5 C and the vegetation is bereft of dew, can indeed be delineated despite the large ESMR-6 instantaneous field of view. However, some ambiguity exists in distinguishing between rainfall areas and wet land surfaces.

Rodgers, E.↗