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At least 343 records · Page 19

Timing Noise in SGR 1806-20

We have phase-connected a sequence of Rossi X-Ray Timing Explorer Proportional Counter Array observations of SGR 1806-20 covering 178 days. We find that a simple secular spin-down model does not adequately fit the data. The period derivative varies gradually during the observations between 8.1 x 10(exp -11) and 11.7 x 10(exp -11) s/s (at its highest, approximately 40% larger than the long-term trend), while the average burst rate as seen with the Burst and Transient Source Experiment drops throughout the time interval. The phase residuals give no compelling evidence for periodicity, but more closely resemble timing noise as seen in radio pulsars. The magnitude of the timing noise, however, is large relative to the noise level typically found in radio pulsars (Delta(sub 8) = 4.8; frequency derivative average power approximately 7 x 10(exp -20) sq cycles/cubic s). Combining these results with the noise levels measured for some anomalous X-ray pulsars, we find that all magnetar candidates have Delta(sub 8) values larger than those expected from a simple extrapolation of the correlation found in radio pulsars. We find that the timing noise in SGR 1806-20 is greater than or equal to the levels found in some accreting systems (e.g., Vela X-1, 4U 1538-52, and 4U 1626-67), but the spin-down of SGR 1806-20 has thus far maintained coherence over 6 yr. Alternatively, an orbital model with a period P(sub orb) = 733 days provides a statistically acceptable fit to the data. If the phase residuals are created by Doppler shifts from a gravitationally bound companion, then the allowed parameter space for the mass function (small) and orbital separation (large) rule out the possibility of accretion from the companion sufficient to power the persistent emission from the SGR.

Woods, P. M.↗

Study of Radiographic Linear Indications and Subsequent Microstructural Features in Gas Tungsten Arc Welds of Inconel 718

This study presents examples and considerations for differentiating linear radiographic indications produced by gas tungsten arc welds in a 0.05-in-thick sheet of Inconel 718. A series of welds with different structural features, including the enigma indications and other defect indications such as lack of fusion and penetration, were produced, radiographed, and examined metallographically. The enigma indications were produced by a large columnar grain running along the center of the weld nugget occurring when the weld speed was reduced sufficiently below nominal. Examples of respective indications, including the effect of changing the x-ray source location, are presented as an aid to differentiation. Enigma, nominal, and hot-weld specimens were tensile tested to demonstrate the harmlessness of the enigma indication. Statistical analysis showed that there is no difference between the strengths of these three weld conditions.

Walley, J. L.↗

An Automated Detection Methodology for Dry Well-Mixed Layers

The intense surface heating over arid land surfaces produces dry well-mixed layers (WML) via dry convection. These layers are characterized by nearly constant potential temperature and low, nearly constant water vapor mixing ratio. To further the study of dry WMLs, we created a detection methodology and supporting software to automate the identification and characterization of dry WMLs from multiple data sources including rawinsondes, remote sensing platforms, and model products. The software is a modular code written in Python, an open source language. Radiosondes from a network of synoptic stations in North Africa were used to develop and test the WML detection process. The detection involves an iterative decision tree that ingests a vertical profile from an input data file, performs a quality check for sufficient data density, and then searches upward through the column for successive points where the simultaneous changes in water vapor mixing ratio and potential temperature are less than the specified maxima. If points in the vertical profile meet the dry WML identification criteria, statistics are generated detailing the characteristics of each layer in the profile. At the end of the vertical profile analysis, there is an option to plot analyzed profiles in a variety of file formats. Initial results show that the detection methodology can be successfully applied across a wide variety of input data and North African environments and for all seasons. It is sensitive enough to identify dry WMLs from other types of isentropic phenomena such as subsidence layers and distinguish the current day’s dry WML from previous days.

Stephen D. Nicholls↗

Impact of U-10Mo HALEU fuel element tolerances on the Massachusetts Institute of Technology reactor safety and operational performance – Thermal hydraulics

The U.S. is coordinating efforts for the conversion of six U.S. High Performance Research Reactors (USHPRR) including one critical facility from highly enriched uranium (HEU) to low-enriched uranium (LEU). In order to continue the mission of these reactors, including the Massachusetts of Institute of Technology Reactor (MITR), and achieve similar performance, high-assay low-enriched uranium (HALEU) with a high-density metallic alloy of uranium with 10 wt% molybdenum (U-10Mo) is being evaluated. The impact of the fabrication specification and tolerances was assessed following the preliminary design of the MITR LEU fuel elements using the U-10Mo monolithic alloy. This research focuses on the analysis of fabrication specification impact on thermal hydraulics (TH) characteristic of the MITR LEU core as a function of the variation of the relevant fuel specification parameters (e.g., coolant channel gap thickness, fuel plate thickness, etc.). The analyses are performed based on an all-fresh LEU fuel conversion plan identified in a preliminary safety analysis report submitted to the Nuclear Regulatory Commission. The reactor power margin to the onset of nucleate boiling (ONB) is assessed under the limiting safety system settings (LSSS), where a scram occurs, to ensure there is sufficient margin to the reactor safety limit, which is defined by the onset of flow instability that occurs after the ONB. The best estimate plus uncertainty approach is employed to analyze this TH characteristic, which yields realistic results while maintaining adequate conservatism, utilizing a statistical uncertainty propagation method with the STAT7 code. The TH characteristic is analyzed as a function of the variability of the specification parameters resulting from the fabrication process. The main findings of this study show that the MITR core can meet the TH safety and operational requirements at the all-LEU initial core startup (cycle 1), selected transition cycles (most reactive cycle and most limiting cycle: cycle 3 and 5, respectively) and equilibrium (cycle 14) cores under all limiting fabrication parameter combinations considered. In addition, the analyses show that the dependency of the core power margin to ONB on those specification parameters that have the most direct impact on TH performance is non-linear but monotonically decreasing within the specification tolerances. The third order polynomial fit curves are reported in detail for selected limiting cases and can serve as a powerful tool for future MITR fuel management in cases such as when HALEU supply is established that may allow additional cycle length or other operational benefits.

Conversion↗

Near-canopy horizontal concentration heterogeneity of semivolatile oxygenated organic compounds and implications for 2-methyltetrols primary emissions

Semivolatile oxygenated organic compounds (SV-OVOCs) are important atmospheric species, in particular for the production and chemistry of atmospheric particulate matter and related impacts on air quality and climate. In this study, SV-OVOCs were collected in the horizontal plane of the roughness layer over the tropical forest in the central Amazon during the wet season of 2018. A sampler mounted to a copter-type, hovering unmanned aerial vehicle was used. Underlying the collection region, a plateau forest transitioned into a slope forest across several hundred meters. The concentrations of pinonic and pinic acids, which are monoterpene oxidation products, had no statistical difference over the two forests. By comparison, across the study period, differences in the concentration of 2-methyltetrols, which are products of isoprene oxidation, ranged from -70% to +480% over the two forests. The chemical lifetime of 2-methyltetrols in the atmosphere is sufficiently long that heterogeneity in the isoprene emission rate from the two forests followed by atmospheric oxidation does not explain the concentration heterogeneity of 2-methyltetrols. Standing waves and local meteorology also cannot account for the heterogeneity. Of the possibilities considered, the most plausible explanation is the direct emission from the forest of 2-methyltetrols produced through biological processes within the plants. Under this explanation, the rate of direct SV-OVOC emissions should be modulated by forest type and related environmental stressors. Direct emissions of SV-OVOCs should be more broadly considered for constraining and improving models of atmospheric composition, transport, and chemistry over tropical forests.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Long-Term Climatic Variations in the Almati Oblast in Central Asian Kazakhstan: Correlations between National Centers for Environmental Prediction (NCEP) Reanalysis II Results and Oblast Meteorological Station Data from 1949 to the Present

As part of a larger analysis of country systems described elsewhere, named a Crop Country Inventory, CCI, large variations in annual crop yield for selected climate sensitive agricultural regions or sub-regions within a country have been studied over extended periods in decades. These climate sensitive regions, principally responsible for large annual variations in an entire country s crop production, generally are characterized by distinctive patterns of atmospheric circulation and synoptic processes that result in large seasonal fluctuations in temperature, precipitation and soil moisture as well as other climate properties. The immediate region of interest is drought prone Kazakhstan in Central Asia, part of the Former Soviet Union, FSU. As a partial validation test in a dry southern region of Kazakhstan, the Almati Oblast was chosen. The Almati Oblast, a sub-region of Kazakhstan located in its southeast corner, is one of 14 oblasts within the Republic of Kazahstan. The climate data set used to characterize this region was taken from the results of the current maturely developed Global Climate Model, GCM. In this paper, the GCM results have been compared to the meteorological station data at the station locations, over various periods. If the empirical correlation of the data sets from both the GCM and station data is sufficiently significant, this would validate the use of the superior GCM profile mapping and integration for the climatic characterization of a sub-region. Precipitation values interpolated from NCEP Reanalysis II data, a global climate database spanning over 5 decades since 1949, have been statistically correlated with monthly-averaged station data from 1949 through 1993, and with daily station data from April through August, 1990 for the Almati Oblast in Kazakhstan. The resultant correlation is significant, which implies that the methodology may be extended to different regions globally for Crop Country Inventory studies.

Welker, Jean E.↗

The Impact of Subsampling on MODIS Level-3 Statistics of Cloud Optical Thickness and Effective Radius

The MODIS Level-3 optical thickness and effective radius cloud product is a gridded l deg. x 1 deg. dataset that is derived from aggregation and subsampling at 5 km of 1 km, resolution Level-2 orbital swath data (Level-2 granules). This study examines the impact of the 5 km subsampling on the mean, standard deviation and inhomogeneity parameter statistics of optical thickness and effective radius. The methodology is simple and consists of estimating mean errors for a large collection of Terra and Aqua Level-2 granules by taking the difference of the statistics at the original and subsampled resolutions. It is shown that the Level-3 sampling does not affect the various quantities investigated to the same degree, with second order moments suffering greater subsampling errors, as expected. Mean errors drop dramatically when averages over a sufficient number of regions (e.g., monthly and/or latitudinal averages) are taken, pointing to a dominance of errors that are of random nature. When histograms built from subsampled data with the same binning rules as in the Level-3 dataset are used to reconstruct the quantities of interest, the mean errors do not deteriorate significantly. The results in this paper provide guidance to users of MODIS Level-3 optical thickness and effective radius cloud products on the range of errors due to subsampling they should expect and perhaps account for, in scientific work with this dataset. In general, subsampling errors should not be a serious concern when moderate temporal and/or spatial averaging is performed.

Oreopoulos, Lazaros↗

Does a Relationship Between Arctic Low Clouds and Sea Ice Matter?

Arctic low clouds strongly affect the Arctic surface energy budget. Through this impact Arctic low clouds influence important aspects of the Arctic climate system, namely surface and atmospheric temperature, sea ice extent and thickness, and atmospheric circulation. Arctic clouds are in turn influenced by these elements of the Arctic climate system, and these interactions create the potential for Arctic cloud-climate feedbacks. To further our understanding of potential Arctic cloudclimate feedbacks, the goal of this paper is to quantify the influence of atmospheric state on the surface cloud radiative effect (CRE) and its covariation with sea ice concentration (SIC). We build on previous research using instantaneous, active remote sensing satellite footprint data from the NASA A-Train. First, the results indicate significant differences in the surface CRE when stratified by atmospheric state. Second, there is a weak covariation between CRE and SIC for most atmospheric conditions. Third, the results show statistically significant differences in the average surface CRE under different SIC values in fall indicating a 3-5 W m(exp -2) larger LW CRE in 0% versus 100% SIC footprints. Because systematic changes on the order of 1 W m(exp -2) are sufficient to explain the observed long-term reductions in sea ice extent, our results indicate a potentially significant amplifying sea ice-cloud feedback, under certain meteorological conditions, that could delay the fall freeze-up and influence the variability in sea ice extent and volume. Lastly, a small change in the frequency of occurrence of atmosphere states may yield a larger Arctic cloud feedback than any cloud response to sea ice.

Taylor, Patrick C.↗

Robust verification of stochastic simulation codes

We introduce a robust verification tool for computational codes, which we call Stochastic Robust Extrapolation based Error Quantification (StREEQ). Unlike the prevalent Grid Convergence Index (GCI) [1] method, our approach is suitable for both stochastic and deterministic computational codes and is generalizable to any number of discretization variables. Building on ideas introduced in the Robust Verification [2] approach, we estimate the converged solution and orders of convergence with uncertainty using multiple fits of a discretization error model. In contrast to Robust Verification, we perform these fits to many bootstrap samples yielding a larger set of predictions with smoother statistics. Here, bootstrap resampling is performed on the lack-of-fit errors for deterministic code responses, and directly on the noisy data set for stochastic responses. This approach lends a degree of robustness to the overall results, capable of yielding precise verification results for sufficiently resolved data sets, and appropriately expanding the uncertainty when the data set does not support a precise result. For stochastic responses, a credibility assessment is also performed to give the analyst an indication of the trustworthiness of the results. Furthermore, this approach is suitable for both code and solution verification, and is particularly useful for solution verification of high-consequence simulations..

97 MATHEMATICS AND COMPUTING↗

Project Dinos I: A joint lensing–dynamics constraint on the deviation from the power law in the mass profile of massive ellipticals

The mass distribution in massive elliptical galaxies encodes their evolutionary history, thus providing an avenue to constrain the baryonic astrophysics in their evolution. The power-law assumption for the radial mass profile in ellipticals has been sufficient to describe several observables to the noise level, including strong lensing and stellar dynamics. In this paper, we quantitatively constrained any deviation, or the lack thereof, from the power-law mass profile in massive ellipticals through joint lensing–dynamics analysis of a large statistical sample with 77 galaxy–galaxy lens systems. We performed an improved and uniform lens modelling of these systems from archival Hubble Space Telescope imaging using the automated lens modelling pipeline dolphin. We combined the lens model posteriors with the stellar dynamics to constrain the deviation from the power law after accounting for the line-of-sight lensing effects, a first for analyses on galaxy–galaxy lenses. We find that the Sloan Lens ACS Survey lens galaxies with a mean redshift of 0.2 are consistent with the power-law profile within 1.1σ (2.8σ) and the Strong Lensing Legacy Survey lens galaxies with a mean redshift of 0.6 are consistent within 0.8σ (2.1σ), for a spatially constant (Osipkov–Merritt) stellar anisotropy profile. We adopted the spatially constant anisotropy profile as our baseline choice based on previous dynamical observables of local ellipticals. However, spatially resolved stellar kinematics of lens galaxies are necessary to differentiate between the two anisotropy models. Future studies will use our lens models to constrain the mass distribution individually in the dark matter and baryonic components.

79 ASTRONOMY AND ASTROPHYSICS↗

Atmospheric condition identification in multivariate data through a metric for total variation

Identification of atmospheric conditions within a multivariable atmospheric data set is a necessary step in the validation of emerging and existing high-fidelity models used to simulate wind plant flows and operation.Atmospheric conditions relevant for wind energy research include stationary conditions, given the need for well-converged statistics for model validation, as well as conditions observed less frequently, such as extreme atmospheric events, which are used in wind turbine and wind plant design.Aggregation of observations without regard to covariance between time series discounts the dynamical nature of the atmosphere and is not sufficiently representative of atmospheric conditions.Identification and characterization of continuous time periods with atmospheric conditions that have a high value for analysis or simulation set the stage for more advanced model validation and the development of real-time control and operational strategies.The current work explores a single metric for variation in a multivariate data sample that quantifies variability within each channel as well as covariance between channels.The total variation is used to identify conditions of interest that conform to desired objective functions, such as stationary conditions, ramps or waves of wind speed, and changes in wind direction.Total variation is somewhat sensitive to the presence of outliers in the input data, and the method is best complemented by quality-control procedures to ensure reliable results.The direct detection and classification of events or conditions of interest within atmospheric data sets is vital to developing our understanding of wind plant response and to the formulation of forecasting and control models.

17 WIND ENERGY↗

Upward Flammability Testing: A Probabilistic Measurement

Examination of NASA-STD-6001 Test 1 data suggests burn length outcome for a given environment has a large statistical variation from run to run. Large data sets show that burn length data form cumulative probability distribution curves, which describe a material's characteristic to burn in a specific environment, suggesting that the current practice of testing three samples at specific conditions is inadequate. Sufficient testing can establish material characteristics probability curves to provide the probability that a material will sustain a burn length of at least 15.24 cm (6.0 in.) or will sustain burning until all material is consumed. A simple pasdfail criterion may not be possible or practical. Future application of flammability data for some material classes may require the engineer to assess risk based on the probability of an occurrence and the probable outcome with different materials as characterized with cumulative burn length distributions for specific use conditions.

Davis, Samuel E.↗

Unraveling the implications of finite specimen size on the interpretation of dynamic experiments for polycrystalline aluminum through direct numerical simulations

Normal and Pressure-shear plate impact (NPI and PSPI) experiments are popular experimental techniques for studying the mean-field macroscopic behavior of polycrystalline metals under high-rate dynamic loading. However, since both configurations rely upon geometry for subjecting the specimen to high strain rates, these experiments often involve a limited specimen size. Moreover, because of the inherent heterogeneities present within polycrystalline metals, it is difficult to ascertain if the size of the specimen and/or regions where measurements are made are sufficiently large for making representative inferences about the mean-field macroscopic properties from single-point velocity measurements. In the present study, we quantify the expected measurement variability on observable point measurements in NPI and PSPI experiments by carrying out direct numerical simulations (DNS) of statistically representative polycrystalline microstructures subjected to dynamic compression and compression-shear loading. In particular, we consider the role of specific material heterogeneities (e.g. the grain-to-grain difference in size, crystallographic orientation) on dispersion in the normal and transverse particle velocity records and on local fluctuations in key state variables (e.g. velocity, accumulated plastic strain) by incorporating these effects directly into a representative synthetic microstructure geometry and crystalline description of pure polycrystalline aluminum. The form of the present study is a large parametric investigation, consisting of ten ensembles of one hundred simulations. Each of the thousand simulations reflects a randomly realized synthetic microstructure in one of five cases of decreasing average grain size for the two loading configurations. Our analysis of the DNS results demonstrates that for both of these experimental configurations, the grain size directly correlates with the coefficient of variation (CV) in simulated point measurements, showing a convergent decrease in CV to zero (i.e. particle velocity record approaches the mean-field value) with decreasing grain size. Remarkably, the magnitude of variations in the particle velocity record is shown to be largest where the deviatoric stresses are most significant. In the case of NPI, this occurs at the elastic and plastic wavefront, whereas, in the case of PSPI, the magnitude of fluctuations are approximately constant throughout the experimental window time. The reasoning for the scatter in particle velocity due to the heterogeneous microstructure is demonstrated to be dependent on the mechanisms for accommodating deformation and on the interaction of reflection waves generated at sites of heterogeneities occurring at the scale of grains. Lastly, we develop a power-law description for the magnitude of scattering versus characteristic length, which provides a statistical framework for assessing the required number of grains per characteristic specimen dimension for minimizing scatter within these two experimental configurations (NPI, PSPI).

36 MATERIALS SCIENCE↗

Optimization of pre-commercial enzyme dosage for a potential lignocellulosic biorefinery

Lignocellulolytic enzymes remain one of the primary cost constraints in second-generation (2G) ethanol biorefineries. Achieving efficient hydrolysis of structural carbohydrates with minimal enzyme dosage, maintaining slurry fermentability for industrially relevant ethanol titers, and maximizing ethanol yield per ton of biomass are among the major challenges in 2G processes. In this study, we optimized the dosages of pre-commercial cellulase (NS22257) and hemicellulase (NS22244) on pilot-scale, hydrothermally pretreated lignocellulosic substrates. Enzyme dosages were evaluated at three levels: 20 mg of cellulase with 7.25 mg of hemicellulase (ED-1), 40 mg with 14.5 mg (ED-2), and 60 mg with 21.75 mg (ED-3). As expected, the highest sugar yields were obtained with ED-3; however, for sweet sorghum, oilcane, and miscanthus, sugar yields from ED-2 and ED-3 were not significantly different ( p < 0.05). For example, sweet sorghum produced 123.78 ± 1.54 g L −1 and 125.76 ± 0.46 g L −1 of total sugars (glucose and xylose) with ED-2 and ED-3, respectively. Although energycane exhibited a statistically significant difference between ED-2 and ED-3, the incremental gain with ED-3 was modest, increasing sugar release by only 9.02 g L −1 relative to ED-2. Importantly, ED-1 resulted in sugar yields of 88.88 ± 3.64 to 106.86 ± 1.21 g L −1 , sufficient to achieve ethanol titers ≥40 g L −1 , the threshold required for industrial relevance. A semi-integrated bioprocess validated this outcome, producing 42.09 ± 2.38 g L −1 ethanol and an estimated yield of 213.38 L of ethanol per dry ton of pretreated biomass, requiring only 20.83 L of cellulase and 6.25 L of hemicellulase per ton. Remarkably, these enzyme dosages were approximately tenfold lower than those reported in prior studies.

Deshavath, Narendra Naik [Univ. of Illinois at Urb↗

Statistical analysis of non-Maxwellian electron distribution functions measured with angularly resolved Thomson scattering

Angularly resolved Thomson scattering is a novel extension of Thomson scattering, enabling the measurement of the electron velocity distribution function over many orders of magnitude. Here, details of the theoretical basis of the technique and the instrument designed for this measurement are described. Angularly resolved Thomson-scattering data from several experiments are shown with descriptions of the corresponding distribution functions. A reduced model describing the distribution function is given and used to perform a Monte Carlo analysis of the uncertainty in the measurements. The electron density and temperature were determined to a precision of 12% and 21%, respectively, on average, while all other parameters defining the distribution function were generally determined to better than 20%. It was found that these uncertainties were primarily due to limited signal to noise and instrumental effects. Furthermore, measurements with this level of precision were sufficient to distinguish between Maxwellian and non-Maxwellian distribution functions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effect of five lubricants on life of AISI 9310 spur gears

Spur-gear surface fatigue tests were conducted with five lubricants using a single lot of consumable-electrode vacuum melted (CVM) AISI 9310 spur gears. The lot of gears was divided into five groups, each of which was tested with a different lubricant. The test lubricants are classified as either a synthetic hydrocarbon, mineral oil, or ester-based lubricant. All five lubricants have imilar viscosity and pressure-viscosity coefficients. A pentaerythritol base stock without sufficient antiwear additives produced a surface fatigue life pproximately 22 percent that of the same base stock with chlorine and phosphorus type additives. The presence of sulfur type antiwear additives in the lubricant did not appear to affect the surface fatigue life of the gears tested. No statistical difference in the 10-percent surface fatigue life was produced with four of the five lubricants.

Townsend, D. P.↗

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 pilot flying an airplane; in this case, activities with distinct visual signatures might be things like communicating, navigating, monitoring, etc. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. We compare, not individual fixations, but groups of fixations aggregated over a fixed time interval (Tau). We assume that the environment has been divided into a finite set of discrete areas-of-interest (AOIs). For a given time interval, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector, where N is the number of AOIs. These proportions can be converted to integer counts by multiplying by Tau divided by the average fixation duration, a parameter that we fix at 283 milliseconds. We compare different intervals by computing the chi-squared 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. We cluster the intervals, first by merging adjacent intervals that are sufficiently similar, optionally shifting the boundary between non-merged intervals to maximize the difference. Then we compare and cluster non-adjacent intervals. The method is evaluated using synthetic data generated by a hand-crafted set of activities. While the method generally finds more activities than put into the simulation, we have obtained agreement as high as 80 percent between the inferred activity labels and ground truth.

Eye Movements↗

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↗