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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Constructing Space-Time Views from Fixed Size Statistical Data: Getting the Best of Both Worlds

Many performance monitoring tools are currently available to the super-computing community. The performance data gathered and analyzed by these tools fall under two categories: statistics and event traces. Statistical data is much more compact but lacks the probative power event traces offer. Event traces, on the other hand, can easily fill up the entire file system during execution such that the instrumented execution may have to be terminated half way through. In this paper, we propose an innovative methodology for performance data gathering and representation that offers a middle ground. The user can trade-off tracing overhead, trace data size vs. data quality incrementally. In other words, the user will be able to limit the amount of trace collected and, at the same time, carry out some of the analysis event traces offer using spacetime views for the entire execution. Two basic ideas are employed: the use of averages to replace recording data for each instance and "formulae" to represent sequences associated with communication and control flow. With the help of a few simple examples, we illustrate the use of these techniques in performance tuning and compare the quality of the traces we collected vs. event traces. We found that the trace files thus obtained are, in deed, small, bounded and predictable before program execution and that the quality of the space time views generated from these statistical data are excellent. Furthermore, experimental results showed that the formulae proposed were able to capture 100% of all the sequences associated with 11 of the 15 applications tested. The performance of the formulae can be incrementally improved by allocating more memory at run-time to learn longer sequences.

Schmidt, Melisa↗
NASA NTRS1997

Constructing Space-Time Views from Fixed Size Statistical Data: Getting the Best of both Worlds

Many performance monitoring tools are currently available to the super-computing community. The performance data gathered and analyzed by these tools fall under two categories: statistics and event traces. Statistical data is much more compact but lacks the probative power event traces offer. Event traces, on the other hand, can easily fill up the entire file system during execution such that the instrumented execution may have to be terminated half way through. In this paper, we propose an innovative methodology for performance data gathering and representation that offers a middle ground. The user can trade-off tracing overhead, trace data size vs. data quality incrementally. In other words, the user will be able to limit the amount of trace collected and, at the same time, carry out some of the analysis event traces offer using space-time views for the entire execution. Two basic ideas arc employed: the use of averages to replace recording data for each instance and formulae to represent sequences associated with communication and control flow. With the help of a few simple examples, we illustrate the use of these techniques in performance tuning and compare the quality of the traces we collected vs. event traces. We found that the trace files thus obtained are, in deed, small, bounded and predictable before program execution and that the quality of the space time views generated from these statistical data are excellent. Furthermore, experimental results showed that the formulae proposed were able to capture 100% of all the sequences associated with 11 of the 15 applications tested. The performance of the formulae can be incrementally improved by allocating more memory at run-time to learn longer sequences.

Schmidt, Melisa↗
NASA NTRS2010

Roles of Engineering Correlations in Hypersonic Entry Boundary Layer Transition Prediction

Efforts to design and operate hypersonic entry vehicles are constrained by many considerations that involve all aspects of an entry vehicle system. One of the more significant physical phenomenon that affect entry trajectory and thermal protection system design is the occurrence of boundary layer transition from a laminar to turbulent state. During the Space Shuttle Return To Flight activity following the loss of Columbia and her crew of seven, NASA's entry aerothermodynamics community implemented an engineering correlation based framework for the prediction of boundary layer transition on the Orbiter. The methodology for this implementation relies upon the framework of correlation techniques that have been in use for several decades. What makes the Orbiter boundary layer transition correlation implementation unique is that a statistically significant data set was acquired in multiple ground test facilities, flight data exists to assist in establishing a better correlation and the framework was founded upon state of the art chemical nonequilibrium Navier Stokes flow field simulations. The basic tenets that guided the formulation and implementation of the Orbiter Return To Flight boundary layer transition prediction capability will be reviewed as a recommended format for future empirical correlation efforts. The validity of this approach has since been demonstrated by very favorable comparison of recent entry flight testing performed with the Orbiter Discovery, which will be graphically summarized. These flight data can provide a means to validate discrete protuberance engineering correlation approaches as well as high fidelity prediction methods to higher confidence. The results of these Orbiter engineering and flight test activities only serve to reinforce the essential role that engineering correlations currently exercise in the design and operation of entry vehicles. The framework of information-related to the Orbiter empirical boundary layer transition prediction capability will be utilized to establish a fresh perspective on this role, to illustrate how quantitative statistical evaluations of empirical correlations can and should be used to assess accuracy and to discuss what the authors' perceive as a recent heightened interest in the application of high fidelity numerical modeling of boundary layer transition. Concrete results will also be developed related to empirical boundary layer transition onset correlations. This will include assessment of the discrete protuberance boundary layer transition onset data assembled for the Orbiter configuration during post-Columbia Return To Flight. Assessment of these data will conclude that momentum thickness Reynolds number based correlations have superior coefficients and uncertainty in comparison to roughness height based Reynolds numbers, aka Re(sub k) or Re(sub kk). In addition, linear regression results from roughness height Reynolds number based correlations will be evaluated, leading to a hypothesis that non-continuum effects play a role in the processes associated with incipient boundary layer transition on discrete protuberances.

Campbell, Charles H.↗
NASA NTRS2004

Uncertainty-Based Approach for Dynamic Aerodynamic Data Acquisition and Analysis

Development of improved modeling methods to provide increased fidelity of flight predictions for aircraft motions during flight in flow regimes with large nonlinearities requires improvements in test techniques for measuring and characterizing wind tunnel data. This paper presents a method for providing a measure of data integrity for static and forced oscillation test techniques. Data integrity is particularly important when attempting to accurately model and predict flight of today s high performance aircraft which are operating in expanded flight envelopes, often maneuvering at high angular rates at high angles-of-attack, even above maximum lift. Current aerodynamic models are inadequate in predicting flight characteristics in the expanded envelope, such as rapid aircraft departures and other unusual motions. Present wind tunnel test methods do not factor changes of flow physics into data acquisition schemes, so in many cases data are obtained over more iterations than required, or insufficient data may be obtained to determine a valid estimate with statistical significance. Additionally, forced oscillation test techniques, one of the primary tools used to develop dynamic models, do not currently provide estimates of the uncertainty of the results during an oscillation cycle. A method to optimize the required number of forced oscillation cycles based on decay of uncertainty gradients and balance tolerances is also presented.

Heim, Eugene H. D.↗
NASA NTRS2007

New Observations of the Heliospheric Magnetic Field from the Voyager Spacecraft

We review recent observations of variations of the heliospheric magnetic field B(t) made by Voyager 1 and 2 (V1 and V2), and we discuss the boundary conditions needed for models to explain the observations. Usually, observations from a spacecraft close to the Sun, such as ACE, WIND or Ulysses are used as input to a time-dependent model. Generally, the predicted profile B(t) can be compared directly with the observed profile only when either V1 or V2 is approximately radially aligned with a near-Sun spacecraft; this happens rarely and only for a brief time interval. The Bastille Day events illustrate this situation. In the absence of radial alignment of the spacecraft it is possible to predict the development of a global structure (a GMIR) with data from ACE or WIND, if they obtain a representative sample the flows that merge to form a GMIR. When latitudinal gradients are small and when there is statistical homogeneity in the azimuthal direction, it is possible to predict the statistical properties of the large-scale fluctuations of B(t) observed by V1 or V2 during a year or so. We illustrate this situation with observations from the recent solar maximum and the declining phase of the solar cycle. Predictions of detailed observations made by V1 and V2 under general conditions (e.g., when there is a large latitudinal gradient) require boundary conditions as a function of time on a surface, such as a Sun-centered sphere with a radius of 1 AU. These conditions can only be provided by global solar observations. We suggest the feasibility of such an approach, using V2 observations for 2005 and 2006. The prediction of observations in the heliosheath requires the solution of the 3-D boundary problem for the supersonic solar wind and propagation of solar wind through the termination shock into the heliosphere. The properties of B(t) observed in the heliosheath have not yet been predicted.

Burlaga, Leonard F.↗
NASA NTRS1973

Test of statistical models for gases with and without internal energy states.

The problem of nonlinear rarefied Couette flow with heat transfer has been studied for both monatomic and diatomic gases using the Boltzmann equation with the Bhatnagar-Gross-Krook type models as the governing equation and the method of discrete ordinates as a tool. The calculated results have been compared with the existing experimental data in order to test the accuracy and the applicability of the statistical models for this one-dimensional problem. The calculated density results are found to be in good agreement with available experimental data; the calculated heat flux solution for the linear case is found to always be lower than the experimental data of Teagan and Springer. The comparisons made here indicate that the statistical models are indeed reasonably accurate so that their use is justified in the type of problems investigated.

Huang, A. B.↗
NASA NTRS2006

Characterization of Days Based On Analysis of National Airspace System Performance Metrics

Days of operations in the National Airspace System can be described in term of traffic demand, runway conditions, equipment outages, and surface and enroute weather conditions. These causes manifest themselves in terms of departure delays, arrival delays, enroute delays and traffic flow management delays, Traffic flow management initiatives such as, ground stops, ground delay programs, miles-in-trail restrictions, rerouting and airborne holding are imposed to balance the air traffic demand with respect to the available capacity, In order to maintain operational efficiency of the National Airspace System, the Federal Aviation Administration (FAA) maintains delay sad other statistics in the Air Traffic Operations Network (OPSNET) and the Aviation System Performance Metrics (ASPM) databases. OPSNET data includes reportable delays of fifteen minutes ox more experienced by Instrument Flight Rule (IFR) flights. Numbers of aircraft affected by departure delays, enroute delays, arrival delays and traffic flow delays are recorded in the OPSNET data. ASPM data consist of number of actual departures, number of canceled departures, percentage of on time departures, percentage of on time gate arrivals, taxi-out delays. taxi-in delays, gate delays, arrival delays and block delays. Surface conditions at the major U.S. airports are classified in terms of Instrument Meteorological Condition (IMC) and Visual Meteorological Condition (VMC) as a function of the time of the day in the ASPM data. The main objective of this paper is to use OPSNET and ASPM data to classify the days in the datasets into few distinct groups, where each group is separated from the other groups in terms of a distance metric. The motivations for classifying the days are two-fold, 1) to enable selection of days of traffic with particular operational characteristics for concept evaluation using system-wide simulation systems such as the National Aeronautics and Space Administration's Airspace Concepts Evaluation Tool (ACES) and 2) to enable evaluation of a given day with respect to the characteristics of the classified groups. The first part of the paper is devoted to the analysis of major trends seen in the OPSNET and ASPM data. The second part of the paper is devoted to describing features or measures derived from the OPSNET and ASPM data that are suitable for characterizing days, and the classification algorithm used for grouping the days. Finally, the method for evaluating the characteristics of a given day with respect to the properties of the groups is described.

Chatterji, Gano B.↗
NASA NTRSDate not supplied

Assessing Carbon Properties in Coastal Waters with a New Observing System Testbed

Large rainfall events over land can lead to a substantial flux of carbon and nutrients to estuaries and the coastal ocean. In the mid-Atlantic on the east coast of North America (35° - 42° N), these events often happen due to tropical storm activity as well as less predictable anomalously large midlatitude storms or abrupt spring snow melt runoff. Storms can directly impact the coastal carbon cycle via export of carbon from land to sea, while also stimulating phytoplankton production due to the influx of nutrients to the coastal ocean. To assess the impact of high precipitation and river flow events on the coastal carbon cycle, we have integrated multiple observing platforms in an analytical framework to dynamically observe carbon-related properties. The new observing system testbed (NOS-T) allows for an estimate of phytoplankton and organic carbon stocks in the surface ocean, with a goal of providing near real time analytical capability. A case study of high river discharge in the mid-Atlantic in the summer and fall of 2018 and 2021 were used to examine how riverine carbon manifests along the land-estuary-ocean continuum particularly in Chesapeake Bay. Chesapeake Bay was chosen as the study site because of long term monitoring by the Chesapeake Bay Program and a robust and well-developed regional biogeochemical modeling system, the Chesapeake Bay Environmental Forecast System (CBEFS), that is publicly available. There is also new capability in Chesapeake Bay to combine hyperspectral radiometric data from the Aerosol Robotic Network site that is online in 2022 with in-water observations of optical properties. Precipitation data from the Global Precipitation Measurement IMERG data set was used to establish triggering criteria for storm carbon flux observation. USGS and in-water carbon data were used to establish statistical models to estimate the mass flux of organic carbon into Chesapeake Bay using measured river discharge. The year 2018 was examined as there was record rainfall and near record river flow in the late summer. The CBEFS modeling was compared with in-water estimates of dissolved organic carbon (DOC) to assess the model’s ability to capture storm fluxes of carbon to the ecosystem. Multiple satellite platforms were also used to assess how remote sensing using passive Earth orbiting sensors can be used to observe carbon in this complex coastal region. A set of recommendations have been established to improve sensing capability to measure aquatic carbon during storm events. A unique challenge in these dynamic inland waters is how rapidly carbon fluxes can evolve in space and time, with many sources contributing to the water leaving reflectance that satellites can observe. To improve our ability to quantify carbon stocks and fluxes in near real time, a suite of satellite sensors and high-resolution modeling capability is needed, all supplemented by in situ monitoring. Future inclusion of in-water observations that would be deployed when the system reaches triggering criteria, as well as taskable orbital instruments, will improve estimates of ocean carbon properties and provide the ability to calculate major carbon stocks and fluxes in near real time following episodic storm events.

land-ocean continuum↗
NASA NTRS1998

The Use of a Satellite Climatological Data Set to Infer Large Scale Three Dimensional Flow Characteristics

Ever since the first satellite image loops from the 6.3 micron water vapor channel on the METEOSAT-1 in 1978, there have been numerous efforts (many to a great degree of success) to relate the water vapor radiance patterns to familiar atmospheric dynamic quantities. The realization of these efforts is becoming evident with the merging of satellite derived winds into predictive models (Velden et al., 1997; Swadley and Goerss, 1989). Another parameter that has been quantified from satellite water vapor channel measurements is upper tropospheric relative humidity (UTH) (e.g., Soden and Bretherton, 1996; Schmetz and Turpeinen, 1988). These humidity measurements, in turn, can be used to quantify upper tropospheric water vapor and its transport to more accurately diagnose climate changes (Lerner et al., 1998; Schmetz et al. 1995a) and quantify radiative processes in the upper troposphere. Also apparent in water vapor imagery animations are regions of subsiding and ascending air flow. Indeed, a component of the translated motions we observe are due to vertical velocities. The few attempts at exploiting this information have been met with a fair degree of success. Picon and Desbois (1990) statistically related Meteosat monthly mean water vapor radiances to six standard pressure levels of the European Centre for Medium Range Weather Forecast (ECMWF) model vertical velocities and found correlation coefficients of about 0.50 or less. This paper presents some preliminary results of viewing climatological satellite water vapor data in a different fashion. Specifically, we attempt to infer the three dimensional flow characteristics of the mid- to upper troposphere as portrayed by GOES VAS during the warm ENSO event (1987) and a subsequent cold period in 1998.

Lerner, Jeffrey A.↗
NASA NTRS1989

Monte Carlo simulation of an expanding gas

By application of simple computer graphics techniques, the statistical performance of two Monte Carlo methods used in the simulation of rarefied gas flows are assessed. Specifically, two direct simulation Monte Carlo (DSMC) methods developed by Bird and Nanbu are considered. The graphics techniques are found to be of great benefit in the reduction and interpretation of the large volume of data generated, thus enabling important conclusions to be drawn about the simulation results. Hence, it is discovered that the method of Nanbu suffers from increased statistical fluctuations, thereby prohibiting its use in the solution of practical problems.

Boyd, Iain D.↗
NASA NTRS2001

Robust Strategy for Rocket Engine Health Monitoring

Monitoring the health of rocket engine systems is essentially a two-phase process. The acquisition phase involves sensing physical conditions at selected locations, converting physical inputs to electrical signals, conditioning the signals as appropriate to establish scale or filter interference, and recording results in a form that is easy to interpret. The inference phase involves analysis of results from the acquisition phase, comparison of analysis results to established health measures, and assessment of health indications. A variety of analytical tools may be employed in the inference phase of health monitoring. These tools can be separated into three broad categories: statistical, rule based, and model based. Statistical methods can provide excellent comparative measures of engine operating health. They require well-characterized data from an ensemble of "typical" engines, or "golden" data from a specific test assumed to define the operating norm in order to establish reliable comparative measures. Statistical methods are generally suitable for real-time health monitoring because they do not deal with the physical complexities of engine operation. The utility of statistical methods in rocket engine health monitoring is hindered by practical limits on the quantity and quality of available data. This is due to the difficulty and high cost of data acquisition, the limited number of available test engines, and the problem of simulating flight conditions in ground test facilities. In addition, statistical methods incur a penalty for disregarding flow complexity and are therefore limited in their ability to define performance shift causality. Rule based methods infer the health state of the engine system based on comparison of individual measurements or combinations of measurements with defined health norms or rules. This does not mean that rule based methods are necessarily simple. Although binary yes-no health assessment can sometimes be established by relatively simple rules, the causality assignment needed for refined health monitoring often requires an exceptionally complex rule base involving complicated logical maps. Structuring the rule system to be clear and unambiguous can be difficult, and the expert input required to maintain a large logic network and associated rule base can be prohibitive.

Santi, L. Michael↗
NASA NTRS2002

Stratospheric Analysis and Forecasting in the Northern Winter of 1999/2000: The NASA DAO's GEOS-3 System

An evaluation is presented of the performance in the northern winter 1999/2000 of the GEOS-3 troposphere-stratosphere data assimilation system (DAS). The impacts of the two main input data types are assessed: upper-air soundings (sondes) provide wind and temperature information and satellite-based (Tiros Operational Vertical Sounders: TOVS) give estimates of the thermal structure. It is shown that in the low stratosphere (300-70hPa) the analyses are generally slightly warmer than the sonde data, but colder than the TOVS data; this relationship reverses between 70 and 10 hPa. There are geographical biases, related to the spatial and temporal coverage of the observation types and to the statistical weights assigned to them in the DAS. Forecasts show a tendency to reduce zonal asymmetries in the atmospheric flow and to suppress stratospheric temperature minima. In the DAS, the analysis increments compensate for this, but it leads to important biases in the multi-day forecasts. The analysis increments are as large as the diabatic forcing in the lower polar stratosphere, indicating a substantial model bias. The results provide important insights into the roles of different data types and the circulation model in producing accurate analyses for studies of polar chemistry and physical processes.

Pawson, Steven↗
NASA NTRS2014

Background Error Covariance Estimation Using Information from a Single Model Trajectory with Application to Ocean Data Assimilation

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory.SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Error Covariance↗
DOE OSTI2024

Observation of Kolmogorov turbulence due to multiscale vortices in dusty plasma experiments

We report the experimental observation of fully developed Kolmogorov turbulence originating from self-excited vortex flows in a three-dimensional (3D) dust cloud. The characteristic -5/3 scaling of 3D Kolmogorov turbulence is consistent in both the spatial and temporal energy spectra within a statistical variation of experimental data. Additionally, the 2/3 scaling in the second-order structure function further supports the presence of Kolmogorov turbulence. We also identified a slight deviation in the tails of the probability distribution functions for velocity gradients, a reflection of intermittency. The experiment showed the formation of a dust cloud in the diffused plasma region away from the electrodes. The dust rotation was observed in multiple experimental campaigns under different discharge conditions at different spatial locations and background plasma environments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2014

Background Error Covariance Estimation using Information from a Single Model Trajectory with Application to Ocean Data Assimilation into the GEOS-5 Coupled Model

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Data Assimilation↗
NASA NTRS1991

Miranda

Observed geology, photometry, and geophysical data are used to examine various processes and properties that may have contributed to Maranda's evolution. Global tectonics and surface flow features constrain the possible heating mechanisms and materials. Statistics on impact craters and comparisons with other satellites suggest that the impactor-source population evolved through time and that ejecta mantling has resurfaced significant portions of the surface. It is proposed that the coronae, which are unique to Miranda, were formed by relaxation of topographic highs, by lithospheric stress driven by intensity anomalies in the asthenosphere, or by diapirs either breeching the surface or feeding large-scale volcanic flooding through preexisting crack structure.

Greenberg, R.↗
NASA NTRS2001

Large Eddy Simulation of a Near Sonic Turbulent Jet and Its Radiated Noise

In this paper numerical simulations are used to calculate the turbulence dynamics simultaneously with the sound field for a high-speed near-sonic (Ma=0.9) compressible jet at two Reynolds numbers of 3,600 and 72,000. LES (Large Eddy Simulation) in conjunction with accurate numerical schemes is used to calculate the unsteady flow and sound in the near field of the jet. It is shown that the jet mean parameters, mean velocity fields and turbulence statistics are in good agreement with experimental data and results from other simulations. The sound in the near-field is calculated directly from the simulations. The calculations are shown to capture the peak in the dilatation and pressure spectra around a Strouhal number St=0.25-0.3, in agreement with typical jet-noise spectra measured in experiments. Dilatation contours in the near-field show the formation of acoustic waves with a dominant wavelength of 3.2-4 jet diameters, corresponding to the peak in the dilatation spectra. As expected, the non-compact noise sources are found to be most dominant in the region corresponding to the end of the potential core. The contribution of the LES model to the radiated noise appears to be weak and does not contaminate the sound field with spurious high-frequency noise. However, the frequency spectra of the sound show a rapid falloff away from the peak frequency. This is attributed to the quasi-laminar state of the shear-layers in the region prior to potential core closure, and a possible effect of insufficient azimuthal resolution at the observed location. Further analysis of the effect of the LES model, especially at high frequencies, is needed.

Constantinescu, G. S.↗
NASA NTRS2011

Validating LES for Jet Aeroacoustics

Engineers charged with making jet aircraft quieter have long dreamed of being able to see exactly how turbulent eddies produce sound and this dream is now coming true with the advent of large eddy simulation (LES). Two obvious challenges remain: validating the LES codes at the resolution required to see the fluid-acoustic coupling, and the interpretation of the massive datasets that are produced. This paper addresses the former, the use of advanced experimental techniques such as particle image velocimetry (PIV) and Raman and Rayleigh scattering, to validate the computer codes and procedures used to create LES solutions. This paper argues that the issue of accuracy of the experimental measurements be addressed by cross-facility and cross-disciplinary examination of modern datasets along with increased reporting of internal quality checks in PIV analysis. Further, it argues that the appropriate validation metrics for aeroacoustic applications are increasingly complicated statistics that have been shown in aeroacoustic theory to be critical to flow-generated sound, such as two-point space-time velocity correlations. A brief review of data sources available is presented along with examples illustrating cross-facility and internal quality checks required of the data before it should be accepted for validation of LES.

Bridges, James↗