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NASA NTRS2024

Low-Cost Sensor Performance Intercomparison, Correction Factor Development, and 2+ Years of Ambient PM2.5 Monitoring in Accra, Ghana

Particulate matter air pollution is a leading cause of global mortality, particularly in Asia and Africa. Addressing the high and wide-ranging air pollution levels requires ambient monitoring, but many low- and middle-income countries (LMICs) remain scarcely monitored. To address these data gaps, recent studies have utilized low-cost sensors. These sensors have varied performance, and little literature exists about sensor intercomparison in Africa. By colocating 2 QuantAQ Modulair-PM, 2 PurpleAir PA-II SD, and 16 Clarity Node-S Generation II monitors with a reference-grade Teledyne monitor in Accra, Ghana, we present the first intercomparisons of different brands of low-cost sensors in Africa, demonstrating that each type of low-cost sensor PM2.5 is strongly correlated with reference PM2.5, but biased high for ambient mixture of sources found in Accra. When compared to a reference monitor, the QuantAQ Modulair-PM has the lowest mean absolute error at 3.04 μg/m3, followed by PurpleAir PA-II (4.54 μg/m3) and Clarity Node-S (13.68 μg/m3). We also compare the usage of 4 statistical or machine learning models (Multiple Linear Regression, Random Forest, Gaussian Mixture Regression, and XGBoost) to correct low-cost sensors data, and find that XGBoost performs the best in testing (R2: 0.97, 0.94, 0.96; mean absolute error: 0.56, 0.80, and 0.68 μg/m3 for PurpleAir PA-II, Clarity Node-S, and Modulair-PM, respectively), but tree-based models do not perform well when correcting data outside the range of the colocation training. Therefore, we used Gaussian Mixture Regression to correct data from the network of 17 Clarity Node-S monitors deployed around Accra, Ghana, from 2018 to 2021. We find that the network daily average PM2.5 concentration in Accra is 23.4 μg/m3, which is 1.6 times the World Health Organization Daily PM2.5 guideline of 15 μg/m3. While this level is lower than those seen in some larger African cities (such as Kinshasa, Democratic Republic of the Congo), mitigation strategies should be developed soon to prevent further impairment to air quality as Accra, and Ghana as a whole, rapidly grow.

Humidity↗

DOE OSTI2021

The persistence of large scale structures. Part I. Primordial non-Gaussianity

Abstract We develop an analysis pipeline for characterizing the topology of large scale structure and extracting cosmological constraints based on persistent homology . Persistent homology is a technique from topological data analysis that quantifies the multiscale topology of a data set, in our context unifying the contributions of clusters, filament loops, and cosmic voids to cosmological constraints. We describe how this method captures the imprint of primordial local non-Gaussianity on the late-time distribution of dark matter halos, using a set of N-body simulations as a proxy for real data analysis. For our best single statistic, running the pipeline on several cubic volumes of size 40 (Gpc/h) 3 , we detect f NL loc =10 at 97.5% confidence on ~ 85% of the volumes. Additionally wetest our ability to resolve degeneracies betweenthe topological signature of f NL loc and variation of σ 8 and argue that correctly identifying nonzero f NL loc in this case is possible via an optimal template method. Our method relies on information living at $\mathcal{O}$(10) Mpc/h, a complementary scale with respect to commonly used methods such as the scale-dependent bias in the halo/galaxy power spectrum. Therefore, while still requiring a large volume, our method does not require sampling long-wavelength modes to constrain primordial non-Gaussianity. Moreover, our statistics are interpretable: we are able to reproduce previous results in certain limits and we make new predictions for unexplored observables, such as filament loops formed by dark matter halos in a simulation box.

Astronomy & Astrophysics↗

DOE OSTI2025

Global models predict clouds at the wrong time of day: Does it matter for radiation and climate?

Accurate prediction of future climate change hinges upon the ability of Earth system models (ESMs) to simulate clouds and their radiative effects. Even if an ESM can simulate the correct clouds, a systematic error in the amount of sunlight reflected by clouds (and, thus, cloud radiative effect) can exist if the clouds are simulated at the incorrect time of day. In this work, we develop an analytical model connecting diurnal cloud biases to emergent mean state radiative biases. With the use of satellite observations, we demonstrate that there are errors in the time of day that clouds are occurring in ESMs that would cause bias in shortwave cloud radiative effect (SWCRE) that is greater than 45% of the total SWCRE bias, but such errors in the cloud diurnal cycle are masked by other compensating errors, indicating that these ESMs are getting the right answer for the wrong reasons.

Geosciences↗

DOE OSTI2025

Urban weather modeling using WRF: linking physical assumptions, code implementation, and observational needs

The Weather Research and Forecasting (WRF) model includes urban schemes that simulate the influence of urban surfaces on the atmosphere using parameterizations for flux, and radiative exchanges. Three core schemes – the Bulk urban parameterization, Single-Layer Urban Canopy Model (SLUCM), and Multi-Layer Urban Canopy Model (MLUCM) – represent increasing levels of complexity. Although the parameterizations within these urban schemes are described in the literature, their specific implementation remains poorly documented, thus slowing down model development efforts. This manuscript provides a roadmap to the three urban schemes in WRF version 4.5.2, presenting equations using the same symbols as in the model code, along with references to code lines, and including graphics and explanations that connect the code to its physical foundations. Our thorough review of the urban parameterizations implemented in WRF version 4.5.2 highlighted a handful of parameters that may introduce discontinuities in simulations: (i) in the SLUCM, a 1 mm h −1 rain rate threshold is employed to switch between two minimum moisture availability parameterizations, thus impacting latent heat flux calculations; (ii) in the SLUCM a threshold is used to partition shortwave radiation into direct and diffuse components; (iii) in all three urban schemes, the bulk Richardson number is employed to select the similarity function, which influences the vertical distribution of heat and momentum. We also identified a highly simplified treatment of the radiative balance on roof surfaces. The implications of these simplifications can be assessed through targeted observations across relevant conditions, including varying precipitation rates, cloud cover, and transitions between stability regimes. Furthermore, the widespread application of the Monin-Obukhov similarity theory in these urban schemes warrants model evaluation under highly stable and unstable conditions and in heterogeneous urban settings with variable land cover and building heights on scales finer than model resolution. To address these challenges, we offer guidance on observational strategies, emphasizing the need for multi-parametric measurements to capture potential compensating biases and multi-height measurements that align with the levels where quantities are diagnostic and prognosed in the model (i.e., the lowest atmospheric level of the WRF model). Finally, our inspection of the code revealed implementation bugs that have now been corrected in WRF versions 4.6.0 and 4.6.1. Sensitivity tests over the Atlanta urban area show that these corrections affect surface temperatures, underscoring the importance of performing rigorous documentation and verification of the implementation of parameterizations in model code.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1988

DSS 14 antenna calibrations for GSSR/VLA Saturn radar experiments

The DSS 14 pointing and gain were calibrated to support X-band bistatic radar observations of Saturn's rings. The observations used the Goldstone Solar System Radar and the National Radio Astronomy Observatory's Very Large Array (VLA) in Socorro, New Mexico. The pointing calibrations were based on conscan offset data collected during Voyager 1 and 2 support passes. The conscan data show angle-of-arrival sensing with no bias and 0.3 mdeg 1-sigma error. Using the calibrations, demonstrated blind pointing performance on Saturn was less than 3 mdeg 1-sigma error. Meteorological observations at the site were used to reduce elevation errors caused by atmospheric refraction. The techniques used corrected about one-third of the error-poorer than expected performance.

Guiar, C. N.↗

DOE OSTI2022

A Compound Poisson Generator Approach to Point-source Inference in Astrophysics

Abstract The identification and description of point sources is one of the oldest problems in astronomy, yet even today the correct statistical treatment for point sources remains one of the field’s hardest problems. For dim or crowded sources, likelihood-based inference methods are required to estimate the uncertainty on the characteristics of the source population. In this work, a new parametric likelihood is constructed for this problem using compound Poisson generator (CPG) functionals that incorporate instrumental effects from first principles. We demonstrate that the CPG approach exhibits a number of advantages over non-Poissonian template fitting (NPTF)—an existing method—in a series of test scenarios in the context of X-ray astronomy. These demonstrations show that the effect of the point-spread function, effective area, and choice of point-source spatial distribution cannot, generally, be factorized as they are in NPTF, while the new CPG construction is validated in these scenarios. Separately, an examination of the diffuse-flux emission limit is used to show that most simple choices of priors on the standard parameterization of the population model can result in unexpected biases: when a model comprising both a point-source population and diffuse component is applied to this limit, nearly all observed flux will be assigned to either the population or to the diffuse component. A new parameterization is presented for these priors that properly estimates the uncertainties in this limit. In this choice of priors, CPG correctly identifies that the fraction of flux assigned to the population model cannot be constrained by the data.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1997

Tests of a Semi-Analytical Case 1 and Gelbstoff Case 2 SeaWiFS Algorithm with a Global Data Set

A semi-analytical algorithm was tested with a total of 733 points of either unpackaged or packaged-pigment data, with corresponding algorithm parameters for each data type. The 'unpackaged' type consisted of data sets that were generally consistent with the Case 1 CZCS algorithm and other well calibrated data sets. The 'packaged' type consisted of data sets apparently containing somewhat more packaged pigments, requiring modification of the absorption parameters of the model consistent with the CalCOFI study area. This resulted in two equally divided data sets. A more thorough scrutiny of these and other data sets using a semianalytical model requires improved knowledge of the phytoplankton and gelbstoff of the specific environment studied. Since the semi-analytical algorithm is dependent upon 4 spectral channels including the 412 nm channel, while most other algorithms are not, a means of testing data sets for consistency was sought. A numerical filter was developed to classify data sets into the above classes. The filter uses reflectance ratios, which can be determined from space. The sensitivity of such numerical filters to measurement resulting from atmospheric correction and sensor noise errors requires further study. The semi-analytical algorithm performed superbly on each of the data sets after classification, resulting in RMS1 errors of 0.107 and 0.121, respectively, for the unpackaged and packaged data-set classes, with little bias and slopes near 1.0. In combination, the RMS1 performance was 0.114. While these numbers appear rather sterling, one must bear in mind what mis-classification does to the results. Using an average or compromise parameterization on the modified global data set yielded an RMS1 error of 0.171, while using the unpackaged parameterization on the global evaluation data set yielded an RMS1 error of 0.284. So, without classification, the algorithm performs better globally using the average parameters than it does using the unpackaged parameters. Finally, the effects of even more extreme pigment packaging must be examined in order to improve algorithm performance at high latitudes. Note, however, that the North Sea and Mississippi River plume studies contributed data to the packaged and unpackaged classess, respectively, with little effect on algorithm performance. This suggests that gelbstoff-rich Case 2 waters do not seriously degrade performance of the semi-analytical algorithm.

Carder, Kendall L.↗

NASA NTRS2010

Validation of TRMM Precipitation Radar Through Comparison of its Multi-Year Measurements to Ground-Based Radar

A procedure to accurately resample spaceborne and ground-based radar data is described, and then applied to the measurements taken from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and the ground-based Weather Surveillance Radar-1988 Doppler (WSR-88D or WSR) for the validation of the PR measurements and estimates. Through comparisons with the well-calibrated, non-attenuated WSR at Melbourne, Florida for the period 1998-2007, the calibration of the Precipitation Radar (PR) aboard the TRMM satellite is checked using measurements near the storm top. Analysis of the results indicates that the PR, after taking into account differences in radar reflectivity factors between the PR and WSR, has a small positive bias of 0.8 dB relative to the WSR, implying a soundness of the PR calibration in view of the uncertainties involved in the comparisons. Comparisons between the PR and WSR reflectivities are also made near the surface for evaluation of the attenuation-correction procedures used in the PR algorithms. It is found that the PR attenuation is accurately corrected in stratiform rain but is underestimated in convective rain, particularly in heavy rain. Tests of the PR estimates of rainfall rate are conducted through comparisons in the overlap area between the TRMM overpass and WSR scan. Analyses of the data are made both on a conditional basis, in which the instantaneous rain rates are compared only at those pixels where both the PR and WSR detect rain, and an unconditional basis, in which the area-averaged rain rates are estimated independently for the PR and WSR. Results of the conditional rain comparisons show that the PR-derived rain is about 9% greater and 19% less than the WSR estimates for stratiform and convective storms, respectively. Overall, the PR tends to underestimate the conditional mean rain rate by 8% for all rain categories, a finding that conforms to the results of the area-averaged rain (unconditional) comparisons.

Liao, Liang↗

NASA NTRS2012

A Full-Envelope Air Data Calibration and Three-Dimensional Wind Estimation Method Using Global Output-Error Optimization and Flight-Test Techniques

A novel, efficient air data calibration method is proposed for aircraft with limited envelopes. This method uses output-error optimization on three-dimensional inertial velocities to estimate calibration and wind parameters. Calibration parameters are based on assumed calibration models for static pressure, angle of attack, and flank angle. Estimated wind parameters are the north, east, and down components. The only assumptions needed for this method are that the inertial velocities and Euler angles are accurate, the calibration models are correct, and that the steady-state component of wind is constant throughout the maneuver. A two-minute maneuver was designed to excite the aircraft over the range of air data calibration parameters and de-correlate the angle-of-attack bias from the vertical component of wind. Simulation of the X-48B (The Boeing Company, Chicago, Illinois) aircraft was used to validate the method, ultimately using data derived from wind-tunnel testing to simulate the un-calibrated air data measurements. Results from the simulation were accurate and robust to turbulence levels comparable to those observed in flight. Future experiments are planned to evaluate the proposed air data calibration in a flight environment.

Taylor, Brian R.↗

NASA NTRS2015

CORRIGENDUM of the MJO Transition from Shallow to Deep Convection in Cloudsat-Calipso Data and GISS GCM Simulations

We have identified several errors in the calculations that were performed to create Fig. 3 of Del Genio et al. (2012). These errors affect the composite evolution of precipitation and column water vapor versus lag relative to the Madden-Julian oscillation (MJO) peak presented in that figure. The precipitation and column water vapor data for the April and November 2009 MJO events were composited incorrectly because the date of the MJO peak at a given longitude was assigned to the incorrect longitude band. In addition, the precipitation data for all MJO events were first accumulated daily and the daily accumulations averaged at each lag to create the composite, rather than the averaging of instantaneous values that was used for other composite figures in the paper. One poorly sampled day in the west Pacific therefore biases the composite precipitation in that region at several lags after the MJO peak. Finally, a 4-day running mean was mistakenly applied to the precipitation and column water vapor data rather than the intended 5-day running mean. The results of the corrections are that an anomalous west Pacific precipitation maximum510 days after the MJO peak is removed and the maximum in west Pacific precipitation one pentad before the MJO peak is now more evident; there is now a clear maximum in precipitation for the entire warm pool one pentad before the MJO peak; west Pacific column water vapor now varies more strongly as a function of lag relative to the peak; and precipitation, and to a lesser extent column water vapor, in general vary more smoothly with time. The corrections do not affect any other parts of the paper nor do they change the scientific conclusions we reached. The 4-day running mean error also affects Figs. 1 and 2 therein, with almost imperceptible impacts that do not affect any results or necessitate major changes to the text.

correction↗

NASA NTRS2021

Validation of Satellite-Based Precipitation Products from TRMM to GPM

The global precipitation measurement mission (GPM) has been in operation for seven years and continues to provide a vast quantity of global precipitation data at finer temporospatial resolutions with improved accuracy and coverage. GPM’s signature algorithm, the integrated multisatellite retrievals for GPM (IMERG) is a next-generation of precipitation product expected for wide variety of research and operational applications. This study evaluates the latest version (V06B) of IMERG and its predecessor, the tropical rainfall measuring mission (TRMM) multisatellite precipitation (TMPA) 3B42 (V7) using ground-based and gauge-corrected multiradar multisensor system (MRMS) precipitation products over the conterminous United States (CONUS). The spatial distributions of all products are analyzed. The error characteristics are further examined for 3B42 and IMERG in winter and summer by an error decomposition approach, which partitions total bias into hit bias, biases due to missed precipitation and false precipitation. The volumetric and categorical statistical metrics are used to quantitatively evaluate the performance of the two satellite-based products. All products show a similar precipitation climatology with some regional differences. The two satellite-based products perform better in the eastern CONUS than in the mountainous Western CONUS. The evaluation demonstrates the clear improvement in IMERG precipitation product in comparison with its predecessor 3B42, especially in reducing missed precipitation in winter and summer, and hit bias in winter, resulting in better performance in capturing lighter and heavier precipitation.

MRMS↗

DOE OSTI2022

Improving Effective Mass Estimations in Pu-Metal Annuli

Determining the effective mass of 240 Pu in a plutonium metal item can be achieved through a number of destructive and non-destructive assay techniques. However, these techniques have one or more shortcomings. These include the need for large quantities of plutonium, long measurement time, or lack of sufficient accuracy. While efforts have been made to mitigate these issues by estimating 240 Pu quantities through neutron coincidence counting techniques, these estimates are subject to systematic bias, and their estimates are not well characterized when other factors of the annulus’ physical form and composition are accounted for. In this work, we expand upon these non-destructive assay techniques via the implementation of random forest machine learning models, which produce correction functions that augment and improve the effective mass estimates derived from classical leakage multiplication, singles, doubles, and triples multiplicity counting equations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2012

The Aquarius Salinity Retrieval Algorithm: Early Results

The Aquarius L-band radiometer/scatterometer system is designed to provide monthly salinity maps at 150 km spatial scale to a 0.2 psu accuracy. The sensor was launched on June 10, 2011, aboard the Argentine CONAE SAC-D spacecraft. The L-band radiometers and the scatterometer have been taking science data observations since August 25, 2011. The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to O2, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind. This is based on the radar backscatter measurements by the scatterometer. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water and an auxiliary field for the sea surface temperature. In the current processing (as of writing this abstract) only v-pol TB are used for this last process and NCEP winds are used for the roughness correction. Before the salinity algorithm can be operationally implemented and its accuracy assessed by comparing versus in situ measurements, an extensive calibration and validation (cal/val) activity needs to be completed. This is necessary in order to tune the inputs to the algorithm and remove biases that arise due to the instrument calibration, foremost the values of the noise diode injection temperatures and the losses that occur in the feedhorns. This is the subject of the second part of our presentation. The basic tool is to analyze the observed difference between the Aquarius measured TA and an expected TA that is computed from a reference salinity field. It is also necessary to derive a relation between the scatterometer backscatter measurements and the radiometer emissivity that is induced by surface winds. In order to do this we collocate Aquarius radiometer and scatterometer measurements with wind speed retrievals from the WindSat and SSMIS F17 microwave radiometers. Both of these satellites fly in orbits that have the same equatorial ascending crossing time (6 pm) as the Aquarius/SAC-D observatory. Rain retrievals from WindSat and SSMIS F 17 can be used to remove Aquarius observations that are rain contaminated. A byproduct of this analysis is a prediction for the wind-induced sea surface emissivity at L-band.

Meissner, Thomas↗

NASA NTRS2021

Casual Rerouting of AERONET Sun/Sky Photometers: Toward a New Network of Ground Measurements Dedicated to the Monitoring of Surface Properties?

This paper presents an innovative method for observing vegetation health at a very high spatial resolution (~5 × 5 cm) and low cost by upgrading an existing Aerosol RObotic NETwork (AERONET) ground station dedicated to the observation of aerosols in the atmosphere. This study evaluates the capability of a sun/sky photometer to perform additional surface reflectance observations. The ground station of Toulouse, France, which belongs to the AERONET sun/sky photometer network, is used for this feasibility study. The experiment was conducted for a 5-year period (between 2016 and 2020). The sun/sky photometer was mounted on a metallic structure at a height of 2.5 m, and the acquisition software was adapted to add a periodical (every hour) ground-observation scenario with the sun/sky photometer observing the surface instead of being inactive. Evaluation is performed by using a classical metric characterizing the vegetation health: the normalized difference vegetation index (NDVI), using as reference the satellite NDVI derived from a Sentinel-2 (S2) sensor at 10 × 10 m resolution. Comparison for the 5-year period showed good agreement between the S2 and sun/sky photometer NDVIs (i.e., bias = 0.004, RMSD = 0.082, and R = 0.882 for a mean value of S2A NDVI around 0.6). Discrepancies could have been due to spatial-representativeness issues (of the ground measurement compared to S2), the differences between spectral bands, and the quality of the atmospheric correction applied on S2 data (accuracy of the sun/sky photometer instrument was better than 0.1%). However, the accuracy of the atmospheric correction applied on S2 data in this station appeared to be of good quality, and no dependence on the presence of aerosols was observed. This first analysis of the potential of the CIMEL CE318 sun/sky photometer to monitor the surface is encouraging. Further analyses need to be carried out to estimate the potential in different AERONET stations. The occasional rerouting of AERONET stations could lead to a complementary network of surface reflectance observations. This would require an update of the software, and eventual adaptations of the measurement platforms to the station environments. The additional cost, based on the existing AERONET network, would be quite limited. These new surface measurements would be interesting for measurements of vegetation health (monitoring of NDVI, and also of other vegetation indices such as the leaf area and chlorophyll indices), for validation and calibration exercise purposes, and possibly to refine various scientific algorithms (i.e., algorithms dedicated to cloud detection or the AERONET aerosol retrieval algorithm itself). CIMEL is ready to include the ground scenario used in this study in all new sun/sky photometers.

Dominique Carrer↗

NASA NTRS2019

Sea Surface Salinity Distribution in the Southern Ocean as Observed from Space

Large-scale spatial and temporal variabilities of sea surface salinity (SSS) in the Southern Ocean from 2011 to 2017 were studied using products derived from microwave sensors on board Aquarius, Soil Moisture and Ocean Salinity (SMOS), and Soil Moisture Active and Passive (SMAP) satellites. Four products, three from Aquarius and one from SMOS, were evaluated and shown to be generally consistent within 0.3 to 0.6 psu and agree favorably with in situ measurements. However, although the Aquarius products show consistent seasonality of SSS with high values of 34.45 psu in October and low values of 33.40 psu in May, theSMOS and SMAP products lack such seasonal variations. This may be caused by larger uncertainties in the SMOS and SMAP data due in part to the lack of concurrent scatterometer measurements that is used to correct for roughness effects. The four products provide similar spatial distributions of SSS with root mean square difference from 0.25 to 0.58 psu. Differences among Aquarius products are mainly due to varying salinity retrieval algorithms, smoothing, and masking of sea ice, while the SMOS product showed the highest SSS deviation that is likely due to the bias adjustment done on the data set. Our analyses show that SSS in the Southern Ocean region has significant meridional variations with the lowest SSS near the ice edge and highest at lower latitudes. The SSS is also lowest in summer indicating the predominant influence of sea ice and glacial melt, but it stays low near ice edges even during the growth season. Salinity together with temperature is the key parameters that control the state and circulation of the World's oceans. The large‐scale distribution of the sea surface salinity of the Southern Ocean is quantified for the first time using Aquarius, Soil Moisture and Ocean Salinity, and Soil Moisture Active and Passive satellite microwave data. Seasonal and interannual changes in the distribution as affected by the sea ice cover, surface temperature, and precipitation are evaluated. Comparative studies were done, using four different products that are publicly available, in conjunction with in situ observations to gain insights into the true nature of the distribution and how consistently the sea surface salinity is depicted by the different products. There are general consistencies in the products, and discrepancies are attributed to different algorithms, smoothing techniques, and sea ice masking. Aquarius data are shown to have higher accuracy than Soil Moisture and Ocean Salinity and Soil Moisture Active and Passive products in part because of having concurrent scatterometer that provides accurate correction to roughness effects.

Garcia-Eidell, Cynthia↗

NASA NTRS1986

An entropy correction method for unsteady full potential flows with strong shocks

An entropy correction method for the unsteady full potential equation is presented. The unsteady potential equation is modified to account for entropy jumps across shock waves. The conservative form of the modified equation is solved in generalized coordinates using an implicit, approximate factorization method. A flux-biasing differencing method, which generates the proper amounts of artificial viscosity in supersonic regions, is used to discretize the flow equations in space. Comparisons between the present method and solutions of the Euler equations and between the present method and experimental data are presented. The comparisons show that the present method more accurately models solutions of the Euler equations and experiment than does the isentropic potential formulation.

Whitlow, W., Jr.↗

NASA NTRS1986

An entropy correction method for unsteady full potential flows with strong shocks

Whitlow, W., Jr.↗

NASA NTRS1988

Application of a nonisentropic full potential method to AGARD standard airfoils

An entropy-correction method for the unsteady full potential equation is presented. The unsteady potential equation is modified to model the entropy jumps across shock waves. The conservative form of the modified equation is solved in generalized coordinates using an implicit, approximate factorization method. A flux-biasing differencing method, which generates the proper amounts of artificial viscosity in supersonic regions, is used to discretize the flow equations in space. Calculated results are presented for the NLR 7301, NACA 0012, and NACA 64A010A airfoils. Comparisons of the present method and solutions of the Euler equations are presented for the NLR 7301 airfoil, and comparisons of the present method and experimental data are presented for all three airfoils. The comparisons show that the present method more accurately models solutions of the Euler equations and experiment than does the isentropic potential formulation. In addition, it is shown that modeling shock-generated entropy extends the range of validity of the full potential method.

Whitlow, Woodrow, Jr.↗