SEARCH · Engineering Papers

Results for “data base for model validation”

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.

SourceResearch connectionFrom yearThrough year

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

At least 559 records · Page 31

All sources NASA NTRS DOE OSTI

NASA NTRS1998

Prediction of Transitional Flows in the Low Pressure Turbine

Current turbulence models tend to give too early and too short a length of flow transition to turbulence, and hence fail to predict flow separation induced by the adverse pressure gradients and streamline flow curvatures. Our discussion will focus on the development and validation of transition models. The baseline data for model comparisons are the T3 series, which include a range of free-stream turbulence intensity and cover zero-pressure gradient to aft-loaded turbine pressure gradient flows. The method will be based on the conditioned N-S equations and a transport equation for the intermittency factor. First, several of the most popular 2-equation models in predicting flow transition are examined: k-e [Launder-Sharina], k-w [Wilcox], Lien-Leschiziner and SST [Menter] models. All models fail to predict the onset and the length of transition, even for the simplest flat plate with zero-pressure gradient(T3A). Although the predicted onset position of transition can be varied by providing different inlet turbulent energy dissipation rates, the appropriate inlet conditions for turbulence quantities should be adjusted to match the decay of the free-stream turbulence. Arguably, one may adjust the low-Reynolds-number part of the model to predict transition. This approach has so far not been very successful. However, we have found that the low-Reynolds-number model of Launder and Sharma [1974], which is an improved version of Jones and Launder [1972] gave the best overall performance. The Launder and Sharma model was designed to capture flow re-laminarization (a reverse of flow transition), but tends to give rise to a too early and too fast transition in comparison with the physical transition. The three test cases were for flows with zero pressure gradient but with different free-stream turbulent intensities. The same can be said about the model when considering flows subject to pressure gradient(T3C1). To capture the effects of transition using existing turbulence models, one approach is to make use of the concept of the intermittency to predict the flow transition. It was originally based on the intermittency distribution of Narasimha [1957], and then gradually evolved into a transport equation for the intermittency factor. Gostelow and associates [1994,1995] have made some improvements to Narasimha's method in an attempt to account for both favorable and adverse pressure gradients. Their approach is based on a linear, explicit combination of laminar and turbulent solutions. This approach fails to predict the overshoot of the skin friction on a flat plate near the end of transition zone, even though the length of transition is well predicted. The major flaw of Gostelow's approach is that it assumes the non-turbulent part being the laminar solution and the turbulent part being the turbulent solution and they do not interact across the transitional region. The technique in condition averaging the flow equations in intermittent flows was first introduced by Libby [1975] and Dopazo [1977] and further refined by Dick and associates [1988, 1996]. This approach employs two sets of transport equations for the non-turbulent part and the other for the turbulent part. The advantage of this approach is that it allows the interaction of non-turbulent and turbulent velocities through the introduction of additional source terms in the continuity and momentum equations for the non-turbulent and turbulent velocities. However, the strong coupling of the two sets of equations has caused some numerical difficulties, which requires special attention. The prediction of the skin friction can be improved by this approach via the implicit coupling of non-turbulent and turbulent velocity flelds. Another improvement of the interrmittency model can be further made by allowing the intermittency to vary in the cross-stream direction. This is one step prior to testing any proposal for the transport equation for the intermittency factor. Instead of solving the transport equation for the intermittency factor, the distribution for the intermittency factor is prescribed by Klebanoff's empirical formula [1955]. The skin friction is very well predicted by this new modification, including the overshoot of the profile near the end of the transition zone. The outcome of this study is very encouraging since it indicates that the proper description of the intermittency distribution is the key to the success of the model prediction. This study will be used to guide us on the modelling of the intermittency transport equation.

Huang, George↗

NASA NTRS2006

A Coupled GCM-Cloud Resolving Modeling System to Study Precipitation Processes

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud resolving models (CRMs) agree with observations better than traditional single column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA Satellite and field campaign cloud related data sets can provide initial conditions as well as validation for both the MMF and CRMs. Also we have implemented a Land Information System (LIS that includes the CLM and NOAH land surface models into the MMF. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM) This modeling system has been applied and tested its performance for two different climate scenarios, El Nino (1998) and La Nina (1999). The coupled new modeling system produced more realistic propagation and intensity of tropical rainfall systems and intraseasonal oscillations, and diurnal variation of precipitation that are very difficult to forecast using even the state-of-the-art GCMs. In this talk I will present: (1) a brief review on GCE model and its applications on precipitation processes (both Microphysical and land processes) and (2) The Goddard MMF and the Major difference between two existing MMFs (CSU MMF and Goddard MMF) and preliminary results (the comparison with traditional GCMs).

Tao, Wei-Kuo↗

NASA NTRS2007

Twist Model Development and Results from the Active Aeroelastic Wing F/A-18 Aircraft

Understanding the wing twist of the active aeroelastic wing (AAW) F/A-18 aircraft is a fundamental research objective for the program and offers numerous benefits. In order to clearly understand the wing flexibility characteristics, a model was created to predict real-time wing twist. A reliable twist model allows the prediction of twist for flight simulation, provides insight into aircraft performance uncertainties, and assists with computational fluid dynamic and aeroelastic issues. The left wing of the aircraft was heavily instrumented during the first phase of the active aeroelastic wing program allowing deflection data collection. Traditional data processing steps were taken to reduce flight data, and twist predictions were made using linear regression techniques. The model predictions determined a consistent linear relationship between the measured twist and aircraft parameters, such as surface positions and aircraft state variables. Error in the original model was reduced in some cases by using a dynamic pressure-based assumption. This technique produced excellent predictions for flight between the standard test points and accounted for nonlinearities in the data. This report discusses data processing techniques and twist prediction validation, and provides illustrative and quantitative results.

Lizotte, Andrew M.↗

NASA NTRS2013

ION Configuration Editor

The configuration of ION (Inter - planetary Overlay Network) network nodes is a manual task that is complex, time-consuming, and error-prone. This program seeks to accelerate this job and produce reliable configurations. The ION Configuration Editor is a model-based smart editor based on Eclipse Modeling Framework technology. An ION network designer uses this Eclipse-based GUI to construct a data model of the complete target network and then generate configurations. The data model is captured in an XML file. Intrinsic editor features aid in achieving model correctness, such as field fill-in, type-checking, lists of valid values, and suitable default values. Additionally, an explicit "validation" feature executes custom rules to catch more subtle model errors. A "survey" feature provides a set of reports providing an overview of the entire network, enabling a quick assessment of the model s completeness and correctness. The "configuration" feature produces the main final result, a complete set of ION configuration files (eight distinct file types) for each ION node in the network.

Borgen, Richard L.↗

NASA NTRS2022

Review of Solar Energetic Particle Models

Solar Energetic Particle (SEP) events are interesting from a scientific perspective as they are the product of a broad set of physical processes from the corona out through the extent of the heliosphere, and provide insight into processes of particle acceleration and transport that are widely applicable in astrophysics. From the operations perspective, SEP events pose a radiation hazard for aviation, electronics in space, and human space exploration, in particular for missions outside of the Earth’s protective magnetosphere including to the Moon and Mars. Thus, it is critical to improve the scientific understanding of SEP events and use this understanding to develop and improve SEP forecasting capabilities to support operations. Many SEP models exist or are in development using a wide variety of approaches and with differing goals. These include computationally intensive physics-based models, fast and light empirical models, machine learning-based models, and mixed-model approaches. The aim of this paper is to summarize all of the SEP models currently developed in the scientific community, including a description of model approach, inputs and outputs, free parameters, and any published validations or comparisons with data.

Kathryn Whitman↗

NASA NTRS2016

Aircraft High-Lift Aerodynamic Analysis Using a Surface-Vorticity Solver

This study extends an existing semi-empirical approach to high-lift analysis by examining its effectiveness for use with a three-dimensional aerodynamic analysis method. The aircraft high-lift geometry is modeled in Vehicle Sketch Pad (OpenVSP) using a newly-developed set of techniques for building a three-dimensional model of the high-lift geometry, and for controlling flap deflections using scripted parameter linking. Analysis of the low-speed aerodynamics is performed in FlightStream, a novel surface-vorticity solver that is expected to be substantially more robust and stable compared to pressure-based potential-flow solvers and less sensitive to surface perturbations. The calculated lift curve and drag polar are modified by an empirical lift-effectiveness factor that takes into account the effects of viscosity that are not captured in the potential-flow solution. Analysis results are validated against wind-tunnel data for The Energy-Efficient Transport AR12 low-speed wind-tunnel model, a 12-foot, full-span aircraft configuration with a supercritical wing, full-span slats, and part-span double-slotted flaps.

Olson, Erik D.↗

NASA NTRS2018

Global High Resolution Crustal Magnetic Field at the Surface of the Moon from Low-Altitude Lunar Prospector Magnetic Gradient Data

We derived new vector gradients based models of crustal magnetic field at the lunar surface with data from the Lunar Prospector (LP) satellite using two model parameterization approaches: a global set of 35820 1° spaced (~30 km) equal area monopoles at 20 km below the surface (O’Brien and Parker, 1994; Olsen et al., 2017) and combined results of subsets of 100000 0.66° spaced monopoles at the same depth. We use the scheme of iteratively reweighted least-squares inversion to compute the initial model. Then the amplitudes of these monopoles are determined by minimizing the misfit to the components together with the global average of |Br| at the ellipsoid surface (i.e. applying a L1 model regularization of Br). In previous approaches using vector fields for modeling, we found that external field contamination leads to spurious anomalies in the downward continued field models even with stringent data selection criteria and ad-hoc noise removal techniques (e.g., satellite’s position in the Moon’s wake w.r.t. the solar wind and in the Earth’s magnetotail, internal/external dipoles fields removal, low-order polynomial removal, joint equivalent source cross-validation technique and visually removing remaining anomalous segments). On the other hand, with the use of gradients-only data (along-track first finite differences), we were able to completely bypass the ad-hoc techniques. Similar processing of Kaguya magnetic data, which have only higher altitude coverage over the most of the Moon except in the region of the South Pole–Aitken (SPA) basin, completely misses some of the anomalies seen in the Lunar Prospector data. The combined Lunar Prospector and Kaguya gradient-based models also severely degrade the derivation of the anomaly fields in many regions. Euler analysis of isolated anomaly features from the Reiner Gamma swirl suggests top depths of about 0.3 to 1.5 km and center depths of 10-14 km; in the region between Stein and Vallier craters north of the SPA basin our analysis suggests top depths of around 1.5 km and center depths of 13-15 km. With the spectral depth determination techniques, the SPA basin region yields depths to the base of magnetization ranging between 15 and 40 km. Three-dimensional modeling and the bulk magnetization determinations of the sources constrained by the Euler and spectral methods is underway.

Gradient↗

NASA NTRS2006

A Coupled GCM-Cloud Resolving Modeling System, and A Regional Scale Model to Study Precipitation Processes

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

Tao, Wei-Kuo↗

NASA NTRS2006

A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CFWs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1 998 and 1999). In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

Tao, Wei-Kuo↗

NASA NTRS2007

A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a superparameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (2ICE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generatio11 regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

Tao, Wei-Kuo↗

NASA NTRS2006

A Coupled GCM-Cloud Resolving Modeling System, and A Regional Scale Model to Study Precipitation Processes

Tao, Wei-Kuo↗

NASA NTRS2013

Damping Effects of Drogue Parachutes on Orion Crew Module Dynamics

Currently, simulation predictions of the Orion Crew Module (CM) dynamics with drogue parachutes deployed are under-predicting the amount of damping as seen in free-flight tests. The Apollo Legacy Chute Damping model has been resurrected and applied to the Orion system. The legacy model has been applied to predict CM damping under drogue parachutes for both Vertical Spin Tunnel free flights and the Pad Abort-1 flight test. Comparisons between the legacy Apollo prediction method and test data are favorable. A key hypothesis in the Apollo legacy drogue damping analysis is that the drogue parachutes' net load vector aligns with the CM drogue attachment point velocity vector. This assumption seems reasonable and produces good results, but has never been quantitatively proven. The wake of the CM influences the drogue parachutes, which makes performance predictions of the parachutes difficult. Many of these effects are not currently modeled in the simulations. A forced oscillation test of the CM with parachutes was conducted in the NASA LaRC 20-Ft Vertical Spin Tunnel (VST) to gather additional data to validate and refine the Apollo legacy drogue model. A second loads balance was added to the original Orion VST model to measure the drogue parachute loads independently of the CM. The objective of the test was to identify the contribution of the drogues to CM damping and provide additional information to quantify wake effects and the interactions between the CM and parachutes. The drogue parachute force vector was shown to be highly dependent on the CM wake characteristics. Based on these wind tunnel test data, the Apollo Legacy Chute Damping model was determined to be a sufficient approximation of the parachute dynamics in relationship to the CM dynamics for preliminary entry vehicle system design. More wake effects should be included to better model the system. These results are being used to improve simulation model fidelity of CM flight with drogues deployed, which has been identified by the project as key to a successful Orion Critical Design Review.

Aubuchon, Vanessa V.↗

NASA NTRS2009

Advances in Land Data Assimilation at the NASA Goddard Space Flight Center

Research in land surface data assimilation has grown rapidly over the last decade. In this presentation we provide a brief overview of key research contributions by the NASA Goddard Space Flight Center (GSFC). The GSFC contributions to land assimilation primarily include the continued development and application of the Land Information System (US) and the ensemble Kalman filter (EnKF). In particular, we have developed a method to generate perturbation fields that are correlated in space, time, and across variables and that permit the flexible modeling of errors in land surface models and observations, along with an adaptive filtering approach that estimates observation and model error input parameters. A percentile-based scaling method that addresses soil moisture biases in model and observational estimates opened the path to the successful application of land data assimilation to satellite retrievals of surface soil moisture. Assimilation of AMSR-E surface soil moisture retrievals into the NASA Catchment model provided superior surface and root zone assimilation products (when validated against in situ measurements and compared to the model estimates or satellite observations alone). The multi-model capabilities of US were used to investigate the role of subsurface physics in the assimilation of surface soil moisture observations. Results indicate that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Building on this experience, GSFC leads the development of the Level 4 Surface and Root-Zone Soil Moisture (L4_SM) product for the planned NASA Soil-Moisture-Active-Passive (SMAP) mission. A key milestone was the design and execution of an Observing System Simulation Experiment that quantified the contribution of soil moisture retrievals to land data assimilation products as a function of retrieval and land model skill and yielded an estimate of the error budget for the SMAP L4_SM product. Terrestrial water storage observations from GRACE satellite system were also successfully assimilated into the NASA Catchment model and provided improved estimates of groundwater variability when compared to the model estimates alone. Moreover, satellite-based land surface temperature (LST) observations from the ISCCP archive were assimilated using a bias estimation module that was specifically designed for LST assimilation. As with soil moisture, LST assimilation provides modest yet statistically significant improvements when compared to the model or satellite observations alone. To achieve the improvement, however, the LST assimilation algorithm must be adapted to the specific formulation of LST in the land model. An improved method for the assimilation of snow cover observations was also developed. Finally, the coupling of LIS to the mesoscale Weather Research and Forecasting (WRF) model enabled investigations into how the sensitivity of land-atmosphere interactions to the specific choice of planetary boundary layer scheme and land surface model varies across surface moisture regimes, and how it can be quantified and evaluated against observations. The on-going development and integration of land assimilation modules into the Land Information System will enable the use of GSFC software with a variety of land models and make it accessible to the research community.

Reichle, Rolf↗

NASA NTRS2001

Validating GOES Instrument Thermal Deformations

Comparison of the Geostationary Operational Environmental Satellite (GOES) instrument thermal model predictions with on-orbit data shows that the models capture the observed temperature and misalignment trends. Lack of precise knowledge as to spacecraft pointing precludes such comparison with instrument pointing predictions. Based on the models, thermally induced instrument attitude variation will dominate GOES N-Q Image Motion Compensation (IMC). Errors due to day-to-day changes in the attitude profiles are predicted to be under 10 microradians except for rapid scans where disturbances may reach 30 microradians.

Harter, Peter↗

NASA NTRS2020

Underlying Fundamentals of Kalman Filtering for River Network Modeling

The grand challenge of producing hydrometeorological estimates every time and everywhere has motivated the fusion of sparse observations with dense numerical models, with a particular interest on discharge in river modeling. Ensemble methods are largely preferred as they enable the estimation of error properties, but at the expense of computational load and generally with underestimations. These imperfect stochastic estimates motivate the use of correction methods, that is, error localization and inflation, although the physical justifications for their optimality are limited. The purpose of this study is to use one of the simplest forms of data assimilation when applied to river modeling and reveal the underlying mechanisms impacting its performance. Our framework based on assimilating daily averaged in situ discharge measurements to correct daily averaged runoff was tested over a 4-yr case study of two rivers in Texas. Results show that under optimal conditions of inflation and localization, discharge simulations are consistently improved such that the mean values of Nash–Sutcliffe efficiency are enhanced from211.32 to 0.55 at observed gauges and from212.24 to21.10 at validation gauges. Yet, parameters controlling the inflation and the localization have a large impact on the performance. Further investigations of these sensitivities showed that optimal inflation occurs when compensating exactly for discrepancies in the magnitude of errors while optimal localization matches the distance traveled during one assimilation window. These results may be applicable to more advanced data assimilation methods as well as for larger applications motivated by upcoming river-observing satellite missions, such as NASA’s Surface Water and Ocean Topography mission.

Streamflow↗

NASA NTRS2012

Method for Pre-Conditioning a Measured Surface Height Map for Model Validation

This software allows one to up-sample or down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. Because the re-sampling of a surface map is accomplished based on the analytical expressions of Zernike-polynomials and a power spectral density model, such re-sampling does not introduce any aliasing and interpolation errors as is done by the conventional interpolation and FFT-based (fast-Fourier-transform-based) spatial-filtering method. Also, this new method automatically eliminates the measurement noise and other measurement errors such as artificial discontinuity. The developmental cycle of an optical system, such as a space telescope, includes, but is not limited to, the following two steps: (1) deriving requirements or specs on the optical quality of individual optics before they are fabricated through optical modeling and simulations, and (2) validating the optical model using the measured surface height maps after all optics are fabricated. There are a number of computational issues related to model validation, one of which is the "pre-conditioning" or pre-processing of the measured surface maps before using them in a model validation software tool. This software addresses the following issues: (1) up- or down-sampling a measured surface map to match it with the gridded data format of a model validation tool, and (2) eliminating the surface measurement noise or measurement errors such that the resulted surface height map is continuous or smoothly-varying. So far, the preferred method used for re-sampling a surface map is two-dimensional interpolation. The main problem of this method is that the same pixel can take different values when the method of interpolation is changed among the different methods such as the "nearest," "linear," "cubic," and "spline" fitting in Matlab. The conventional, FFT-based spatial filtering method used to eliminate the surface measurement noise or measurement errors can also suffer from aliasing effects. During re-sampling of a surface map, this software preserves the low spatial-frequency characteristic of a given surface map through the use of Zernike-polynomial fit coefficients, and maintains mid- and high-spatial-frequency characteristics of the given surface map by the use of a PSD model derived from the two-dimensional PSD data of the mid- and high-spatial-frequency components of the original surface map. Because this new method creates the new surface map in the desired sampling format from analytical expressions only, it does not encounter any aliasing effects and does not cause any discontinuity in the resultant surface map.

Sidick, Erkin↗

NASA NTRS2010

Improving the Representation of Snow Crystal Properties with a Single-Moment Mircophysics Scheme

Single-moment microphysics schemes are utilized in an increasing number of applications and are widely available within numerical modeling packages, often executed in near real-time to aid in the issuance of weather forecasts and advisories. In order to simulate cloud microphysical and precipitation processes, a number of assumptions are made within these schemes. Snow crystals are often assumed to be spherical and of uniform density, and their size distribution intercept may be fixed to simplify calculation of the remaining parameters. Recently, the Canadian CloudSat/CALIPSO Validation Project (C3VP) provided aircraft observations of snow crystal size distributions and environmental state variables, sampling widespread snowfall associated with a passing extratropical cyclone on 22 January 2007. Aircraft instrumentation was supplemented by comparable surface estimations and sampling by two radars: the C-band, dual-polarimetric radar in King City, Ontario and the NASA CloudSat 94 GHz Cloud Profiling Radar. As radar systems respond to both hydrometeor mass and size distribution, they provide value when assessing the accuracy of cloud characteristics as simulated by a forecast model. However, simulation of the 94 GHz radar signal requires special attention, as radar backscatter is sensitive to the assumed crystal shape. Observations obtained during the 22 January 2007 event are used to validate assumptions of density and size distribution within the NASA Goddard six-class single-moment microphysics scheme. Two high resolution forecasts are performed on a 9-3-1 km grid, with C3VP-based alternative parameterizations incorporated and examined for improvement. In order to apply the CloudSat 94 GHz radar to model validation, the single scattering characteristics of various crystal types are used and demonstrate that the assumption of Mie spheres is insufficient for representing CloudSat reflectivity derived from winter precipitation. Furthermore, snow density and size distribution characteristics are allowed to vary with height, based upon direct aircraft estimates obtained from C3VP data. These combinations improve the representation of modeled clouds versus their radar-observed counterparts, based on profiles and vertical distributions of reflectivity. These meteorological events are commonplace within the mid-latitude cold season and present a challenge to operational forecasters. This study focuses on one event, likely representative of others during the winter season, and aims to improve the representation of snow for use in future operational forecasts.

Molthan, Andrew L.↗

NASA NTRS2008

Comparison Between Numerically Simulated and Experimentally Measured Flowfield Quantities Behind a Pulsejet

Pulsed combustion is receiving renewed interest as a potential route to higher performance in air breathing propulsion systems. Pulsejets offer a simple experimental device with which to study unsteady combustion phenomena and validate simulations. Previous computational fluid dynamic (CFD) simulation work focused primarily on the pulsejet combustion and exhaust processes. This paper describes a new inlet sub-model which simulates the fluidic and mechanical operation of a valved pulsejet head. The governing equations for this sub-model are described. Sub-model validation is provided through comparisons of simulated and experimentally measured reed valve motion, and time averaged inlet mass flow rate. The updated pulsejet simulation, with the inlet sub-model implemented, is validated through comparison with experimentally measured combustion chamber pressure, inlet mass flow rate, operational frequency, and thrust. Additionally, the simulated pulsejet exhaust flowfield, which is dominated by a starting vortex ring, is compared with particle imaging velocimetry (PIV) measurements on the bases of velocity, vorticity, and vortex location. The results show good agreement between simulated and experimental data. The inlet sub-model is shown to be critical for the successful modeling of pulsejet operation. This sub-model correctly predicts both the inlet mass flow rate and its phase relationship with the combustion chamber pressure. As a result, the predicted pulsejet thrust agrees very well with experimental data.

Geng, Tao↗