Search NASA⌕ Search

SEARCH · Search NASA

Results for “Simulation and experiment”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Robustness of Observing System Simulation Experiments

Observing System Simulation Experiments (OSSEs) are used to investigate the potential performance of proposed new instruments on numerical weather prediction (NWP). As OSSEs involve a framework in which the atmosphere and observations are all completely simulated, it is necessary to perform validation of the OSSE to ensure that it is sufficiently realistic to provide useful experimental results. A common issue that affects the forecast skill and observation impacts is the tendency of OSSEs to have insufficient model error compared to NWP in the real world. In this work, two versions of the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) NWP OSSE framework are compared, with the newer framework having more simulated forecast model error than the older framework due to changes to the NWP system. The performance of the updated OSSE is validated against corresponding behavior of the same NWP system in the real world in terms of the simulated observations, the analysis increments, forecast error, and observation impacts. OSSE results of analysis and forecast impacts for three proposed new observation systems are also compared between the older and newer frameworks to evaluate the robustness of the OSSE experiments and the role of model error in observation impacts. These three new instruments are the Geostationary eXtended Observations (GeoXO) hyperspectral infrared sounder (GXS), the Midwave Infrared Sounding of Temperature and humidity in a Constellation for Winds (MISTiC Winds) atmospheric motion vectors, and additional Global Navigation Satellite System Radio Occultations (GNSS-RO).

Observing System Simulation Experiments↗
NASA NTRS1984

Accuracy of diagnostic heat and moisture budgets using SESAME-79 field data as revealed by observing system simulation experiments

Observing system simulation experiments are used to investigate the accuracy of diagnostic heat and moisture budgets which employ the AVE-SESAME 1979 data. The time-including, four-dimensional data set of a mesoscale model is used to simulate rawinsonde observations from AVE-SESAME 1979. The 5 C/day (heat budget) and 2 g/kg per day (moisture budget) magnitudes of error obtained indicate difficulties in the diagnosis of the heating rate in weak convective systems. The influences exerted by observational frequency, objective analysis, observational density, vertical interpolation, and observational errors on the budget are also studied, and it is found that the temporal and spatial resolution of the SESAME regional network is marginal for diagnosing convective effects on a horizontal time scale of 550 x 550 km.

Kuo, Y.-H.↗
NASA NTRS1992

NWP Impact of Cloud Top and Boundary Layer Winds from a Satellite Borne Lidar: an Observing System Simulation Experiment

Observing systems simulation experiments (OSSE's) provide a powerful tool to assess the impact of proposed satellite borne observing systems on meteorological applications models. We describe the results of an OSSE conducted to assess the impact of data from a low power lidar wind sensor on the forecast accuracy of a global spectral numerical weather prediction (NWP) model, the Air Force Geophysics Laboratory Global Data Assimilation System. The instrument would be operating at near-infrared wavelengths thereby increasing the backscatter signal relative to comparable infrared lidar.

Isaacs, R. G.↗
NASA NTRS2012

Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

Nearing, Grey S.↗
NASA NTRS2017

An Introduction to Observing System Simulation Experiments

Observing System Simulation Experiments (OSSEs) are used to estimate the potential impact of proposed new instruments and data on numerical weather prediction. OSSEs can also be used to help design new observing platforms and to investigate the behavior of data assimilation systems. A basic overview of how to design and perform an OSSE will be given, as well as best practices and pitfalls. Some examples using the OSSE framework developed at the NASA Global Modeling and Assimilation Office will be shown.

OSSE↗
NASA NTRS2018

Observing System Simulation Experiments

Observing System Simulation Experiments can be powerful tools for evaluating and exploring both the behavior of data assimilation systems and the potential impacts of future observing systems. With great power comes great responsibility - given a pure modeling framework, how can we be sure our results are meaningful? The challenges and pitfalls of OSSE calibration and validation will be addressed, as well as issues of incestuousness, selection of appropriate metrics, and experiment design. The use of idealized observational networks to investigate theoretical ideas in a fully complex modeling framework will also be discussed.

Prive, Nikki↗
NASA NTRS1991

Solution to the indexing problem of frequency domain simulation experiments

A frequency domain simulation experiment is one in which selected system parameters are oscillated sinusoidally to induce oscillations in one or more system statistics of interest. A spectral (Fourier) analysis of these induced oscillations is then performed. To perform this spectral analysis, all oscillation frequencies must be referenced to a common, independent variable - an oscillation index. In a discrete-event simulation, the global simulation clock is the most natural choice for the oscillation index. However, past efforts to reference all frequencies to the simulation clock generally yielded unsatisfactory results. The reason for these unsatisfactory results is explained in this paper and a new methodology which uses the simulation clock as the oscillation index is presented. Techniques for implementing this new methodology are demonstrated by performing a frequency domain simulation experiment for a network of queues.

Mitra, Mousumi↗
NASA NTRS1988

Pyro shock simulation: Experience with the MIPS simulator

The Mechanical Impulse Pyro Shock (MIPS) Simulator at GE Astro Space Division is one version of a design that is in limited use throughout the aerospace industry, and is typically used for component shock testing at levels up to 10,000 response g's. Modifications to the force imput, table and component boundary conditions have allowed a range of test conditions to be achieved. Twelve different designs of components with weights up to 23 Kg are in the process or have completed qualification testing in the Dynamic Simulation Lab at GE in Valley Forge, Pa. A summary of the experience gained through the use of this simulator is presented as well as examples of shock experiments that can be readily simulated at the GE Astro MIPS facility.

Dwyer, Thomas J.↗
NASA NTRS2014

Status of the NASA GMAO Observing System Simulation Experiment

An Observing System Simulation Experiment (OSSE) is a pure modeling study used when actual observations are too expensive or difficult to obtain. OSSEs are valuable tools for determining the potential impact of new observing systems on numerical weather forecasts and for evaluation of data assimilation systems (DAS). An OSSE has been developed at the NASA Global Modeling and Assimilation Office (GMAO, Errico et al 2013). The GMAO OSSE uses a 13-month integration of the European Centre for Medium- Range Weather Forecasts 2005 operational model at T511/L91 resolution for the Nature Run (NR). Synthetic observations have been updated so that they are based on real observations during the summer of 2013. The emulated observation types include AMSU-A, MHS, IASI, AIRS, and HIRS4 radiance data, GPS-RO, and conventional types including aircraft, rawinsonde, profiler, surface, and satellite winds. The synthetic satellite wind observations are colocated with the NR cloud fields, and the rawinsondes are advected during ascent using the NR wind fields. Data counts for the synthetic observations are matched as closely as possible to real data counts, as shown in Figure 2. Errors are added to the synthetic observations to emulate representativeness and instrument errors. The synthetic errors are calibrated so that the statistics of observation innovation and analysis increments in the OSSE are similar to the same statistics for assimilation of real observations, in an iterative method described by Errico et al (2013). The standard deviations of observation minus forecast (xo-H(xb)) are compared for the OSSE and real data in Figure 3. The synthetic errors include both random, uncorrelated errors, and an additional correlated error component for some observational types. Vertically correlated errors are included for conventional sounding data and GPS-RO, and channel correlated errors are introduced to AIRS and IASI (Figure 4). HIRS, AMSU-A, and MHS have a component of horizontally correlated error. The forecast model used by the GMAO OSSE is the Goddard Earth Observing System Model, Version 5 (GEOS-5) with Gridpoint Statistical Interpolation (GSI) DAS. The model version has been updated to v. 5.13.3, corresponding to the current operational model. Forecasts are run on a cube-sphere grid with 180 points along each edge of the cube (approximately 0.5 degree horizontal resolution) with 72 vertical levels. The DAS is cycled at 6-hour intervals, with 240 hour forecasts launched daily at 0000 UTC. Evaluation of the forecasting skill for July and August is currently underway. Prior versions of the GMAO OSSE have been found to have greater forecasting skill than real world forecasts. It is anticipated that similar forecast skill will be found in the updated OSSE.

OSSE↗
NASA NTRS2018

Adjoint Estimation of Observation Impact Explored with an Observing System Simulation Experiment

In an Observing System Simulation Experiment, the full, true state of the simulated atmosphere is known. This knowledge allows the direct calculation of analysis and forecast errors, and also may be used in conjunction with an adjoint tool to calculate metrics that are unachievable in the real world. For example, the errors that result from the use of the analysis state as verification when running adjoint calculations of observation impact on a forecast can be quantified. The adjoint itself can also be used to operate on the analysis state rather than on the forecast state. Results from these and other adjoint experiments using the NASA/GMAO OSSE framework will be presented.

Prive, Nikki↗
NASA NTRS1993

Gas-grain simulation experiment module conceptual design and gas-grain simulation facility breadboard development

This report delineates the Option portion of the Phase A Gas-Grain Simulation Facility study. The conceptual design of a Gas-Grain Simulation Experiment Module (GGSEM) for Space Shuttle Middeck is discussed. In addition, a laboratory breadboard was developed during this study to develop a key function for the GGSEM and the GGSF, specifically, a solid particle cloud generating device. The breadboard design and test results are discussed and recommendations for further studies are included. The GGSEM is intended to fly on board a low earth orbit (LEO), manned platform. It will be used to perform a subset of the experiments planned for the GGSF for Space Station Freedom, as it can partially accommodate a number of the science experiments. The outcome of the experiments performed will provide an increased understanding of the operational requirements for the GGSF. The GGSEM will also act as a platform to accomplish technology development and proof-of-principle experiments for GGSF hardware, and to verify concepts and designs of hardware for GGSF. The GGSEM will allow assembled subsystems to be tested to verify facility level operation. The technology development that can be accommodated by the GGSEM includes: GGSF sample generation techniques, GGSF on-line diagnostics techniques, sample collection techniques, performance of various types of sensors for environmental monitoring, and some off-line diagnostics. Advantages and disadvantages of several LEO platforms available for GGSEM applications are identified and discussed. Several of the anticipated GGSF experiments require the deagglomeration and dispensing of dry solid particles into an experiment chamber. During the GGSF Phase A study, various techniques and devices available for the solid particle aerosol generator were reviewed. As a result of this review, solid particle deagglomeration and dispensing were identified as key undeveloped technologies in the GGSF design. A laboratory breadboard version of a solid particle generation system was developed and characterization tests performed. The breadboard hardware emulates the functions of the GGSF solid particle cloud generator in a ground laboratory environment, but with some modifications, can be used on other platforms.

Zamel, James M.↗
NASA NTRS1989

Thermal histories of the samples of two KOSI comet nucleus simulation experiments

Temperatures recorded during two KOSI comet nucleus simulation experiments strongly suggest that heat transport by vapor flow into the interior of the sample is very important. Two comet nucleus simulation experiments have been done by the KOSI team in a big space simulator. The thermal evolution of the sample during insolation and the results of simplified thermal evolution calculations are discussed. The observed thermal histories cannot be explained by a simple model with heat transferred by heat conduction at a constant conductivity, so a coupled heat and mass transfer problem was considered. The porous ice matrix was assumed to have a constant thermal conductivity and to be in thermal equilibrium with vapor in the pores, the internal pressure being the vapor pressure. The vapor was modelled as an ideal gas because, at the temperatures relevant to the problem, the mean free path length of the vapor molecules is large in comparison with the pore dimensions. The heat capacity at constant volume per unit mass of the two phase mixture was also assumed constant. The vapor was allowed to flow and transfer heat in response to an internal pressure gradient.

Spohn, T.↗
NASA NTRS2015

The THS Experiment: Simulating Titans Atmospheric Chemistry at Low Temperature (200K)

In Titan's atmosphere, composed mainly of N2 (95-98%) and CH4 (2-5%), a complex chemistry occurs at low temperature, and leads to the production of heavy organic molecules and subsequently solid aerosols. Here, we used the Titan Haze Simulation (THS) experiment, an experimental setup developed at the NASA Ames COSmIC simulation facility to study Titan's atmospheric chemistry at low temperature. In the THS, the chemistry is simulated by plasma in the stream of a supersonic expansion. With this unique design, the gas is cooled to Titan-like temperature ( approximately 150K) before inducing the chemistry by plasma, and remains at low temperature in the plasma discharge (approximately 200K). Different N2-CH4-based gas mixtures can be injected in the plasma, with or without the addition of heavier precursors present as trace elements on Titan, in order to monitor the evolution of the chemical growth. Both the gas- and solid phase products resulting from the plasma-induced chemistry can be monitored and analyzed using a combination of complementary in situ and ex situ diagnostics. A recent mass spectrometry[1] study of the gas phase has demonstrated that the THS is a unique tool to probe the first and intermediate steps of Titan's atmospheric chemistry at Titan-like temperature. In particular, the mass spectra obtained in a N2-CH4-C2H2-C6H6 mixture are relevant for comparison to Cassini's CAPS-IBS instrument. The results of a complementary study of the solid phase are consistent with the chemical growth evolution observed in the gas phase. Grains and aggregates form in the gas phase and can be jet deposited on various substrates for ex situ analysis. Scanning Electron Microscopy images show that more complex mixtures produce larger aggregates. A mass spectrometry analysis of the solid phase has detected the presence of aminoacetonitrile, a precursor of glycine, in the THS aerosols. X-ray Absorption Near Edge Structure (XANES) measurements also show the presence of imine and nitrile functional groups, showing evidence of nitrogen chemistry. These complementary studies show the high potential of THS to better understand Titan's chemistry and the origin of aerosol formation.

Laboratory↗
NASA NTRS2015

Technology Advancement for Active Remote Sensing of Carbon Dioxide from Space Using the ASCENDS CarbonHawk Experiment Simulator: First Results

The ASCENDS CarbonHawk Experiment Simulator (ACES) is a newly developed lidar developed at NASA Langley Research Center and funded by NASA's Earth Science Technology Office (ESTO) Instrument Incubator Program (IIP) that seeks to advance technologies critical to measuring atmospheric column carbon dioxide (CO2) mixing ratios in support of the NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) mission. The technology advancements targeted include: (1) increasing the power-aperture product to approach ASCENDS mission requirements by implementing multi-aperture telescopes and multiple co-aligned laser transmitters; (2) incorporating high-efficiency, high-power Erbium-Doped Fiber Amplifiers (EDFAs); (3) developing and incorporating a high-bandwidth, low-noise HgCdTe detector and transimpedence amplifier (TIA) subsystem capable of long-duration autonomous operation on Global Hawk aircraft, and (4) advancing algorithms for cloud and aerosol discrimination. The ACES instrument architecture is being developed for operation on high-altitude aircraft and will be directly scalable to meet the ASCENDS mission requirements. These technologies are critical towards developing not only spaceborne instruments but also their airborne simulators, with lower platform requirements for size, mass, and power, and with improved instrument performance for the ASCENDS mission. ACES transmits five laser beams: three from commercial EDFAs operating near 1.57 microns, and two from the Exelis oxygen (O2) Raman fiber laser amplifier system operating near 1.26 microns. The three EDFAs are capable of transmitting up to 10 watts average optical output power each and are seeded by compact, low noise, stable, narrow-linewidth laser sources stabilized with respect to a CO2 absorption line using a multi-pass gas absorption cell. The Integrated-Path Differential Absorption (IPDA) lidar approach is used at both wavelengths to independently measure the CO2 and O2 column number densities and retrieve the average column CO2 mixing ratio. The ACES receiver uses three fiber-coupled 17.8-cm diameter athermal telescopes. The transmitter assembly consists of five fiber-coupled laser collimators and an associated Risley prism pair for each laser to co-align the outgoing laser beams and to align them with the telescope field of view. The backscattered return signals collected by the three telescopes are combined in a fiber bundle and sent to a single low noise detector. The detector/TIA development has improved the existing detector subsystem by increasing its bandwidth to 4.7 MHz from 500 kHz and increasing the duration of autonomous, service-free operation periods from 4 hours to >24 hours. The new detector subsystem enables the utilization of higher laser modulation rates, which provides greater flexibility for implementing advanced thin-cloud discrimination algorithms as well as improving range-determination resolution and error reduction. The cloud/aerosol discrimination algorithm development by Langley and Exelis features a new suite of algorithms for the minimization/elimination of bias errors in the return signal induced by the presence of intervening thin clouds. Multiple laser modulation schemes are being tested in an effort to significantly mitigate the effects of thin clouds on the retrieved CO2 column amounts. Full instrument development concluded in the spring of 2014. After ground range tests of the instrument, ACES successfully completed six test flights on the Langley Hu-25 aircraft in July, 2014, and recorded data at multiple altitudes over land and ocean surfaces with and without intervening clouds. Preliminary results from these test flights will be presented in this paper.

Obland, Michael D.↗
NASA NTRS1986

Simulation experiments for testing the assimilation of geostationary satellite temperature retrievals into a numerical prediction model

A simulation experiment is presented which tests a procedure that assimilates temperature soundings from geostationary satellites using a method developed by Gal-Chen (1983). The simulation is used to decide whether the increased temporal resolution of geostationary satellite data can be used to improve numerical simulation of a baroclinically unstable wave, and to assess the impact of gaps in the satellite sounding fields on the model simulations. Background information on the simulation experiment is presented, including discussion of the variational approach utilized, the numerical model, updating procedures, and control run. The simulation results indicate that, for the case of a baroclinically unstable wave, considerable improvements in the short-range forecast may be realized if geostationary satellite data are inserted with a frequency near 1 hr during a 6 hr analysis cycle compared with a single insertion.

Gal-Chen, T.↗