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Results for “model-predictive control”

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

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47 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Validation and Recalibration of the Solubility Models in Support of the Heater Test in Salt Formations

The US Department of Energy Office of Nuclear Energy is conducting a brine availability heater test to characterize the thermal, mechanical, hydrological and chemical response of salt at elevated temperatures. In the heater test, brines will be collected and analyzed for chemical compositions. In order to support the geochemical modeling of chemical evolutions of the brines during the heater test, we are recalibrating and validating the solubility models for the mineral constituents in salt formations up to 100°C, based on the solubility data in multiple component systems as well as simple systems from literature. In this work, we systematically compare the model-predicted values based on the various solubility models related to the constituents of salt formations, with the experimental data. As halite is the dominant constituent in salt formations, we first test the halite solubility model in the Na-Mg-Cl dominated brines. We find the existing halite solubility model systematically over-predict the solubility of halite. We recalibrate the halite model, which can reproduce halite solubilities in Na-Mg-Cl dominated brines well. As gypsum/anhydrite in salt formations controls the sulfate concentrations in associated brines, we test the gypsum solubility model in NaCl solutions up to 5.87 mol•kg –1 from 25 ° C to 50 ° C. The testing shows that the current gypsum solubility model reproduces the experimental data well when NaCl concentrations are less than 1 mol•kg –1 . However, at NaCl concentrations higher than 1, the model systematically overpredicts the solubility of gypsum. In the Na + —Cl – —SO 4 2– —CO 3 2– system, the validation tests up to 100 ° C demonstrate that the model excellently reproduces the experimental data for the solution compositions equilibrated with one single phase such as halite (NaCl) or thenardite (Na 2 SO 4 ), with deviations equal to, or less than, 1.5 %. The model is much less ideal in reproducing the compositions in equilibrium with the assemblages of halite + thenardite, and of halite + thermonatrite (Na 2 CO 3 •H 2 O), with deviations up to 31 %. The high deviations from the experimental data for the multiple assemblages in this system at elevated temperatures may be attributed to the facts that the database has the Pitzer interaction parameters for Cl – —CO 3 2– and SO 4 2– —CO 3 2– only at 25 ° C. Finally, in the Na + —Ca 2+ —SO 4 2– —HCO 3 – system, the validation tests also demonstrate that the model reproduces the equilibrium compositions for one single phase such as gypsum better than the assemblages of more than one phase.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Induced microearthquakes predict permeability creation in the brittle crust

Predicting the evolution of permeability accurately during stimulation at the reservoir scale and at the resolution of individual fractures is essential to characterize the fluid transport and the reactive/heat-transfer characteristics of reservoirs where stress exerts significant control. Here, we develop a hybrid machine learning (ML) model to visualize in situ permeability evolution for an intermediate-scale (~10 m) hydraulic stimulation experiment. This model includes an ML model that was trained using the well history of flow rate and wellhead pressure and MEQ data from the first three stimulation episodes to predict average permeability from the statistical features of the MEQs alone for later episodes. Moreover, a physics-inspired model is integrated to estimate in situ fracture permeability spatially. This method relates fracture permeability to fracture dilation and scales dilation to the equivalent MEQ magnitude, according to laboratory observations. The seismic data are then applied to define incremental changes in permeability in both space and time. Our results confirm the excellent agreement between the ground truth and model-predicted permeability evolution. The resulting permeability map defines and quantifies flow paths in the reservoir with the averaged permeability comparing favorably with the ground truth of permeability.

induced seismicity↗
DOE OSTI2024

Multiscale Modeling of Nanoparticle Precipitation in Oxide Dispersion-Strengthened Steels Produced by Laser Powder Bed Fusion

Laser Powder Bed Fusion (LPBF) enables the efficient production of near-net-shape oxide dispersion-strengthened (ODS) alloys, which possess superior mechanical properties due to oxide nanoparticles (e.g., yttrium oxide, Y-O, and yttrium-titanium oxide, Y-Ti-O) embedded in the alloy matrix. To better understand the precipitation mechanisms of the oxide nanoparticles and predict their size distribution under LPBF conditions, we developed an innovative physics-based multiscale modeling strategy that incorporates multiple computational approaches. These include a finite volume method model (Flow3D) to analyze the temperature field and cooling rate of the melt pool during the LPBF process, a density functional theory model to calculate the binding energy of Y-O particles and the temperature-dependent diffusivities of Y and O in molten 316L stainless steel (SS), and a cluster dynamics model to evaluate the kinetic evolution and size distribution of Y-O nanoparticles in as-fabricated 316L SS ODS alloys. The model-predicted particle sizes exhibit good agreement with experimental measurements across various LPBF process parameters, i.e., laser power (110–220 W) and scanning speed (150–900 mm/s), demonstrating the reliability and predictive power of the modeling approach. The multiscale approach can be used to guide the future design of experimental process parameters to control oxide nanoparticle characteristics in LPBF-manufactured ODS alloys. Additionally, our approach introduces a novel strategy for understanding and modeling the thermodynamics and kinetics of precipitation in high-temperature systems, particularly molten alloys.

Wang, Zhengming (ORCID:0000000241627112)↗
NASA NTRS1993

Topex Microwave Radiometer thermal control - Post-system-test modifications and on-orbit performance

The Topex Microwave Radiometer has had an excellent thermal performance since launch. The instrument, however, went through a hardware modification right before launch to correct for a thermal design inadequacy that was uncovered during the spacecraft thermal vacuum test. This paper reports on how the initially obscure problem was tracked down, and how the thermal models were revised, validated, and utilized to investigate the solution options and guide the hardware modification decisions. Details related to test data interpretation, analytical uncertainties, and model-prediction vs. test-data correlation, are documented. Instrument/spacecraft interface issues, where the problem originated and where in general pitfalls abound, are dealt with specifically. Finally, on-orbit thermal performance data are presented, which exhibit good agreement with flight predictions, and lessons learned are discussed.

Lin, Edward I.↗
NASA NTRS1995

Simulated interannual variability of the Greenland Sea deep water formation and its connection to surface forcing

A fully prognostic Arctic ice-ocean model is used to study the interannual variability of deepwater formation in the Greenland Sea Gyre based on the simulations for the Arctic ice-ocean system for the period 1955 and 1960 - 1985. The model uses monthly climatology for thermodynamic forcing components (such as air temperature and cloudiness), together with constant annual net precipitation and river runoff. The daily wind forcing is derived from analyzed sea level air pressures from the National Center for Atmospheric Research (NCAR). In summary, the model shows that the occurence of deep convection in the Greenland Sea Gyre is controlled by the extensive Fram Strait ice export and/or local wind conditions in the Greenland Sea. In the latter case the weakening of the local wind curl allows the Polar Front to move eastward. The movement of the Polar Front causes adverse ice conditions, often together with much larger than normal ice export from the Arctic, such as in 1968, which can block convection in the gyre. The density difference between upper and lower layers is investigated as an indication of water mass formation through convection, occurring as strong diffusion in the model. The model-simulated density difference between the average top 100 m and deep levels reveals that the period 1960 - 1985 had only a few distinct years with weak stratification, and, especially, the model predicts no deep convection since the nid-1970s. The common factor for the years of the weakest decrease of the model-predicted heat content of the upper 2000 m which can, to a high degree, be explained by local heat loss.

Haekkinen, Sirpa↗
NASA NTRS2003

Variational Continuous Assimilation of TMI and SSM/I Rain Rates: Impact on GEOS-3 Hurricane Analyses and Forecasts

We describe a variational continuous assimilation (VCA) algorithm for assimilating tropical rainfall data using moisture and temperature tendency corrections as the control variable to offset model deficiencies. For rainfall assimilation, model errors are of special concern since model-predicted precipitation is based on parameterized moist physics, which can have substantial systematic errors. This study examines whether a VCA scheme using the forecast model as a weak constraint offers an effective pathway to precipitation assimilation. The particular scheme we exarnine employs a '1+1' dimension precipitation observation operator based on a 6-h integration of a column model of moist physics from the Goddard Earth Observing System (GEOS) global data assimilation system DAS). In earlier studies, we tested a simplified version of this scheme and obtained improved monthly-mean analyses and better short-range forecast skills. This paper describes the full implementation ofthe 1+1D VCA scheme using background and observation error statistics, and examines how it may improve GEOS analyses and forecasts of prominent tropical weather systems such as hurricanes. Parallel assimilation experiments with and without rainfall data for Hurricanes Bonnie and Floyd show that assimilating 6-h TMI and SSM/I surfice rain rates leads to more realistic storm features in the analysis, which, in turn, provide better initial conditions for 5-day storm track prediction and precipitation forecast. These results provide evidence that addressing model deficiencies in moisture tendency may be crucial to making effective use of precipitation information in data assimilation.

Hou, Arthur Y.↗
NASA NTRS2013

Atmospheric Dissolved Iron Depostiion to the Global Oceans: Effects of Oxalate-Promoted Fe Dissolution, Photochemical Redox Cycling, and Dust Mineralogy

Mineral dust deposition is suggested to be a significant atmospheric supply pathway of bioavailable iron (Fe) to Fe-depleted surface oceans. In this study, mineral dust and dissolved Fe (Fed) deposition rates are predicted for March 2009 to February 2010 using the 3-D chemical transport model GEOS-Chem implemented with a comprehensive dust-Fe dissolution scheme. The model simulates Fed production during the atmospheric transport of mineral dust taking into account inorganic and organic (oxalate)-promoted Fe dissolution processes, photochemical redox cycling between ferric (Fe(III)) and ferrous (Fe(II)) forms of Fe, dissolution of three different Fe-containing minerals (hematite, goethite, and aluminosilicates), and detailed mineralogy of windblown dust from the major desert regions. Our calculations suggest that during the yearlong simulation is approximately 0.26 Tg (1 Tg = 1012 g) of Fed was deposited to global oceanic regions. Compared to simulations only taking into account proton-promoted Fe dissolution, the addition of oxalate to the dust-Fe mobilization scheme increased total annual model-predicted Fed deposition to global oceanic regions by approximately 75%. The implementation of Fe(II)/Fe(III) photochemical redox cycling in the model allows for the distinction between different oxidation states of deposited Fed. Our calculations suggest that during the daytime, large fractions of Fed deposited to the global oceans is likely to be in Fe(II) form, while nocturnal fluxes of Fed are largely in Fe(III) form. Model simulations also show that atmospheric fluxes of Fed can be strongly influenced by the mineralogy of Fe-containing compounds. This study shows that Fed deposition to the oceans is controlled by total dust-Fe mass concentrations, mineralogy, the surface area of dust particles, atmospheric chemical composition, cloud processing, and meteorological parameters and exhibits complex and spatiotemporally variable patterns. Our study suggests that the explicit model representation of individual processes leading to Fed production within mineral dust are needed to improve the understanding of the atmospheric Fe cycle, and quantify the effect of dust-Fe on ocean biological productivity, carbon cycle, and climate.

Johnson, M. S.↗
NASA NTRS2014

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

aerosol optical depth↗
NASA NTRS2016

B33C-0612: Evaluation of Simulated Biospheric Carbon Dioxide Fluxes and Atmospheric Concentrations Using Global in Situ Observations

Atmospheric mixing ratios of carbon dioxide (CO2) are largely controlled by anthropogenic emission sources and biospheric sources/sinks. Global biospheric fluxes of CO2 are controlled by complex processes facilitating the exchange of carbon between terrestrial ecosystems and the atmosphere. These processes which play a key role in these terrestrial ecosystem-atmosphere carbon exchanges are currently not fully understood, resulting in large uncertainties in the quantification of biospheric CO2 fluxes. Current models with these inherent deficiencies have difficulties simulating the global carbon cycle with high accuracy. We are developing a new modeling platform, GEOS-Chem-CASA by integrating the year-specific NASA-CASA (National Aeronautics and Space Administration - Carnegie Ames Stanford Approach) biosphere model with the GEOS-Chem (Goddard Earth Observation System-Chemistry) chemical transport model to improve the simulation of atmosphere-terrestrial ecosystem carbon exchange. We use NASA-CASA to explicitly represent the exchange of CO2 between terrestrial ecosystem and atmosphere by replacing the baseline GEOS-Chem land net CO2 flux and forest biomass burning CO2 emissions. We will present the estimation and evaluation of these "bottom-up" land CO2 fluxes, simulated atmospheric mixing ratios, and forest disturbance changes over the last decade. In addition, we will present our initial comparison of atmospheric column-mean dry air mole fraction of CO2 predicted by the model and those retrieved from NASA's OCO-2 (Orbiting Carbon Observatory-2) satellite instrument and model-predicted surface CO2 mixing ratios with global in situ observations. This evaluation is the first step necessary for our future work planned to constrain the estimates of biospheric carbon fluxes through "top-down" inverse modeling, which will improve our understanding of the processes controlling atmosphere-terrestrial ecosystem greenhouse gas exchanges, especially over regions which lack in situ observations.

in situ observations↗
NASA NTRS2017

The Mars Crustal Magnetic Field Control of Plasma Boundary Locations and Atmospheric Loss: MHD Prediction and Comparison with MAVEN

We present results from a global Mars time-dependent MHD simulation under constant solar wind and solar radiation impact considering inherent magnetic field variations due to continuous planetary rotation. We calculate the 3-D shapes and locations of the bow shock (BS) and the induced magnetospheric boundary (IMB) and then examine their dynamic changes with time. We develop a physics-based, empirical algorithm to effectively summarize the multidimensional crustal field distribution. It is found that by organizing the model results using this new approach, the Mars crustal field shows a clear, significant influence on both the IMB and the BS. Specifically, quantitative relationships have been established between the field distribution and the mean boundary distances and the cross-section areas in the terminator plane for both of the boundaries. The model-predicted relationships are further verified by the observations from the NASA Mars Atmosphere and Volatile EvolutioN (MAVEN) mission. Our analysis shows that the boundaries are collectively affected by the global crustal field distribution, which, however, cannot be simply parameterized by a local parameter like the widely used subsolar longitude. Our calculations show that the variability of the intrinsic crustal field distribution in Mars-centered Solar Orbital itself may account for approx.60% of the variation in total atmospheric loss, when external drivers are static. It is found that the crustal field has not only a shielding effect for atmospheric loss but also an escape-fostering effect by positively affecting the transterminator ion flow cross-section area.

Global↗
NASA NTRS1993

TOPEX Microwave Radiometer Thermal Control: Post-System-Test Modifications and On-Orbit Performance

The Topex Microwave Radiometer has had an excellent thermal performance since launch. The instrument, however, went through a hardware modification right before launch to correct for athermal design inadequacy that was uncovered during the spacecraft thermal vacuum test. This paper reports on how the initially obscure problem was tracked down, and how the thermal models were revised, validated, and utilized to investigate the solution options and guide the hardware modification decisions. Details related to test data interpretation, analytical uncertainties, and model-prediction vs. test-data correlation, are documented. Instrument/spacecraft interface issues, where the problem originated and where in general pitfalls abound, are dealt with specifically. Finally, on-orbit thermal performance data are presented, which exhibit good agreement with flight predictions, and lessons learned are discussed.

Lin, Edward I.↗