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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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A FORTRAN batch simulation of the YAV-8B aircraft and supporting documentation are presented. The aircraft is described. Simulation outputs are compared with flight test data.
Equations for a lumped parameter mathematical model of a subsonic wind tunnel circuit are presented. The equation state variables are internal energy, density, and mass flow rate. The circuit model is structured to allow for integration and analysis of tunnel subsystem models which provide functions such as control of altitude pressure and temperature. Thus the model provides a useful tool for investigating the transient behavior of the tunnel and control requirements. The model was applied to the proposed NASA Lewis Altitude Wind Tunnel (AWT) circuit and included transfer function representations of the tunnel supply/exhaust air and refrigeration subsystems. Both steady state and frequency response data are presented for the circuit model indicating the type of results and accuracy that can be expected from the model. Transient data for closed loop control of the tunnel and its subsystems are also presented, demonstrating the model's use as a control analysis tool.
An algebraic eddy-viscosity model is derived from the renormalization group (RNG) theory of turbulence. A new length scale, based on boundary layer characteristics (displacement thickness, shape factor), is proposed. The model was applied to transitional boundary layer flow over a flat plate. Integral characteristics, such as the total skin friction coefficient, and mean velocity profile across the boundary layer, are found to be in good agreement with experimental data.
Fire is a major type of disturbance that has important influences on ecosystem dynamics and carbon cycles. Yet our understanding of ecosystem fires and their carbon cycle consequences is still limited, largely due to the difficulty of large-scale fire monitoring and the complex interactions between fire, vegetation, climate, and anthropogenic factors. Here, using data from satellite-derived fire observations and ecosystem model simulations, we performed a comprehensive investigation of the spatial and temporal dynamics of China's ecosystem fire disturbances and their carbon emissions over the past two decades (1997–2016). Satellite-derived results showed that on average about 3.47 - 4.53 x 10 4 km 2 of the land was burned annually during the past two decades, among which annual burned forest area was about 0.81 - 1.25 × 10 4 km 2 , accounting for 0.33-0.51% of the forest area in China. Biomass burning emitted about 23.02 TgC per year. Compared to satellite products, simulations from the Energy Exascale Earth System Land Model (ELM) strongly overestimated China's burned area and fire-induced carbon emissions. Annual burned area and fire-induced carbon emissions were high for boreal forest in Northeast China's Daxing'anling region and subtropical dry forest in South Yunnan, as revealed by both the satellite product and the model simulations. Our results suggest that climate and anthropogenic factors play critical roles in controlling the spatial and seasonal distribution of China's ecosystem fire disturbances. Our findings highlight the importance of multiple complementary approaches in assessing ecosystem fire disturbance and its carbon consequences. Further studies are required to improve the methods of observing and modelling China's ecosystem fire disturbances, which will provide valuable information for fire management and ecosystem sustainability in an era when both human activities and the natural environment are rapidly changing.
This data package contains model input and output files for local and global sensitivity analysis (SA) of a reactive transport model simulating redox cycling within a floodplain aquifer. The reaction network is implemented in CrunchFlow and focuses on spatially and temporally heterogeneous Fe cycling, though it contains several other species and redox pathways (37 aqueous species and 7 minerals in total). The package contains data from 600 Monte Carlo simulations (for global SA) and 104 one-at-a-time simulations (for local SA). It includes all input files required to run the CrunchFlow model, as well as limited model output – .csv files containing time series of primary species concentrations at 21 grid cells within the domain. These time series files contain the following species: H+, CO32-, SO42-, Cl-, Ca2+, Mg2+, Na+, K+, Fe(II), Fe(III), HS-, CH3COO-, O2(aq), S(aq), and Br-.These data were used to demonstrate the application of a novel form of global SA, distance-based generalized sensitivity analysis (DGSA) to a reactive transport model. The 2D model simulates the export of reduced species from pockets of fine-grained, organic-rich sediments embedded in a coarse sand aquifer. Stochastic simulations jointly varied 17 key model input parameters across several orders of magnitude, including the spatial variability of each parameter. DGSA on the model results reveal that the amplitude and variability of exported Fe(II) are most sensitive to the interaction between sand permeability and individual reaction rates. By contrast, the propagation of reducing conditions downgradient from the fine-grained lenses depends most heavily on the rate of dissolved organic carbon and sulfate release from the fines.
Rendezvous algorithms encode a communication pattern that is useful when processors sending data do not know who the receiving processors should be, or vice versa. The idea is to define an intermediate decomposition where datums from different sending processors can ”rendezvous” to perform a computation, in a manner that both the senders and eventual receivers of the results can identify the appropriate rendezvous processor. Though they were originally designed for interpolating between overlaid grids with independent parallel decompositions (Plimpton et al., 2004), we have recently found rendezvous algorithms useful for a variety of operations in particle- or grid-based simulation codes when running large problems on large numbers of processors. In particular, we show they can perform well when a load-balanced intermediate decomposition is randomized and not spatial, requiring all-to-all communication to move data between processors. In this case rendezvous algorithms leverage the large bisection communication bandwidths which parallel machines provide. We describe how rendezvous algorithms work in a scientific computing context and give specific examples for molecular dynamics and Direct Simulation Monte Carlo codes which result in dramatic performance improvements versus simpler algorithms which do not scale as well. We explain how a generic rendezvous algorithm can be implemented, and also point out similarities with the MapReduce paradigm popularized by Google and Hadoop.
An overview of an initial development of a model of bone loss due to skeletal unloading in weight bearing sites is presented. The skeletal site chosen for the initial application of the model is the femoral neck region because hip fractures can be debilitating to the overall performance health of astronauts. The paper begins with the motivation for developing such a model of the time course of change in bone in order to understand the mechanism of bone demineralization experienced by astronauts in microgravity, to quantify the health risk, and to establish countermeasures. Following this, a general description of a mathematical formulation of the process of bone remodeling is discussed. Equations governing the rate of change of mineralized bone volume fraction and active osteoclast and osteoblast are illustrated. Some of the physiology of bone remodeling, the theory of how imbalance in remodeling can cause bone loss, and how the model attempts to capture this is discussed. The results of a preliminary validation analysis that was carried out are presented. The analysis compares a set of simulation results against bone loss data from control subjects who participated in two different bed rest studies. Finally, the paper concludes with outlining the current limitations and caveats of the model, and planned future work to enhance the state of the model.
This project demonstrated the feasibility of developing a numerical modeling tool that provides an efficient and unique approach to analyze the geomechanical performance of a deep geological repository (DGR) for high-level nuclear waste. The numerical modeling tool is physics-based and models the thermo-hydro-mechanical (THM) processes during the required time (up to one million years) for a DGR. The unique capability of the developed code is explicit representation of fracturing and a discrete fracture network (DFN) in the model that includes the entire repository layout for simulated time of one million years. Therefore, it can potentially address one of the challenges of analysis of a DGR, which is efficient numerical simulation of a multi-scale, physics-based models.
The main challenge of the microgrid is to design a suitable protection scheme due to the complexity of the architecture of the microgrid. The importance of the proposed protection technique is threefold. First, it presents a co-simulation platform to integrate between a simulated model on power system computer aided design (PSCAD)/real time digital simulator computer aided design (RSCAD) software’s and physical devices schweitzer engineering laboratories (SEL) 421-7 relays to protect the microgrid that includes different resources connected based on inverter interface. Second, it presents a comprehensive hardware/software setup to test the protective relays in a closed loop system and shows how to configure the protective relay’s International Electrotechnical Commission 61850 communications. Third, IEEE 1588 standard is used to provide sub nanoseconds latency between the simulated model that emulated on real time digital simulator (RTDS) and the external devices. Also, the measurement signals are synchronized between RTDS and the external devices using giga-transceiver synchronization card (GTSYNC) interface card and SEL-2488 satellite-synchronized network clock. The results showed that the co-simulation infrastructure introduces a highly dependable design, analysis, and testing environment for cyber and physical data flow in the system. Besides that, the voltages at ac/dc sides and frequency at fault condition were maintained due to the energy storage device contributions at different modes of operation.
Work continued on two projects which had been started during previous years. Both projects involve calculations of the subsonic, turbulent far wake of a two-dimensional object at a Reynolds number of 1000 (based on wake momentum thickness). This flow was used as a test case for direct comparison of various turbulence models and a direct numerical simulations (DNS) of this flow were undertaken. In the turbulence model comparison studies, for any particular model tested, a unique self-similar solution was obtained far enough downstream, regardless of inlet conditions. Furthermore, different turbulence models led to different far-wake equilibrium solutions. No turbulence model could correctly predict all features of the turbulent far wake. For example, the spreading rate and turbulent shear stresses were underpredicted by all the standard models (both two-equation and full Reynolds stress models). In cases where a more correct spreading rate was achieved, it was at the expense of the turbulent kinetic energy, which was overpredicted. In general, the Algebraic Dissipation Rate Model of Gatski and Speziale, 1992, when added to any of the standard models, improved the results dramatically. Also, full Reynolds stress closure models did a much better job at predicting the shapes of both the mean and turbulence profiles, but the spreading rate was not significantly improved over that predicted by the simpler two-equation models. There are two main conclusions from these studies: First, in a comparison such as this, it is not enough to compare just one parameter, like the spreading rate. A good prediction for one parameter does not necessarily imply good predictions for all parameters in a flow. Second, since no turbulence model could correctly predict the turbulent far wake, much of the important physics of turbulent free shear flows is apparently lost by the assumptions inherent in today's methods of turbulence modeling; turbulence models must be improved. Direct simulations of this flow were begun last year in order to provide a data base through which some of the deficiencies of the existing turbulence models could be identified. Quantities such as the pressure-strain correlation, turbulent diffusion, and the dissipation rate tensor can be easily calculated from the DNS results, whereas these quantities are nearly impossible to measure experimentally. Improvements to existing turbulence models (and development of new models) require knowledge about flow quantities such as these. During this summer, diagnostics codes were written which will calculate the parameters mentioned above, along with other single-point and multi-point statistics. The DNS calculations are still in progress at the time of this writing. When these calculations are complete, the diagnostics codes will be applied so that the results can aid turbulence modelers. In addition, the results will show whether or not there exists a universal equilibrium turbulent far wake, independent of initial conditions.
We present a method to compress the 2D transverse phase space projections from a hadron accelerator and use that information to predict the beam transmission. This method assumes that obtaining at least three projections of the 4D transverse phase space is possible and that an accurate simulation model is available for the beamline. Using a simulated model, we show that—a computer can train a convolutional autoencoder to reduce phase-space information which can later be used to predict the beam transmission. Finally, we argue that although using projections from a realistic nonlinear distribution produces less accurate results, the method still generalizes well.
The Large Space Telescope (LST) program is aimed at placing a three-meter diffraction-limited telescope in a 270-nm orbit to perform astronomical observations that are not possible with earth-based telescopes. A complex simulation model is described which was developed to determine whether the stringent pointing stability requirements could be met. The model (programmed on a hybrid computer) included detailed dynamic representation of control moment gyros (CMGs) and reaction wheels (RWs), including their noise characteristics; dynamic sensor representation (including noise); shockmounts for the CMG actuators; detailed representation of an image motion compensation system; and a detailed flexible body vehicle model. Stability and performance studies based on the simulation model showed that the body pointing system will meet LST requirements in the presence of CMG vibrational disturbances and sensor noise. The recommended system consists of three orthogonally mounted RWs for primary short-term control, and a cluster of CMG actuators for continuous RW desaturation and vehicle maneuvering.
No abstract available
The rapid change in Arctic sea ice in recent decades has led to a rising demand for seasonal sea ice prediction. A recent modeling study that employed a prognostic melt pond model in a stand-alone sea ice model found that September Arctic sea ice extent can be accurately predicted from the melt pond fraction in May. Here we show that satellite observations show no evidence of predictive skill in May. However, we find that a significantly strong relationship (high predictability) first emerges as the melt pond fraction is integrated from early May to late June, with a persistent strong relationship only occurring after late July. Our results highlight that late spring to mid summer melt pond information is required to improve the prediction skill of the seasonal sea ice minimum. Furthermore, satellite observations indicate a much higher percentage of melt pond formation in May than does the aforementioned model simulation, which points to the need to reconcile model simulations and observations, in order to better understand key mechanisms of melt pond formation and evolution and their influence on sea ice state.
Reliance on natural gas for power generation has increased the coupling between gas and power networks. While this coupling can bring operational and economic benefits, it can also yield challenges, as the constraints in one system can impact the other. Co-simulation can capture the constraints and interactions between these systems, but so far, there has been limited comparison of co-simulation results to those of an integrated model. In this work, we develop a new co-simulation framework using the HELICS platform and the SAInt tool for modeling transient gas and AC optimal power flow. We evaluate this co-simulation framework against a fully integrated version of the SAInt power and gas simulators, thus providing a benchmarking of the co-simulation approach. We compare results across the two approaches for two test networks and a network representing the Belgian power and gas networks, testing both normal operating conditions and cases with compressor disruptions. In each of the cases tested, we find nearly identical results from the two approaches across various metrics of interest, such as nodal pressure, gas flow rates, and active power generation. This alignment suggests that co-simulation can yield comparable results to fully integrated models for modeling coupled gas and electricity networks.
We report the Eastern Africa region experiences frequent extreme precipitation events that can cause destruction of property and environment, and loss of lives. Thus, there is a need to understand how these events may change in the future and how well the global climate models that are used to make projections can simulate precipitation extremes in this region before they can be used in downscaling or flood and drought impact assessment studies. In this work, we evaluated the ability of sixteen Coupled Model Intercomparison Project Phase 6 (CMIP6) models to simulate present-day precipitation extremes over the Eastern Africa region during the two rainy seasons (March–May and September–November). We used nine extreme precipitation indices (including seven (one) indices of wet (dry) extremes) defined by the Expert Team on Climate Change Detection and Indices. The CMIP6 models were evaluated against two gridded observation datasets: Global Precipitation Climatology Project One-Degree Daily Dataset and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis 3B42. Three model performance metrics (percentage bias, normalized root-mean-square error, and pattern correlation coefficient) were employed to further assess the strengths and weakness of the models. Our results show that the multi-model ensemble mean generally provides a better representation of observed precipitation and related extremes compared to individual models when considering all metrics and seasons. Several consistent biases are evident across CMIP6 models, which tend to overestimate the total-wet day precipitation and consecutive wet days, and underestimate very wet days and maximum 5-day precipitation in both seasons. Furthermore, no single model consistently performs best, model performance varies with the season and index under consideration and is generally independent of horizontal resolution.
We demonstrate how observations of N2O and mean age in the tropical and midlatitude lower stratosphere (LS) can be used to identify realistic transport in models. The results are applied to 15 Chemistry Climate Models (CCMs) participating in the 2010 WMO assessment. Comparison of the observed and simulated N2O/mean age relationship identifies models with fast or slow circulations and reveals details of model ascent and tropical isolation. The use of this process-oriented N2O/mean age diagnostic identifies models with compensating transport deficiencies that produce fortuitous agreement with mean age. We compare the diagnosed model transport behavior with a model's ability to produce realistic LS O3 profiles in the tropics and midlatitudes. Models with the greatest tropical transport problems show the poorest agreement with observations. Models with the most realistic LS transport agree more closely with LS observations and each other. We incorporate the results of the chemistry evaluations in the SPARC CCMVal Report (2010) to explain the range of CCM predictions for the return-to-1980 dates for global (60 S-60 N) and Antarctic column ozone. Later (earlier) Antarctic return dates are generally correlated to higher (lower) vortex Cl(sub y) levels in the LS, and vortex Cl(sub y) is generally correlated with the model's circulation although model Cl(sub y) chemistry or Cl(sub y) conservation can have a significant effect. In both regions, models that have good LS transport produce a smaller range of predictions for the return-to-1980 ozone values. This study suggests that the current range of predicted return dates is unnecessarily large due to identifiable model transport deficiencies.
The accelerated fuel qualification (AFQ) methodology is applied by simulating accelerated fuel tests of the General Atomics Electromagnetic Systems’ fuel system for its 44-MW(electric) gas-cooled, fast-spectrum fast modular reactor (FMR). This fuel is comprised of UO 2 pellets in SiGA® cladding, a silicon carbide ceramic matrix composite. Fast reactors, like the FMR, offer many benefits, including high fuel utilization and flexibility, but may require a lengthy material design process if tests are performed using fast neutron irradiation alone. A thermal neutron irradiation can instead be used to rapidly test how well key components of the current material models extend to high burnup. Thermal neutrons produce a different radial power distribution within the pin than fast neutrons. However, the temperature and burnup values for the two neutron types are comparable, and the differences between the simulated fuel responses are relatively small, demonstrating the weak sensitivity of the physics-based fuel model calculations on the neutron type and the irradiation rate. Furthermore, the deformation of the SiGA cladding saturates after about 1 displacement per atom for both neutron spectra. In an accelerated fuel test, the irradiation time required to reach the target fuel burnup can be reduced by a factor of 3 by using a small rodlet with a 45% smaller pellet diameter while maintaining the same linear power. Therefore, the time for data collection up to high burnup can be significantly reduced while maintaining the same temperature profile, which largely determines the material response. Tests of fuel rodlets of standard and compact size will be carried out in the Idaho National Laboratory’s Advanced Test Reactor (ATR), including full size and compact rodlets with varying gap sizes. By applying physics-based mechanistic modeling and simulation in accordance with the AFQ methodology, this type of compact rodlet testing in a thermal test reactor captures the necessary phenomena to test fuel material models up to high burnup and to simulate the expected impact of fast neutron radiation on the fuel in FMR operations. Finally, this approach to testing fast reactor fuels in existing thermal test reactors, paired with advanced physics-based mechanistic modeling and simulation, is expected to be applicable to a range of advanced fuels and will decrease the overall fuel qualification timeframe from decades to years.