Simulation, models, and games - sources of measurement.
Sources of measurement through analogy in simulation, models and games
MAN-MACHINE SYSTEM↗
SEARCH · Engineering Papers
Results for “modeling simulation”
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 Simulation Model of the Planetary Boundary Layer at Kennedy Space Center
A simulation model which predicts the behavior of the Atmospheric Boundary Layer has been developed and coded. The model is partially evaluated by comparing it with laboratory measurements and the sounding measurements at Kennedy Space Center. The applicability of such an approach should prove quite widespread.
Hwang, B.↗
A simulation model for reliability evaluation of Space Station power systems
A detailed simulation model for the hybrid Space Station power system is presented which allows photovoltaic and solar dynamic power sources to be mixed in varying proportions. The model considers the dependence of reliability and storage characteristics during the sun and eclipse periods, and makes it possible to model the charging and discharging of the energy storage modules in a relatively accurate manner on a continuous basis.
Singh, C.↗
PrimeSupplier Cross-Program Impact Analysis and Supplier Stability Indicator Simulation Model
PrimeSupplier, a supplier cross-program and element-impact simulation model, with supplier solvency indicator (SSI), has been developed so that the shuttle program can see early indicators of supplier and product line stability, while identifying the various elements and/or programs that have a particular supplier or product designed into the system. The model calculates two categories of benchmarks to determine the SSI, with one category focusing on agency programmatic data and the other focusing on a supplier's financial liquidity. PrimeSupplier was developed to help NASA smoothly transition design, manufacturing, and repair operations from the Shuttle program to the Constellation program, without disruption in the industrial supply base.
Calluzzi, Michael↗
Stone Content Influence on Land Surface Model Simulation of Soil Moisture and Evapotranspiration at Reynolds Creek Watershed
Considerable advancement in spatiotemporal resolution of remote sensing and ground-based measurements has enabled refinement of parameters used in land surface models for simulating surface water fluxes. However, land surface modeling capabilities are still inadequate for accurate representation of subsurface properties and processes, which continue to limit the accuracy of land surface model simulation. Our objective in this study was to examine the performance of the variously parameterized Noah-Multiphysics (Noah-MP) land surface model and to improve simulations of evapotranspiration (ET) and soil moisture dynamics in stony soils using verification from eddy covariance ET and in-situ soil moisture data. Meteorological and eddy covariance data from the Lower Sheep sub-catchment within the Reynolds Creek Experimental Watershed in Southwestern Idaho were employed to drive Noah-MP and to assess simulation results. We evaluated the performance of Noah-MP considering four different scenarios: (1) A one-layer soil profile with Noah-MP default soil hydraulic parameters, followed by five-layer soil profiles using -(2) Noah-MP default soil hydraulic parameters -(3) soil hydraulic parameters derived from a pedotransfer function using field observations, and -(4) hydraulic parameters from (3) which also accounted for stone content in each layer. Each modeling experiment was forced with the same set of initial conditions, atmospheric input and vegetation parameters. Our results indicated that enhanced representation of soil profile properties and stone content information noticeably improve the Noah-MP land surface model simulation of soil moisture content and evapotranspiration.
Land surface models, Soil hydrology, Noah-MP, Evap↗
Strategy and gaps for modeling, simulation, and control of hybrid systems
The purpose of this report is to establish a strategy for modeling and simulation of candidate hybrid energy systems. Modeling and simulation is necessary to design, evaluate, and optimize the system technical and economic performance. Accordingly, this report first establishes the simulation requirements to analysis candidate hybrid systems. Simulation fidelity levels are established based on the temporal scale, real and synthetic data availability or needs, solution accuracy, and output parameters needed to evaluate case-specific figures of merit. Accordingly, the associated computational and co-simulation resources needed are established; including physical models when needed, code assembly and integrated solutions platforms, mathematical solvers, and data processing. This report first attempts to describe the figures of merit, systems requirements, and constraints that are necessary and sufficient to characterize the grid and hybrid systems behavior and market interactions. Loss of Load Probability (LOLP) and effective cost of Effective Cost of Energy (ECE), as opposed to the standard Levelized Cost of Electricty (LCOE), are introduced as technical and economical indices for integrated energy system evaluations. Financial assessment methods are subsequently introduced for evaluation of non-traditional, hybrid energy systems. Algorithms for coupled and iterative evaluation of the technical and economic performance are subsequently discussed. This report further defines modeling objectives, computational tools, solution approaches, and real-time data collection and processing (in some cases using real test units) that will be required to model, co-simulate, and optimize; (a) an energy system components (e.g., power generation unit, chemical process, electricity management unit), (b) system domains (e.g., thermal, electrical or chemical energy generation, conversion, and transport), and (c) systems control modules. Co-simulation of complex, tightly coupled, dynamic energy systems requires multiple simulation tools, potentially developed in several programming languages and resolved on separate time scales. Whereas further investigation and development of hybrid concepts will provide a more complete understanding of the joint computational and physical modeling needs, this report highlights areas in which co-simulation capabilities are warranted. The current development status, quality assurance, availability and maintainability of simulation tools that are currently available for hybrid systems modeling is presented. Existing gaps in the modeling and simulation toolsets and development needs are subsequently discussed. This effort will feed into a broader Roadmap activity for designing, developing, and demonstrating hybrid energy systems.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
How Well Do Global Climate Models Simulate the Variability of Atlantic Tropical Cyclones Associated with ENSO?
The variability of Atlantic tropical cyclones (TCs) associated with El Nino-Southern Oscillation (ENSO) in model simulations is assessed and compared with observations. The model experiments are 28-yr simulations forced with the observed sea surface temperature from 1982 to 2009. The simulations were coordinated by the U.S. CLIVAR Hurricane Working Group and conducted with five global climate models (GCMs) with a total of 16 ensemble members. The model performance is evaluated based on both individual model ensemble means and multi-model ensemble mean. The latter has the highest anomaly correlation (0.86) for the interannual variability of TCs. Previous observational studies show a strong association between ENSO and Atlantic TC activity, as well as distinctions in the TC activities during eastern Pacific (EP) and central Pacific (CP) El Nino events. The analysis of track density and TC origin indicates that each model has different mean biases. Overall, the GCMs simulate the variability of Atlantic TCs well with weaker activity during EP El Nino and stronger activity during La Nina. For CP El Nino, there is a slight increase in the number of TCs as compared with EP El Nino. However, the spatial distribution of track density and TC origin is less consistent among the models. Particularly, there is no indication of increasing TC activity over the U.S. southeast coastal region as in observations. The difference between the models and observations is likely due to the bias of vertical wind shear in response to the shift of tropical heating associated with CP El Nino, as well as the model bias in the mean circulation.
Tropical Cyclones↗
Earth System Model Simulations of Ameriflux sites using dynamic roots and dynamic leaf to root allocation
This data package contains point-scale Earth System Model simulations run with DOE's E3SM Model. The package includes four sets of simulations, one set of simulations run in the default configuration, a second set of simulations run with the dynamic root module enabled, the third set with dynamic leaf to fine root allocation, and the fourth with the combination of dynamic roots and dynamic allocation. These simulations were run in point mode a Ameriflux sites, US-MMS, US-Moz, US-Syv, and US-NR1. These datasets can be used to assess the impact that dynamic roots have on Land Surface fluxes such as carbon and water. The simulations were run with atmospheric forcing from the Global Soil Wetness Project. We provide specifically here Gross Primary Production, Transpiration, relative root fraction per soil layer as well as Air Temperature, Precipitation and all the parameterizations used for the simulations. Our purpose for generating and analyzing these simulations was to assess the role that root dynamics and foraging for water has in the recovery timescale of ecosystems following climate perturbation. All data provided are in the "netcdf" format using standard CF-1 (Climate and Forecast) Convention. The data are all machine readable using various software platforms including Matlab, NCO, Panoply and R.
54 ENVIRONMENTAL SCIENCES↗
Simulation Models for Improved Water Heating Systems
This research improved the design of computer simulation models of water heaters and hot water distribution systems to increase their accuracy and flexibility, and to allow for future inclusion of new technologies. The models will be incorporated into the Buildings Library at Lawrence Berkeley National Laboratory to assist those performing whole-building energy simulations.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Production of Lightning NO(x) and its Vertical Distribution Calculated from 3-D Cloud-scale Chemical Transport Model Simulations
A 3-D cloud scale chemical transport model that includes a parameterized source of lightning NO(x), based on observed flash rates has been used to simulate six midlatitude and subtropical thunderstorms observed during four field projects. Production per intracloud (P(sub IC) and cloud-to-ground (P(sub CG)) flash is estimated by assuming various values of P(sub IC) and P(sub CG) for each storm and determining which production scenario yields NO(x) mixing ratios that compare most favorably with in-cloud aircraft observations. We obtain a mean P(sub CG) value of 500 moles NO (7 kg N) per flash. The results of this analysis also suggest that on average, P(sub IC) may be nearly equal to P(sub CG), which is contrary to the common assumption that intracloud flashes are significantly less productive of NO than are cloud-to-ground flashes. This study also presents vertical profiles of the mass of lightning NO(x), after convection based on 3-D cloud-scale model simulations. The results suggest that following convection, a large percentage of lightning NO(x), remains in the middle and upper troposphere where it originated, while only a small percentage is found near the surface. The results of this work differ from profiles calculated from 2-D cloud-scale model simulations with a simpler lightning parameterization that were peaked near the surface and in the upper troposphere (referred to as a "C-shaped" profile). The new model results (a backward C-shaped profile) suggest that chemical transport models that assume a C-shaped vertical profile of lightning NO(x) mass may place too much mass neat the surface and too little in the middle troposphere.
Ott, Lesley↗
A Simulation Model of Carbon Cycling and Methane Emissions in Amazon Wetlands
An integrative carbon study is investigating the hypothesis that measured fluxes of methane from wetlands in the Amazon region can be predicted accurately using a combination of process modeling of ecosystem carbon cycles and remote sensing of regional floodplain dynamics. A new simulation model has been build using the NASA- CASA concept for predicting methane production and emission fluxes in Amazon river and floodplain ecosystems. Numerous innovations area being made to model Amazon wetland ecosystems, including: (1) prediction of wetland net primary production (NPP) as the source for plant litter decomposition and accumulation of sediment organic matter in two major vegetation classes - flooded forests (varzea or igapo) and floating macrophytes, (2) representation of controls on carbon processing and methane evasion at the diffusive boundary layer, through the lake water column, and in wetland sediments as a function of changes in floodplain water level, (3) inclusion of surface emissions controls on wetland methane fluxes, including variations in daily surface temperature and of hydrostatic pressure linked to water level fluctuations. A model design overview and early simulation results are presented.
Potter, Christopher↗
Significant impact of forcing uncertainty in a large ensemble of climate model simulations
Forcing due to solar and volcanic variability, on the natural side, and greenhouse gas and aerosol emissions, on the anthropogenic side, are the main inputs to climate models. Reliable climate model simulations of past and future climate change depend crucially upon them. Here we analyze large ensembles of simulations using a comprehensive Earth System Model to quantify uncertainties in global climate change attributable to differences in prescribed forcings. The different forcings considered here are those used in the two most recent phases of the Coupled Model Intercomparison Project (CMIP), namely CMIP5 and CMIP6. We show significant differences in simulated global surface air temperature due to volcanic aerosol forcing in the second half of the 19th century and in the early 21st century. The latter arise from small-to-moderate eruptions incorporated in CMIP6 simulations but not in CMIP5 simulations. We also find significant differences in global surface air temperature and Arctic sea ice area due to anthropogenic aerosol forcing in the second half of the 20th century and early 21st century. These differences are as large as those obtained in different versions of an Earth System Model employing identical forcings. In simulations from 2015 to 2100, we find significant differences in the rates of projected global warming arising from CMIP5 and CMIP6 concentration pathways that differ slightly but are equivalent in terms of their nominal radiative forcing levels in 2100. Our results highlight the influence of assumptions about natural and anthropogenic aerosol loadings on carbon budgets, the likelihood of meeting Paris targets, and the equivalence of future forcing scenarios.
54 ENVIRONMENTAL SCIENCES↗
A Statistical Framework for Evaluating Rain Microphysics in Model Simulations and Disdrometer Observations
Abstract Statistical analyses of a large disdrometer data set and a diverse set of model simulations for convection using the Regional Atmospheric Modeling System were conducted, with the mutual goal of providing insights into precipitation formation and microphysical processes. We demonstrate that a two‐moment bulk microphysical model successfully captures the dominant observed modes of variability in rainfall related to rainfall intensity and raindrop size distributions. The model reproduced the general distribution of observed precipitation groups (PGs) derived from Principal Component Analysis. The multi‐variable analysis also uncovered some shortcomings in the model as well as limitations of the disdrometer data. The model solutions were constrained in their predicted drop size distributions (DSDs) due to the fixed DSD parameters assumed in a two‐moment microphysics scheme. A case study from the Mid‐latitude Continental Clouds and Convection Experiment field project demonstrated how model results can be used to contextualize the disdrometer observations which are limited in sample size, spatial coherence, and detection of small drops and low drop concentrations. The case study also showed that the spatial patterns of the statistically derived PGs revealed by the model are consistent with the hypothesized microphysical processes that determine surface rain DSDs. This work demonstrates how leveraging the strengths of observations and models together can improve our understanding and representation of rain microphysical processes.
54 ENVIRONMENTAL SCIENCES↗
An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space
In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.
97 MATHEMATICS AND COMPUTING↗
Simulation model of the F/A-18 high angle-of-attack research vehicle utilized for the design of advanced control laws
The 'f18harv' six degree-of-freedom nonlinear batch simulation used to support research in advanced control laws and flight dynamics issues as part of NASA's High Alpha Technology Program is described in this report. This simulation models an F/A-18 airplane modified to incorporate a multi-axis thrust-vectoring system for augmented pitch and yaw control power and actuated forebody strakes for enhanced aerodynamic yaw control power. The modified configuration is known as the High Alpha Research Vehicle (HARV). The 'f18harv' simulation was an outgrowth of the 'f18bas' simulation which modeled the basic F/A-18 with a preliminary version of a thrust-vectoring system designed for the HARV. The preliminary version consisted of two thrust-vectoring vanes per engine nozzle compared with the three vanes per engine actually employed on the F/A-18 HARV. The modeled flight envelope is extensive in that the aerodynamic database covers an angle-of-attack range of -10 degrees to +90 degrees, sideslip range of -20 degrees to +20 degrees, a Mach Number range between 0.0 and 2.0, and an altitude range between 0 and 60,000 feet.
Strickland, Mark E.↗
Enhancing Long-Term Trend Simulation of OH Through the Synergy of Model Simulations and Aura Ozone Monitoring Instrument (OMI) NO 2 and HCHO Retrievals
During the last few years, tremendous progress has been made to develop an efficient parameterization module using agile machine learning techniques. The aim of this module is to provide dynamic response of the tropospheric hydroxyl radical (OH) to its major drivers, including trace gases, aerosols, clouds, and meteorology. This module, named ECCOH (pronounced “echo”) and implemented in NASA’s GEOS-5 global model, offers an unrealized opportunity to unravel the convoluted response of OH to its underlying drivers while approaching the accuracy of full-chemistry without incurring excessive computational costs, making it suitable for climate models. However, the accurate representation of OH in ECCOH poses challenges due to the lack of representation of some of its critical inputs such as the abundance of NO 2 and HCHO concentrations. As such, we leverage the well-characterized satellite observations of NO2 and HCHO columns from Aura OMI to enhance their representation in ECCOH using an optimal interpolation method for the time period of 2005 - present. We show how the inclusion of OMI information can affect the spatiotemporal variability and long-term trends of OH, CO, and CH 4 across the globe. Additionally, we underscore the necessity of obtaining high-fidelity information regarding tropospheric ozone from the southern hemisphere from space, a region currently lacking full verification in models, posing a challenge to get a reasonable amount of chemical sink for CH 4 .
OH↗
Monthly averages of ED2 model simulations initialized with airborne lidar structure, Jan 1981-Dec 2018, Brazilian Amazon
Deforestation and forest degradation (selective logging, fires, fragmentation) have impacted nearly 40% of the original extent of the Brazilian Amazon, and have markedly impacted forest structure across the region. To date, few studies analysed how shifts in forest structure from degradation influence the forest sensitivity to climate extremes, because of the complex interactions between forest structure and micro-environmental conditions. To address this knowledge gap, we carried out a series of simulations across the Brazilian Amazon using the Ecosystem Demography Model (ED2), using observed forest structure derived from 541 airborne lidar transects (375 ha each) and two scenarios representing forest recovery and expansion of degradation to investigate how shifts in forest structure impact ecosystem function under near-average and extreme climate conditions, as part of the manuscript Longo et al 2025 "Degradation and Deforestation Increase the Sensitivity of the Amazon Forest to Climate Extremes". This dataset provides the output results from the ED2 model simulations for the three simulations at monthly time scales, in NetCDF format. For all simulations, we used bias-corrected hourly reanalyses (WFDE5) for most meteorological drivers, except for precipitation, which was obtained from CHIRPS. The meteorological drivers used in the study span 38 years (Jan 1981–Dec 2018). The output results correspond to the last 38 years of simulation (one full cycle of meteorological drivers), in which ED2 simulations used static stand structure (i.e., the forest structure was held constant). The following files are provided:ED2_emean_Global_R004_BrAmaz_s1c0t0l0f0.nc. This corresponds to the Control simulation. The forest structure was obtained from the airborne lidar.ED2_emean_Global_R005_BrAmaz_s1c0t1l1f0.nc. This corresponds to the Degraded simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that expanded deforestation and selective logging across the Amazon.ED2_emean_Global_R006_BrAmaz_s1c0t1l0f0.nc. This corresponds to the Recovery simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that completely halted deforestation and degradation, allowing degraded forests to recover for 38 years.We also provide file ED2_zones_R004_BrAmaz_s1c0t0l0f0.nc, which classifies each grid cell into zones used in the reference manuscript: 1: Southeast. 2: South. 3: West. 4: Central. 5: Northeast. 6: North. 7: Northwest". Index 0 corresponds to grid cells excluded from sub-region analyses because they were dominated by flooded forests, deforestation, and naturally non-forest vegetation.
54 ENVIRONMENTAL SCIENCES↗
The Quasi-Biennial Oscillation in Model-Simulated and Observed Equatorial Temperature of the Lower Stratosphere
In an otherwise thorough survey of metrics for models that simulate the Quasi-Biennial Oscillation, Schenzinger et al. say “there is no comparable observational dataset” to compare with model-simulated stratospheric temperatures (Geosci. Model Dev. 10, 2157-2168, 2017). They compare model temperatures only with reanalysis datasets, which come from numerical weather prediction models and therefore are not direct observations. But stratospheric brightness temperatures have been directly observed by microwave radiometers on board a series of satellites since 1979. Christy and Drouilhet (J. Climate 7, 106-120, 1994) found a QBO signal in 1979-1992 data from the Microwave Sounding Unit’s lower stratospheric Channel 4 (with peak weighting function at the 75hPa pressure level and half-power values at 120 and 40hPa, about 20±5 km altitude). To detect the QBO signal, Christy and Drouilhet used a latitude weighting that matches the QBO’s anti-correlation between the Equator and ±15°. Fernandez et al. also found a QBO signal in 1979-2000 MSU data, using EOF analysis (J. Climate 17, 3934-3946, 2004). Recently, Christy and Covey extended Christy and Drouilhet’s analysis through 2017 (“Stratospheric Temperature,” Section 2b5 in State of the Climate in 2017. Bull. Amer. Meteor. Soc. 99, S150–S152; Figure 2.10c). The QBO signal was again clearly visible. Although temperature trends for the lower atmosphere are sensitive to inter-satellite calibration and other processing details, giving rise to some controversy, data for the lower stratosphere are more robust. Christy and Covey’s Figure 2.9 shows that data processed separately by the National Oceanic and Atmospheric Administration (NOAA) and by Remote Sensing Systems (RSS) gives a QBO index that is virtually identical to that of Christy’s group at the University of Alabama at Huntsville (UAH).
58 GEOSCIENCES↗