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Results obtained using a vortex filament model, as opposed to sheets are discussed, against using various modeling techniques and including the computer codings.
Results from the fully and biogeochemically coupled simulations in which CO 2 increases at a rate of 1 % yr –1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon–concentration and carbon–climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO 2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent (sixth) Coupled Model Intercomparison Project (CMIP6) and compared with eight models from the fifth CMIP (CMIP5). The strength of the carbon–concentration feedback is of comparable magnitudes over land (mean ± standard deviation = 0.97 ± 0.40 PgC ppm –1 ) and ocean (0.79 ± 0.07 PgC ppm –1 ), while the carbon–climate feedback over land (–45.1 ± 50.6 PgC °C –1 ) is about 3 times larger than over ocean (–17.2 ± 5.0 PgC °C –1 ). The strength of both feedbacks is an order of magnitude more uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77 ± 0.37 °C EgC –1 and is similar to that found in CMIP5 models (1.63 ± 0.48 °C EgC –1 ) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.
Formulation is presented to demonstrate the significance of a simplified radiation model in investigating the flow-phenomena in the viscous radiating shock layer of a Jovian entry body. For this, a nongray absorption model for hydrogen-helium gas is developed which consists of 30 steps over the spectral range of 0-20 eV. By employing this model results were obtained for temperature, pressure, density, and radiative flux in the shock layer and along the body surface. These are compared with results of two sophisticated radiative transport models available in the literature. Use of the present radiation model results in significant reduction in computational time. Results of this model are found to be in general agreement with results of other models. It is concluded that use of the present model is justified in investigating the flow phenomena around a Jovian entry body because it is relatively simple, computationally fast, and yields fairly accurate results.
Results of acoustic tests of three 62.2 cm (24.5 inch) diameter models of the prop-fan (a small diameter, highly loaded. Multi-bladed variable pitch advanced turboprop) are presented. Results show that there is little difference in the noise produced by unswept and slightly swept designs. However, the model designed for noise reduction produces substantially less noise at test conditions simulating 0.8 Mach number cruise speed or at conditions simulating takeoff and landing. In the near field at cruise conditions the acoustically designed. In the far field at takeoff and landing conditions the acoustically designed model is 5 db quieter than unswept or slightly swept designs. Correlation between noise measurement and theoretical predictions as well as comparisons between measured and predicted acoustic pressure pulses generated by the prop-fan blades are discussed. The general characteristics of the pulses are predicted. Shadowgraph measurements were obtained which showed the location of bow and trailing waves.
Results of computations are presented using vortex sheets to model the wake and test the sensitivity of the solutions to various assumptions used in the development of the models. The complete codings are included.
This work presents new vapor-liquid data for the pure components 2-dimethylmonoethanolamine (DMMEA) and N-methylethanolamine (MMEA) and for the binary systems of aqueous methyldiethanolamine (MDEA), DMMEA, MMEA, and 1-(2-aminoethyl)piperazine (AEP). New Antoine models are developed for the pure component systems, and new and improved NRTL models for the binary systems. In the model development, together with new data from this work, all available data on VLE, excess heat of mixing, H E , freezing point depression, and specific heat were gathered, evaluated and used selectively for parameter optimization. Emphasis has been put on a best possible representation of amine volatility to enable reasonable predictions of amine emissions from absorption plants and to form a basis for subsequent models of ternary systems with CO 2 . In conclusion, model predictions are compared with experimental results and other models, source by source, and the overall results are satisfactory.
The periods of May 27 - June 5, 2017 and Oct 24 — 29, 2016 are 'unusual' in terms of radiation belt dynamics and their solar wind driving conditions. The first period was under the influence of a slow CME-led major geomagnetic storm with Dstmin = -125 nT and the second period was under high speed solar wind streams. Observations from Van Allen Probes show great variabilities in different electron energy channels for both periods. During the second period of Oct 24 - 29, 2016, electron fluxes are found to be near the highest upper limit among various storms during 2013–2018 (Hua, Bortnik and Ma, 2022). In this paper, we provide solar wind sources and geomagnetic conditions for these two storm periods and point out challenges in understanding, modeling, and forecasting radiation belt dynamics. In-depth analysis of modeling results utilizing radiation belt models available at the Community Coordinated Modeling Center such as VERB and CIMI will be performed. Initial modeling results indicate rather large discrepancies with the observations. Model validation using different metrics introduced in Zheng et al. (2019) will be carried out to gain a deeper understanding of the physical processes involved and to identity potential causes of modeling inadequacies.
Results are presented that demonstrate how good reduced-order models can be obtained directly by recursive parameter identification using input/output (I/O) data of high-order nonlinear systems. Three different methods of obtaining a third-order linear model from a seventh-order nonlinear turbojet engine model are compared. The first method is to obtain a linear model from the original model and then reduce the linear model by standard reduction techniques such as residualization and balancing. The second method is to identify directly a third-order linear model by recursive least-squares parameter estimation using I/O data of the original model. The third method is to obtain a reduced-order model from the original model and then linearize the reduced model. Frequency responses are used as the performance measure to evaluate the reduced models. The reduced-order models along with their Bode plots are presented for comparison purposes.
The effect of ice cover on ocean-wave attenuation is investigated for waves under flexure in the marginal ice zone (MIZ) with SAR image spectra and the results of models. Directional wavenumber spectra are taken from the SAR image data, and the wave-attenuation rate is evaluated with SAR image spectra and by means of the model by Liu and Mollo-Christensen (1988). Eddy viscosity is described by means of dimensional analysis as a function of ice roughness and wave-induced velocity, and comparisons are made with the remotely sensed data. The model corrects the open-water model by introducing the effects of a continuous ice sheet, and turbulent eddy viscosity is shown to depend on ice thickness, floe sizes, significant wave height, and wave period. SAR and wave-buoy data support the trends described in the model results, and a characteristic rollover is noted in the model and experimental wave-attenuation rates at high wavenumbers.
Many tools can be used to visualize field and state variables for a single scale analysis so that the influence of relevant mechanisms can be evaluated. Finite element software is often utilized to simulate a unit cell of a material and visualize results at that scale. Material properties can be homogenized from individual constituents and local deformation, damage, and failure mechanisms can be evaluated within the unit cell due to globally applied boundary conditions. Such solutions can produce satisfactory results if a user is only interested in analyzing a single scale. But materials in general contain features across multiple length scales, and assumptions must be made when attempting to account for lower length scale phenomena within a higher length scale model. Multiscale modeling is an attractive means to model materials because detailed material responses can be tracked across multiple disparate length scales while reducing the amount of required assumptions. However, as the complexity of these models increases, a large amount of data can be produced, and data traceability can become increasingly more difficult. Field and state variables, which are naturally dependent on spatial position, may themselves be calculated from one or more lower length scale unit cell models each with their own appropriate field and state variables. The NASA Multiscale Analysis Tool (NASMAT) is one software that can be used to perform a multiscale analysis efficiently and output requested data at all length scales in the analysis. A companion open-source Python software, NASMAT PrePost, can be used to visualize NASMAT model results and rapidly interrogate multiscale data across multiple length scales. This presentation will demonstrate some of the key features of NASMAT PrePost on two multiscale problems by quickly displaying and demonstrating connectivity among multiscale results from large datasets.
This paper examines the sensitivity of Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperatures (Tbs) to surface roughness by a using radiative transfer model to simulate AMSR-E Tbs as a function of incidence angle at which the surface is viewed. The simulated Tbs are then used to examine the influence that surface roughness has on two operational sea ice algorithms, namely: 1) the National Aeronautics and Space Administration Team (NT) algorithm and 2) the enhanced NT algorithm, as well as the impact of roughness on the AMSR-E snow depth algorithm. Surface snow and ice data collected during the AMSR-Ice03 field campaign held in March 2003 near Barrow, AK, were used to force the radiative transfer model, and resultant modeled Tbs are compared with airborne passive microwave observations from the Polarimetric Scanning Radiometer. Results indicate that passive microwave Tbs are very sensitive even to small variations in incidence angle, which can cause either an over or underestimation of the true amount of sea ice in the pixel area viewed. For example, this paper showed that if the sea ice areas modeled in this paper mere assumed to be completely smooth, sea ice concentrations were underestimated by nearly 14% using the NT sea ice algorithm and by 7% using the enhanced NT algorithm. A comparison of polarization ratios (PRs) at 10.7,18.7, and 37 GHz indicates that each channel responds to different degrees of surface roughness and suggests that the PR at 10.7 GHz can be useful for identifying locations of heavily ridged or rubbled ice. Using the PR at 10.7 GHz to derive an "effective" viewing angle, which is used as a proxy for surface roughness, resulted in more accurate retrievals of sea ice concentration for both algorithms. The AMSR-E snow depth algorithm was found to be extremely sensitive to instrument calibration and sensor viewing angle, and it is concluded that more work is needed to investigate the sensitivity of the gradient ratio at 37 and 18.7 GHz to these factors to improve snow depth retrievals from spaceborne passive microwave sensors.
Results are presented from numerical simulations performed with the general circulation model (GCM) for winter and summer. The monthly mean simulated fields for each integration are compared with observed geographical distributions and zonal averages. In general, the simulated sea level pressure and upper level geopotential height field agree well with the observations. Well simulated features are the winter Aleutian and Icelandic lows, the summer southwestern U.S. low, the summer and winter oceanic subtropical highs in both hemispheres, and the summer upper level Tibetan high and Atlantic ridge. The surface and upper air wind fields in the low latitudes are in good agreement with the observations. The geographical distirbutions of the Earth-atmosphere radiation balance and of the precipitation rates over the oceans are well simulated, but not all of the intensities of these features are correct. Other comparisons are shown for precipitation along the ITCZ, rediation balance, zonally averaged temperatures and zonal winds, and poleward transports of momentum and sensible heat.
Results of NASA sponsored acoustic tests of three 2 ft. diameter models of the Prop-Fan (a small diameter, highly loaded, many-bladed variable pitch advanced turboprop) are presented. The highly swept model designed for noise reduction produces substantially less near field noise at simulated 0.8 Mach number cruise conditions than the unswept or slightly swept models. It also produces less far field noise at conditions simulating takeoff and landing. The noise reduction mechanism is discussed. Correlation between harmonic noise measurements and theoretical predictions and between measured and predicted acoustic pressure pulses is good. Shadowgraph measurements which show the location of blade associated wave patterns were obtained. Predicted and measured wave locations show good general agreement. Full scale near and far field noise is predicted.
Results of a July simulation produced by the UCLA general circulation model are analyzed with a view to improving the model. It is shown that while many features of the July climatology are well reproduced, others, such as the intensity of the jet streams in the upper troposphere, the frequency of cyclogenesis, the structure of the subtropical pressure belt in the Southern Hemisphere, and the precipitation are not well reproduced. It is suggested that the sources of error are related to inadequate vertical and horizontal resolutions, to the choice of upper boundary at 50 mb, to poor representation of topographically forced motions, and to the indirect coupling between the general circulation model and the planetary boundary model. The analysis has led to the introduction of major design changes in the model.
Results from an investigation to determine the low-speed tumbling characteristics of twelve generic flying-wing models are summarized. There is a concern that airplanes with flying-wing planforms could inadvertently enter an out-of-control tumbling motion under certain conditions. The objectives of this investigation were to: 1) identify the geometric and mass-related parameters that cause flying wings to be capable of sustained tumbling, 2) analyze some of the driving mechanisms that cause tumbling, and 3) determine the feasibility of using computer simulations to predict the tumbling characteristics of flying wings. Free-tumble and free-to-pitch tests were conducted with dynamically-scaled, generic flying wing models. The use of computer simulations as a predictive tool for tumbling was explored. Results indicated that center-of-gravity location, mass distribution, and geometric aspect ratio strongly affected the tumbling characteristics of the models tested and that positive static stability did not necessarily preclude tumbling. The magnitude of dynamic effects were found to be of the same order as static effects for the models undergoing autorotation-in-pitch. The simulations indicated that the dynamic terms in the equations of motion used to predict tumbling must be obtained using experimental methods that account for the large amplitude/high pitch-rate environment that characterizes tumbling.
A new bias flow impedance model is developed for perforated plates from basic principles using as little empiricisms as possible. A quality experimental database was used to determine the predictive validity of the model. Results show that the model performs better for higher (15%) rather than lower (5%) percent open area (POA) samples. Based on the least squares ratio of numerical vs. experimental results, model predictions were on average within 20% and 30% for the higher and lower (POA), respectively. It is hypothesized on the work of other investigators that at lower POAs the higher fluid velocities in the perforate's orifices start forming unsteady vortices, which is not accounted for in our model. The numerical model, in general also underpredicts the experiments. It is theorized that the actual acoustic C(sub D) is lower than the measured raylometer C(sub D) used in the model. Using a larger C(sub D) makes the numerical model predict lower impedances. The frequency domain model derived in this paper shows very good agreement with another model derived using a time domain approach.
A “screening analysis” is implemented at Pahute Mesa (PM), Nevada National Security Site (NNSS), to determine subsets of the 43 radionuclides listed in the radionuclide inventory of Finnegan et al. (2016) that are of relevance or potential relevance to the hydrologic source term (HST) for assessment of radionuclide transport in groundwater. Consideration is added to how levels of contamination are defined and whether any other radionuclides not in the inventory are relevant to the HST. A model is developed to estimate a range of possible source concentrations in groundwater that account for uncertainty in partitioning into melt glass and sorption into surrounding rock of the exchange zone for the 82 PM underground nuclear tests detonated in vertical shafts. The model also accounts for the varied hydrogeochemical settings. Transport parameters needed for the screening model calculations are developed from databases for hydrogeologic units, chemistry, mineralogy, fracture spacing, fracture aperture, fracture openness, matrix porosity, bulk density, saturation, and alteration. Of key importance is consideration of diagenetic zonation of the mineralogy related to hydrothermal alteration. The screening analysis compares model results with available groundwater radiochemistry data. Consistency between screening model results and available data helps validate the model for application to all 43 radionuclides, most of which have no measurements or only non-detect measurements of concentration in groundwater. The screening analysis determines that ten radionuclides – tritium, Sr-90, I-129, Cs-137, U-232, U-233, U-234, U-238, and the total of Pu-239 and Pu-240 are relevant to the HST. Determination of relevance is primarily based on data and/or model results indicating source concentration exceeding a maximum contaminant level (MCL) out to 100 years since the time of detonation. U-238 is relevant to assessment of contamination relative to MCLs for uranium and gross alpha particle activity. Five other radionuclides – C-14, Cl-36, Tc-99, Np-237, and Pu-238 – are determined potentially relevant to the HST based on a 0.1 MCL threshold. The screening analysis recommends additional attention to the natural daughter radionuclides of the uranium series (U-238) and thorium series (Th-232) decay chains, particularly Ra-226 and Ra-228, that were not included the inventory.
Objective: Real-time determination of human kinematics and kinetics could advance biomechanics research and enable valuable applications of biofeedback and generalizable exoskeleton control. Here, this work aims to investigate a taskindependent, user-independent method for obtaining precise realtime joint state estimation across lower-body joints during a wide variety of tasks. Methods: We developed a generalizable sensing approach using a suit comprised of inertial measurement units (IMUs) and pressure insoles. With the suit, we collected a dataset of 33 tasks commonly performed during construction and hazardous waste cleanup (N = 10). We then trained deep learning user-independent, task-agnostic models to estimate joint lowerbody kinematics and dynamics using only worn sensor data. We likewise computed joint kinematics and dynamics analytically from sensor data to serve as a comparison tool for model results. Results: Our models achieved overall angle estimation root-meansquared-errors (RMSE) of 6.56±.92°, 8.60±1.01°, 7.58±.89°, and 6.00±.73° compared to 13.9±.1.3°, 15.31±1.0°, 10.76±.70°, and 7.56±.48° via analytical methods at the lower back, hip, knee, and ankle, respectively. Likewise, our models achieved overall normalized moment estimation RMSEs of .207±.069 Nm/kg, .242±.044 Nm/kg, .202±.038 Nm/kg, and .193±.034 Nm/kg compared to .306±.036 Nm/kg, .407±.021 Nm/kg, 1.18 ±.022 Nm/kg, and 1.73±.071 Nm/kg via analytical methods at the lower back, hip, knee, and ankle, respectively. Conclusion: These results are comparable to other state-of-the-art wearable sensing systems, establishing deep learning as a viable sensing approach that generalizes to new users and tasks. Significance: This work shows promise for enabling accurate real-world biomechanical data collection and enhancement of biofeedback systems and wearable robot control.