Predicting plastic anisotropy using crystal plasticity and Bayesian neuralnetwork surrogate models.
Abstract not provided.
Lim, Hojun↗
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Data-driven plastic anisotropy predictions using crystal plasticity and deep learning models .
Abstract not provided.
Lim, Hojun↗
Investigating plastic anisotropy using crystal plasticity and deep learning models .
Abstract not provided.
Lim, Hojun↗
A computerized engineering model for evaporative water cooling towers
Explore the source record for details and available documents.
Park, J. E.↗
NASA-GRA--Geared-Rotor Analyzer
NASA-GRA computer program designed to solve for steady-state dynamic responses of multigeared rotor systems. Based on transfer-matrix method combined with harmonic-balance method. Includes accurate gear-mesh model for spur and helical gears, containing time-varying mesh stiffnesses, gear-mounting errors, and gear-profile errors. Also includes accurate disk model containing inertia-based dynamic coupling terms due to mass and skew unbalances and massless-elastic-shaft model and linearly coupled fluid-film bearing model. Written in FORTRAN 77.
Park, N.↗
Parameter identification and modeling of longitudinal aerodynamics
Using a comprehensive flight test database and a parameter identification software program produced at NASA Ames Research Center, a math model of the longitudinal aerodynamics of the Harrier aircraft was formulated. The identification program employed the equation error method using multiple linear regression to estimate the nonlinear parameters. The formulated math model structure adhered closely to aerodynamic and stability/control theory, particularly with regard to compressibility and dynamic manoeuvring. Validation was accomplished by using a three degree-of-freedom nonlinear flight simulator with pilot inputs from flight test data. The simulation models agreed quite well with the measured states. It is important to note that the flight test data used for the validation of the model was not used in the model identification.
Aksteter, J. W.↗
Mapping the Extent of Mangrove Ecosystem Degradation by Integrating an Ecological Conceptual Model with Satellite Data
Anthropogenic and natural disturbances can cause degradation of ecosystems, reducing their capacity to sustain biodiversity and provide ecosystem services. Understanding the extent of ecosystem degradation is critical for estimating risks to ecosystems, yet there are few existing methods to map degradation at the ecosystem scale and none using freely available satellite data for mangrove ecosystems. In this study, we developed a quantitative classification model of mangrove ecosystem degradation using freely available earth observation data. Crucially, a conceptual model of mangrove ecosystem degradation was established to identify suitable remote sensing variables that support the quantitative classification model, bridging the gap between satellite-derived variables and ecosystem degradation with explicit ecological links. We applied our degradation model to two case-studies, the mangroves of Rakhine State, Myanmar, which are severely threatened by anthropogenic disturbances, and Shark River within the Everglades National Park, USA, which is periodically disturbed by severe tropical storms. Our model suggested that 40% (597 km2) of the extent of mangroves in Rakhine showed evidence of degradation. In the Everglades, the model suggested that the extent of degraded mangrove forest increased from 5.1% to 97.4% following the Category 4 Hurricane Irma in 2017. Quantitative accuracy assessments indicated the model achieved overall accuracies of 77.6% and 79.1% for the Rakhine and the Everglades, respectively. We highlight that using an ecological conceptual model as the basis for building quantitative classification models to estimate the extent of ecosystem degradation ensures the ecological relevance of the classification models. Our developed method enables researchers to move beyond only mapping ecosystem distribution to condition and degradation as well. These results can help support ecosystem risk assessments, natural capital accounting, and restoration planning and provide quantitative estimates of ecosystem degradation for new global biodiversity targets.
Calvin K. F. Lee↗
Hypertriton puzzle in relativistic heavy-ion collisions
The yields of hadrons and light nuclei in relativistic collisions of heavy-nuclei at a center of mass energy of $\sqrt{s_{NN}}$ = 2.6 TeV can be described remarkably well by a thermal distribution of an ideal gas of hadrons and light nuclei interacting only via the decay of resonances. Given the particularly small binding energy of hypertritons relative to the temperature describing the yields (about 156 MeV), one might naturally expect hypertrions to dissociate in medium, making the agreement of hypertriton yields with thermal predictions highly puzzling. The puzzle is compounded by the fact that small binding energy is associated with the large size of the hypertriton. This size is on a similar scale to the overall size of the fireball and much larger than the length scale over which temperatures in the fireball vary over phenomenologically relevant amounts. Here, this paper quantifies the tension this effect causes and shows that it is sufficiently large to render the thermal model inconsistent: its natural assumptions are in conflict with its outputs. The possibility that hypertritons are formed at freeze out as compact objects, quark droplets, that subsequently evolve into hypertritons is considered as a way to resolve the puzzle. It is noted that beyond making the assumption that compact quark droplets form, additional detailed dynamical assumptions which have not been justified are needed to make the thermal model work. The issue of why, despite these issues, the hypertriton is well described by a simple statistical description at freeze out is unresolved. Resolving the hypertriton puzzle is important as it may clarify whether the phenomenological success of the simple thermal model for yields accurately reflects the simple picture of the underlying physics on which it is based.
hydrodynamic models↗
Debunking common myths in coastal circulation modeling
Despite tremendous progress in algorithm development, computational efficiency and transition into operations over the past two decades, coastal modeling still lacks scientific rigor due to proliferation of many ‘gray’ areas related to various modeling choices made by modelers. Here, in this paper, we propose some guiding principles for the modeling community to improve performance, and we also debunk commonly held myths that make the coastal modeling lack rigor. Using our own experience in developing seamless cross-scale unstructured-grid based models for the past two decades, we describe in unprecedented detail the end-to-end modeling process (i.e., from digital elevation models (DEMs) to mesh generation to post analysis), and demonstrate that defensible modeling is within reach for any end user by following three guiding principles: (1) Bathymetry is a first order forcing in coastal domains and thus should be respected in all aspects of modeling; (2) Oceanographic processes are driven across multiple spatial scales and so models should enable appropriate resolution as needed; and (3) Model assessment should focus on physical processes. Through qualitative and quantitative model assessments, we demonstrate the fundamental role played by bathymetry/topography as embedded in DEMs in making the results defensible, which is unfortunately glossed over in many modeling studies. Focusing on process-based assessment simplifies the calibration process. A major conclusion of this work is that model developers and operators should maximize the scientific rigor for in silico oceanography by avoiding some common pitfalls that rely on error compensation at the expense of representation of physical system processes. We present some best practice procedures for defensive and trustworthy numerical modeling.
54 ENVIRONMENTAL SCIENCES↗
Imaging radar polarimetry from wave synthesis
It was shown that it is possible to measure the complete scattering matrix of an object using data acquired on a single aircraft pass, and can combine the signals later in the data processor to generate radar images corresponding to any desired combination of transmit and receive polarization. Various scattering models predict different dependence on polarization state of received power from an object. The imaging polarimeter permits determination of this dependence, which is called the polarization signature, of each point in a radar image. Comparison of the theoretical predictions and observational data yield identification of possible scattering mechanisms for each area of interest. It was found that backscatter from the ocean is highly polarized and well-modeled by Bragg scattering, while scattering from trees in a city park possesses a considerable unpolarized component. Urban regions exhibit the characteristics expected from dihedral corner reflectors and their polarization signatures are quite different from the one-bounce Bragg model.
Zebker, Howard A.↗
Imaging radar polarimetry from wave synthesis
It is shown that it is possible to measure the complete scattering matrix of an object using data acquired on a single aircraft pass, and combine the signals later in the data processor to generate radar images corresponding to any desired combination of transmit and receive polarization. Various scattering models predict different dependence on polarization state of received power from an object. The imaging polarimeter permits determination of this dependence, the polarization signature, of each point in a radar image. Comparison of predictions and observational data reveals scattering mechanisms for each area of interest. Backscatter from the ocean is highly polarized and well-modeled by Bragg scattering, while scattering from trees in a city park possesses a considerable unpolarized component. Urban regions exhibit the characteristics expected from dihedral corner reflectors, and their polarization signatures are quite different from the on-bounce Bragg model.
Zebker, H. A.↗
Modeling charging infrastructure impact on the electric vehicle market in China
The plug-in electric vehicle (PEV) is deemed as a critical technological revolution, and the governments are imposing various vehicle policies to promote its development. Meanwhile, the market success of PEVs depends on many aspects. The study reported herein integrates one’s use of charging infrastructure at home, public place and workplace into the market dynamics analysis tool, New Energy and Oil Consumption Credits (NEOCC) model, to systematically assess the charging infrastructure (home parking ratio, public charging opportunity, and charging costs) impact on PEV ownership costs and analyze how the PEV market shares may be affected by the attributes of the charging infrastructure. Compared to the charging infrastructure, the impact of battery costs is incontrovertibly decisive on PEV market shares, the charging infrastructure is still non-negligible in the PEV market dynamics. The simulation results find that the public charging infrastructure has more effectiveness on promoting the PEV sales in the PEV emerging market than it does in the PEV mature market. However, the improvement of charging infrastructure does not necessarily lead to a larger PEV market if the charging infrastructure incentives do not coordinate well with other PEV policies. Besides, the increase of public charging opportunities has limited motivations on the growth of public PEV fleets, which are highly correlated to the number of public fast charging stations or outlets. It also finds that more home parking spaces can stimulate more sales of personal plug-in hybrid electric vehicles instead of personal battery electric vehicles.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Data for KETCHUP: Parameterizing of Large-Scale Kinetic Models Using Multiple Datasets with Different Reference States
Repository for Kinetic Estimation Tool Capturing Heterogeneous Datasets Using Pyomo (KETCHUP), a flexible parameter estimation tool that leverages a primal-dual interior-point algorithm to solve a nonlinear programming (NLP) problem that identifies a set of parameters capable of recapitulating the steady-state fluxes and concentrations in wild-type and perturbed metabolic networks. KETCHUP can use K-FIT [2] input files. Example K-FIT input files are located in the K-FIT repository at https://github.com/maranasgroup/K-FIT.
Metabolomics↗
Tropospheric aerosols over the western North Atlantic Ocean during the winter and summer deployments of ACTIVATE 2020: life cycle, transport, and distribution
The Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) is a NASA mission to characterize aerosol–cloud interactions over the western North Atlantic Ocean (WNAO). Such characterization requires understanding of life cycle, composition, transport pathways, and distribution of aerosols over the WNAO. This study uses the GEOS-Chem model to simulate aerosol distributions and properties that are evaluated against aircraft, ground-based, and satellite observations during the winter and summer field deployments in 2020 of ACTIVATE. Transport in the boundary layer (BL) behind cold fronts was a major mechanism for the North American continental outflow of pollution to the WNAO in winter. Turbulent mixing was the main driver for the upward transport of sea salt within and ventilation out of BL in winter. The BL aerosol composition was dominated by sea salt, which increased in the summer, followed by organics and sulfate. Aircraft in situ aerosol measurements provided useful constraints on wet scavenging in GEOS-Chem. The model generally captured observed features such as continental outflow, land–ocean gradient, and mixing of anthropogenic aerosols with sea salt. Model sensitivity experiments with elevated smoke injection heights to the mid-troposphere (versus within BL) better reproduced observations of smoke aerosols from the western US wildfires over the WNAO in the summer. Model analysis suggests strong hygroscopic growth of sea salt particles and their seeding of marine BL clouds over the WNAO (< 35° N). Future modeling efforts should focus on improving parameterizations for aerosol wet scavenging, implementing realistic smoke injection heights, and applying high-resolution models that better resolve vertical transport.
54 ENVIRONMENTAL SCIENCES↗
An assessment of potential weather effects due to operation of the Space Orbiting Light Augmentation Reflector Energy System (SOLARES)
Implementation of SOLARES will input large quantities of heat continuously into a stationary location on the Earth's surface. The quantity of heat released by each of the SOlARES ground receivers, having a reflector orbit height of 6378 km, exceeds by 30 times that released by large power parks which were studied in detail. Using atmospheric models, estimates are presented for the local weather effects, the synoptic scale effects, and the global scale effects from such intense thermal radiation.
Allen, N. C.↗
Space station needs, attributes, and architectural options. Volume 1. Executive summary
The initial space station should be manned, placed in 28.5 deg orbit, and provide substantial economic, performance, and social benefits. The most beneficial space station capabilities include: a space test facility; a transport harbor; satellite servicing and assembly; and an observatory. A space industrial park could be added once further development effort validates the cost and expanding commercial market for space processed materials. The potential accrued gross mission model benefit derived from these capabilities is $5.9B without the industrial park, and $9.3B with it. An unclassified overview of all phases of the study is presented.
Pritchard, E. B.↗