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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

River Regulation Alleviates the Impacts of Climate Change on US Thermoelectricity Production

Climate change and anthropogenic activities can both influence stream temperature, which is a critical indicator of thermoelectric power generation potential. Previous studies emphasized the vulnerability of power-generation systems to climate warming (ref 1, 2). Despite the fact that two-thirds of the global rivers are regulated by dams (ref 3), the relative impacts of water management and climate change on stream temperature and thermoelectric production have not yet been evaluated. Using an integrated modeling system applied to the conterminous United States, simulations confirm the dominant role of climate change in shaping the future trends of stream temperature. However, water management, reservoir regulation in particular, can mitigate the stream temperature warming and reduce the frequency and magnitude of extreme high stream temperatures through redistribution of the seasonal streamflow. Moreover, water management can alleviate the loss of power plant usable capacity from climate change to the level of reduced warming from emission mitigation. By regulating the flow and temperature regimes, water management is a promising adaptation measure to alleviate climate change induced effects in the water-energy nexus.

Zhang, Xiao↗
NASA NTRS1983

Numerical experiments with a stochastic zonal climate model

A zonally averaged energy balance climate model is developed to generate zonal temperature variability through fluctuating meridional energy transports. Stochastic transport fluctuations are included in the model by multiplying the eddy diffusion coefficients by Gaussian random deviates. For a variability of eddy coefficients of 50 percent, the model is found to generate an interannual temperature variability of 0.03 K for the global temperature, and 0.04 and 0.05 K for the Northern and Southern Hemispheres, respectively. It is shown that the temperature variability level generated is linearly related to the transport variability level introduced. An increase in the level of model-generated temperature variability and a change in the shape of variance spectra of temperature anomaly time series are obtained by switching from the multiplicative noise model to an additive noise model. The results of these model studies are compared with a time series of central England temperatures as well as GCM generated climate variability.

Schneider, S. H.↗
NASA NTRS1986

A comparison of SIR-B directional ocean wave spectra with aircraft scanning radar spectra

Directional ocean wave spectra derived from Shuttle Imaging Radar-B (SIR-B) L-band imagery collected off the coast of Southern Chile on 11 and 12 October 1984 were compared with independent spectral estimates from two airborne scanning radars. In sea states with significant wave heights ranging from 3 to 5 meters, the SIR-B-derived sspectra at 18 deg and 25 deg off nadir yielded reasonable estimates of wavelengths, directions, and spectral shapes for all wave systems encountered, including a purely azimuth-traveling system. A SIR-B image intensity variance spectrum containing predominantly range-traveling waves closely resembles an independent aircraft estimate of the slope variance spectrum. The prediction of a U.S. Navy global spectral ocean wave model on 11 October 1984 exhibited no significant bias in dominant wave number but contained a directional bias of about 30 deg with respect to the mean of the aircraft and spacecraft estimates.

Beal, R. C.↗
NASA NTRS1992

Lyapunov function-based control laws for revolute robot arms - Tracking control, robustness, and adaptive control

A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).

Wen, John T.↗
NASA NTRS1992

Dynamic analysis of a pre-and-post ice impacted blade

The dynamic characteristics of an engine blade are evaluated under pre-and-post ice impact conditions using the NASA in-house computer code BLASIM. The ice impacts the leading edge of the blade causing severe local damage. The local structural response of the blade due to the ice impact is predicted via a transient response analysis by modeling only a local patch around the impact region. After ice impact, the global geometry of the blade is updated using deformations of the local patch and a free vibration analysis is performed. The effects of ice impact location, ice size and ice velocity on the blade mode shapes and natural frequencies are investigated. The results indicate that basic nature of the mode shapes remains unchanged after impact and that the maximum variation in natural frequencies occurs for the twisting mode of the blade.

Abumeri, G. H.↗
NASA NTRS2017

Is There a CME Rate Floor? CME and Magnetic Flux Values for the Last Four Solar Cycle Minima

The recent prolonged activity minimum has led to the question of whether there is a base level of the solar magnetic field evolution that yields a ''floor'' in activity levels and also in the solar wind magnetic field strength. Recently, a flux transport model coupled with magneto-frictional simulations has been used to simulate the continuous magnetic field evolution in the global solar corona for over 15 years, from 1996 to 2012. Flux rope eruptions in the simulations are estimated (Yeates), and the results are in remarkable agreement with the shape of the SOlar Heliospheric Observatory/Large Angle and Spectrometric Coronagraph Experiment coronal mass ejection (CME) rate distribution. The eruption rates at the two recent minima approximate the observed-corrected CME rates, supporting the idea of a base level of solar magnetic activity. In this paper, we address this issue by comparing annual averages of the CME occurrence rates during the last four solar cycle minima with several tracers of the global solar magnetic field. We conclude that CME activity never ceases during a cycle, but maintains a base level of 1 CME every 1.5 to approx. 3 days during minima. We discuss the sources of these CMEs.

Webb, D. F.↗
NASA NTRS1990

Statistical analysis of modeling error in structural dynamic systems

The paper presents a generic statistical model of the (total) modeling error for conventional space structures in their launch configuration. Modeling error is defined as the difference between analytical prediction and experimental measurement. It is represented by the differences between predicted and measured real eigenvalues and eigenvectors. Comparisons are made between pre-test and post-test models. Total modeling error is then subdivided into measurement error, experimental error and 'pure' modeling error, and comparisons made between measurement error and total modeling error. The generic statistical model presented in this paper is based on the first four global (primary structure) modes of four different structures belonging to the generic category of Conventional Space Structures (specifically excluding large truss-type space structures). As such, it may be used to evaluate the uncertainty of predicted mode shapes and frequencies, sinusoidal response, or the transient response of other structures belonging to the same generic category.

Hasselman, T. K.↗
DOE OSTI2021

A Parameterization of the Cloud Scattering Polarization Signal Derived From GPM Observations for Microwave Fast Radative Transfer Models

Microwave cloud polarized observations have shown the potential to improve precipitation retrievals since they are linked to the orientation and shape of ice habits. Stratiform clouds show larger brightness temperature (TB) polarization differences (PDs), defined as the vertically polarized TB (TBV) minus the horizontally polarized TB (TBH), with ~10 K PD values at 89 GHz due to the presence of horizontally aligned snowflakes, while convective regions show smaller PD signals, as graupel and/or hail in the updraft tend to become randomly oriented. The launch of the global precipitation measurement (GPM) microwave imager (GMI) has extended the availability of microwave polarized observations to higher frequencies (166 GHz) in the tropics and midlatitudes, previously only available up to 89 GHz. This study analyzes one year of GMI observations to explore further the previously reported stable relationship between the PD and the observed TBs at 89 and 166 GHz, respectively. The latitudinal and seasonal variability is analyzed to propose a cloud scattering polarization parameterization of the PD-TB relationship, capable of reconstructing the PD signal from simulated TBs. Given that operational radiative transfer (RT) models do not currently simulate the cloud polarized signals, this is an alternative and simple solution to exploit the large number of cloud polarized observations available. Finally, the atmospheric radiative transfer simulator (ARTS) is coupled with the weather research and forecasting (WRF) model, in order to apply the proposed parameterization to the RT simulated TBs and hence infer the corresponding PD values, which show to reproduce the observed GMI PDs well.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A combined experimental and numerical approach that eliminates the non-uniqueness associated with the Johnson-Cook parameters obtained using inverse methods

Abstract Johnson-Cook constitutive model is a commonly used material model for machining simulations. The model includes five parameters that capture the initial yield stress, strain-hardening, strain-rate hardening, and thermal softening behavior of the material. These parameters are difficult to determine using experiments since the conditions observed during machining (such as high strain-rates of the order of $$10^5$$ 10 5 /sec - $$10^6$$ 10 6 /sec) are challenging to recreate in the laboratory. To address this problem, several researchers have recently proposed inverse approaches where a combination of experiments and analytical models are used to predict the Johnson-Cook parameters. The errors between the measured cutting forces, chip thicknesses and temperatures and those predicted by analytical models are minimized and the parameters are determined. In this work, it is shown that only two of the five Johnson-Cook parameters can be determined uniquely using inverse approaches. Two different algorithms, namely, Adaptive Memory Programming for Global Optimization (AMPGO) and Particle Swarm Optimization (PSO), are used for this purpose. The extended Oxley’s model is used as the analytical tool for optimization. For determining a parameter’s value, a large range for each parameter is provided as an input to the algorithms. The algorithms converge to several different sets of values for the five Johnson-Cook parameters when all the five parameters are considered as unknown in the optimization algorithm. All of these sets, however, yield the same chip shape and cutting forces in FEM simulations. Further analyses show that only the strain-rate and thermal softening parameters can be determined uniquely and the three parameters present in the strain-hardening term of the Johnson-Cook model cannot be determined uniquely using the inverse method. A combined experimental and numerical approach is proposed to eliminate this determine all parameters uniquely.

42 ENGINEERING↗
NASA NTRS1991

A detailed numerical investigation of Burke-Schumann gaseous and spray flames

The classical Burke-Schumann gaseous diffusion flame, and the effect of introducing fuel in the form of liquid sprays are investigated numerically. The time-dependent two-dimensional, axisymmetric conservation equations are solved for the gas phase. A Lagrangian approach is used for the dispersed phase. The chemical reactions are modeled through the one-step global reaction scheme. The numerical results show that the computed flame structure is significantly different from that given by the analytical solution. The computed flame is about 15 percent longer and 5 percent narrower than the classical Burke-Schumann flame. The predicted flame shape is, however, in better agreement with experimental observations than the Burke-Schumann flame. The effects of introducing liquid sprays is found to produce thinner and longer flames than its counterpart gaseous flame. A detailed comparison of the structures of gaseous and spray flames is made, and the differences are discussed.

Mawid, M. A.↗
DOE OSTI2023

Human‐induced salinity changes impact marine organisms and ecosystems

Abstract Climate change is fundamentally altering marine and coastal ecosystems on a global scale. While the effects of ocean warming and acidification on ecology and ecosystem functions and services are being comprehensively researched, less attention is directed toward understanding the impacts of human‐driven ocean salinity changes. The global water cycle operates through water fluxes expressed as precipitation, evaporation, and freshwater runoff from land. Changes to these in turn modulate ocean salinity and shape the marine and coastal environment by affecting ocean currents, stratification, oxygen saturation, and sea level rise. Besides the direct impact on ocean physical processes, salinity changes impact ocean biological functions with the ecophysiological consequences are being poorly understood. This is surprising as salinity changes may impact diversity, ecosystem and habitat structure loss, and community shifts including trophic cascades. Climate model future projections (of end of the century salinity changes) indicate magnitudes that lead to modification of open ocean plankton community structure and habitat suitability of coral reef communities. Such salinity changes are also capable of affecting the diversity and metabolic capacity of coastal microorganisms and impairing the photosynthetic capacity of (coastal and open ocean) phytoplankton, macroalgae, and seagrass, with downstream ramifications on global biogeochemical cycling. The scarcity of comprehensive salinity data in dynamic coastal regions warrants additional attention. Such datasets are crucial to quantify salinity‐based ecosystem function relationships and project such changes that ultimately link into carbon sequestration and freshwater as well as food availability to human populations around the globe. It is critical to integrate vigorous high‐quality salinity data with interacting key environmental parameters (e.g., temperature, nutrients, oxygen) for a comprehensive understanding of anthropogenically induced marine changes and its impact on human health and the global economy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Data optimization for large batch distributed training of deep neural networks

Distributed training in deep learning (DL) is common practice as data and models grow. The current practice for distributed training of deep neural networks faces the challenges of communication bottlenecks when operating at scale, and model accuracy deterioration with an increase in global batch size. Present solutions focus on improving message exchange efficiency as well as implementing techniques to tweak batch sizes and models in the training process. The loss of training accuracy typically happens because the loss function gets trapped in a local minima. We observe that the loss landscape minimization is shaped by both the model and training data and propose a data optimization approach that utilizes machine learning to implicitly smooth out the loss landscape resulting in fewer local minima. Our approach filters out data points which are less important to feature learning, enabling us to speed up the training of models on larger batch sizes to improved accuracy.

Gahlot, Shubhankar↗
DOE OSTI2024

Large-Eddy Simulation Study of Flow and Combustion Dynamics in a Full-Scale Hydrogen–Air Rotating Detonation Combustor-Stator Integrated System

In the present work, a first-of-its-kind three-dimensional (3D) large-eddy simulation (LES) study is conducted to numerically investigate the combustion dynamics as well as aero-thermal phenomena in a full-scale nonpremixed hydrogen–air rotating detonation engine (RDE) (with a diverging-shaped lower-end wall), when integrated with nozzle guide vanes (NGV) acting as the turbine stator. The wall-modeled LES framework incorporates hydrogen–air detailed chemical kinetics and adaptive mesh refinement (AMR). A comparative analysis is carried out for two operating conditions with different fuel/air mass flow rates but global equivalence ratio of unity, and considering RDE configurations without and with stator. The LES model is validated against available experimental data for the low mass flux condition with respect to detonation wave speed/height, wave dynamics, and axial static pressure distribution. Numerical results indicate significant deflagrative combustion occurring in the fill region near the inner wall due to formation of recirculation zones in the injection near-field driven by the backward facing step. The leading detonation wave is found to be trailed by an azimuthal reflected-shock combustion (ARSC) wave, consistent with experimental observations, which consumes unburned vitiated reactants that leak through the main detonation wave. The main detonation wave characteristics, such as detonation wave speed/height and combustion efficiency, do not change appreciably with the presence of NGV. A novel combustion diagnostic technique based on chemical explosive mode analysis (CEMA) is employed to quantify the fraction of heat release occurring in the detonative mode versus deflagrative mode for the simulated conditions. The exit flow is found to be nearly fully subsonic and supersonic for the low and high mass flux conditions, respectively. Further analysis of the exit flow profiles shows that the presence of NGV renders the flow more axial and significantly impacts the exit Mach number and total pressure, while the total temperature shows negligible change. In addition, the low mass flux operating point, despite exhibiting more deflagrative losses within the combustor, yields overall lower pressure drop from plenum to exhaust, which is mainly attributed to lower pressure drop across the injectors. Lastly, the rotating detonation engine-nozzle guide vanes (RDE-NGV) configuration exhibits higher total pressure loss compared to rotating detonation engine (RDE) without stator across both the mass flux conditions. In conclusion, this study extends the state-of-the-art in numerical modeling of pressure gain combustion (PGC) systems by demonstrating high-fidelity 3D reacting LES of full-scale RDE-NGV systems relevant to RDE-turbine integration for stationary power generation.

Combustion↗
NASA NTRS2014

Spacecraft Stabilization and Control for Capture of Non-Cooperative Space Objects

This paper addresses stabilization and control issues in autonomous capture and manipulation of non-cooperative space objects such as asteroids, space debris, and orbital spacecraft in need of servicing. Such objects are characterized by unknown mass-inertia properties, unknown rotational motion, and irregular shapes, which makes it a challenging control problem. The problem is further compounded by the presence of inherent nonlinearities, signi cant elastic modes with low damping, and parameter uncertainties in the spacecraft. Robust dissipativity-based control laws are presented and are shown to provide global asymptotic stability in spite of model uncertainties and nonlinearities. It is shown that robust stabilization can be accomplished via model-independent dissipativity-based controllers using thrusters alone, while stabilization with attitude and position control can be accomplished using thrusters and torque actuators.

Joshi, Suresh↗
NASA NTRS1980

Simulation study of a geometric shape factor technique for estimating earth-emitted radiant flux densities from wide-field-of-view radiation measurements

Geometric shape factors were computed and applied to satellite simulated irradiance measurements to estimate Earth emitted flux densities for global and zonal scales and for areas smaller than the detector field of view (FOV). Wide field of view flat plate detectors were emphasized, but spherical detectors were also studied. The radiation field was modeled after data from the Nimbus 2 and 3 satellites. At a satellite altitude of 600 km, zonal estimates were in error 1.0 to 1.2 percent and global estimates were in error less than 0.2 percent. Estimates with unrestricted field of view (UFOV) detectors were about the same for Lambertian and limb darkening radiation models. The opposite was found for restricted field of view detectors. The UFOV detectors are found to be poor estimators of flux density from the total FOV and are shown to be much better as estimators of flux density from a circle centered at the FOV with an area significantly smaller than that for the total FOV.

Weaver, W. L.↗
NASA NTRS2006

Observing Ice in Clouds from Space

There are many satellite observations of cloud top properties and the liquid and rain content of clouds, however, we do not yet quantitatively understand the processes that control the water budget of the upper troposphere where ice is the predominant phase, and how these processes are linked to precipitation processes and the radiative energy budget. The ice in clouds in the upper troposphere either melts into rain or is detrained, and persists, as cirrus clouds affecting the hydrological and energy cycle, respectively. Fully modeling the Earth's climate and improving weather and climate forecasts requires accurate satellite measurements of various cloud properties at the temporal and spatial scales of cloud processes. These properties include cloud horizontal and vertical structure, cloud water content and some measure of particle sizes and shapes. The uncertainty in knowledge of these ice characteristics is reflected in the large discrepancies in model simulations of the upper tropospheric water budget. Model simulations are sensitive to the partition of ice between precipitation and outflow processes, i.e., to the parameterization of ice clouds and ice processes. One barrier to achieving accurate global ice cloud properties is the lack of adequate observations at millimeter and submillimeter wavelengths (183-874 GHz). Recent advances in instrumentation have allowed for the development and implementation of an airborne submillimeter-wave radiometer. The brightness temperatures at these frequencies are especially sensitive to cirrus ice particle sizes (because they are comparable to the wavelength). This allows for more accurate ice water path estimates when multiple channels are used to probe into the cloud layers. Further, submillimeter wavelengths offer simplicity in the retrieval algorithms because they do not probe into the liquid and near surface portions of clouds, thus requiring only one term of the radiative transfer equation (ice scattering) to relate brightness temperatures to ice. The next step is a satellite mission designed to acquire global Earth radiance measurements in the submillimeter-wave region, thus bridging the measurement gap between microwave sounders and shorter-wavelength infrared and visible sensors. This presentation provides scientific justification and an approach to measuring ice water path and particle size from a satellite platform that spans a range encompassing both the hydrologically active and radiatively active components of cloud systems.

Ackerman, S.↗
DOE OSTI2025

Multiscale Physics of Atomic Nuclei from First Principles

Atomic nuclei exhibit multiple energy scales ranging from hundreds of MeV in binding energies to fractions of an MeV for low-lying collective excitations. As the limits of nuclear binding are approached near the neutron and proton drip lines, traditional shell structure starts to melt with an onset of deformation and an emergence of coexisting shapes. It is a long-standing challenge to describe this multiscale physics starting from nuclear forces with roots in quantum chromodynamics. Here, we achieve this within a unified and nonperturbative quantum many-body framework that captures both short- and long-range correlations starting from modern nucleon-nucleon and three-nucleon forces from chiral effective field theory. The short-range (dynamic) correlations which account for the bulk of the binding energy are included within a symmetry-breaking framework, while long-range (static) correlations (and fine details about the collective structure) are included by employing symmetry projection techniques. Our calculations accurately reproduce—within theoretical error bars—available experimental data for low-lying collective states and the electromagnetic quadrupole transitions in 20−30 Ne. In addition, we reveal coexisting spherical and deformed shapes in 30 Ne, which indicates the breakdown of the magic neutron number 𝑁 = 20 as the key nucleus 28 O is approached, and we predict that the drip line nuclei 32,34 Ne are strongly deformed and collective. By developing reduced-order models for symmetry-projected states, we perform a global sensitivity analysis and find that the subleading singlet 𝑆-wave contact and a pion-nucleon coupling strongly impact nuclear deformation in chiral effective field theory. The techniques developed in this work clarify how microscopic nuclear forces generate the multiscale physics of nuclei spanning collective phenomena as well as short-range correlations and allow one to capture emergent and dynamical phenomena in finite fermion systems such as atom clusters, molecules, and atomic nuclei.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2010

Error Budgeting and Tolerancing of Starshades for Exoplanet Detection

A flower-like starshade positioned between a star and a space telescope is an attractive option for blocking the starlight to reveal the faint reflected light of an orbiting Earth-like planet. Planet light passes around the petals and directly enters the telescope where it is seen along with a background of scattered light due to starshade imperfections. We list the major perturbations that are expected to impact the performance of a starshade system and show that independent models at NGAS and JPL yield nearly identical optical sensitivities. We give the major sensitivities in the image plane for a design consisting of a 34-m diameter starshade, and a 2-m diameter telescope separated by 39,000 km, operating between 0.25 and 0.55 um. These sensitivities include individual petal and global shape terms evaluated at the inner working angle. Following a discussion of the combination of individual perturbation terms, we then present an error budget that is consistent with detection of an Earth-like planet 26 magnitudes fainter than its host star.

starshades↗