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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Data driven pathway analysis and forecast of global warming and sea level rise

Climate change is a critical issue of our time, and its causes, pathways, and forecasts remain a topic of broader discussion. In this paper, we present a novel data driven pathway analysis framework to identify the key processes behind mean global temperature and sea level rise, and to forecast the magnitude of their increase from the present to 2100. Based on historical data and dynamic statistical modeling alone, we have established the causal pathways that connect increasing greenhouse gas emissions to increasing global mean temperature and sea level, with its intermediate links encompassing humidity, sea ice coverage, and glacier mass, but not for sunspot numbers. Our results indicate that if no action is taken to curb anthropogenic greenhouse gas emissions, the global average temperature would rise to an estimated 3.28 °C (2.46–4.10 °C) above its pre-industrial level while the global sea level would be an estimated 573 mm (474–671 mm) above its 2021 mean by 2100. However, if countries adhere to the greenhouse gas emission regulations outlined in the 2021 United Nations Conference on Climate Change (COP26), the rise in global temperature would lessen to an average increase of 1.88 °C (1.43–2.33 °C) above its pre-industrial level, albeit still higher than the targeted 1.5 °C, while the sea level increase would reduce to 449 mm (389–509 mm) above its 2021 mean by 2100.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Scientific machine learning for modeling and simulating complex fluids

The formulation of rheological constitutive equations—models that relate internal stresses and deformations in complex fluids—is a critical step in the engineering of systems involving soft materials. While data-driven models provide accessible alternatives to expensive first-principles models and less accurate empirical models in many engineering disciplines, the development of similar models for complex fluids has lagged. The diversity of techniques for characterizing non-Newtonian fluid dynamics creates a challenge for classical machine learning approaches, which require uniformly structured training data. Consequently, early machine-learning based constitutive equations have not been portable between different deformation protocols or mechanical observables. Here, we present a data-driven framework that resolves such issues, allowing rheologists to construct learnable models that incorporate essential physical information, while remaining agnostic to details regarding particular experimental protocols or flow kinematics. These scientific machine learning models incorporate a universal approximator within a materially objective tensorial constitutive framework. By construction, these models respect physical constraints, such as frame-invariance and tensor symmetry, required by continuum mechanics. We demonstrate that this framework facilitates the rapid discovery of accurate constitutive equations from limited data and that the learned models may be used to describe more kinematically complex flows. This inherent flexibility admits the application of these “digital fluid twins” to a range of material systems and engineering problems. We illustrate this flexibility by deploying a trained model within a multidimensional computational fluid dynamics simulation—a task that is not achievable using any previously developed data-driven rheological equation of state.

Science & Technology - Other Topics↗
NASA NTRS1979

Selected topics from the structural acoustics program for the B-1 aircraft

The major elements of the structural acoustics program for the B-1 aircraft are considered. Acoustic pressures measured at 280 sites on the surface of the vehicle were used to develop pressure models for a resizing of airframe components for aircraft No. 4 (A/C4). Acoustical fatigue design data for two dynamically complex structural configurations were acquired in laboratory programs, the conceptions for and executions of which detailed significant departures from the conventional. Design requirements for mechanical fasteners for configurations other than these two made use of analytical extensions of regrettably limited available information.

Belcher, P. M.↗
NASA NTRS1990

NASA/ASEE Summer Faculty Fellowship Program, 1990, Volume 1

The 1990 Johnson Space Center (JSC) NASA/American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program was conducted by the University of Houston-University Park and JSC. A compilation of the final reports on the research projects are presented. The topics covered include: the Space Station; the Space Shuttle; exobiology; cell biology; culture techniques; control systems design; laser induced fluorescence; spacecraft reliability analysis; reduced gravity; biotechnology; microgravity applications; regenerative life support systems; imaging techniques; cardiovascular system; physiological effects; extravehicular mobility units; mathematical models; bioreactors; computerized simulation; microgravity simulation; and dynamic structural analysis.

Bannerot, Richard B.↗
DOE OSTI2015

Artium mater in relativistic astrophysics : New perspectives for a European-Latin American PhD program

Following the successful scientific space missions by the European Space Agency (ESA) and the European Southern Observatory (ESO) in Chile, as well as the high-energy particle activities at CERN in Genve, we have created a Ph.D. program dedicated to the formation of scientists in the field of relativistic astrophysics. The students of such a program will lead the theoretical developments of one of the most active fields of research, based on the above observational and experimental facilities. This program needs expertise in the most advanced topics of mathematical and theoretical physics, and in relativistic field theories. It requires the ability to model the observational data received from the above facilities, as well as all the basic knowledge in astronomy, astrophysics and cosmology. This activity is necessarily international, no single university can cover the broad expertises. From this, the proposed program of the IRAP Ph.D., in one of the youngest and most dynamical French universities, pole of research and teaching in the Euro-Mediterranean region (PRES): the University of Nice. It benefits from the presence of the astrophysics research institute of Observatoire de la Cte d’Azur involved in relativistic and non-photonic astrophysics. The participation of the Freie Universitaet Berlin, Oldenburg and Bremen Universities and of the Einstein Institute in Potsdam offers the possibility of teaching in relativistic field theories at the highest level. The University of Savoy offers the link to the particle physics at CERN. The activities at the University of Rome, at Stockholm University and at ICRANet offer teaching programs in all the fields of relativistic astrophysics, including cosmology, the physics of gravitational collapse, gamma-ray bursts, and black hole physics. Finally, the University of Ferrara will be present with lectures and researches in the topics they have pioneered such as x-ray astrophysics and observational cosmology. Through ICRANet the extra-European connections with Brazil, China and India will be guaranteed: in China, with the Shanghai Observatory of the Chinese Academy of Science, studying the formation and evolution of large-scale structure and galaxies; in India, with the Indian Centre for Space Physics (ICSP), renowned for its research on compact objects as well as on solar physics and astrochemistry; in Brazil with ICRANet Brazil where a successful program of research and teaching in relativistic astrophysics has been established in recent years.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Fluctuating hydrodynamics and the Rayleigh–Plateau instability

The Rayleigh–Plateau instability occurs when surface tension makes a fluid column become unstable to small perturbations. At nanometer scales, thermal fluctuations are comparable to interfacial energy densities. Consequently, at these scales, thermal fluctuations play a significant role in the dynamics of the instability. These microscopic effects have previously been investigated numerically using particle-based simulations, such as molecular dynamics (MD), and stochastic partial differential equation–based hydrodynamic models, such as stochastic lubrication theory. In this paper, we present an incompressible fluctuating hydrodynamics model with a diffuse-interface formulation for binary fluid mixtures designed for the study of stochastic interfacial phenomena. An efficient numerical algorithm is outlined and validated in numerical simulations of stable equilibrium interfaces. We present results from simulations of the Rayleigh–Plateau instability for long cylinders pinching into droplets for Ohnesorge numbers of Oh = 0.5 and 5.0. Both stochastic and perturbed deterministic simulations are analyzed and ensemble results show significant differences in the temporal evolution of the minimum radius near pinching. Short cylinders, with lengths less than their circumference, were also investigated. As previously observed in MD simulations, we find that thermal fluctuations cause these to pinch in cases where a perturbed cylinder would be stable deterministically. Finally, we show that the fluctuating hydrodynamics model can be applied to study a broader range of surface tension–driven phenomena.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Process prediction and detection of faults using probabilistic bidirectional recurrent neural networks on real plant data

Attaining Industry 4.0 for manufacturing operations requires advanced monitoring systems and real-time data analytics of plant data, among other topics. We propose a Probabilistic Bidirectional Recurrent Network (PBRN) for industrial process monitoring for the early detection of faults. The model is based on a Gated Recurrent Unit (GRU) neural network that allows the model to retain long-term dependencies between sensor data along a time horizon, hence learning the dynamic behavior of the process. To reduce the false-positive detection rate of the model, we compel the model to learn from a highly noisy sensor reading while outputting noise-free sensor outputs. The performance of the proposed model is compared to other data-driven statistical process monitoring schemes using real plant data from an industrial Air Separations Unit (ASU) containing noisy sensor readings. We show that the model can learn from noisy data without reducing its performance. Using two different fault cases, we demonstrate the model’s ability to carry out early fault detection with average false-positive rates of 2.9% and 4.9% for both fault cases. The missed detection rates are 0.1% and 0.2%, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Integrated Transmission-and-Distribution System Modeling of Power Systems: State-of-the-Art and Future Research Directions

Integrated transmission-and-distribution (T&D) modeling is a new and developing method for simulating power systems. Interest in integrated T&D modeling is driven by the changes taking place in power systems worldwide that are resulting in more decentralized power systems with increasingly high levels of distributed energy resources. Additionally, the increasing role of the hitherto passive energy consumer in the management and operation of power systems requires more capable and detailed integrated T&D modeling to understand the interactions between T&D systems. Although integrated T&D modeling has not yet found widespread commercial application, its potential for changing the decades-old power system modeling approaches has led to several research efforts in the last few years that tried to (i) develop algorithms and software for steady-state and dynamic modeling of power systems and (ii) demonstrate the advantages of this modeling approach compared with traditional, separated T&D system modeling. In this paper, we provide a review of integrated T&D modeling research efforts and the methods employed for steady-state and dynamic modeling of power systems. We also discuss our current research in integrated T&D modeling and the potential directions for future research. This paper should be useful for power systems researchers and industry members because it will provide them with a critical summary of current research efforts and the potential topics where research efforts are needed to further advance and demonstrate the utility of integrated T&D modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1976

The neutral atmospheres of comets

A comprehensive review of current knowledge about the neutral gas atmospheres of comets is given, with emphasis on the task of deriving the chemical composition of the cometary nucleus. The discussion centers on the following major topics: photometric and spectrophotometric observations of the neutral atmosphere and its constituent neutral radicals, molecules, and atoms; excitation processes responsible for the observed emissions from the neutral coma; the parent molecules of the neutral radicals; the gas-phase chemistry likely to take place in the dense inner coma; dynamic models (both exospheric and hydrodynamic) of the neutral atmosphere; and the chemical compositions of comets. The primary conclusions reached on the basis of all the data considered are that: (1) the chemical composition of the dust component is most likely to be the same as that of the stream meteoroids which burn up on hitting the earth's upper atmosphere; (2) the dominant icy component in most comets is probably H2O; and (3) anomalous abundances of other volatile species are present in some comets.

Mendis, D. A.↗
DOE OSTI2018

Surface-screening mechanisms in ferroelectric thin films and their effect on polarization dynamics and domain structures

For over 70 years, ferroelectric materials have been one of the central research topics for condensed matter physics and material science, an interest driven both by fundamental science and applications. However, ferroelectric surfaces, the key component of ferroelectric films and nanostructures, still present a significant theoretical and even conceptual challenge. Indeed, stability of ferroelectric phase per se necessitates screening of polarization charge. At surfaces, this can lead to coupling between ferroelectric and semiconducting properties of material, or with surface (electro) chemistry, going well beyond classical models applicable for ferroelectric interfaces. In this paper, we summarize recent studies of surface-screening phenomena in ferroelectrics. We provide a brief overview of the historical understanding of the physics of ferroelectric surfaces, and existing theoretical models that both introduce screening mechanisms and explore the relationship between screening and relevant aspects of ferroelectric functionalities starting from phase stability itself. Given that the majority of ferroelectrics exist in multiple-domain states, we focus on local studies of screening phenomena using scanning probe microscopy techniques. We discuss recent studies of static and dynamic phenomena on ferroelectric surfaces, as well as phenomena observed under lateral transport, light, chemical, and pressure stimuli. Finally, we also note that the need for ionic screening renders polarization switching a coupled physical–electrochemical process and discuss the non-trivial phenomena such as chaotic behavior during domain switching that stem from this.

36 MATERIALS SCIENCE↗
DOE OSTI2015

A review on the relativistic effective field theory with parameterized couplings for nuclear matter and neutron stars

Nuclear science has developed many excellent theoretical models for many-body systems in the domain of the baryon-meson strong interaction for the nucleus and nuclear matter at low, medium and high densities. However, a full microscopic understanding of nuclear systems in the extreme density domain of compact stars is still lacking. The aim of this contribution is to shed some light on open questions facing the nuclear many-body problem at the very high density domain. Here we focus our attention on the conceptual issue of naturalness and its role in shaping the baryon-meson phase space dynamics in the description of the equation of state (EoS) of nuclear matter and neutrons stars. In particular, in order to stimulate possible new directions of research, we discuss relevant aspects of a recently developed relativistic effective theory for nuclear matter within Quantum Hadrodynamics (QHD) with genuine many-body forces and derivative natural parametric couplings. Among other topics we discuss in this work the connection of this theory with other known effective QHD models of the literature and its potentiality in describing a new physics for dense matter. The model with parameterized couplings exhausts the whole fundamental baryon octet (n, p, Σ{sup −}, Σ{sup 0}, Σ{sup +}, Λ, Ξ{sup −}, Ξ{sup 0}) and simulates n-order corrections to the minimal Yukawa baryon couplings by considering nonlinear self-couplings of meson fields and meson-meson interaction terms coupled to the baryon fields involving scalar-isoscalar (σ, σ∗), vector-isoscalar (ω, Φ), vector-isovector (ϱ) and scalar-isovector (δ) virtual sectors. Following recent experimental results, we consider in our calculations the extreme case where the Σ{sup −} experiences such a strong repulsion that its influence in the nuclear structure of a neutron star is excluded at all. A few examples of calculations of properties of neutron stars are shown and prospects for the future are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Infinite neural network quantum states: entanglement and training dynamics

We study infinite limits of neural network quantum states (∞-NNQS), which exhibit representation power through ensemble statistics, and also tractable gradient descent dynamics. Ensemble averages of entanglement entropies are expressed in terms of neural network correlators, and architectures that exhibit volume-law entanglement are presented. The analytic calculations of entanglement entropy bound are tractable because the ensemble statistics are simplified in the Gaussian process limit. A general framework is developed for studying the gradient descent dynamics of neural network quantum states (NNQS), using a quantum state neural tangent kernel (QS-NTK). For ∞-NNQS the training dynamics is simplified, since the QS-NTK becomes deterministic and constant. An analytic solution is derived for quantum state supervised learning, which allows an ∞-NNQS to recover any target wavefunction. Numerical experiments on finite and infinite NNQS in the transverse field Ising model and Fermi Hubbard model demonstrate excellent agreement with theory. ∞-NNQS opens up new opportunities for studying entanglement and training dynamics in other physics applications, such as in finding ground states.

quantum state supervised learning↗
NASA NTRS1983

Quasi-steady solar wind dynamics

Progress in understanding the large scale dynamics of quasisteady, corotating solar wind structure was reviewed. The nature of the solar wind at large heliocentric distances preliminary calculations from a 2-D MHD model are used to demonstrate theoretical expectations of corotating structure out to 30 AU. It is found that the forward and reverse shocks from adjacent CIR's begin to interact at about 10 AU, producing new shock pairs flanking secondary CIR's. These sawtooth secondary CIR's interact again at about 20 AU and survive as visible entities to 30 AU. The model predicts the velocity jumps at the leading edge of the secondary CIR's at 30 AU should be very small but there should still be sizable variations in the thermodynamic and magnetic parameters. The driving dynamic mechanism in the distant solar wind is the relaxation of pressure gradients. The second topic is the influence of weak, nonimpulsive time dependence in quasisteady dynamics. It is suggested that modest large scale variations in the coronal flow speed on periods of several hours to a day may be responsible for many of the remaining discrepancies between theory and observation. Effects offer a ready explanation for the apparent rounding of stream fronts between 0.3 and 1.0 AU discovered by Helios.

Pizzo, V. J.↗
DOE OSTI2020

Sea Level Rise in the CESM Large Ensemble: The Role of Individual Climate Forcings and Consequences for the Coming Decades

The emergence of a spatial pattern in the externally forced response (FR) of dynamic sea level (DSL) during the altimeter era has recently been demonstrated using climate models but our understanding of its initial emergence, drivers, and implications for the future is poor. Here the anthropogenic forcings of the DSL pattern are explored using the Community Earth System Model Large Ensemble (CESM-LE) and Single-Forcing Large Ensemble, a newly available set of simulations where values of individual forcing agents remain fixed at 1920 levels, allowing for an estimation of their effects. Statistically significant contributions to the DSL FR are identified for greenhouse gases (GHGs) and industrial aerosols (AERs), with particularly strong contributions resulting from AERs in the mid-twentieth century and GHGs in the late twentieth and twenty-first century. Secondary, but important, contributions are identified for biomass burning aerosols in the equatorial Atlantic Ocean in the mid-twentieth century, and for stratospheric ozone in the Southern Ocean during the late twentieth century. Key to understanding regional DSL patterns are ocean heat content and salinity anomalies, which are driven by surface heat and freshwater fluxes, ocean dynamics, and the spatial structure of seawater thermal expansivity. Finally, potential implications for the interpretation of DSL during the satellite era and the longer records from tide gauges are suggested as a topic for future research.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

Development of a Probabilistic Dynamic Synthesis Method for the Analysis of Nondeterministic Structures

Accounting for the statistical geometric and material variability of structures in analysis has been a topic of considerable research for the last 30 years. The determination of quantifiable measures of statistical probability of a desired response variable, such as natural frequency, maximum displacement, or stress, to replace experience-based "safety factors" has been a primary goal of these studies. There are, however, several problems associated with their satisfactory application to realistic structures, such as bladed disks in turbomachinery. These include the accurate definition of the input random variables (rv's), the large size of the finite element models frequently used to simulate these structures, which makes even a single deterministic analysis expensive, and accurate generation of the cumulative distribution function (CDF) necessary to obtain the probability of the desired response variables. The research presented here applies a methodology called probabilistic dynamic synthesis (PDS) to solve these problems. The PDS method uses dynamic characteristics of substructures measured from modal test as the input rv's, rather than "primitive" rv's such as material or geometric uncertainties. These dynamic characteristics, which are the free-free eigenvalues, eigenvectors, and residual flexibility (RF), are readily measured and for many substructures, a reasonable sample set of these measurements can be obtained. The statistics for these rv's accurately account for the entire random character of the substructure. Using the RF method of component mode synthesis, these dynamic characteristics are used to generate reduced-size sample models of the substructures, which are then coupled to form system models. These sample models are used to obtain the CDF of the response variable by either applying Monte Carlo simulation or by generating data points for use in the response surface reliability method, which can perform the probabilistic analysis with an order of magnitude less computational effort. Both free- and forced-response analyses have been performed, and the results indicate that, while there is considerable room for improvement, the method produces usable and more representative solutions for the design of realistic structures with a substantial savings in computer time.

Brown, A. M.↗
DOE OSTI2015

A review on regional convection‐permitting climate modeling: Demonstrations, prospects, and challenges

Abstract Regional climate modeling using convection‐permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large‐scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Gerischer Electrochemistry Today

Semiconductor photoelectrochemistry is a dynamic and interdisciplinary field at the forefront of research in solar fuels, energy conversion, and catalysis. Here, this Perspective captures the collective insights from the second Gerischer Electrochemistry Today Symposium, held at Colorado State University in Fort Collins, CO, in August 2024, which convened leading researchers, early-career scientists, and industry partners to define the critical next steps for the field. Through interactive sessions, technical talks, panel discussions, and training initiatives─including a Semiconductor Electrochemistry Bootcamp─the symposium emphasized three pillars of advancement: (i) facilitating the exchange of new ideas in semiconductor electrochemistry and charge separation; (ii) fostering the development of future researchers, research topics, and participation in the semiconductor workforce; and (iii) building community. This Energy Focus distills key themes from the meeting and identifies major knowledge gaps in the following areas: mechanisms of charge separation and recombination, role of defects and disorder, dynamic and operando characterization methods, interfacial chemistry and surface passivation, theoretical and modeling limitations, and standardization and benchmarking. The inclusive and collaborative structure of the symposium enabled the generation of this comprehensive report that will serve as a roadmap for fundamental and applied research in the rapidly evolving field of semiconductor electrochemistry over the next decade.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1988

A review of research in rotor loads

The research accomplished in the area of rotor loads over the last 13 to 14 years is reviewed. The start of the period examined is defined by the 1973 AGARD Milan conference and the 1974 hypothetical rotor comparison. The major emphasis of the review is research performed by the U.S. Army and NASA at their laboratories and/or by the industry under government contract. For the purpose of this review, two main topics are addressed: rotor loads prediction and means of rotor loads reduction. A limited discussion of research in gust loads and maneuver loads is included. In the area of rotor loads predictions, the major problem areas are reviewed including dynamic stall, wake induced flows, blade tip effects, fuselage induced effects, blade structural modeling, hub impedance, and solution methods. It is concluded that the capability to predict rotor loads has not significantly improved in this time frame. Future progress will require more extensive correlation of measurements and predictions to better understand the causes of the problems, and a recognition that differences between theory and measurement have multiple sources, yet must be treated as a whole. There is a need for high-quality data to support future research in rotor loads, but the resulting data base must not be seen as an end in itself. It will be useful only if it is integrated into firm long-range plans for the use of the data.

Bousman, William G.↗