Search NASA⌕ Search

SEARCH · Search NASA

Results for “dynamic processes”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

ENRICHMENT OF r-PROCESS ELEMENTS IN DWARF SPHEROIDAL GALAXIES IN CHEMO-DYNAMICAL EVOLUTION MODEL

The rapid neutron-capture process (r-process) is a major process for the synthesis of elements heavier than iron-peak elements, but the astrophysical site(s) of the r-process has not yet been identified. Neutron star mergers (NSMs) are suggested to be a major r-process site according to nucleosynthesis studies. Previous chemical evolution studies, however, required unlikely short merger times of NSMs to reproduce the observed large star-to-star scatters in the abundance ratios of r-process elements to iron: the [Eu/Fe] of extremely metal-poor stars in the Milky Way (MW) halo. This problem can be solved by considering chemical evolution in dwarf spheroidal galaxies (dSphs), which would be building blocks of the MW and have lower star formation efficiencies than the MW halo. We demonstrate the enrichment of r-process elements in dSphs by NSMs using an N-body/smoothed particle hydrodynamics code. Our high-resolution model reproduces the observed [Eu/Fe] due to NSMs with a merger time of 100 Myr when the effect of metal mixing is taken into account. This is because metallicity is not correlated with time ∼300 Myr from the start of the simulation due to the low star formation efficiency in dSphs. We also confirm that this model is consistent with observed properties of dSphs such as radial profiles and metallicity distribution. The merger time and the Galactic rate of NSMs are suggested to be ≲300 Myr and ∼10{sup −4} year{sup −1}, respectively, which are consistent with the values suggested by population synthesis and nucleosynthesis studies. This study supports the argument that NSMs are the major astrophysical site of the r-process.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Chemical Kinetic Effects on Detonation Wave Generation in a Semi-Bounded Channel

The coupled effects of mixing and ignition are investigated in a semi-bounded channel that emulates a rotating detonation engine geometry. In previous studies, a robust mechanism of self-excited detonation wave generation was discovered with O 2 /CH 4 reactants in this experiment. The behavior requires symbiosis between the chemical kinetics of the reactant mixture and the dynamics of the reactant injection process. The reactant jet dynamics are controlled principally by the geometry of the system and the pressure differences across the injector. The chemical kinetics are modified by changing the reactant composition to investigate how the combustion behavior changes when the kinetics become the rate-controlling process. Ignition delay timescales are increased by introducing an inert gas, N 2 , to the oxidizer flow; conversely, ignition delay time-scales are decreased by replacing natural gas fuel with hydrogen, H 2 . The effects of the oxidizer modifications to the chemical kinetics for each fuel are studied independently to characterize the amplification process associated with the self-excited instability, and apply this understanding to the sustainability of detonations in a comparable RDE environment.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1993

Upper Atmosphere Research Satellite (UARS) onboard attitude determination using a Kalman filter

The Upper Atmospheric Research Satellite (UARS) requires a highly accurate knowledge of its attitude to accomplish its mission. Propagation of the attitude state using gyro measurements is not sufficient to meet the accuracy requirements, and must be supplemented by a observer/compensation process to correct for dynamics and observation anomalies. The process of amending the attitude state utilizes a well known method, the discrete Kalman Filter. This study is a sensitivity analysis of the discrete Kalman Filter as implemented in the UARS Onboard Computer (OBC). The stability of the Kalman Filter used in the normal on-orbit control mode within the OBC, is investigated for the effects of corrupted observations and nonlinear errors. Also, a statistical analysis on the residuals of the Kalman Filter is performed. These analysis is based on simulations using the UARS Dynamics Simulator (UARSDSIM) and compared against attitude requirements as defined by General Electric (GE). An independent verification of expected accuracies is performed using the Attitude Determination Error Analysis System (ADEAS).

Garrick, Joseph↗
DOE OSTI2018

Effect of synchrotron radiation on the dynamics of electron spin precession in the process of laser-plasma acceleration

A model was developed and tested for studying the dynamics of spin precession and trajectories of charged particles in the wake fields generated in a laser-plasma accelerator. The model takes into account the radiation reaction force in the Landau – Lifshits form. An investigation is made of the effect of synchrotron radiation on the dynamics of energy gaining and spin precession of electrons accelerated in model constant fields as well as on the particle beam polarisation in the acceleration at a separate acceleration stage in the case of self-consistent description of the nonlinear dynamics of a laser pulse and its generated accelerating and focusing plasma wake fields. It is shown that synchrotron radiation hardly affects the energy gain rate and polarisation of the electrons that are accelerated in the fields characteristic for a moderately nonlinear mode of laser-plasma acceleration up to an energy of 3.8 TeV. (extreme light fields and their interaction with matter)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Matrix Diffusion Controls Mountain Hillslope Groundwater Ages and Inferred Storage Dynamics

Groundwater age distributions provide fundamental insights on coupled water and biogeochemical processes in mountain watersheds. Field-based studies have found mixtures of young and old-aged groundwater in mountain catchments underlain by bedrock; yet, the processes that dictate these groundwater age distributions are poorly understood. In this work, we use the coupled ParFlow-CLM integrated hydrologic and EcoSLIM particle tracking models to simulate groundwater age distributions on a lower montane hillslope in the East River Watershed, Colorado (USA). We develop a convolution-based approach to propagate fracture-matrix diffusion processes to the EcoSLIM advection-dominated age distributions. We compare observed 3 H and 4 He concentrations from two groundwater wells against model predictions that have varying advective transport times and matrix diffusion magnitudes. Based on a Monte Carlo analysis that considers uncertain matrix and fracture parameters, we find that matrix diffusion is needed to jointly predict 3 H and 4 He observations at both wells. The advection-dominated age distributions lack adequate mixing of young and old-aged water to capture the observed co-occurrence of 3 H and 4 He. The model scenario that best matches the 3 H, 4 He, and water level observations when considering both advective flowpath and matrix diffusion mixing processes has a dynamic bedrock groundwater reservoir that is susceptible to considerable storage losses during low-snow periods. This dynamic groundwater system amplifies the need to assimilate deeper bedrock groundwater into watershed hydro-biogeochemical predictions. This work further highlights the importance of considering matrix diffusion when interpreting environmental tracers in bedrock groundwater systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Probing Clustering Dynamics between Silicon and PAA or LiPAA Slurries under Processing Conditions

This work explores the complex interplay between slurry aggregation, agglomeration, and conformation (i.e., shape) of poly(acrylic acid) (PAA)- and lithiated PAA-based silicon slurries as a function of the shear rate and the resulting slurry homogeneity. These values were measured by small-angle neutron scattering (SANS) and rheology-coupled ultra-SANS at conditions relevant to battery electrode casting. Different binder solution preparation methods, either a ball milling (BM) process or a planetary centrifugal mixing (PCM) process, dramatically modify the resulting polymer dynamics and organization around a silicon material. This is due to the different energy profiles of mixing where the more violent and higher energy PCM causes extensive breakdown and reformation of the binder, which is now likely in a branched conformation, while the lower energy BM results in simply lower-molecular weight linear polymers. In conclusion, the breakdown and reorganization of the polymer structure affect silicon slurry homogeneity, which affects subsequent electrode architecture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Computational Fluid Dynamics Modeling of Low Temperature Ignition Processes From a Nanosecond Pulsed Discharge at Quiescent Conditions

Recent interest in nonequilibrium plasma discharges as sources of ignition for the automotive industry has not yet been accompanied by the availability of dedicated models to perform this task in computational fluid dynamics (CFD) engine simulations. The need for a low-temperature plasma (LTP) ignition model has motivated much work in simulating these discharges from first principles. Most ignition models assume that an equilibrium plasma comprises the bulk of discharge kernels. LTP discharges, however, exhibit highly nonequilibrium behavior. In this work, a method to determine a consistent initialization of LTP discharge kernels for use in engine CFD codes like CONVERGE is proposed. The method utilizes first principles discharge simulations. Such an LTP kernel is introduced in a flammable mixture of air and fuel, and the subsequent plasma expansion and ignition simulation is carried out using a reacting flow solver with detailed chemistry. Finally, the proposed numerical approach is shown to produce results that agree with experimental observations regarding the ignitability of methane-air and ethylene-air mixtures by LTP discharges.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

System risk quantification and decision making support using functional modeling and dynamic Bayesian network

Risk-informed decision-making requires a probabilistic assessment of the likelihood of success of control action, given the system status. This paper presents a systematic state transition modeling approach integrating dynamic probabilistic risk assessment with a decision-making process using a dynamic Bayesian network (DBN) coupled with functional modeling. A functional model designed with multilevel flow modeling (MFM) technique was used to build a system state structure inferred by energy, mass, and information flow so that one can verify the developed model with respect to system functionality. The MFM model represents the causal relationship among the nodes, which captures the structure of process parameters and control units. Each node may have multiple possible states, and the DBN structured by the MFM model represents the time-domain transitions among the defined states. Furthermore, the MFM-DBN integrated state transition modeling is a white-box approach that allows one to draw the system's risk profile by updating the system states and supports the decisions probabilistically with physical inference. An example of a simple heating system has been used to illustrate this process, including decision-making support based on quantitative risk profile. For demonstrating its applicability to a complex system operational decision making, a case study of station blackout accident scenario leading to the seal loss of coolant accident in a nuclear power plant is presented. The proposed approach effectively provided the risk profile along time for each option so that the operators can make the best decision, which minimizes the plant risk.

42 ENGINEERING↗
DOE OSTI2019

Optimization of process models for determining volatility distribution and viscosity of organic aerosols from isothermal particle evaporation data

The composition of organic aerosol under different ambient conditions as well as their phase state have been a subject of intense study in recent years. One way to study particle properties is to measure the particle size shrinkage in a diluted environment at isothermal conditions. From these measurements it is possible to separate the fraction of low-volatility compounds from high-volatility compounds. In this work, we analyse and evaluate a method for obtaining particle composition and viscosity from measurements using process models coupled with input optimization algorithms. Two optimization methods, the Monte Carlo genetic algorithm and Bayesian inference, are used together with process models describing the dynamics of particle evaporation. The process model optimization scheme in inferring particle composition in a volatility-basis-set sense and composition-dependent particle viscosity is tested with artificially generated data sets and real experimental data. Optimizing model input so that the output matches these data yields a good match for the estimated quantities. Both optimization methods give equally good results when they are used to estimate particle composition to artificially test data. Finally, the timescale of the experiments and the initial particle size are found to be important in defining the range of values that can be identified for the properties from the optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1982

Soviet National Middle Atmosphere Program

Soviet national MAP program comprises seven projects: lower thermosphere (structure and dynamics); high latitude energetic sources and their effect on the structure and dynamics of the upper atmosphere under conditions of the polar night; climate of the stratosphere and mesosphere (effects of various energetic sources on its formation); winter variability in the lower ionosphere; noctilucent clouds (climatology, dynamics, nature, and genesis); wave processes and structure and dynamics of the stratosphere and mesosphere; and dynamics of the ozone layer.

Danilov, A. D.↗
DOE OSTI2021

AI-enabled Dynamic Finish Machining Optimization for Sustained Surface Integrity

While machining processes are typically leveraged to establish geometric features, many functional characteristics of advanced materials are directly determined by their machining-induced surface integrity (SI). Current modeling approaches struggle to predict surface integrity, and typically neglect the effects of progressive tool-wear, resulting in inefficient ‘static’ process parameters. We present a novel integrated approach based on model-informed artificial intelligence (AI), which optimizes ‘dynamic’ process parameters in real-time. Here, by maximizing the useful life of a cutting tool over which a required set of SI parameters can be maintained, our paradigm will enable significantly more efficient processing of next-generation materials and components.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Process-based Neural Network to Forecast Vegetation Dynamics

This white paper calls for an AI-based emulator of DOE’s dynamic vegetation model that is computationally efficient and accommodates/parameterizes the governing processes built in the model. This AI-based emulator is needed for model calibration, sensitivity analysis, prediction, uncertainty quantification, and decision making. This AI-based emulator will incorporate physics and biological information in the form of conservation laws and constitutive relationships.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Leading-process actomyosin coordinates organelle positioning and adhesion receptor dynamics in radially migrating cerebellar granule neurons

During brain development, neurons migrate from germinal zones to their final positions to assemble neural circuits. A unique saltatory cadence involving cyclical organelle movement (e.g., centrosome motility) and leading-process actomyosin enrichment prior to nucleokinesis organizes neuronal migration. While functional evidence suggests that leading-process actomyosin is essential for centrosome motility, the role of the actin-enriched leading process in globally organizing organelle transport or traction forces remains unexplored. Our results show that myosin ii motors and F-actin dynamics are required for Golgi apparatus positioning before nucleokinesis in cerebellar granule neurons (CGNs) migrating along glial fibers. Moreover, we show that primary cilia are motile organelles, localized to the leading-process F-actin-rich domain and immobilized by pharmacological inhibition of myosin ii and F-actin dynamics. Finally, leading process adhesion dynamics are dependent on myosin ii and F-actin. In conclusion, we propose that actomyosin coordinates the overall polarity of migrating CGNs by controlling asymmetric organelle positioning and cell-cell contacts as these cells move along their glial guides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Simulation of the dynamics of gas mixtures during plasma processing in the C75 Cavity

Plasma processing using a mixture of noble gas and oxygen is a technique that is currently being used to reduce field emission and multipacting in accelerating cavities. Plasma is created inside the cavity when the gas mixture is exposed to an electromagnetic field that is generated by applying RF power through the fundamental power or higher-order mode couplers. Oxygen ions and atomic oxygen are created in the plasma which breaks down the hydrocarbons on the surface of the cavity and the residuals from this process are removed as part of the process gas flow. Removal of hydrocarbons from the surface increases the work function and reduces the secondary emission coefficient. This work describes the initial results of plasma simulation, which provides insight into the ignition process, distribution of different species, and interactions of free oxygen and oxygen ions with the cavity surfaces. The simulations have been done with an Ar/?2 plasma using COMSOL® multiphysics. These simulations help in understanding the dynamics and control of plasma inside the cavity and the exploration of different gas mixtures.

Dhakal, Pashupati↗
DOE OSTI2022

Sharing is caring: An extensive analysis of parameter-based transfer learning for the prediction of building thermal dynamics

In recent years deep neural networks have been proposed as a lightweight data-driven model to capture high-dimensional, nonlinear physical processes to predict building thermal responses. However, the need of a large amount of data for the training process of deep neural networks clashes with the potential limited data availability in most existing or new buildings. Transfer learning aims to enhance the performance of a target learner exploiting knowledge from related and similar environments. This study conducted a suite of experiments that leveraged 250 data-driven models based on a synthetic dataset of a building archetype to study the influence of data availability, energy efficiency level, occupancy and climate for the transfer process of thermal dynamics. The performance of the transfer learning process was compared against a classical machine learning approach. Here, the results suggest that building thermal dynamics can be effectively transferred under the same climatic conditions, increasing performance when dealing with different occupancy schedules, efficiency levels and low data availability. Furthermore, the paper compares the performance of both transfer learning and machine learning approaches in an online fashion, to support the implementation in real-world deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2003

Cardea: Providing Support for Dynamic Resource Access in a Distributed Computing Environment

The environment framing the modem authorization process span domains of administration, relies on many different authentication sources, and manages complex attributes as part of the authorization process. Cardea facilitates dynamic access control within this environment as a central function of an inter-operable authorization framework. The system departs from the traditional authorization model by separating the authentication and authorization processes, distributing the responsibility for authorization data and allowing collaborating domains to retain control over their implementation mechanisms. Critical features of the system architecture and its handling of the authorization process differentiate the system from existing authorization components by addressing common needs not adequately addressed by existing systems. Continuing system research seeks to enhance the implementation of the current authorization model employed in Cardea, increase the robustness of current features, further the framework for establishing trust and promote interoperability with existing security mechanisms.

Lepro, Rebekah↗