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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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A model is developed to determine the critical parameters that control noise generation by blade-vortex interaction (BVI). The equations for evaluation BVI are derived. The analysis of BVI using the model reveals that the interaction is dependent on incoming vortex strength, blade lift, the interaction length, and the miss distance of the interaction. Several methods for reduction of the noise source are proposed.
A computational study has been conducted to gain a better understanding of the criteria governing the merger of corotating vortices. The zero-equation and one-equation turbulent-flow models are used to model the interaction of two rolled-up, corotational vortices. A model appropriate for the swirling flow under consideration has been proposed to prescribe the algebraic variation of mixing-length in the flow field. The unsteady, two-dimensional equations in a cross-plane are solved for primitive variables using an implicit finite-difference code. The computed downstream merging distances are in good agreement with available wind tunnel data.
We have investigated the nature of the annual cycle of suspended dust in the martian atmosphere. This has been undertaken to understand the dynamical processes responsible for lifting dust from the surface, locations where dust is preferentially lifted, and preferred sites for dust deposition upon the surface. Our efforts have involved carrying out a number of numerical simulations with the Ames Mars General Circulation Model (GCM) interactively coupled with an aerosol transport/ micro-physical model. The model generates an annual dust cycle similar to that observed. Various feedbacks are present in the atmosphere/ surface system which enter into the generation of the cycle. Several locations are primary surface sources of dust, while much of the remaining planet's surface acts a sink for suspended dust.
A computational fluid dynamics (CFD) approach is presented to model the blood flow through the human circulatory system under altered gravity conditions. Models required for CFD simulation relevant to major hemodynamic issues are introduced such as non-Newtonian flow models governed by red blood cells, a model for arterial wall motion due to fluid-wall interactions, a vascular bed model for outflow boundary conditions, and a model for auto-regulation mechanism. The three-dimensional unsteady incompressible Navier-Stokes equations coupled with these models are solved iteratively using the pseudocompressibility method and dual time stepping. Moving wall boundary conditions from the first-order fluid-wall interaction model are used to study the influence of arterial wall distensibility on flow patterns and wall shear stresses during the heart pulse. A vascular bed modeling utilizing the analogy with electric circuits is coupled with an auto-regulation algorithm for multiple outflow boundaries. For the treatment of complex geometry, a chimera overset grid technique is adopted to obtain connectivity between arterial branches. For code validation, computed results are compared with experimental data for steady and unsteady non-Newtonian flows. Good agreement is obtained for both cases. In sin-type Gravity Benchmark Problems, gravity source terms are added to the Navier-Stokes equations to study the effect of gravitational variation on the human circulatory system. This computational approach is then applied to localized blood flows through a realistic carotid bifurcation and two Circle of Willis models, one using an idealized geometry and the other model using an anatomical data set. A three- dimensional anatomical Circle of Willis configuration is reconstructed from human-specific magnetic resonance images using an image segmentation method. The blood flow through these Circle of Willis models is simulated to provide means for studying gravitational effects on the brain circulation under auto-regulation.
The Human View was developed as an additional architectural viewpoint to focus on the human part of a system. The Human View can be used to collect and organize data in order to understand how human operators interact and impact the other elements of a system. This framework can also be used to develop a model to describe how humans interact with each other in network enabled systems. These socio-technical interactions form the foundation of the emerging area of Human Interoperability. Human Interoperability strives to understand the relationships required between human operators that impact collaboration across networked environments, including the effect of belonging to different organizations. By applying organizational relationship concepts from network theory to the Human View elements, and aligning these relationships with a model developed to identify layers of coalition interoperability, the conditions for different levels for Human Interoperability for network enabled systems can be identified. These requirements can then be captured in the Human View products to improve the overall network enabled system.
Improving the realism and accuracy of the GLAS general circulation model (by adding an interactive biosphere that will simulate the transfers of latent and sensible heat from land surface to atmosphere as functions of the atmospheric conditions and the morphology and physiology of the vegetation) is proposed.
We report a molecular modeling study to investigate the polymer-carbon black (CB) composite-analyte interactions in resistive sensors. These sensors comprise the JPL electronic nose (ENose) sensing array developed for monitoring breathing air in human habitats. The polymer in the composite is modeled based on its stereoisomerism and sequence isomerism, while the CB is modeled as uncharged naphthalene rings with no hydrogens. The Dreiding 2.21 force field is used for the polymer, solvent molecules and graphite parameters are assigned to the carbon black atoms. A combination of molecular mechanics (MM) and molecular dynamics (NPT-MD and NVT-MD) techniques are used to obtain the equilibrium composite structure by inserting naphthalene rings in the polymer matrix. Polymers considered for this work include poly(4-vinylphenol), polyethylene oxide, and ethyl cellulose. Analytes studied are representative of both inorganic and organic compounds. The results are analyzed for the composite microstructure by calculating the radial distribution profiles as well as for the sensor response by predicting the interaction energies of the analytes with the composites. c2003 Elsevier Science B.V. All rights reserved.
The wide variety of optical appearances observed in spiral galaxies has encouraged the growth of two theoretical approaches to explain the spiral patterns exhibited by such young objects as OB associations, giant H II regions, and dark dust lanes. These approaches are related to the density wave theory of spiral structure and 'stochastic, self-propagating star formation'. Levinson and Roberts (1981) tried to reconcile these two theoretical approaches, and considered a disk filled with discrete gas clouds. The present investigation is concerned with refinements and extensions of the model of Levinson and Roberts. Attention is given to gravitational forces and dynamical propagation, cloud-cloud collisions, supernova interactions, computational models, a theory concerning the interactions of the gas cloud and stellar association systems, the time evolution of the gas cloud-stellar association systems, and aspects of collisionally triggered star formation.
The problem is to develop analysis methods, modeling stategies, and simulation tools to predict with assurance the on-orbit performance and integrity of large complex space structures that cannot be verified on the ground. The problem must incorporate large reliable structural models, multi-body flexible dynamics, multi-tier controller interaction, environmental models including 1g and atmosphere, various on-board disturbances, and linkage to mission-level performance codes. All areas are in serious need of work, but the weakest link is multi-body flexible dynamics.
In the two year period, the researchers have developed innovative 2-D simulation codes for modeling the interaction between electron beams and plasma waves and particles in the auroral ionosphere. These new simulations include kinetic wave particles as well as wave-wave interactions near and above approximately 500 km. The principal numerical model consists of partial-differential equations which evolve large amplitude magnetized 2-D Langmuir waves self-consistently with the electron distribution function. Progress was also made in developing 2-D Particle in Cell (PIC) codes.
There is a growing debate over the means by which regions can foster the growth of entrepreneurial activity in order to stimulate recovery and growth of their economies. On one side, agglomeration theory suggests the regions grow because of strong clusters that foster knowledge spillover locally; on the other side, the entrepreneurial action camp argues that innovative business models are generated by entrepreneurs with unique market perspectives who draw on knowledge from more distant domains. We will show you the design for a novel agent-based model of new venture creation that will demonstrate the relationship between agglomeration and action. The primary focus of this model is information exchange as the medium for these agent interactions. Our modeling and simulation study proposes to reveal interesting relationships in these perspectives, offer a foundation on which these disparate theories from economics and sociology can find common ground, and expand the use of agent-based modeling into entrepreneurship research.
With NASA’s goal to land the next human on the lunar surface in the next few years, it has become vitally important that we have a better understanding of how future landing spacecraft will interact with the unique properties of regolith¬¬––the layer of loose, unconsolidated dust and rock on the lunar surface¬¬––which can cause hazards like visual obstructions, particulate clouds, and cratering of the landing zone. Researchers from the Fluid Dynamics Branch at NASA’s Marshall Space Flight Center are performing plume-surface interaction (PSI) simulations between lander engine plumes and unprepared regolith surfaces, and have developed new tools to provide predictive PSI environments for various NASA projects and missions, including the Human Lander System (HLS), Commercial Lunar Payload Services (CLPS), and future Mars landers. These tools allow the researchers to determine how to best meet the simulation and time requirements for each project by varying model fidelity. The highest fidelity tool is the Gas Granular Flow Solver (Loci/GGFS) that models gas-particle multi-phase interactions to predict regolith cratering and ejection of particles into the immediate surroundings of the lander. At its highest fidelity, it can model microscopic regolith particle interactions with a particle size/shape distribution that statistically replicates actual regolith, however, to be most effective with today’s computing resources, it is currently run using only one to three equivalent particle sizes/shapes. The team also incorporated engineering models into their software suite to create production-ready hybrid tools with reduced fidelity. At the lowest fidelity, the computational fluid dynamics (CFD) code Loci/CHEM+DIGGEM can predict crater depth over time by relating local CFD-predicted surface shear stresses to a model of erosion mass flux.
Project SIREN (Search, Intercept, Retrieve, Expulsion Nuclear) has been created to identify and evaluate the technologies and operational strategies needed to rendezvous with and capture aerospace radioactive materials (e.g., a distressed or spent space reactor core) before such materials can reenter the terrestrial atmosphere and then to safely move these captured materials to an acceptable space destination for proper disposal. A major component of the current Project SIREN effort is the development of an interactive technology model (including a computerized data base) that explores in building block fashion the interaction of the technologies and procedures needed to successfully accomplish a SIREN mission. This SIREN model will include appropriate national and international technology elements-both contemporary and projected into the next century. To permit maximum flexibility and use, the SIREN technology data base is being programmed for use on 386-class PC's.
Interdisciplinary approaches to the modeling of global problems are discussed in terms of multilevel cooperation. A multilevel regionalized model of the Lake Erie Basin is analyzed along with a multilevel regionalized world modeling project. Other topics discussed include: a stratified model of interacting region in a world system, and the application of the model to the world food crisis in south Asia. Recommended research for future development of integrated models is included.
This report summarizes my internship project with the NASA Digital Astronaut Project to analyze the Digital Astronaut (DA) physiology backbone model. The Digital Astronaut Project (DAP) applies integrated physiology models to support space biomedical operations, and to assist NASA researchers in closing knowledge gaps related to human physiologic responses to space flight. The DA physiology backbone is a set of integrated physiological equations and functions that model the interacting systems of the human body. The current release of the model is HumMod (Human Model) version 1.5 and was developed over forty years at the University of Mississippi Medical Center (UMMC). The physiology equations and functions are scripted in an XML schema specifically designed for physiology modeling by Dr. Thomas G. Coleman at UMMC. Currently it is difficult to examine the physiology backbone without being knowledgeable of the XML schema. While investigating and documenting the tags and algorithms used in the XML schema, I proposed a standard methodology for a graphical representation. This standard methodology may be used to transcribe graphical representations from the DA physiology backbone. In turn, the graphical representations can allow examination of the physiological functions and equations without the need to be familiar with the computer programming languages or markup languages used by DA modeling software.
A CFD model for simulating the self-pressurization of a large scale liquid hydrogen storage tank is utilized in this paper to model the MHTB self-pressurization experiment. The kinetics-based Schrage equation is used to account for the evaporative and condensi ng interfacial mass flows in this model. The effect of the accommodation coefficient for calculating the interfacial mass transfer rate on the tank pressure during tank selfpressurization is studied. The values of the accommodation coefficient which were considered in this study vary from 1.0e-3 to 1.0e-1 for the explicit VOF model and from 1.0e-4 to 1.0e-3 for the implicit VOF model. The ullage pressure evolutions are compared against experimental data. A CFD model for controlling pressure in cryogenic storage tanks by spraying cold liquid into the ullage is also presented. The Euler-Lagrange approach is utilized for tracking the spray droplets and for modeling the interaction between the droplets and the continuous phase (ullage). The spray model is coupled with the VOF model by performing particle tracking in the ullage, removing particles from the ullage when they reach the interface, and then adding their contributions to the liquid. Droplet-ullage heat and mass transfer are modeled. The flow, temperature, and interfacial mass flux, as well as droplets trajectories, size distribution and temperatures predicted by the model are presented. The ul lage pressure and vapor temperature evolutions are compared with experimental data obtained from the MHTB spray bar mixing experiment. The effect of the accommodation coefficient for calculating the interfacial and droplet mass transfer rates on the tank pressure during mixing of the vapor using spray is studied. The values used for the accommodation coefficient at the interface vary from 1.0e-5 to 1.0e-2. The droplet accommodation coefficient values vary from 2.0e-6 to 1.0e-4.
Dust plays important roles in energy cycle and climate variations. The dust deposition is the major source of iron in the open ocean, which is an essential micronutrient for phytoplankton growth and therefore may influence the ocean uptake of atmospheric CO2. Mineral dust can also act as fertilizer for forests over long time periods. Over 35 years of simulated global aerosol products from NASA atmospheric reanalysis, second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) are available from NASA Goddard Earth Science Data and Information Services Center (GES DISC). The MERRA-2 covers the period 1980-present, continuing as an ongoing climate analysis. Aerosol assimilation is included throughout the period, using MODIS, MISR, AERONET, and AVHRR (in the pre-EOS period). The aerosols are assimilated by using MERRA-2 aerosol model, which interact directly with the radiation parameterization, and radiatively coupled with atmospheric model dynamics in the Goddard Earth Observing System Model, Version 5 (GEOS-5). Dust deposition data along with other major aerosol compositions (e.g. black carbon, sea salt, and sulfate, etc.) are simulated as dry and wet deposition, respectively. The hourly and monthly data are available at spatial resolution of 0.5ox0.625o (latitude x longitude). Quick data exploration of climatology and interannual variations of MERRA-2 aerosol can be done through the online visualization and analysis tool, Giovanni. This presentation, using dust deposition as an example, demonstrates a number of MERRA-2 data services at GES DISC. Global distributions of dust depositions, and their seasonal and inter-annual variations are investigated from MERRA-2 monthly aerosol products.
This work presents a general framework for model reduction of non-equilibrium energy transfer and dissociation processes. The multi-group maximum-entropy method is coupled with the quasi-classical trajectory method to directly construct a reduced order model for chemical non-equilibrium. Kinetic data is calculated by applying detailed balance at a microscopic level, overcoming the limitation of calculating recombination kinetic data. This approach enables the construction of a reduced order model for kinetics which bypasses the need to compute state-to-state kinetic data. This physics based reduced order model ensures that an equilibrium distribution is reached given infinite time, while allowing for non-equilibrium distributions during the relaxation and dissociation processes. A proof-of-concept test case demonstrates the applicability of this model by comparison with state-to-state kinetic data for the N2(Chi (sup 1) Sigma ((sub g), (sup plus sign)) minus N ((exp 4) S (sub u)) system with excellent agreement.