Analytical study of control devices for high amplitude combustion instability Quarterly report
Mathematical model and analysis of combustion processes in annular rocket engines for control of high amplitude combustion instability
Burstein, S. Z.↗
SEARCH · Search NASA
Results for “analytical process”
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.
Thermal analysis of M551 experiment for materials processing in space
Heat flow in a disc due to moving heat generated by electron beam was studied analytically. Computer programs based on the finite-element method were developed for the analysis of two and three dimensional mathematical models. The limited experimental data were compared with the analytical results, and factors which had influence on heat flow in the disc were studied. The computer programs were modified to consider the effects of metal melting and solidification as well as radiation. Temperature dependency of thermophysical properties was also considered.
Muraki, T.↗
International Space Station Payload Analytical Integration Overview
This paper contains a general description of the NASA Space Station Payloads Office (SSPO) integration process for International Space Station (ISS) payloads. The end-to-end processes described herein cover the Increment and execute preparation, real-time operations and post-flight phases of payload integration. The paper describes the necessary agreements, plans, documents and reviews required to integrate and operate payloads into standard payload locations. It also summarizes the Program boards, panels and points of contact that a Payload Developer (PI)) will participate in or interface with during the course of the process. The purpose is to provide potential PDs with an outline of the SSPO processes to deliver payloads to orbit, conduct research on orbit and return them to Earth.
Scheib, J.↗
A simple hyperbolic model for communication in parallel processing environments
We introduce a model for communication costs in parallel processing environments called the 'hyperbolic model,' which generalizes two-parameter dedicated-link models in an analytically simple way. Dedicated interprocessor links parameterized by a latency and a transfer rate that are independent of load are assumed by many existing communication models; such models are unrealistic for workstation networks. The communication system is modeled as a directed communication graph in which terminal nodes represent the application processes that initiate the sending and receiving of the information and in which internal nodes, called communication blocks (CBs), reflect the layered structure of the underlying communication architecture. The direction of graph edges specifies the flow of the information carried through messages. Each CB is characterized by a two-parameter hyperbolic function of the message size that represents the service time needed for processing the message. The parameters are evaluated in the limits of very large and very small messages. Rules are given for reducing a communication graph consisting of many to an equivalent two-parameter form, while maintaining an approximation for the service time that is exact in both large and small limits. The model is validated on a dedicated Ethernet network of workstations by experiments with communication subprograms arising in scientific applications, for which a tight fit of the model predictions with actual measurements of the communication and synchronization time between end processes is demonstrated. The model is then used to evaluate the performance of two simple parallel scientific applications from partial differential equations: domain decomposition and time-parallel multigrid. In an appropriate limit, we also show the compatibility of the hyperbolic model with the recently proposed LogP model.
Stoica, Ion↗
Modeling, simulation, and analysis of optical remote sensing systems
Remote Sensing of the Earth's resources from space-based sensors has evolved in the past 20 years from a scientific experiment to a commonly used technological tool. The scientific applications and engineering aspects of remote sensing systems have been studied extensively. However, most of these studies have been aimed at understanding individual aspects of the remote sensing process while relatively few have studied their interrelations. A motivation for studying these interrelationships has arisen with the advent of highly sophisticated configurable sensors as part of the Earth Observing System (EOS) proposed by NASA for the 1990's. Two approaches to investigating remote sensing systems are developed. In one approach, detailed models of the scene, the sensor, and the processing aspects of the system are implemented in a discrete simulation. This approach is useful in creating simulated images with desired characteristics for use in sensor or processing algorithm development. A less complete, but computationally simpler method based on a parametric model of the system is also developed. In this analytical model the various informational classes are parameterized by their spectral mean vector and covariance matrix. These class statistics are modified by models for the atmosphere, the sensor, and processing algorithms and an estimate made of the resulting classification accuracy among the informational classes. Application of these models is made to the study of the proposed High Resolution Imaging Spectrometer (HRIS). The interrelationships among observational conditions, sensor effects, and processing choices are investigated with several interesting results.
Kerekes, John Paul↗
Performance and Reliability Optimization for Aerospace Systems subject to Uncertainty and Degradation
This report summarizes work performed by the Space Systems Laboratory (SSL) for NASA Langley Research Center in the field of performance optimization for systems subject to uncertainty. The objective of the research is to develop design methods and tools to the aerospace vehicle design process which take into account lifecycle uncertainties. It recognizes that uncertainty between the predictions of integrated models and data collected from the system in its operational environment is unavoidable. Given the presence of uncertainty, the goal of this work is to develop means of identifying critical sources of uncertainty, and to combine these with the analytical tools used with integrated modeling. In this manner, system uncertainty analysis becomes part of the design process, and can motivate redesign. The specific program objectives were: 1. To incorporate uncertainty modeling, propagation and analysis into the integrated (controls, structures, payloads, disturbances, etc.) design process to derive the error bars associated with performance predictions. 2. To apply modern optimization tools to guide in the expenditure of funds in a way that most cost-effectively improves the lifecycle productivity of the system by enhancing the subsystem reliability and redundancy. The results from the second program objective are described. This report describes the work and results for the first objective: uncertainty modeling, propagation, and synthesis with integrated modeling.
Miller, David W.↗
Some procedures for computerized electronic data processing of absorption measurements from artificial earth satellites
The processing of data obtained from solar absorption radiation measurements is discussed. The position of the satellite was obtained by numerical integration of the differential equations of motion using initial conditions. The position of the sun was calculated as a function of time, and the tangential elevation was determined approximately from the positions of the satellite and the sun. The coefficients of an approximation formula and of a data smoothing process were determined, and the inversion of an Abel integral equation is solved analytically.
Trinkkeller, B.↗
Low gravity synthesis of polymers with controlled molecular configuration
Heterogeneous chemical systems have been studied for the synthesis of isotactic polypropylene in order to establish baseline parameters for the reaction process and to develop sensitive and accurate methods of analysis. These parameters and analytical methods may be used to make a comparison between the polypropylene obtained at one g with that of zero g (gravity). Baseline reaction parameters have been established for the slurry (liquid monomer in heptane/solid catalyst) polymerization of propylene to yield high purity, 98% isotactic polypropylene. Kinetic data for the slurry reaction showed that a sufficient quantity of polymer for complete characterization can be produced in a reaction time of 5 min; this time is compatible with that available on a sounding rocket for a zero-g simulation experiment. The preformed (activated) catalyst was found to be more reproducible in its activity than the in situ formed catalyst.
Heimbuch, A. H.↗
Viscous effects in aircraft trailing vortices
The mechanism of merging of like-signed aircraft vortices leading to a rapid redistribution of trailed vorticity in a wake through both convective and turbulent processes was investigated. Research was done experimentally in a small wind tunnel and analytically through the use of a code which computes turbulent transport using a second-order closure turbulent model. Computations are reported which demonstrate the merging phenomenon, and comparisons are made with experimental results. The usefulness of point vortex computations in predicting merging was explored. Limited computations showed that jet exhaust does not appreciably alter the merging phenomenon. The effect of ambient atmospheric turbulence on the aging of an aircraft wake was investigated at a constant turbulent dissipation rate. It was shown that under stable atmospheric conditions, when atmospheric macroscales are less than or equal to the vortex spacing, misleading results may be obtained.
Bilanin, A. J.↗
On the flight dynamics of aeroelastic vehicles
The nonlinear equations of motion for an elasic airplane are developed from first principles. Lagrange's Equation and the Principle of Virtual Work are used to generate the equations of motion and strip theory is then employed to obtain closed form integral expressions for the generalized forces. The inertial coupling is minimized by appropriate choice of the body reference axes and by making use of free vibration modes of the body. In addition, particular attention is paid to the simplifying assumptions used during the development of the equations of motion. A unique aspect of this modeling process is that since the generalized aerodynamic forces are determined from closed form, analytic expressions, this method can be used to gain insight into the effects of parameter variations not easily obtained from numerical models. A numerical example is also presented in which the modeling method is applied to a representative elastic aircraft. The model is used to address the effects of aerodynamic coupling which occurs between the rigid body degrees of freedom and the elastic degrees of freedom. Finally, model simplification is addressed and two methods are evaluated. The resulting frequency responses are compared.
Schmidt, D. K.↗
Shock drift acceleration
This is a review of the fundamental physics of the interactions of charged particles treated individually while they interact with fast mode magnetohydrodynamic shocks. Numerical simulation and analytical theory are used to develop predictions of the expected characteristics of this process strong upstream anisotropies directed along the magnetic field and downstream anisotropies tending to be peaked more perpendicular to the field; relatively more of the enhancement of higher-energy particles occurring upstream; sensitive dependence on shock normal to magnetic field angle of the efficiency of energization. Observations which display all of the above characteristics are reviewed. Also discussed is the relationship of shock drift acceleration to the models for stochastic transport of charged particles in the vicinity of shocks. Extensions of this work in both the observational and theoretical approaches are discussed.
Armstrong, Thomas P.↗
Advanced electromagnetic methods for aerospace vehicles
High- and low-frequency methods to analyze various radiation elements located on aerospace vehicles with combinations of conducting, nonconducting, and energy absorbing surfaces and interfaces. The focus was on developing fundamental concepts, techniques, and algorithms which would remove some of the present limitations in predicting radiation characteristics of antennas on complex aerospace vehicles. In order to accomplish this, the following subjects were examined: (1) the development of techniques for rigorous analysis of surface discontinuities of metallic and nonmetallic surfaces using the equivalent surface impedance concept and Green's function; (2) the effects of anisotropic material on antenna radiation patterns through the use of an equivalent surface impedance concept which is incorporated into the existing numerical electromagnetics computer codes; and (3) the fundamental concepts of precipitation static (P-Static), such as formulations and analytical models. A computer code was used to model the P-Static process on a simple structure. Measurement techniques were also developed to characterized the electrical properties at microwave frequencies. Samples of typical materials used in airframes were tested and the results are included.
Balanis, Constantine A.↗
Performance of residual carrier array-feed combining in correlated noise
An array feed combining system for the recovery of signal-to-noise ratio (SNR) loss due to antenna reflector deformation has been implemented and is currently being evaluated on the Jet Propulsion Laboratory's 34-meter DSS-13 antenna. In this system, the defocused signal field captured by a focal plane array feed is recovered using real-time signal-processing and signal-combining techniques. The current signal-processing and signal-combining algorithms are optimum under the assumption that the white Gaussian noise processes in the received signals from different array elements are mutually uncorrelated. Experimental data at DSS 13 indicate that these noise processes are indeed mutually correlated. The main result of this article is an analytical derivation of the actual SNR performance of the current suboptimal signal-combining algorithm in this correlated-noise environment. The analysis here shows that the combined signal SNR can either be improved or degraded depending on the relation between the array signal and noise correlation coefficient phases. Further performance improvement will require the development of signal-combining methods that take into account the correlated noises.
Tan, H. H.↗
Genetic Network Inference: From Co-Expression Clustering to Reverse Engineering
Advances in molecular biological, analytical, and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various aspects of clustering, ranging from distance measures to clustering algorithms and multiple-duster memberships. More advanced analysis aims to infer causal connections between genes directly, i.e., who is regulating whom and how. We discuss several approaches to the problem of reverse engineering of genetic networks, from discrete Boolean networks, to continuous linear and non-linear models. We conclude that the combination of predictive modeling with systematic experimental verification will be required to gain a deeper insight into living organisms, therapeutic targeting, and bioengineering.
Dhaeseleer, Patrik↗
Cognitive Network Modeling as a Basis for Characterizing Human Communication Dynamics and Belief Contagion in Technology Adoption
Societal level macro models of social behavior do not sufficiently capture nuances needed to adequately represent the dynamics of person-to-person interactions. Likewise, individual agent level micro models have limited scalability - even minute parameter changes can drastically affect a model's response characteristics. This work presents an approach that uses agent-based modeling to represent detailed intra- and inter-personal interactions, as well as a system dynamics model to integrate societal-level influences via reciprocating functions. A Cognitive Network Model (CNM) is proposed as a method of quantitatively characterizing cognitive mechanisms at the intra-individual level. To capture the rich dynamics of interpersonal communication for the propagation of beliefs and attitudes, a Socio-Cognitive Network Model (SCNM) is presented. The SCNM uses socio-cognitive tie strength to regulate how agents influence--and are influenced by--one another's beliefs during social interactions. We then present experimental results which support the use of this network analytical approach, and we discuss its applicability towards characterizing and understanding human information processing.
Hutto, Clayton↗
The Distribution and Annihilation of Dark Matter Around Black Holes
We use a Monte Carlo code to calculate the geodesic orbits of test particles around Kerr black holes, generating a distribution function of both bound and unbound populations of dark matter (DM) particles. From this distribution function, we calculate annihilation rates and observable gamma-ray spectra for a few simple DM models. The features of these spectra are sensitive to the black hole spin, observer inclination, and detailed properties of the DM annihilation cross-section and density profile. Confirming earlier analytic work, we find that for rapidly spinning black holes, the collisional Penrose process can reach efficiencies exceeding 600%, leading to a high-energy tail in the annihilation spectrum. The high particle density and large proper volume of the region immediately surrounding the horizon ensures that the observed flux from these extreme events is non-negligible.
astroparticle physics↗
Information Management Workflow and Tools Enabling Multiscale Modeling Within ICME Paradigm
With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Fortunately, material information management systems and physics-based multiscale modeling methods have kept pace with the growing user demands. Herein, recent efforts to establish workflow for and demonstrate a unique set of web application tools for linking NASA GRC's Integrated Computational Materials Engineering (ICME) Granta MI database schema and NASA GRC's Integrated multiscale Micromechanics Analysis Code (ImMAC) software toolset are presented. The goal is to enable seamless coupling between both test data and simulation data, which is captured and tracked automatically within Granta MI®, with full model pedigree information. These tools, and this type of linkage, are foundational to realizing the full potential of ICME, in which materials processing, microstructure, properties, and performance are coupled to enable application-driven design and optimization of materials and structures.
Materials Engineering↗
Integration of Information Management System, Workflow and Computational Tools Enabling Multiscale Modeling Within an ICME Paradigm
With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Fortunately, material information management systems and physics-based multiscale modeling methods have kept pace with the growing user demands. Herein, recent efforts to develop a set of Python functions that exchange information between NASA GRC's Integrated multiscale Micromechanics Analysis Code (ImMAC) software toolset and its Integrated Computational Materials Engineering (ICME), Granta MI® database schema is presented. The goal is to enable seamless coupling between both test data and simulation data, which is captured and tracked automatically within Granta MI®, with full model pedigree information. These tools, and this type of linkage, are foundational to realizing the full potential of ICME, in which materials processing, microstructure, properties, and performance are coupled to enable application-driven design and optimization of materials and structures.
multiscale modeling; Micromechanics; Computational↗