Computational Modeling of Metal Organic Frameworks for Carbon Capture
Computational Modeling of Metal Organic Frameworks for Carbon Capture
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Computational Modeling of Metal Organic Frameworks for Carbon Capture
Analog computer modeling of human systemic arterial tree, based on lump parameter circuit approximation
Computer modeling of rocket engine ignition transients
A computer model of the JPL hydrogen maser frequency standard was developed. This model allows frequency stability data to be generated, as a function of various maser parameters, many orders of magnitude faster than these data can be obtained by experimental test. In particular, the maser performance as a function of the various automatic tuning servo parameters may be readily determined. Areas of discussion include noise sources, first-order autotuner loop, second-order autotuner loop, and a comparison of the loops.
A computer model of the Spartan Release Engagement Mechanism (REM) is presented in a series of numerical charts and engineering drawings. A crack growth analysis code is used to predict the fracture mechanics of critical components.
A realistic computer model for simulating isothermal and non-isothermal phase transformations proceeding by homogeneous and heterogeneous nucleation and interface-limited growth is presented. A new treatment for particle size effects on the crystallization kinetics is developed and is incorporated into the numerical model. Time-dependent nucleation rates, size-dependent growth rates, and surface crystallization are also included. Model predictions are compared with experimental measurements of DSC/DTA peak parameters for the crystallization of lithium disilicate glass as a function of particle size, Pt doping levels, and water content. The quantitative agreement that is demonstrated indicates that the numerical model can be used to extract key kinetic data from easily obtained calorimetric data. The model can also be used to probe nucleation and growth behavior in regimes that are otherwise inaccessible. Based on a fit to data, an earlier prediction that the time-dependent nucleation rate in a DSC/DTA scan can rise above the steady-state value at a temperature higher than the peak in the steady-state rate is demonstrated.
An advanced computational model is being developed to predict the formation of indium nitride (InN) film from the reaction of trimethylindium (In(CH3)3) with ammonia (NH3). The components are introduced into the reactor in the gas phase within a background of molecular nitrogen (N2). Organometallic chemical vapor deposition occurs on a heated sapphire surface. The model simulates heat and mass transport with gas and surface chemistry under steady state and pulsed conditions. The development and validation of an accurate model for the interactions between the diffusion of gas phase species and surface kinetics is essential to enable the regulation of the process in order to produce a low defect material. The validation of the model will be performed in concert with a NASA-North Carolina State University project.
Over the past decade we developed a model to enable computer simulation of the mechanical and subsequent energetic response of explosives and propellants to mechanical insults such as impacts, perforations, drops, and falls. The model is embedded in computer simulation programs that solve the non-linear, large deformation equations of compressible solid and fluid flow in space and time. It is implemented as a user-defined model, which returns the updated stress tensor and composition that result from the simulation supplied strain tensor change. Although it is multi-phase, in that gas and solid species are present, it is single-velocity, in that the gas does not flow through the porous solid. More than 70 time-dependent variables are made available for additional analyses and plotting. The model encompasses a broad range of possible responses: mechanical damage with no energetic response, and a continuous spectrum of degrees of violence including delayed and prompt detonation. This work describes the basic workings of the model.
Very high resolution stereoscopic images of high temperature loop structures observed at UV and X-ray wavelengths in the solar corona can be used to understand physical processes in the corona. An existing computational model is described and sample results are given to demonstrate that computational modeling of coronal structures can indeed take advantage of very high resolution images. The sample results include the run of temperature and number density along a typical loop and the variation of the differential emission measure with temperature. The integration of the differential emission measure with temperature along a column commensurate with an instrument's spatial resolution is the relevant parameter obtained from UV and X-ray observations. The effects of loop geometry and energy input are examined.
A computer program for analyzing rocket engine performance was developed. The program is concerned with the formation, distribution, flow, and combustion of liquid sprays and combustion product gases in conventional rocket combustion chambers. The capabilities of the program to determine the combustion characteristics of the rocket engine are described. Sample data code sheets show the correct sequence and formats for variable values and include notes concerning options to bypass the input of certain data. A seperate list defines the variables and indicates their required dimensions.
The investigation of specific interactions among biological molecules must take into consideration the stereochemistry of the structures. Thus, models of the molecules are essential for describing the spatial organization of potentially interacting groups, and estimations of conformation are required for a description of spatial organization. Both the function of visualizing molecules, and that of estimating conformation through calculations of energy, are part of the molecular modeling system described in the present paper. The potential uses of the system in investigating some aspects of the origin of life rest on the assumption that translation of conformation from genetic elements to catalytic elements would have been required for the development of the first replicating systems subject to the process of biological evolution.
In a previous work, embedded ensemble propagation was proposed to improve the efficiency of sampling-based uncertainty quantification methods of computational models on emerging computational architectures. It consists of simultaneously evaluating the model for a subset of samples together, instead of evaluating them individually. A first approach introduced to solve parametric linear systems with ensemble propagation is ensemble reduction. In Krylov methods for example, this reduction consists in coupling the samples together using an inner product that sums the sample contributions. Ensemble reduction has the advantages of being able to use optimized implementations of BLAS functions and having a stopping criterion which involves only one scalar. However, the reduction potentially decreases the rate of convergence due to the gathering of the spectra of the samples. In this paper, we investigate a second approach: ensemble propagation without ensemble reduction in the case of GMRES. This second approach solves each sample simultaneously but independently to improve the convergence compared to ensemble reduction. This raises two new issues which are solved in this paper: the fact that optimized implementations of BLAS functions cannot be used anymore and that ensemble divergence, whereby individual samples within an ensemble must follow different code execution paths, can occur. We tackle those issues by implementing a high-performing ensemble GEMV and by using masks. The proposed ensemble GEMV leads to a similar cost per GMRES iteration for both approaches, i.e. with and without reduction. For illustration, we study the performances of the new linear solver in the context of a mesh tying problem. Furthermore, this example demonstrates improved ensemble propagation speed-up without reduction.
This paper presents a set of studies in full mission simulation and the development of a predictive computational model of human performance in control of complex airspace operations. NASA and the FAA have initiated programs of research and development to provide flight crew, airline operations and air traffic managers with automation aids to increase capacity in en route and terminal area to support the goals of safe, flexible, predictable and efficient operations. In support of these developments, we present a computational model to aid design that includes representation of multiple cognitive agents (both human operators and intelligent aiding systems). The demands of air traffic management require representation of many intelligent agents sharing world-models, coordinating action/intention, and scheduling goals and actions in a potentially unpredictable world of operations. The operator-model structure includes attention functions, action priority, and situation assessment. The cognitive model has been expanded to include working memory operations including retrieval from long-term store, and interference. The operator's activity structures have been developed to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. System stability and operator actions can be predicted by using the model. The model's predictive accuracy was verified using the full-mission simulation data of commercial flight deck operations with advanced air traffic management techniques.
A Stirling engine digital computer model developed at NASA Lewis Research Center was configured to predict the performance of the GPU-3 single-cylinder rhombic drive engine. Revisions to the basic equations and assumptions are discussed. Model predictions with the early results of the Lewis Research Center GPU-3 tests are compared.
A computational model of the deterministic and stochastic process of remote sensing has been developed based upon the results of the investigations presented. The model is used in studying concepts for improving worldwide environment and resource monitoring. A review of various atmospheric radiative transfer models is presented as well as details of the selected model. Functional forms for spectral diffuse reflectance with variability introduced are also presented. A cloud detection algorithm and the stochastic nature of remote sensing data with its implications are considered.
A computable model of human spatial vision is used to make predictions for phase-discrimination experiments. This model is being developed to deal with a broad range of problems in vision and was not specifically formulated to deal with phase discrimination. In the model, cross-correlation of the stimuli with an array of sensors produces feature vectors that are operated on by a position-uncertain ideal observer to simulate detection and discrimination experiments. In this report, the stimuli are compound sinusoidal gratings composed of a fundamental and a higher-frequency component added in various phases. Model predictions are compared with three key results from the literature: (1) the effect of the contrast of the fundamental on phase discrimination, (2) threshold phase difference as a function of the fundamental frequency, and (3) the contrast required for phase discrimination as a function of the frequency ratio of the two grating components. In the first two cases, the predictions capture the main features of the data, although quantitative discrepancies remain. In the third case, the model fails, and this failure suggests additional restrictions on the combination of information across sensors.
This paper describes a novel computational model for dynamic vision which promises to be both powerful and robust. Furthermore the paradigm is ideal for an active vision system where camera vergence changes dynamically. Its basis is the retinotopically indexed object-centered encoding of the early visual information. Specifically, the relative distances of objects to a set of referents is encoded in image registered maps. To illustrate the efficacy of the method, it is applied to the problem of dynamic stereo vision. Integration of depth information over multiple frames obtained by a moving robot generally requires precise information about the relative camera position from frame to frame. Usually, this information can only be approximated. The method facilitates the integration of depth information without direct use or knowledge of camera motion.
Presentation on Computational Modeling of Functional Materials for Energy Applications