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At least 1,117 records · Page 62

Stirling Engine Dynamic System Modeling

The Thermo-Mechanical systems branch at the Glenn Research Center focuses a large amount time on Stirling engines. These engines will be used on missions where solar power is inefficient, especially in deep space. I work with Tim Regan and Ed Lewandowski who are currently developing and validating a mathematical model for the Stirling engines. This model incorporates all aspects of the system including, mechanical, electrical and thermodynamic components. Modeling is done through Simplorer, a program capable of running simulations of the model. Once created and then proven to be accurate, a model is used for developing new ideas for engine design. My largest specific project involves varying key parameters in the model and quantifying the results. This can all be done relatively trouble-free with the help of Simplorer. Once the model is complete, Simplorer will do all the necessary calculations. The more complicated part of this project is determining which parameters to vary. Finding key parameters depends on the potential for a value to be independently altered in the design. For example, a change in one dimension may lead to a proportional change to the rest of the model, and no real progress is made. Also, the ability for a changed value to have a substantial impact on the outputs of the system is important. Results will be condensed into graphs and tables with the purpose of better communication and understanding of the data. With the changing of these parameters, a more optimal design can be created without having to purchase or build any models. Also, hours and hours of results can be simulated in minutes. In the long run, using mathematical models can save time and money. Along with this project, I have many other smaller assignments throughout the summer. My main goal is to assist in the processes of model development, validation and testing.

Nakis, Christopher G.↗

Quaoar: New, Longitudinaly Resolved, Spectroscopic Characterization of Its Surface

(50000) Quaoar, one of the largest Trans-neptunian objects, is comparable in size to Pluto's moon Charon. However, while Charon's surface is rich almost exclusively in H2O ice, Quaoar's surface characterized by ices of CH4, N2, as well as C2H6, a product of irradiation of CH4 (Dalle Ore et al. 2009). Because of its distance from the Sun, Quaoar is expected to have preserved, to a degree, its original composition, however, its relatively small size did not make it a prime candidate for presence of volatile ices in the study by Schaller and Brown (2007). Furthermore, based on the Brown et al. (2011) study (Brown, Schaller, & Fraser, 2011. A Hypothesis for the Color Diversity of the Kuiper Belt. ApJL, 739, L60) its red coloration points to CH3OH as the ice which, when irradiated, might have produced the red material. We present new visible to near-infrared (0.3-2.48 micrometers) spectro-photometric data obtained with the XSHOOTER (Vernet et al. 2011, A&A, 536A, 105 ) instrument at the VLT-ESO facility at four different longitudes on the surface of Quaoar. The data are complemented by previously published photometric observations obtained in the near-infrared (3.6, 4.5 micrometers) with the Spitzer Space Telescope, which provide an extra set of constraints in the model calculation process in spite of the different observing times that preclude establishing the spatial consistency between the two sets. For each of the four spectra we perform spectral modeling of the entire wavelength range -from 0.3 to 4.5 micrometers- by means of a code based on the Shkuratov radiative transfer formulation of the slab model. We obtain spatially resolved compositional information for the surface of Quaoar supporting the presence of CH4 and C2H6, as previously reported, along with evidence for N2 and NH3OH. The albedo at the two Spitzer bands indicates the likely presence of CO and CO2. CH3OH, predicted on the basis of Quaoar's coloration (Brown et al. 2011), is not found at any of the four longitudes, implying that the presence of this ice is a sufficient, but not necessary condition for reddening of TNO surfaces. Other ices, in particular CH4 (Brunetto et al. 2006), have been shown to be plausible precursors for reddening of TNO surfaces.

Ices↗

Rapid Model Import Tool (RMIT) User Guide

The NASA Rapid Model Import Tool (RMIT) is designed to import 3D models built in commercially available Computer Aided Design (CAD) and Digital Content Creation (DCC) development software such as; Catia, Creo, 3DS Max, Maya, etc. Upon import, RMIT processes the models to reduce file size and exports the results in a format compatible with Augmented Reality (AR) and Virtual Reality (VR) development software applications. RMIT intends to make CAD models directly accessible to engineers from local AR/VR compatible laptops and desktops.

Joseluis Chavez↗

Extension of the coherence function to quadratic models

It is shown how the use of higher coherence functions can recover some of the lost coherence due to nonlinear relationship between two fluctuating quantities whose degree of mutual coherence is being measured. The relationship between the two processes is modeled with the aid of a linear term and a quadratic term. As a specific example, the relationship between plasma density and potential fluctuations in a plasma is considered. The fraction of power in the auto-power spectrum of the potential fluctuations due to a linear relationship and to a quadratic relationship between the density and potential fluctuations is estimated.

Kim, Y. C.↗

A double layer model for solar X-ray and microwave pulsations

The wide range of wavelengths over which quasi-periodic pulsations have been observed suggests that the mechanism causing them acts upon the supply of high energy electrons driving the emission processes. A model is described which is based upon the radial shrinkage of a magnetic flux tube. The concentration of the current, along with the reduction in the number of available charge carriers, can rise to a condition where the current demand exceeds the capacity of the thermal electrons. Driven by the large inductance of the external current circuit, an instability takes place in the tube throat, resulting in the formation of a potential double layer, which then accelerates electrons and ions to MeV energies. The double layer can be unstable, collapsing and reforming repeatedly. The resulting pulsed particle beams give rise to pulsating emission which are observed at radio and X-ray wavelengths.

Tapping, K. F.↗

LPV Modeling of a Flexible Wing Aircraft Using Modal Alignment and Adaptive Gridding Methods

One of the earliest approaches in gain-scheduling control is the gridding based approach, in which a set of local linear time-invariant models are obtained at various gridded points corresponding to the varying parameters within the flight envelop. In order to ensure smooth and effective Linear Parameter-Varying control, aligning all the flexible modes within each local model and maintaining small number of representative local models over the gridded parameter space are crucial. In addition, since the flexible structural models tend to have large dimensions, a tractable model reduction process is necessary. In this paper, the notion of s-shifted H2- and H Infinity-norm are introduced and used as a metric to measure the model mismatch. A new modal alignment algorithm is developed which utilizes the defined metric for aligning all the local models over the entire gridded parameter space. Furthermore, an Adaptive Grid Step Size Determination algorithm is developed to minimize the number of local models required to represent the gridded parameter space. For model reduction, we propose to utilize the concept of Composite Modal Cost Analysis, through which the collective contribution of each flexible mode is computed and ranked. Therefore, a reduced-order model is constructed by retaining only those modes with significant contribution. The NASA Generic Transport Model operating at various flight speeds is studied for verification purpose, and the analysis and simulation results demonstrate the effectiveness of the proposed modeling approach.

LPV Modeling↗

Designing a training tool for imaging mental models

The training process can be conceptualized as the student acquiring an evolutionary sequence of classification-problem solving mental models. For example a physician learns (1) classification systems for patient symptoms, diagnostic procedures, diseases, and therapeutic interventions and (2) interrelationships among these classifications (e.g., how to use diagnostic procedures to collect data about a patient's symptoms in order to identify the disease so that therapeutic measures can be taken. This project developed functional specifications for a computer-based tool, Mental Link, that allows the evaluative imaging of such mental models. The fundamental design approach underlying this representational medium is traversal of virtual cognition space. Typically intangible cognitive entities and links among them are visible as a three-dimensional web that represents a knowledge structure. The tool has a high degree of flexibility and customizability to allow extension to other types of uses, such a front-end to an intelligent tutoring system, knowledge base, hypermedia system, or semantic network.

Dede, Christopher J.↗

Relations between transverse electric fields and field-aligned currents

A model for the field-aligned propagation of transverse electric fields and associated field-aligned sheet currents is presented which takes into account the wave nature of the process. The model is applied to the separate cases of ionospheric and magnetospheric sources, and the resulting ionospheric electric field to field-aligned sheet current ratios are determined for comparison with experimental observations. It is found that the magnetospheric wave 'conductivity' for shear mode Alfven waves is small with respect to typical values of the height-integrated ionospheric Pedersen conductivity. For plasma convecting across a stationary disturbance a dynamic equilibrium is achieved in which field-aligned currents flow continuously away from the source on convecting field lines. Consistency with typical ionospheric electric fields requires that the field-aligned sheet currents are limited to around 0.1 A/m for ionospheric polarization sources, while magnetospheric sources are easily capable of 1 A/m or more.

Mallinckrodt, A. J.↗

Stabilization of discrete-event processes

Discrete-event processes are modeled by state-machines in the Ramadge-Wonham framework with control by a feedback event disablement mechanism. In this paper, concepts of stabilization of discrete-event processes are defined and investigated. The possibility of driving a process (under control) from arbitrary initial states to a prescribed subset of the state set and then keeping it there indefinitely is examined. This stabilization property is studied also with respect to 'open-loop' processes and their asymptotic behavior is characterized. Polynomial time algorithms are presented for verifying various types of attraction and for the synthesis of attractors.

Brave, Y.↗

The New NASA Orbital Debris Engineering Model ORDEM2000

The NASA Orbital Debris Program Office at Johnson Space Center has developed a new computer-based orbital debris engineering model, ORDEM2000, which describes the orbital debris environment in the low Earth orbit region between 200 and 2000 km altitude. The model is appropriate for those engineering solutions requiring knowledge and estimates of the orbital debris environment (debris spatial density, flux, etc.). ORDEM2000 can also be used as a benchmark for ground-based debris measurements and observations. We incorporated a large set of observational data, covering the object size range from 10 mm to 10 m, into the ORDEM2000 debris database, utilizing a maximum likelihood estimator to convert observations into debris population probability distribution functions. These functions then form the basis of debris populations. We developed a finite element model to process the debris populations to form the debris environment. A more capable input and output structure and a user-friendly graphical user interface are also implemented in the model. ORDEM2000 has been subjected to a significant verification and validation effort. This document describes ORDEM2000, which supersedes the previous model, ORDEM96. The availability of new sensor and in situ data, as well as new analytical techniques, has enabled the construction of this new model. Section 1 describes the general requirements and scope of an engineering model. Data analyses and the theoretical formulation of the model are described in Sections 2 and 3. Section 4 describes the verification and validation effort and the sensitivity and uncertainty analyses. Finally, Section 5 describes the graphical user interface, software installation, and test cases for the user.

Liou, Jer-Chyi↗

Application of Machine Learning to Rotorcraft Health Monitoring

Machine learning is a powerful tool for data exploration and model building with large data sets. This project aimed to use machine learning techniques to explore the inherent structure of data from rotorcraft gear tests, relationships between features and damage states, and to build a system for predicting gear health for future rotorcraft transmission applications. Classical machine learning techniques are difficult, if not irresponsible to apply to time series data because many make the assumption of independence between samples. To overcome this, Hidden Markov Models were used to create a binary classifier for identifying scuffing transitions and Recurrent Neural Networks were used to leverage long distance relationships in predicting discrete damage states. When combined in a workflow, where the binary classifier acted as a filter for the fatigue monitor, the system was able to demonstrate accuracy in damage state prediction and scuffing identification. The time dependent nature of the data restricted data exploration to collecting and analyzing data from the model selection process. The limited amount of available data was unable to give useful information, and the division of training and testing sets tended to heavily influence the scores of the models across combinations of features and hyper-parameters. This work built a framework for tracking scuffing and fatigue on streaming data and demonstrates that machine learning has much to offer rotorcraft health monitoring by using Bayesian learning and deep learning methods to capture the time dependent nature of the data. Suggested future work is to implement the framework developed in this project using a larger variety of data sets to test the generalization capabilities of the models and allow for data exploration.

machine learning↗

Harmonized Emissions Component (HEMCO) 3.0 as a Versatile Emissions Component for Atmospheric Models: Application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS Models

Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to re-grid, combine, overwrite, subset, and scale emissions from different inventories through a configuration file and with no change to the model source code. The configuration file also maps emissions to model species with appropriate units. HEMCO can operate in offline stand-alone mode, but more importantly it provides an online facility for models to compute emissions at runtime. HEMCO complies with the Earth System Modeling Framework (ESMF) for portability across models. We present a new version here, HEMCO 3.0, that features an improved three-layer architecture to facilitate implementation into any atmospheric model and improved capability for calculating emissions at any model resolution including multiscale and unstructured grids. The three-layer architecture of HEMCO 3.0 includes (1) the Data Input Layer that reads the configuration file and accesses the HEMCO library of emission inventories and other environmental data, (2) the HEMCO Core that computes emissions on the user-selected HEMCO grid, and (3) the Model Interface Layer that re-grids (if needed) and serves the data to the atmospheric model and also serves model data to the HEMCO Core for computing emissions dependent on model state (such as from dust or vegetation). The HEMCO Core is common to the implementation in all models, while the Data Input Layer and the Model Interface Layer are adaptable to the model environment. Default versions of the Data Input Layer and Model Interface Layer enable straightforward implementation of HEMCO in any simple model architecture, and options are available to disable features such as re-gridding that may be done by independent couplers in more complex architectures. The HEMCO library of emission inventories and algorithms is continuously enriched through user contributions so that new inventories can be immediately shared across models. HEMCO can also serve as a general data broker for models to process input data not only for emissions but for any gridded environmental datasets. We describe existing implementations of HEMCO 3.0 in (1) the GEOS-Chem “Classic” chemical transport model with shared-memory infrastructure, (2) the high-performance GEOS-Chem (GCHP) model with distributed-memory architecture, (3) the NASA GEOS Earth System Model (GEOS ESM), (4) the Weather Research and Forecasting model with GEOS-Chem (WRF-GC), (5) the Community Earth System Model Version 2 (CESM2), and (6) the NOAA Global Ensemble Forecast System – Aerosols (GEFS-Aerosols), as well as the planned implementation in the NOAA Unified Forecast System (UFS). Implementation of HEMCO in CESM2 contributes to the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA) by providing a common emissions infrastructure to support different simulations of atmospheric chemistry across scales.

Haipeng Lin↗

TopiQAL: Topic-aware Question Answering using Scalable Domain-specific Supercomputers

We all have questions. About today's temperature, scores of our favorite baseball team, the Universe, and about vaccine for COVID-19. Life, physical, and natural scientists have been trying to find answers to various topics using scientific methods and experiments, while computer scientists have built language models as a tiny step towards automatically answering all of these questions across domains given a little bit of context. In this paper, we propose an architecture using state-of-the-art Natural Language Processing language models namely Topic Models and Bidirectional Encoder Representations from Transformers (BERT) that can transparently and automatically retrieve articles of relevance to questions across domains, and fetch answers to topical questions related to COVID-19 current and historical medical research literature. We demonstrate the benefits of using domain-specific supercomputers like Tensor Processing Units (TPUs), residing on cloud-based infrastructure, using which we could achieve significant gains in training and inference times, also with very minimal cost.

Penberthy, Scott↗

Utilization of remote sensing observations in hydrologic models

Most of the remote sensing related work in hydrologic modeling has centered on modifying existing models to take advantage of the capabilities of new sensor techniques. There has been enough success with this approach to insure that remote sensing is a powerful tool in modeling the watershed processes. Unfortunately, many of the models in use were designed without recognizing the growth of remote sensing technology. Thus, their parameters were selected to be map or field crew definable. It is believed that the real benefits will come through the evolution of new models having new parameters that are developed specifically to take advantage of our capabilities in remote sensing. The ability to define hydrologically active areas could have a significant impact. The ability to define soil moisture and the evolution of new techniques to estimate evoportransportation could significantly modify our approach to hydrologic modeling. Still, without a major educational effort to develop an understanding of the techniques used to extract parameter estimates from remote sensing data, the potential offered by this new technology will not be achieved.

Ragan, R. M.↗

Premixing quality and flame stability: A theoretical and experimental study

Models for predicting flame ignition and blowout in a combustor primary zone are presented. A correlation for the blowoff velocity of premixed turbulent flames is developed using the basic quantities of turbulent flow, and the laminar flame speed. A statistical model employing a Monte Carlo calculation procedure is developed to account for nonuniformities in a combustor primary zone. An overall kinetic rate equation is used to describe the fuel oxidation process. The model is used to predict the lean ignition and blow out limits of premixed turbulent flames; the effects of mixture nonuniformity on the lean ignition limit are explored using an assumed distribution of fuel-air ratios. Data on the effects of variations in inlet temperature, reference velocity and mixture uniformity on the lean ignition and blowout limits of gaseous propane-air flames are presented.

Radhakrishnan, K.↗

Simple construction and performance of a conical plastic cryocooler

Low power cryocoolers with conical displacers offer several advantages over stepped displacers. The described fabrication process allows quick and reproducible manufacturing of plastic conical displacer units. This could be of commercial interest, but it also makes systematic optimization feasible by constructing a number of different models. The process allows for a wide range of displacer profiles. Low temperature performance as dominated by regenerator losses, and several effects are discussed. A simple device is described which controls gas flow during expansion.

Lambert, N.↗

Intensity dependent spread theory

The Intensity Dependent Spread (IDS) procedure is an image-processing technique based on a model of the processing which occurs in the human visual system. IDS processing is relevant to many aspects of machine vision and image processing. For quantum limited images, it produces an ideal trade-off between spatial resolution and noise averaging, performs edge enhancement thus requiring only mean-crossing detection for the subsequent extraction of scene edges, and yields edge responses whose amplitudes are independent of scene illumination, depending only upon the ratio of the reflectance on the two sides of the edge. These properties suggest that the IDS process may provide significant bandwidth reduction while losing only minimal scene information when used as a preprocessor at or near the image plane.

Holben, Richard↗