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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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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Computational Model of the Chilldown and Propellant Loading of the Space Shuttle External Tank

This paper describes a computational model of the chilldown and propellant loading of the Space Shuttle External Tank liquid oxygen and hydrogen tanks at Launch Complex 39B at Kennedy Space Center. The purpose of the computational model is to predict the time required to chilldown the entire assembly consisting of the ground system transfer line and propellant tanks in order to compare with observed loading times, to evaluate the feasibility of similar models developed for the Ares I Upper Stage. The model also predicts the history of inflow and outflow from the tank, pressure and temperature inside the tank, and heat leak through the walls. The Generalized Fluid System Simulation Program (GFSSP), a general purpose network flow analysis code, has been used to develop this computational model. The paper describes the simulation of the loading process for both tanks and compares the resulting predictions to measurements

LeClair, Andre C.↗
NASA NTRS2012

The Effect of Geocenter Motion on Jason-2 and Jason-1 Orbits and the Mean Sea Level

We have investigated the impact of geocenter motion on Jason-2 orbits. This was accomplished by computing a series of Jason-1, Jason-2 GPS-based and SLR/DORIS-based orbits using ITRF2008 and the IGS repro1 framework based on the most recent GSFC standards. From these orbits, we extract the Jason-2 orbit frame translational parameters per cycle by the means of a Helmert transformation between a set of reference orbits and a set of test orbits. The fitted annual and seasonal terms of these time-series are compared to two different geocenter motion models. Subsequently, we included the geocenter motion corrections in the POD process as a degree-1 loading displacement correction to the tracking network. The analysis suggested that the GSFC's Jason-2 std0905 GPS-based orbits are closely tied to the center of mass (CM) of the Earth whereas the SLR/DORIS std0905 orbits are tied to the center of figure (CF) of the ITRF2005 (Melachroinos et al., 2012). In this study we extend the investigation to the centering of the GPS constellation and the way those are tied in the Jason-1 and Jason-2 POD process. With a new set of standards, we quantify the GPS and SLR/DORIS-based orbit centering during the Jason-1 and Jason-2 inter-calibration period and how this impacts the orbit radial error over the globe, which is assimilated into mean sea level (MSL) error, from the omission of the full term of the geocenter motion correction.

Melachroinos, Stavros A.↗
NASA NTRS2007

Escalation: How Much is Enough?

Determining the escalation percentage to an estimate is often the subject of fierce debate. Cost increases are determined by dynamic relati onships between many factors, including acts of nature, interest rate s, oil prices, global commodity markets, wars, wage rates, and the ov erall health of the economy, as well as supply and demand for the required goods or services. How much escalation is enough? Are the recen t price increases temporary aberrations, or will they continue to pla gue us? This paper examines historical escalation rates, as well as i ndications of trends. Various analysis methods -- Monte Carlo simulations, neural networks, trend impact analysis, and the Delphi method -- are examined in an attempt to determine future trends.

Butts, Glenn↗
NASA NTRS2015

Numerical Modeling of Self-Pressurization and Pressure Control by Thermodynamic Vent System in a Cryogenic Tank

This paper presents a numerical model of a system-level test bed - the multipurpose hydrogen test bed (MHTB) using Generalized Fluid System Simulation Program (GFSSP). MHTB is representative in size and shape of a fully integrated space transportation vehicle liquid hydrogen (LH2) propellant tank and was tested at Marshall Space Flight Center (MSFC) to generate data for cryogenic storage. GFSSP is a finite volume based network flow analysis software developed at MSFC and used for thermo-fluid analysis of propulsion systems. GFSSP has been used to model the self-pressurization and ullage pressure control by Thermodynamic Vent System (TVS). A TVS typically includes a Joule-Thompson (J-T) expansion device, a two-phase heat exchanger, and a mixing pump and spray to extract thermal energy from the tank without significant loss of liquid propellant. Two GFSSP models (Self-Pressurization & TVS) were separately developed and tested and then integrated to simulate the entire system. Self-Pressurization model consists of multiple ullage nodes, propellant node and solid nodes; it computes the heat transfer through Multi-Layer Insulation blankets and calculates heat and mass transfer between ullage and liquid propellant and ullage and tank wall. TVS model calculates the flow through J-T valve, heat exchanger and spray and vent systems. Two models are integrated by exchanging data through User Subroutines of both models. The integrated models results have been compared with MHTB test data of 50% fill level. Satisfactory comparison was observed between test and numerical predictions.

Majumdar, Alok↗
NASA NTRS2019

Complex Dynamics of Air Traffic Flow

Air traffic in the United States has continued to grow at a steady pace since 1980, except for a dip immediately after the tragic events of September 11, 2001. There are different growth scenarios associated both with the magnitude and the composition of the future air traffic. The Terminal Area Forecast (TAF), prepared every year by the FAA, projects the growth of traffic in the United States. Both Boeing and Airbus publish market outlooks for air travel annually. Although predicting the future growth of traffic is difficult, there are two significant trends: heavily congested major airports continue to see an increase in traffic, and the emergence of regional jets and other smaller aircraft with fewer passengers operating directly between non-major airports. The interaction between air traffic demand and the ability of the system to provide the necessary airport and airspace resources can be modeled as a network. The size of the resulting network varies depending on the choice of its nodes. It would be useful to understand the properties of this network to guide future design and development. Many questions, such as the growth of delay with increasing traffic demand and impact of the en route weather on future air traffic, require a systematic understanding of the properties of the air traffic network. There has been a major advance in the understanding of the behavior of networks with a large number of components. Several theories have been advanced about the evolution of large biological and engineering networks by authors in diversified disciplines like physics, mathematics, biology and computer science. Several networks exhibit a scale-free property in the sense that the probabilistic distribution of their nodes as a function of connections decreases slower than an exponential. These networks are characterized by the fact that a small number of components have a disproportionate influence on the performance of the network. Scale-free networks are tolerant to random failure of components, but are vulnerable to selective attack on components. This paper examines two network representations for the baseline air traffic system. A network defined with the 40 major airports as nodes and with standard flight routes as links has a characteristic scale: all nodes have 60 or more links and no node has more than 460 links. Another network is defined with baseline aircraft routing structure exhibits an exponentially truncated scale-free behavior. Its degree ranges from 2 connections to 2900 connections, and 225 nodes have more than 250 connections. Furthermore, those high-degree nodes are homogeneously distributed in the airspace. A consequence of this scale-free behavior is that the random loss of a single node has little impact, but the loss of multiple high-degree nodes (such as occurs during major storms in busy airspace) can adversely impact the system. Two future scenarios of air traffic growth are used to predict the growth of air traffic in the United States. It is shown that a three-times growth in the overall traffic may result in a ten-times impact on the density of traffic in certain parts of the United States.

Scale-free Networks↗
DOE OSTI2024

Automating Log Synthesis and Visualization with Python and Splunk

The goal of this project is to automate log analysis by utilizing Splunk, Bash, and Python together. Simplifying the monitoring and analysis of network traffic was the main goal. In order to accomplish this, a Bash script was created to use 'tcpdump' to automate network sniffing. It also included a 24-hour file rotation mechanism to effectively manage the pcap files that were generated. After that, a Python script was written to read these pcap files and retrieve pertinent data about network traffic. After processing the collected data, Splunk is used to summarize the important metrics and visualize said information with relevant graphs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Comparative Analysis of HEATNETS for Geothermal Network Performance: Preprint

Thermal energy networks (TENs), also known as 5th generation district energy systems, or more specifically geothermal networks when exchanging heat with geothermal boreholes, are an important technology for decarbonization. In these networks an ambient loop connects buildings and thermal sources, such as a borehole field, to exchange energy and maintain a desired loop temperature. Water-source heat pumps are used at the buildings to connect to the ambient or thermal loop to meet to the building heating and cooling loads and maintain comfort. A semi-transient, reduced-order technical model and techno-economic model, called HEATNETS, has been developed at NREL that captures the flow of energy around a TEN. In this work, a comparison of the HEATNETS technical model and a well-known coding platform used for modeling geothermal networks, TRNSYS, has been completed for a proposed geothermal network as a verification process. Hourly data provided from the TRNSYS simulation included building loads, pumping power, heat pump power, temperature entering and leaving the borehole field, and mass flow rates. The hourly borehole temperatures were used to create a linear regression model utilized in HEATNETS to estimate the borehole field heat exchange. The building loads and mass flow rates were direct inputs to HEATNETS while the pumping power, heat pump power, borehole temperatures, and coefficients of performance were all simulated and calculated by HEATNETS, allowing for direct comparison of the thermal energy transfer, rather than also comparing control systems responses. HEATNETS considers the full process from design inputs to economic outputs and can provide modeling options for high-level initial system design and operational optimization. This study shows that HEATNETS, while not intended to replace other modeling tools, can be a unique modeling tool for the performance of a full geothermal network system.

15 GEOTHERMAL ENERGY↗
NASA NTRS2004

Analysis of telescope site selection for optical Deep Space Network.

In this paper, therefore, we present an analysis of site selection for an optical deep space network as performed by the ODSN study group at JPL. Given a set of mission requirements, we illustrate how the high-level requirements, along with the properties of the atmospheric channel, can be used to determine the site selection and the architecture of an ODSN. Moreover, we characterize candidate sites for a global optical network and their possible suitability for global architectures such as the linear dispersed optical subnet (LDOS) and cluster optical subnet network (COS).

Cesarone, Robert↗
NASA NTRS1991

Network interface unit design options performance analysis

An analysis is presented of three design options for the Space Station Freedom (SSF) onboard Data Management System (DMS) Network Interface Unit (NIU). The NIU provides the interface from the Fiber Distributed Data Interface (FDDI) local area network (LAN) to the DMS processing elements. The FDDI LAN provides the primary means for command and control and low and medium rate telemetry data transfers on board the SSF. The results of this analysis provide the basis for the implementation of the NIU.

Miller, Frank W.↗
DOE OSTI2025

Criticality analysis of nuclear binding energy neural networks

Machine learning methods, in particular deep learning methods such as artificial neural networks (ANNs) with many layers, have become widespread and useful tools in nuclear physics. However, these ANNs are typically treated as ‘black boxes’, with their architecture (width, depth, and weight/bias initialization) and the training algorithm and parameters chosen empirically by optimizing learning based on limited exploration. We test a non-empirical approach to understanding and optimizing nuclear physics ANNs by adapting a criticality analysis based on renormalization group flows in terms of the hyperparameters for weight/bias initialization, training rates, and the ratio of depth to width. This treatment utilizes the statistical properties of neural network initialization to find a generating functional for network outputs at any layer, allowing for a path integral formulation of the ANN outputs as a Euclidean statistical field theory. We use a prototypical example to test the applicability of this approach: a simple ANN for nuclear binding energies. We find that with training using a stochastic gradient descent optimizer, the predicted criticality behavior is realized, and optimal performance is found with critical tuning. However, the use of an adaptive learning algorithm leads to somewhat superior results without concern for tuning and thus obscures the analysis. Nevertheless, the criticality analysis offers a way to look within the black box of ANNs, which is a first step towards potential improvements in network performance beyond using adaptive optimizers.

artificial neural network↗
NASA NTRS1997

Precise Point Positioning for the Efficient and Robust Analysis of GPS Data From Large Networks

Networks of dozens to hundreds of permanently operating precision Global Positioning System (GPS) receivers are emerging at spatial scales that range from 10(exp 0) to 10(exp 3) km. To keep the computational burden associated with the analysis of such data economically feasible, one approach is to first determine precise GPS satellite positions and clock corrections from a globally distributed network of GPS receivers. Then, data from the local network are analyzed by estimating receiver specific parameters with receiver-specific data; satellite parameters are held fixed at their values determined in the global solution. This "precise point positioning" allows analysis of data from hundreds to thousands of sites every day with 40 Mflop computers, with results comparable in quality to the simultaneous analysis of all data. The reference frames for the global and network solutions can be free of distortion imposed by erroneous fiducial constraints on any sites.

Zumberge, J. F.↗
NASA NTRS1997

Precise Point Positioning for the Efficient and Robust Analysis of GPS Data from Large Networks

Networks of dozens to hundreds of permanently operating precision Global Positioning System (GPS) receivers are emerging at spatial scales that range from 10(exp 0) to 10(exp 3) km. To keep the computational burden associated with the analysis of such data economically feasible, one approach is to first determine precise GPS satellite positions and clock corrections from a globally distributed network of GPS receivers. Their, data from the local network are analyzed by estimating receiver- specific parameters with receiver-specific data satellite parameters are held fixed at their values determined in the global solution. This "precise point positioning" allows analysis of data from hundreds to thousands of sites every (lay with 40-Mflop computers, with results comparable in quality to the simultaneous analysis of all data. The reference frames for the global and network solutions can be free of distortion imposed by erroneous fiducial constraints on any sites.

Zumberge, J. F.↗