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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

A function space approach to smoothing with applications to model error estimation for flexible spacecraft control

A function space approach to smoothing is used to obtain a set of model error estimates inherent in a reduced-order model. By establishing knowledge of inevitable deficiencies in the truncated model, the error estimates provide a foundation for updating the model and thereby improving system performance. The function space smoothing solution leads to a specification of a method for computation of the model error estimates and development of model error analysis techniques for comparison between actual and estimated errors. The paper summarizes the model error estimation approach as well as an application arising in the area of modeling for spacecraft attitude control.

Rodriguez, G.↗
NASA NTRS1983

Model error estimation for distributed systems described by elliptic equations

A function space approach is used to develop a theory for estimation of the errors inherent in an elliptic partial differential equation model for a distributed parameter system. By establishing knowledge of the inevitable deficiencies in the model, the error estimates provide a foundation for updating the model. The function space solution leads to a specification of a method for computation of the model error estimates and development of model error analysis techniques for comparison between actual and estimated errors. The paper summarizes the model error estimation approach as well as an application arising in the area of modeling for static shape determination of large flexible systems.

Rodriguez, G.↗
NASA NTRS1992

A viscoplastic theory for anisotropic materials

The purpose of this work is the development of a unified, cyclic, viscoplastic model for anisotropic materials. The first part of the paper presents the foundations of the model in the framework of thermodynamics with internal variables. The second part considers the particular case of cubic symmetry, and addresses the cyclic behavior of a nickel-base single-crystal superalloy, CMSX-2, at high temperature (950 C).

Nouailhas, D.↗
NASA NTRS1983

An efficient computational method for characterizing the effects of random surface errors on the average power pattern of reflectors

Based on the works of Ruze (1966) and Vu (1969), a novel mathematical model has been developed to determine efficiently the average power pattern degradations caused by random surface errors. In this model, both nonuniform root mean square (rms) surface errors and nonuniform illumination functions are employed. In addition, the model incorporates the dependence on F/D in the construction of the solution. The mathematical foundation of the model rests on the assumption that in each prescribed annular region of the antenna, the geometrical rms surface value is known. It is shown that closed-form expressions can then be derived, which result in a very efficient computational method for the average power pattern. Detailed parametric studies are performed with these expressions to determine the effects of different random errors and illumination tapers on parameters such as gain loss and sidelobe levels. The results clearly demonstrate that as sidelobe levels decrease, their dependence on the surface rms/wavelength becomes much stronger and, for a specified tolerance level, a considerably smaller rms/wavelength is required to maintain the low sidelobes within the required bounds.

Rahmat-Samii, Y.↗
NASA NTRSDate not supplied

Predicting Air Traffic Management Initiatives Using Supervised Learning

Terminal Traffic Management Initiatives (TMIs) such as Ground Stops (GS) and Ground Delay Programs (GDP) are implemented to manage excess demand or lowered capacity at an airport. Air Traffic Flow Management (TFM) specialists identify situations such as aviation constraints, current and forecasted weather conditions, airport demand and capacity, and initiate TMIs for safe and orderly movement of air traffic. In this paper, we outline supervised learning techniques that can be used to predict and recommend TMIs at an airport based on current weather and airport conditions. Our research involves building classic Machine Learning (ML) models such as Logistic Regression, K-Nearest Neighbor, Random Forest and XGBoost, as well as Long short-term memory (LSTM) networks. We trained the models on 3-year historical data (weather, airport demand, capacity and TMIs) from Newark (EWR) airport which was selected based on its higher TMI implementation rates and varied weather conditions. Although Random Forest and XGBoost algorithms are able to predict if a TMI is needed or not, they have difficulty in predicting specific program type. For this purpose, we found that LSTM time-series forecasting models performed better as they also learn from past TMI program type sequences. This study also lays down the foundation for advanced modeling techniques and architectures to predict TMIs in advance for future periods. The ability to predict TMIs in advance will be highly beneficial to the traffic controllers and managers as this will help them to prepare for and manage TMIs more efficiently.

Manoj Agrawal↗
NASA NTRSDate not supplied

Framework for Analyzing the Complex Interactions Between Spacecraft Motion and Slosh Dynamics in Low-G Environments

The fuel-to-dry-mass ratio of spacecraft continues to grow as new human spaceflight missions target destinations from Earth. Large amounts of liquid propellant can lead to significant coupling between the rigid-body dynamics of the spacecraft and the motion of the fuel within its storage tank. The present work gives an overview of the dynamic features and a flowchart for a method of simulating the motion of a spacecraft with fuel slosh inside a cylindrical, domed tank in a low-g environment. The method involves modeling the liquid propellant as a particle that transfers momentum to the spacecraft through perfectly inelastic collisions with the tank wall. The foundation of the modeling methodology is the approach taken during the Apollo program used to predict the effect of fuel slosh on the complex motion exhibited by the Service Module following separation from the Crew Module. This paper discusses the motivation, methodology, and conclusions from the Apollo-era method, and subsequently builds upon it by incorporating corrections to the derivation of the dynamics and filling in the gaps due to unavailability of the detailed contractor report and simulation code. The results presented in this paper provide an example that demonstrates the effect that fuel slosh can have on the trajectory of a spacecraft in a low-g environment.

William J Elke III↗
NASA NTRSDate not supplied

Framework for Analyzing the Complex Interactions Between Spacecraft Motion and Slosh Dynamics in Low-G Environments

The fuel-to-dry-mass ratio of spacecraft continues to grow as new human spaceflight missions target destinations farther from Earth. Large amounts of liquid propellant can lead to significant coupling between the rigid-body dynamics of the spacecraft and the motion of the fuel within its storage tank. The present work gives an overview of the dynamic features and a flowchart for a method of simulating the motion of a spacecraft with fuel slosh inside a cylindrical, domed tank in a low-g environment. The method involves modeling the liquid propellant as a particle that transfers momentum to the spacecraft through perfectly inelastic collisions with the tank wall. The foundation of the modeling methodology is the approach taken during the Apollo program used to predict the effect of fuel slosh on the complex motion exhibited by the Service Module following separation from the Command Module. This paper discusses the motivation, methodology, and conclusions from the Apollo-era method, then presents corrections to the derivation of the dynamics and fills in the gaps left from the unavailability of the detailed contractor report and simulation code. The results presented in this paper provide an example that demonstrates the effect that fuel slosh can have on the trajectory of a spacecraft in a low-g environment.

William J Elke III↗
NASA NTRSDate not supplied

State of Wildfires

Fire is an essential component of ecosystems and acts as key driver of biogeochemical cycling with impacts on vegetation structure and composition, soil conditions, and climate feedbacks. Fire behavior and effects vary based on the types of fuel, fuel dryness, and frequency of ignition. Due to changing climate and land use patterns, fire danger is increasing in many regions globally, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Recurrent fires help to determine the distribution of trees and grasses, and overall fuel load, which inform the behavior of future fires. Process-based models can be used to capture multi-scale impacts at the forest stand-level up to the landscape level, and across minutes to centuries, but must capture variation in fire behavior and intensity as a function of the fuel and climate, from high intensity forest crown fires within boreal regions to low intensity rapid grass fires of the tropics. Fire model development demonstrates our ability to capture large scale fire influenced biogeography and vegetation distribution at the earth system scale through vegetation traits and fire feedbacks. At the individual stand scale the importance of interactions and feedbacks between above and below ground process is essential to capturing the vegetation dynamics across boreal forest systems. Improving the mechanics of including plant physiology and specifically live fuel moisture content is the next step to advancing the capability of process based models to inform fire research. Advances in the testing and creation of a mechanistic live fuel moisture model demonstrate the foundation for future live fuel dynamics research that can be informed by field and remote sensing information. Improved remote sensing, technological and modeling capabilities support a more comprehensive and cohesive fire response that will be better equipped to overcome current barriers and anticipate the new reality of fires in a warming world.

wildfires↗
NASA NTRSDate not supplied

LLMs and GenAI Tools to Depict Contributions of Human Systems to Spaceflight Tasks Execution

Recent advancements in Artificial Intelligence and Machine Learning (AI/ML) technologies, particularly Large Language Models (LLMs) capable of sophisticated syntax analysis, offer substantial potential in automating complex processes, thereby saving time and human resources. This study explores the development of an LLM-driven model designed to analyze and categorize a diverse set of Mars mission tasks into 18 predefined Human System Task Categories (HSTCs) based on their textual descriptions. As part of developing the Crew Health and Performance – Probabilistic Risk Assessment (CHP-PRA projects Performance Risk Model (PRisM) proof-of-concept, we established a framework to project performance scores from small-scale tests onto a preliminary list of Mars tasks. The foundation of our model was a comprehensive spreadsheet populated by NASA experts and clinicians, which detailed each Mars task alongside binary indicators of HSTC involvement. This dataset enabled the initial application of supervised ML, training and testing on existing HSTC labels. The HSTCs were originally defined from a medical system perspective, focusing on task impairments due to deteriorated human health. To expand our model's scope to include categories impacting performance, we face the challenge of generating binary labels (0 or 1) for new categories without pre-existing data. We address this by employing Generative AI (GenAI) software to determine whether a given task involved a new category by asking, "Does task A involve using category B?" We validate our approach by comparing the GenAI's binary classifications with the expert-provided labels for existing HSTCs. Notably, we utilize Ollama [4], a locally hosted GenAI tool that does not require cloud access, thus safeguarding NASA's proprietary data from unauthorized exposure. This study demonstrates the feasibility of leveraging cutting-edge AI tools to advance research, paving the way for automation and rapid decision-making in space exploration.

Mona Matar↗
NASA NTRS2016

The Impact of ARM on Climate Modeling

Climate models are among humanity's most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability, and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of the Earth down to one hundred kilometers or smaller, and implicitly include the effects of processes on even smaller scales down to a micron or so. The atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM). In an AGCM, calculations are done on a three-dimensional grid, which in some of today's climate models consists of several million grid cells. For each grid cell, about a dozen variables are time-stepped as the model integrates forward from its initial conditions. These so-called prognostic variables have special importance because they are the only things that a model remembers from one time step to the next; everything else is recreated on each time step by starting from the prognostic variables and the boundary conditions. The prognostic variables typically include information about the mass of dry air, the temperature, the wind components, water vapor, various condensed-water species, and at least a few chemical species such as ozone. A good way to understand how climate models work is to consider the lengthy and complex process used to develop one. Lets imagine that a new AGCM is to be created, starting from a blank piece of paper. The model may be intended for a particular class of applications, e.g., high-resolution simulations on time scales of a few decades. Before a single line of code is written, the conceptual foundation of the model must be designed through a creative envisioning that starts from the intended application and is based on current understanding of how the atmosphere works and the inventory of mathematical methods available.

atmospheric circulation↗
NASA NTRS2003

A Comprehension Based Analysis of Autoflight System Interfaces

This cooperative agreement supported Dr. Peter Polson's participation in two interrelated research programs. The first was the development of the Situation-Goal-Behavior (SGB) Model that is both a formal description of an avionics system's logic and behavior and a representation of a system that can be understood by avionics designers, pilots, and training developers. The second was the development of a usability inspection method based on an approximate model, RAFIV, of pilot interactions with the Flight Management System (FMS). The main purpose of this report is to integrate the two models and provide a context in order to better characterize the accomplishments of this research program. A major focus of both the previous and this Cooperative Agreement was the development of usability evaluation methods that can be effectively utilized during all phases of the design, development, and certification process of modern avionics systems. The current efforts to validate these methods have involved showing that they generate useful analyses of known operational and training problems with the current generation of avionics systems in modern commercial airliners. This report is organized into seven sections. Following the overview, the second section describes the Goal-Situation-Behavior model and its applications. The next section summarizes the foundations of the RAFIV model and describes the model in some detail. The contents of both these sections are derived from previous reports referenced in footnotes. The fourth section integrates these two models into a complete design evaluation and training development framework. The fifth section contains conclusions and possible future directions for research. References are in Section 6. Section 7 contains the titles and abstracts of the papers paper describing in more detail the results of this research program.

Palmer, Everett↗
NASA NTRS2010

NASA's Spaceflight Visual Impairment and Intracranial Hypertension Research Plan: An accelerated Research Collaboration

To date six long duration astronauts have experienced in flight visual changes and post flight signs of optic disc edema, globe flattening, choroidal folds, hyperoptic shifts and or raised intracranial pressure. In some cases the changes were transient while in others they are persistent with varying degrees of visual impairment. Given that all astronauts exposed to microgravity experience a cephalad fluid shift, and that both symptomatic and asymptomatic patients have exhibited optic nerve sheath edema on MRI, there is a high probability that all astronauts develop in-flight idiopathic intracranial hypertension to some degree. Those who are susceptible, have an increased likelihood of developing treatment resistant papilledema resulting in visual impairment and possible long-term vision loss. Such an acquired disability would have a profound mission impact and would be detrimental to the long term health of the astronaut. The visual impairment and increased intracranial pressure phenomenon appears to have multiple contributing factors. Consequently, the working "physiological fault bush" with elevated intracranial pressure at its center, is divided into ocular effects, and CNS and other effects. Some of these variables have been documented and or measured through operational data gathering, while others are unknown, undocumented and or hypothetical. Both the complexity of the problem and the urgency to find a solution require that a unique, non-traditional research model be employed such as the Accelerated Research Collaboration(TM) (ARC) model that has been pioneered by the Myelin Repair Foundation. In the ARC model a single entity facilitates and manages all aspects of the basic, translational, and clinical research, providing expert oversight for both scientific and managerial efforts. The result is a comprehensive research plan executed by a multidisciplinary team and the elimination of stove-piped research. The ARC model emphasizes efficient and effective communication between management and investigators; and real-time sharing of scientific discoveries in an effort to solve complex problems.

Otto, Christian↗
NASA NTRS2012

Model Based Systems Engineering on the Europa Mission Concept Study

At the start of 2011, the proposed Jupiter Europa Orbiter (JEO) mission was staffing up in expectation of becoming an official project later in the year for a launch in 2020. A unique aspect of the pre-project work was a strong emphasis and investment on the foundations of Model-Based Systems Engineering (MBSE). As so often happens in this business, plans changed: NASA's budget and science priorities were released and together fundamentally changed the course of JEO. As a result, it returned to being a study task whose objective is to propose more affordable ways to accomplish the science. As part of this transition, the question arose as to whether it could continue to afford the investment in MBSE. In short, the MBSE infusion has survived and is providing clear value to the study effort. By leveraging the existing infrastructure and a modest additional investment, striking advances in the capture and analysis of designs using MBSE were achieved. In the process, the need to remain relevant in the new environment has brought about a wave of innovation and progress. The effort has reaffirmed the importance of architecting. It has successfully harnessed the synergistic relationship of architecting to system modeling. We have found that MBSE can provide greater agility than traditional methods. We have also found that a diverse 'ecosystem' of modeling tools and languages (SysML, Mathematica, even Excel) is not only viable, but an important enabler of agility and adaptability. This paper will describe the successful application of MBSE in the dynamic environment of early mission formulation, the significant results produced and lessons learned in the process.

Bayer, Todd J.↗
NASA NTRS2010

Using SCOR as a Supply Chain Management Framework for Government Agency Contract Requirements

This paper will present a model that uses the Supply-Chain Operations Reference (SCOR) model as a foundation for a framework to illustrate the information needed throughout a product lifecycle to support a healthy supply chain management function and the subsequent contract requirements to enable it. It will also show where in the supply chain the information must be extracted. The ongoing case study used to exemplify the model is NASA's (National Aeronautics and Space Administration) Ares I program for human spaceflight. Effective supply chain management and contract requirements are ongoing opportunities for continuous improvement within government agencies, specifically development of systems for human spaceflight operations. Multiple reports from the Government Accountability Office (GAO) reinforce this importance. The SCOR model is a framework for describing a supply chain with process building blocks and business activities. It provides a set of metrics for measuring supply chain performance and best practices for continuously improving. This paper expands the application of the SCOR to also provide the framework for defining information needed from different levels of the supply chain and at different phases of the lifecycle. These needs can be incorporated into contracts to enable more effective supply chain management. Depending on the phase of the lifecycle, effective supply chain management will require involvement from different levels of the organization and different levels of the supply chain.

Paxton, Joseph↗
NASA NTRS2000

A Cybernetic Approach to the Modeling of Agent Communities

In an earlier paper [1] examples of agent technology in a NASA context were presented. Both groundbased and space-based applications were addressed. This paper continues the discussion of one aspect of the Goddard Space Flight Center's continuing efforts to develop a community of agents that can support both ground-based and space-based systems autonomy. The paper focuses on an approach to agent-community modeling based on the theory of viable systems developed by Stafford Beer. It gives the status of an initial attempt to capture some of the agent-community behaviors in a viable system context. This paper is expository in nature and focuses on a discussion of the modeling of some of the underlying concepts and infrastructure that will serve as the basis of more detailed investigative work into the behavior of agent communities. The paper is organized as follows. First, a general introduction to agent community requirements is presented. Secondly, a brief introduction to the cybernetic concept of a viable system is given. This concept forms the foundation of the modeling approach. Then the concept of an agent community is modeled in the cybernetic context.

Truszkowski, Walt↗
NASA NTRS1993

The atmospheric effects of stratospheric aircraft. Report of the 1992 Models and Measurements Workshop. Volume 1: Workshop objectives and summary

This Workshop on Stratospheric Models and Measurements (M&M) marks a significant expansion in the history of model intercomparisons. It provides a foundation for establishing the credibility of stratospheric models used in environmental assessments of chlorofluorocarbons, aircraft emissions, and climate-chemistry interactions. The core of the M&M comparisons involves the selection of observations of the current stratosphere (i.e., within the last 15 years): these data are believed to be accurate and representative of certain aspects of stratospheric chemistry and dynamics that the models should be able to simulate.

Prather, Michael J.↗
NASA NTRS1993

The atmospheric effects of stratospheric aircraft. Report of the 1992 Models and Measurements Workshop. Volume 2: Comparisons with global atmospheric measurements

This Workshop on Stratospheric Models and Measurements (M&M) marks a significant expansion in the history of model intercomparisons. It provides a foundation for establishing the credibility of stratospheric models used in environmental assessments of chlorofluorocarbons, aircraft emissions, and climate-chemistry interactions. The core of the M&M comparisons involves the selection of observations of the current stratosphere (i.e., within the last 15 years): these data are believed to be accurate and representative of certain aspects of stratospheric chemistry and dynamics that the models should be able to simulate.

Prather, Michael J.↗