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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

A Decision-Support Model for Selecting Additive Manufacturing Versus Subtractive Manufacturing Based on Energy Consumption

This paper presents a simple computational model for determining whether additive manufacturing or subtractive manufacturing is more energy efficient for production of a given metallic part. The key discriminating variable is the fraction of the bounding envelope that contains material – i.e. the volume fraction of solid material. For both the additive process and the subtractive process, the total energy associated with the production of a part is defined in terms of the volume fraction of that part. The critical volume fraction is that for which the energy consumed by subtractive manufacturing equals the energy consumed by additive manufacturing. For volume fractions less than the critical value, additive manufacturing is more energy efficient. For volume fractions greater than the critical value, subtractive manufacturing is more efficient. The model considers the entire manufacturing lifecycle – from production and transport of feedstock material through processing to return of post-production scrap for recycling. Energy consumed by processing equipment while idle is also accounted for in the model. Although the individual energy components in the model are identified and accounted for in the expressions for additive and subtractive manufacturing, values for many of these components may not be currently available. Energy values for some materials’ production and subtractive and additive manufacturing processes can be found in the literature. However, since many of these data are reported for a very specific application, it may be difficult, if not impossible, to reliably apply these data to new process-material manufacturing scenarios since, very often, insufficient information is provided to enable extrapolation to broader use. Consequently, this paper also highlights the need to develop improved knowledge of the energy embodied in each phase of the manufacturing process. To be most valuable, users of the model should determine the energy consumed by their manufacturing process equipment on the basis of energy-per-unit-volume of production for each material of interest – considering both alloy composition and form. Energy consumed during machine idle per unit time should also be determined by the user then scaled to specific processing scenarios. Energy required to generate feedstock material (billet, plate, bar, wire, powder) must be obtained from suppliers.

J K Watson↗
NASA NTRS2019

Airspace Technology Demonstration 2 (ATD-2): Analysis of APREQ Flights at CLT

5/22/2019 National Aeronautics and Space Administration 1 Airspace Technology Demonstration 2 (ATD-2) Analysis of APREQ Flights at CLT May 22, 2019 5/22/2019 Objective 2 Quantify impact of IADS Phase 1 & 2 capabilities on APREQ flights at CLT with respect to: • Compliance to the Controlled Take Off Time (CTOT) • Benefits for APREQ flights that use IDAC to renegotiate for an earlier CTOT • Benefits of pre-scheduling APREQ flights using the Earliest Off Block Time (EOBT) • Relationship between EOBT compliance and rescheduling CTOT 5/22/2019 CLT APREQ Daily Compliance(Compliance Improvement Since ATD-2 Start) 3 Steady increase of APREQ compliance over the life of the project. Reduced variation in compliance leading to improved predictability. In addition to overall improved compliance into TBM systems, the predictability is increasing 5/22/2019 APREQ Compliance 10K Rolling Window 4 The most substantial APREQ compliance improvements started with Phase 2 capability (AEFS integration, ZTL IDAC, pre-scheduling and scheduler updates). 5/22/2019 IADS Phase 1 & 2 Benefit Mechanisms 5 1. Collaborative surface metering •Reduced engine run time •Reduced fuel consumption and emissions 2. Overhead stream operational integration a.Scheduling controlled flights at the gate •Reduced engine run time •Reduced fuel consumption and emissions b.APREQ renegotiating for an earlier slot •Reduced total delay •Passenger value of time and crew costs •Reduced engine run time •Reduced fuel consumption and emissions Benefits (1) and (2a) achieved through tactical gate holds Benefit (2b) achieved through APREQ renegotiation process described below Step 1: APREQ flight has a release time but is capable of taking off earlier Step 2: FAA TMC uses the IDAC green space / red space to identify and request an earlierslot in the overhead stream Step 3: Aircraft receives earlierrelease time and the difference between the release times is the reduction in delay 5/22/2019 Benefits for APREQ flights using IDAC to renegotiate for earlierCTOT 6 LBS Fuel 270.7 hours of delay saved by electronically renegotiating a better overhead stream time for 2,071 flights. • The benefits described here are associated with better use of existing capacity in the overhead stream, and technology to reduce surface delay. •These benefits are in addition to (distinct from) surface metering savings. 5/22/2019 APREQ Delay For Pre-Scheduled Flights into KATL Have Been Reduced and are More Predictable For the Last Five Months 7 Substantial Improvements in predictability of delay for the last 5 months 5/22/2019 EOBT Compliance / CTOT Reschedulefor Pre-Scheduled Flights into KATL 8 5/22/2019 Wrap-up 9 • Compliance to the CTOT has improved throughout the lifecycle of ATD-2 with biggest improvements following the introduction of Phase 2 capabilities • Rescheduling APREQ flights using IDAC has reduced 270.7 hours of delay at CLT • Predictability of local surface delay for APREQ flights is substantially improved via pre-scheduling with the IADS system • Pre-scheduled flights that reschedule for later times tend to call ready later with respect to EOBT

CLT↗
NASA NTRS2019

Preparing General Mission Analysis Tool for Operational Maneuver Planning of the Advanced Composition Explorer Mission

The General Mission Analysis Tool (GMAT) is an open-source space mission design, analysis and trajectory optimization tool. GMAT is developed by a team of NASA, private industry, public and private contributors. GMAT is designed to model, optimize and estimate spacecraft trajectories in flight regimes ranging from low Earth orbit to lunar applications, interplanetary trajectories and other deep space missions. GMAT has also been flight qualified to support operational maneuver planning for the Advanced Composition Explorer (ACE) mission. ACE was launched in August, 1997 and is orbiting the Sun-Earth L1 libration point. The primary science objective of ACE is to study the composition of both the solar wind and the galactic cosmic rays. Operational orbit determination, maneuver operations and product generation for ACE are conducted by NASA Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF). This paper discusses the entire engineering lifecycle and major operational certification milestones that GMAT successfully completed to obtain operational certification for the ACE mission. Operational certification milestones such as gathering of the requirements for ACE operational maneuver planning, gap analysis, test plans and procedures development, system design, pre-shadow operations, training to FDF ACE maneuver planners, shadow operations, Test Readiness Review (TRR) and finally Operational Readiness Review (ORR) are discussed. These efforts have demonstrated that GMAT is flight quality software ready to support ACE mission operations in the FDF.

mission design↗
NASA NTRS2019

Model Based Engineering for Software Assurance

NASA's successful development of next generation space vehicles, habitats, and robotic systems will require reliable hardware and software systems. The aim of this initiative is to develop modeling methodology and tools to support Model-Based Systems Engineering (MBSE) for software assurance and reliability analysis. This effort expands the Unified Modeling Language (UML) software design models to include fault data for the extraction of Failure Modes and Effects Criticality Analysis (FMECA) and Fault Tree Analysis (FTA) for software. We explored different modeling approaches to integrate the UML software design models with the Systems Modeling Language (SysML) system models to generate an integrated model and reliability tools that take into account software and hardware interfaces.The benefits of this concept directly affect the safety community with quick turnarounds to produce software assurance and reliability analysis artifacts and the ability to visualize failure effects, both hardware and software. The result is enhanced system design integrity and early identification of system risks. This initiative will enable software assurance activities early in the system design lifecycle, facilitating the discovery of design weaknesses and enhancing the capability to produce safe, hazard-free systems

Wang, Lui↗
NASA NTRS2019

A Validation Study of the Performance Prediction Methodology of the Early Warning Metrics

Complex projects frequently experience delays and develop backlogs of their project control milestones during the acquisition and development lifecycles. In response, the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) formed an independent group of Subject Matter Experts (SMEs) to monitor the execution performance of GSFC Flight projects and instruments that are under development. The SME team’s objective is to generate data driven performance-based indicators that quantify the degree to which projects are meeting their respective schedule and budget commitments. One of these performance-based indicators, the Early Warning Metrics, provides performance forecasts and insight to project performance relative to historical successful projects. Herein this paper describes the purpose and utility of the Early Warning Metrics. Additionally, the initial prediction method used in the creation of the metrics is described along with its validity and the validity of comparable prediction methods.

Holloman, Sherrica↗
NASA NTRS2019

Formalizing and Analyzing Requirements with FRET

Formal verification and simulation are powerful tools to validate requirements against complex systems. Requirements are developed in early stages of the software lifecycle and are typically written in ambiguous natural language. There is a gap between such requirements and formal notations that can be used by verification tools, and lack of support for proper association of requirements with software artifacts for verification. We propose to write requirements in an intuitive, structured natural language with formal semantics, and to support formalization and model/code verification as a smooth, well-integrated process. To this end, we have developed an end-to-end, open source requirements analysis framework that checks Simulink models against requirements written structured natural language.

Mavridou, Anastasia↗
NASA NTRS2017

The NASA Analogy Software Cost Model: A Web-Based Cost Analysis Tool

This paper provides an overview of the many new features and algorithm updates in the release of the NASA Analogy Software Cost Tool (ASCoT). ASCoT is a web-based tool that provides a suite of estimation tools to support early lifecycle NASA Flight Software analysis. ASCoT employs advanced statistical methods such as Cluster Analysis to provide an analogy based estimate of software delivered lines of code and development effort, a regression based Cost Estimating Relationships (CER) model that estimates cost (dollars), and a COCOMO II based estimate. The ASCoT algorithms are designed to primarily work with system level inputs such as mission type (earth orbiter vs. planetary vs. rover), the number of instruments, and total mission cost. This allows the user to supply a minimal number of mission-level parameters which are better understood early in the life-cycle, rather than a large number of complex inputs.

Hihn, Jairus↗
NASA NTRS2019

Feature Learning for Multispectral Satellite Imagery Classification Using Neural Architecture Search

Automated classification of remote sensing data is an integral tool for earth scientists, and deep learning has proven very successful at solving such problems. However, building deep learning models to process the data requires expert knowledge of machine learning. We introduce DELTA, a software toolkit to bridge this technical gap and make deep learning easily accessible to earth scientists. Visual feature engineering is a critical part of the machine learning lifecycle, and hence is a key area that will be automated by DELTA. Hand-engineered features can perform well, but require a cross functional team with expertise in both machine learning and the specific problem domain, which is costly in both researcher time and labor. The problem is more acute with multispectral satellite imagery, which requires considerable computational resources to process. In order to automate the feature learning process, a neural architecture search samples the space of asymmetric and symmetric autoencoders using evolutionary algorithms. Since denoising autoencoders have been shown to perform well for feature learning, the autoencoders are trained on various levels of noise and the features generated by the best performing autoencoders evaluated according to their performance on image classification tasks. The resulting features are demonstrated to be effective for Landsat-8 flood mapping, as well as benchmark datasets CIFAR10 and SVHN.

Robert Campbell↗
NASA NTRS2020

Predicting Gate Conflicts using NASA ATD-2 Fused Data Sources

The modern day National Airspace System (NAS) is powered by System Wide Information Management (SWIM) which is a real-time digital data sharing infrastructure that provides a high fidelity view of the lifecycle of a flight. The newly available data within the SWIM feeds can be leveraged to help drive efficiencies in the NAS. In this talk, we investigate the gate conflict prediction problem as a concrete use case which could help drive efficiencies. We begin with a high level description of NASA's Airspace Technology Demonstration 2 which is built upon the real-time SWIM feeds and produces the data used in our investigation. We model gate conflicts as a regression problem and describe the iterative process of model building, model validation, and evaluation used to assess the efficacy of our approach.

Coupe, William J.↗
NASA NTRS2020

Enabled International Collaborations in EDL: Lessons Learned and Recommendations

The modern day National Airspace System (NAS) is powered by System Wide Information Management (SWIM) which is a real-time digital data sharing infrastructure that provides a high fidelity view of the lifecycle of a flight. The newly available data within the SWIM feeds can be leveraged to help drive efficiencies in the NAS. In this talk, we investigate the gate conflict prediction problem as a concrete use case which could help drive efficiencies. We begin with a high level description of NASA's Airspace Technology Demonstration 2 which is built upon the real-time SWIM feeds and produces the data used in our investigation. We model gate conflicts as a regression problem and describe the iterative process of model building, model validation, and evaluation used to assess the efficacy of our approach.

William J. Coupe↗
NASA NTRS2020

Androgynous Fasteners for Robotic Structural Assembly

We describe the design and analysis of an androgynous fastener for autonomous robotic assembly of high performance structures. The design of these fasteners aims to prioritize ease of assembly through simple actuation with large driver positioning tolerance requirements, while producing a reversible mechanical connection with high strength and stiffness per mass. This can be applied to high strength to weight ratio structural systems, such as discrete building block based systems that offer reconfigurability, scalability, and system lifecycle efficiency. Such periodic structures are suitable for navigation and manipulation by relatively small mobile robots. The integration of fasteners, which are lightweight and can be robotically installed, into a high performance robotically managed structural system is of interest to reduce launch energy requirements, enable higher mission adaptivity, and decrease system life-cycle costs.

Formoso, Olivia↗
NASA NTRS2020

Bridging the Gap Between Requirements and Simulink Model Analysis

Formal verification and simulation are powerful tools for the verification of requirements against complex systems. Requirements are developed in early stages of the software lifecycle and are typically expressed in natural language. There is a gap between such requirements and their software implementations.We present a framework that bridges this gap by supporting a tight integration and feedback loop between high-level requirements and their analysis against software artifacts. Our framework implements an analysis portal within the fret requirements elicitation tool, thus forming an end-to-end, open-source environment where requirements are written in an intuitive, structured natural language, and are verified automatically against Simulink models.

Mavridou, Anastasia↗
NASA NTRS2020

Bridging the Gap Between Requirements and Model Analysis : Evaluation on Ten Cyber-Physical Challenge Problems

Formal verfication and simulation are powerful tools to validate requirements against complex systems. [Problem] Requirements are developed in early stages of the software lifecycle and are typically written in ambiguous natural language. There is a gap between such requirements and formal notations that can be used by verification tools, and lack of support for proper association of requirements with software artifacts for verification. [Principal idea] We propose to write requirements in an intuitive, structured natural language with formal semantics, and to support formalization and model/code verification as a smooth, well-integrated process. [Contribution] We have developed an end-to-end, open source requirements analysis framework that checks Simulink models against requirements written in structured natural language. Our framework is built in the Formal Requirements Elicitation Tool (fret); we use fret's requirements language named fretish, and formalization of fretish requirements in temporal logics. Our proposed framework contributes the following features: 1) automatic extraction of Simulink model information and association of fretish requirements with target model signals and components; 2) translation of temporal logic formulas into synchronous dataflow cocospec specifications as well as Simulink monitors, to be used by verification tools; we establish correctness of our translation through extensive automated testing; 3) interpretation of counterexamples produced by verification tools back at requirements level. These features support a tight integration and feedback loop between high level requirements and their analysis. We demonstrate our approach on a major case study: the Ten Lockheed Martin Cyber-Physical, aerospace-inspired challenge problems.

Mavridou, Anastasia↗
NASA NTRSDate not supplied

TPSAS-NF1676L-10947-DND

There are large uncertainties in quantifying dust effects on the climate because of the limitations on the measurements and observations of dust-cloud-precipitation-dynamics interactions. As a major terrestrial source of atmospheric aerosols, dusts may serve as a significant climate forcing for the changing climate due to its effect on solar and thermal radiation as well as on clouds and precipitation processes. Latest satellites measurements enable us to determine dust loadings and cloud distributions and can potentially be used to reduce the uncertainties in the estimations of aerosol effects on climate. This study uses sensors on various satellites to investigate the impact of mineral dust on cloud microphysical and precipitation processes in convective systems. A trans-Atlantic dust outbreak of Saharan origin occurring in early March 2004 is considered. For the observed convective systems under a given convective strength, small hydrometeors were found more prevalent in the dusty stratiform regions than in those regions that were dust free. Evidence of abundant cloud ice particles in the dust regions, particularly at altitudes where heterogeneous nucleation of mineral dust prevails, further supports the observed changes of clouds and precipitation. These microphysical effects of the dusts on clouds are to shift the size spectrum of precipitation-sized hydrometeors from heavy precipitation to light precipitation and ultimately to suppress precipitation and increase the lifecycle of cloud systems, especially for stratiform clouds.

B Lin↗
NASA NTRSDate not supplied

ECLSS Does Not Exist in a Vacuum: Integrated Analysis is Necessary to Inform System Architecture Decisions

Environmental Control and Life Support System (ECLSS) architecture selection has profound implications for mission cost and mass extending far beyond the ECLSS itself. Similarly, other mission architecture decisions – particularly involving transportation systems – can influence optimal ECLSS architectures. Loop closure influences requirements for water, oxygen, and other consumables. System maintainability and reliability influences spares mass and risk. System, consumables, and spares mass interact with transportation system architectures and propellant demands and propulsion element sizing. All these interactions with other systems must be considered when evaluating ECLSS options. Analyses that focus only on maximizing ECLSS loop closure – or minimizing ECLSS mass, or minimizing ECLSS life cycle cost – may lead to sub-optimal or even counterproductive system architecture and investment decisions at the mission level. For example, an ECLSS architecture that minimizes ECLSS lifecycle cost but results in excessively high logistics mass could lead to significantly increased transportation system costs or make interplanetary transportation infeasible. Increased loop closure could result in higher development costs and higher mass if system/spares mass increases outweigh consumables reduction. In addition, systems mass and consumables mass are not directly comparable and have different impacts on propellant requirements, as consumables mass changes over the course of the mission. This paper presents an integrated analysis examining the overall impact of different ECLSS and transportation architectures on mass for a crewed Mars mission, including the habitat and transportation systems as well as consumables, spares, and propellant. Key observations are discussed, along with opportunities for further sensitivity analysis and model development. Overall, ECLSS development activities must consider their impacts at the mission level, as part of an integrated system, rather than in isolation.

Systems Analysis↗
NASA NTRS2020

Guidance for Human Error Analysis (HEA)

NASA’s Human-Rating Requirements for Space Systems in NASA Procedural Requirements (NPR) 8705.2C requires Program Managers to conduct a human error analysis (HEA) for all mission phases. The purpose of the HEA is to enable programs to understand and manage potential catastrophic hazards that could be caused by human error, understand the relative risks and uncertainties within the system design, and influence decisions throughout the system lifecycle. This document provides guidance to NASA civil servants and contractors on how the Agency’s HEA requirement can be fulfilled.

Human Error Analysis; NASA Procedural Requirement;↗
NASA NTRSDate not supplied

Bridging the Gap Between Requirements and Simulink Model Analysis

Formal veri fication and simulation are powerful tools for the veri fication of requirements against complex systems. Requirements are developed in early stages of the software lifecycle and are typically expressed in natural language. There is a gap between such requirements and their software implementations. We present a framework that bridges this gap by supporting a tight integration and feedback loop between high-level requirements and their analysis against software artifacts. Our framework implements an analysis portal within the fret requirements elicitation tool, thus forming an end-to-end, open-source environment where requirements are written in an intuitive, structured natural language, and are veri fied automatically against Simulink models.

FRET↗
NASA NTRS2020

Predicting Gate Conflicts at Charlotte Douglas International Airport Using NASA ATD-2 Fused Data Sources

NASA is conducting the Airspace Technology Demonstration-2 to evaluate an Integrated Arrival, Departure, and Surface (IADS) traffic management system. The IADS system is powered by real-time System Wide Information Management feeds which provide an accurate and high fidelity view of the lifecycle of a flight. This data can be leveraged to drive efficiencies in the National Airspace System. For non safety critical applications there is opportunity for third party service providers to offer this type of data-driven prediction service in near real-time. This paper investigates the gate conflict prediction problem as a concrete use case which could help drive efficiencies. We model gate conflicts as a regression problem and describe the iterative process of model building, model validation, and evaluation used to assess the efficacy of our approach. We quantify our predictive accuracy and identify paths for improvement. Through this iterative process we hope to evolve our models and methods to a near real-time prediction service.

Airspace Technology Demonstration 2↗