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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 NTRS1994

A Modular, Portable Model of Image Fidelity

There is a persistent need for a trustworthy model of perceptual image fidelity, especially in applications such as image compression and display design. A fidelity model provides a measure of the visual discriminability of two images. Ahumada has previously shown that the existing fidelity models may be categorized according to their inclusion of various canonical properties, such as a contrast sensitivity function, spatial frequency channels, etc. This suggests that research would be aided by the availability of a modular model, in which these components could be easily inserted or removed. A further impediment to research in this area has been that most models are written in low-level languages and are consequently large, non-portable, and difficult to understand, modify, and maintain. We therefore believe research would also be aided by models written in high-level languages. To serve both of these purposes, and to honor our conference host for his lifetime dedication to the problem of image quality. Global brightness and its effect on perceptual image quality. We offer a modular model written in the high-level language Mathematica. We will demonstrate this model and show how it may be modified.

Watson, Andrew B.↗
NASA NTRS2002

Fast Bound Methods for Large Scale Simulation with Application for Engineering Optimization

In this work, we have focused on fast bound methods for large scale simulation with application for engineering optimization. The emphasis is on the development of techniques that provide both very fast turnaround and a certificate of Fidelity; these attributes ensure that the results are indeed relevant to - and trustworthy within - the engineering context. The bound methodology which underlies this work has many different instantiations: finite element approximation; iterative solution techniques; and reduced-basis (parameter) approximation. In this grant we have, in fact, treated all three, but most of our effort has been concentrated on the first and third. We describe these below briefly - but with a pointer to an Appendix which describes, in some detail, the current "state of the art."

Patera, Anthony T.↗
NASA NTRS1995

Metrics and Benchmarks for Visualization

What is a "good" visualization? How can the quality of a visualization be measured? How can one tell whether one visualization is "better" than another? I claim that the true quality of a visualization can only be measured in the context of a particular purpose. The same image generated from the same data may be excellent for one purpose and abysmal for another. A good measure of visualization quality will correspond to the performance of users in accomplishing the intended purpose, so the "gold standard" is user testing. As a user of visualization software (or at least a consultant to such users) I don't expect visualization software to have been tested in this way for every possible use. In fact, scientific visualization (as distinct from more "production oriented" uses of visualization) will continually encounter new data, new questions and new purposes; user testing can never keep up. User need software they can trust, and advice on appropriate visualizations of particular purposes. Considering the following four processes, and their impact on visualization trustworthiness, reveals important work needed to create worthwhile metrics and benchmarks for visualization. These four processes are (1) complete system testing (user-in-loop), (2) software testing, (3) software design and (4) information dissemination. Additional information is contained in the original extended abstract.

Uselton, Samuel P.↗
NASA NTRS2002

How Do We Work Together?

In essence, project management is about people. Virtually every successful project is defined by good relations between the people involved. In the same way, nearly every failed or troubled project is about poor relationships between the people involved. Let's consider one type of relationship: the one between the government and the contractor. It's easy to say that a contractor must earn the government's trust, but what does that mean in practice? Who needs to earn whose trust? What's the timeline for doing that? How does anyone know when he or she is trusted? What is the relationship supposed to be like before one feels like trust has really been established? So many questions it makes my head hurt. I have always found it better to begin a relationship assuming that everyone is trustworthy until, and unless, something occurs to belie trust.

Little, Terry↗
NASA NTRS2003

Expedition 7 Crew Interview: Yuri Malenchenko

Cosmonaut Yuri Malenchenko of Expedition Seven is seen during a pre-launch interview. He begins by telling why he wanted to become a cosmonaut. Malenchenko expresses his reaction about the news of the Space Shuttle Columbia accident, and how this mission will be different from other missions. He also expresses the challenges that face Malenchenko and Ed Lu such as the crew reduction from three to two, less supplies and no space shuttle flights. Malenchenko says that he will have to work on a compressed schedule, which will make the mission even more challenging. A description of the handover of Expedition Six is given. Malenchenko and Ed Lu will be cramped in a confined space on the Soyuz Spacecraft for two days before docking, and he talks about this experience. Lastly, Malenchenko gives his thoughts on how it will be to work with Ed Lu in space, and tells of Lu's trustworthiness and reliability as a fellow crew member.

Source record↗
NASA NTRS1995

Summary of a Crew-Centered Flight Deck Design Philosophy for High-Speed Civil Transport (HSCT) Aircraft

Past flight deck design practices used within the U.S. commercial transport aircraft industry have been highly successful in producing safe and efficient aircraft. However, recent advances in automation have changed the way pilots operate aircraft, and these changes make it necessary to reconsider overall flight deck design. Automated systems have become more complex and numerous, and often their inner functioning is partially or fully opaque to the flight crew. Recent accidents and incidents involving autoflight system mode awareness Dornheim, 1995) are an example. This increase in complexity raises pilot concerns about the trustworthiness of automation, and makes it difficult for the crew to be aware of all the intricacies of operation that may impact safe flight. While pilots remain ultimately responsible for mission success, performance of flight deck tasks has been more widely distributed across human and automated resources. Advances in sensor and data integration technologies now make far more information available than may be prudent to present to the flight crew.

Palmer, Michael T.↗
NASA NTRS1998

Analytic Verification of Flight Software

In the realm of space exploration, the biggest obstacle to widespread application of autonomy in flight software is not technical feasibility; it is doubt about its trustworthiness as a replacement for human-in-the-loop decision-making.

model↗
NASA NTRS2007

Build-up Approach to Updating the Mock Quiet Spike(TradeMark) Beam Model

A crucial part of aircraft design is ensuring that the required margin for flutter is satisfied. A trustworthy flutter analysis, which begins by possessing an accurate dynamics model, is necessary for this task. Traditionally, a model was updated manually by fine tuning specific stiffness parameters until the analytical results matched test data. This is a time consuming iterative process. NASA Dryden Flight Research Center has developed a mode matching code to execute this process in a more efficient manner. Recently, this code was implemented in the F-15B/Quiet Spike(TradeMark) (Gulfstream Aerospace Corporation, Savannah, Georgia) model update. A build-up approach requiring several ground vibration test configurations and a series of model updates was implemented in order to determine the connection stiffness between aircraft and test article. The mode matching code successfully updated various models for the F-15B/Quiet Spike(TradeMark) project to within 1 percent error in frequency and the modal assurance criteria values ranged from 88.51-99.42 percent.

Herrera, Claudia Y.↗
NASA NTRS2007

Build-up Approach to Updating the Mock Quiet Spike(TM)Beam Model

A crucial part of aircraft design is ensuring that the required margin for flutter is satisfied. A trustworthy flutter analysis, which begins by possessing an accurate dynamics model, is necessary for this task. Traditionally, a model was updated manually by fine tuning specific stiffness parameters until the analytical results matched test data. This is a time consuming iterative process. The NASA Dryden Flight Research Center has developed a mode matching code to execute this process in a more efficient manner. Recently, this code was implemented in the F-15B/Quiet Spike (Gulfstream Aerospace Corporation, Savannah, Georgia) model update. A build-up approach requiring several ground vibration test configurations and a series of model updates was implemented to determine the connection stiffness between aircraft and test article. The mode matching code successfully updated various models for the F-15B/Quiet Spike project to within 1 percent error in frequency and the modal assurance criteria values ranged from 88.51-99.42 percent.

Herrera, Claudia Y.↗
NASA NTRS2003

Personalizing Knowledge Delivery Services for Emerging Knowledge Processes (EKPs): A Conceptual Framework

The contents include: 1) What do most KMS in use today assume?; 2) Assumptions are violated when KMS is used by EKP workers - Why?; 3) Current State of KMS for EKPs are inadequate; 4) What would an "adequate" KMS for EKPs look like?; 5) "User-as-Consumer" Analogue: Ecommerce/Eem ployee Services; 6) Why is an ideal KMS for EKPs hard to achieve?; 7) So, what type of KMS design would work?; 8) Human-Based KMS for EKP - Proposal Call Managers at R&DLAB; 9) Proposal Call Managers (PCMs); 10) Specific PCM tasks; 11) Why is a R&DLAB PCM a human metaphor for a KMS for EKP?; 12) Data Collection; 13) Finding #1; 14) Finding #2; 15) Finding #3; 16) Factors affecting How/when; 17) Finding #4; 18) Finding #5; 19) Implication#l for a KMS for EKP: From System to Service; 20) Implication #2: From technology or human-centric to Mixed Mode; 21) Implication #3: From Simple User Profiles to Dynamic Delivery Profiles; 22) Implication #4: Maintaining a trustworthy environment; 23) Implication #5: Constructing a dynamic delivery profile; 24) Implications for Research: Model; and 25) Example Research Qs on KMS Support for EKPs.

knowledge management↗
NASA NTRS2008

Dawn: Cooperation, not Control

On September 27, 2007, a Delta II rocket carrying the Dawn spacecraft lifted off from Kennedy Space Center. Part of NASAs Discovery program, the $370 million Dawn mission began its three-billion-mile voyage to the asteroid belt to study the asteroid Vesta and Ceres, a dwarf planet. The spacecraft is scheduled to reach Vesta in 2011. After spending nine months measuring the composition, shape, and topography of that body, it will travel a billion miles to carry out a similar analysis of Ceres in 2015. The Important Lessons: The demands of Dawn and other challenging missions have taught some important lessons for successful program and project management. These are the main ones: a) Program management, particularly of uncoupled and loosely coupled projects, should be more about enabling than controlling. You're working with motivated, high-performing teams and institutions with a track record of quality and success. Emphasize commander's intent over rudder control; let them know where you want to go and when you want to be there, then let them figure out how to get there. b) Open and honest discussion of issues is essential. People fill the void of the unknown with their worst fears. Get folks around the table and have open, honest, and frank dialogue. I've seldom seen this fail to get to the root of issues. c) You have to earn your seat at the table, proving that you are competent, trustworthy, and dedicated to the success of the mission. d) Know when to fold 'em. Your pride can get rolled up in making a milestone or launch date, but you have to make a judgment based on the realities of the situation and not wear down the team trying to meet an increasingly impossible deadline. e) The NASA governance model that gives a voice to the concerns of engineers and safety experts works-trust it and use it.

May, Todd↗
NASA NTRS2008

Global Test Range: Toward Airborne Sensor Webs

This viewgraph presentation reviews the planned global sensor network that will monitor the Earth's climate, and resources using airborne sensor systems. The vision is an intelligent, affordable Earth Observation System. Global Test Range is a lab developing trustworthy services for airborne instruments - a specialized Internet Service Provider. There is discussion of several current and planned missions.

Mace, Thomas H.↗
NASA NTRS2009

Deriving Safety Cases from Automatically Constructed Proofs

Formal proofs provide detailed justification for the validity of claims and are widely used in formal software development methods. However, they are often complex and difficult to understand, because the formalism in which they are constructed and encoded is usually machine-oriented, and they may also be based on assumptions that are not justified. This causes concerns about the trustworthiness of using formal proofs as arguments in safety-critical applications. Here, we present an approach to develop safety cases that correspond to formal proofs found by automated theorem provers and reveal the underlying argumentation structure and top-level assumptions. We concentrate on natural deduction style proofs, which are closer to human reasoning than resolution proofs, and show how to construct the safety cases by covering the natural deduction proof tree with corresponding safety case fragments. We also abstract away logical book-keeping steps, which reduces the size of the constructed safety cases. We show how the approach can be applied to the proofs found by the Muscadet prover.

Basir, Nurlida↗
NASA NTRS2009

Deriving Safety Cases from Machine-Generated Proofs

Proofs provide detailed justification for the validity of claims and are widely used in formal software development methods. However, they are often complex and difficult to understand, because they use machine-oriented formalisms; they may also be based on assumptions that are not justified. This causes concerns about the trustworthiness of using formal proofs as arguments in safety-critical applications. Here, we present an approach to develop safety cases that correspond to formal proofs found by automated theorem provers and reveal the underlying argumentation structure and top-level assumptions. We concentrate on natural deduction proofs and show how to construct the safety cases by covering the proof tree with corresponding safety case fragments.

Basir, Nurlida↗
NASA NTRS2009

Deriving Safety Cases for the Formal Safety Certification of Automatically Generated Code

We present an approach to systematically derive safety cases for automatically generated code from information collected during a formal, Hoare-style safety certification of the code. This safety case makes explicit the formal and informal reasoning principles, and reveals the top-level assumptions and external dependencies that must be taken into account; however, the evidence still comes from the formal safety proofs. It uses a generic goal-based argument that is instantiated with respect to the certified safety property (i.e., safety claims) and the program. This will be combined with a complementary safety case that argues the safety of the framework itself, in particular the correctness of the Hoare rules with respect to the safety property and the trustworthiness of the certification system and its individual components. Keywords: Automated code generation, Hoare logic, formal code certification, safety case, Goal Structuring Notation.

Basir, Nurlida↗
NASA NTRS2012

Intercomparison of the LASCO-C2, SECCHI-COR1, SECCHI-COR2, and Mk4 Coronagraphs

In order to assess the reliability and consistency of white-light coronagraph measurements, we report on quantitative comparisons between polarized brightness [pB] and total brightness [B] images taken by the following white-light coronagraphs: LASCO-C2 on SOHO, SECCHI-COR1 and -COR2 on STEREO, and the ground-based MLSO-Mk4. The data for this comparison were taken on 16 April 2007, when both STEREO spacecraft were within 3.1 deg. of Earth’s heliographic longitude, affording essentially the same view of the Sun for all of the instruments. Due to the difficulties of estimating stray-light backgrounds in COR1 and COR2, only Mk4 and C2 produce reliable coronal-hole values (but not at overlapping heights), and these cannot be validated without rocket flights or ground-based eclipse measurements. Generally, the agreement between all of the instruments’ pB values is within the uncertainties in bright streamer structures, implying that measurements of bright CMEs also should be trustworthy. Dominant sources of uncertainty and stray light are discussed, as is the design of future coronagraphs from the perspective of the experiences with these instruments.

Coronagraph↗
NASA NTRS2014

Detailed Uncertainty Analysis of the ZEM-3 Measurement System

The measurement of Seebeck coefficient and electrical resistivity are critical to the investigation of all thermoelectric systems. Therefore, it stands that the measurement uncertainty must be well understood to report ZT values which are accurate and trustworthy. A detailed uncertainty analysis of the ZEM-3 measurement system has been performed. The uncertainty analysis calculates error in the electrical resistivity measurement as a result of sample geometry tolerance, probe geometry tolerance, statistical error, and multi-meter uncertainty. The uncertainty on Seebeck coefficient includes probe wire correction factors, statistical error, multi-meter uncertainty, and most importantly the cold-finger effect. The cold-finger effect plagues all potentiometric (four-probe) Seebeck measurement systems, as heat parasitically transfers through thermocouple probes. The effect leads to an asymmetric over-estimation of the Seebeck coefficient. A thermal finite element analysis allows for quantification of the phenomenon, and provides an estimate on the uncertainty of the Seebeck coefficient. The thermoelectric power factor has been found to have an uncertainty of +9-14 at high temperature and 9 near room temperature.

Seebeck effect↗
NASA NTRS2013

Evidence Arguments for Using Formal Methods in Software Certification

We describe a generic approach for automatically integrating the output generated from a formal method/tool into a software safety assurance case, as an evidence argument, by (a) encoding the underlying reasoning as a safety case pattern, and (b) instantiating it using the data produced from the method/tool. We believe this approach not only improves the trustworthiness of the evidence generated from a formal method/tool, by explicitly presenting the reasoning and mechanisms underlying its genesis, but also provides a way to gauge the suitability of the evidence in the context of the wider assurance case. We illustrate our work by application to a real example-an unmanned aircraft system- where we invoke a formal code analysis tool from its autopilot software safety case, automatically transform the verification output into an evidence argument, and then integrate it into the former.

Argumentation↗