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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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NASA NTRS2011

Modeling Weather Impact on Ground Delay Programs

Scheduled arriving aircraft demand may exceed airport arrival capacity when there is abnormal weather at an airport. In such situations, Federal Aviation Administration (FAA) institutes ground-delay programs (GDP) to delay flights before they depart from their originating airports. Efficient GDP planning depends on the accuracy of prediction of airport capacity and demand in the presence of uncertainties in weather forecast. This paper presents a study of the impact of dynamic airport surface weather on GDPs. Using the National Traffic Management Log, effect of weather conditions on the characteristics of GDP events at selected busy airports is investigated. Two machine learning methods are used to generate models that map the airport operational conditions and weather information to issued GDP parameters and results of validation tests are described.

Wang, Yao↗

NASA NTRS2016

Proof-of-Concept Demonstrations of a Flight Adjustment Logging and Communication Network

The National Airspace System is a highly complex system of systems within which a number of participants with widely varying business and operating models exist. From the airspace user's perspective, a means by which to operate flights in a more flexible and efficient manner is highly desired to meet their business objectives. From the air navigation service provider's viewpoint, there is a need for increasing the capacity of the airspace, while maintaining or increasing the levels of efficiency and safety that currently exist in order to meet the charter under which they operate. Enhancing the communication between airspace operators and users is essential in order to meet these demands. In the spring of 2015, a prototype system that implemented an airborne tool to optimize en-route flight paths for fuel and time savings was designed and tested. The system utilized in-flight Internet as a high-bandwidth data link to facilitate collaborative decision making between the flight deck and an airline dispatcher. The system was tested and demonstrated in a laboratory environment, as well as in-situ. Initial results from these tests indicate that this system is not only feasible, but could also serve as a growth path and testbed for future air traffic management concepts that rely on shared situational awareness through data exchange and electronic negotiation between multiple entities operating within the National Airspace System.

Underwood, Matthew C.↗

NASA NTRS2013

A Scala DSL for RETE-Based Runtime Verification

Runtime verification (RV) consists in part of checking execution traces against formalized specifications. Several systems have emerged, most of which support specification notations based on state machines, regular expressions, temporal logic, or grammars. The field of Artificial Intelligence (AI) has for an even longer period of time studied rule-based production systems, which at a closer look appear to be relevant for RV, although seemingly focused on slightly different application domains, such as for example business processes and expert systems. The core algorithm in many of these systems is the Rete algorithm. We have implemented a Rete-based runtime verification system, named LogFire (originally intended for offline log analysis but also applicable to online analysis), as an internal DSL in the Scala programming language, using Scala's support for defining DSLs. This combination appears attractive from a practical point of view. Our contribution is in part conceptual in arguing that such rule-based frameworks originating from AI may be suited for RV.

matching problem↗

NASA NTRS1997

Application of Domain Knowledge to Software Quality Assurance

This work focused on capturing, using, and evolving a qualitative decision support structure across the life cycle of a project. The particular application of this study was towards business process reengineering and the representation of the business process in a set of Business Rules (BR). In this work, we defined a decision model which captured the qualitative decision deliberation process. It represented arguments both for and against proposed alternatives to a problem. It was felt that the subjective nature of many critical business policy decisions required a qualitative modeling approach similar to that of Lee and Mylopoulos. While previous work was limited almost exclusively to the decision capture phase, which occurs early in the project life cycle, we investigated the use of such a model during the later stages as well. One of our significant developments was the use of the decision model during the operational phase of a project. By operational phase, we mean the phase in which the system or set of policies which were earlier decided are deployed and put into practice. By making the decision model available to operational decision makers, they would have access to the arguments pro and con for a variety of actions and can thus make a more informed decision which balances the often conflicting criteria by which the value of action is measured. We also developed the concept of a 'monitored decision' in which metrics of performance were identified during the decision making process and used to evaluate the quality of that decision. It is important to monitor those decision which seem at highest risk of not meeting their stated objectives. Operational decisions are also potentially high risk decisions. Finally, we investigated the use of performance metrics for monitored decisions and audit logs of operational decisions in order to feed an evolutionary phase of the the life cycle. During evolution, decisions are revisisted, assumptions verified or refuted, and possible reassessments resulting in new policy are made. In this regard we implemented a machine learning algorithm which automatically defined business rules based on expert assessment of the quality of operational decisions as recorded during deployment.

Wild, Christian W.↗

NASA NTRS2008

Problem Reporting System

The Problem Reporting System (PRS) is a Web application, running on two Web servers (load-balanced) and two database servers (RAID-5), which establishes a system for submission, editing, and sharing of reports to manage risk assessment of anomalies identified in NASA's flight projects. PRS consolidates diverse anomaly-reporting systems, maintains a rich database set, and incorporates a robust engine, which allows tracking of any hardware, software, or paper process by configuring an appropriate life cycle. Global and specific project administration and setup tools allow lifecycle tailoring, along with customizable controls for user, e-mail, notifications, and more. PRS is accessible via the World Wide Web for authorized user at most any location. Upon successful log-in, the user receives a customizable window, which displays time-critical 'To Do' items (anomalies requiring the user s input before the system moves the anomaly to the next phase of the lifecycle), anomalies originated by the user, anomalies the user has addressed, and custom queries that can be saved for future use. Access controls exist depending on a user's role as system administrator, project administrator, user, or developer, and then, further by association with user, project, subsystem, company, or item with provisions for business-to-business exclusions, limitations on access according to the covert or overt nature of a given project, all with multiple layers of filtration, as needed. Reporting of metrics is built in. There is a provision for proxy access (in which the user may choose to grant one or more other users to view screens and perform actions as though they were the user, during any part of a tracking life cycle - especially useful during tight build schedules and vacations to keep things moving). The system also provides users the ability to have an anomaly link to or notify other systems, including QA Inspection Reports, Safety, GIDEP (Government-Industry Data Exchange Program) Alert, Corrective Actions, and Lessons Learned. The PRS tracking engine was designed as a very extensible and scalable system, able to support additional applications, with future development possibilities already discussed, including Incident Surprise Anomalies (for anomalies occurring during Operations phases of NASA Flight projects), GIDEP and NASA Alerts, and others.

Potter, Don↗

NASA NTRS2015

Developing a Business Intelligence Process for a Training Module in SharePoint 2010

Prior to this project, training information for the employees of the National Center for Critical Processing and Storage (NCCIPS) was stored in an array of unrelated spreadsheets and SharePoint lists that had to be manually updated. By developing a content management system through a web application platform named SharePoint, this training system is now highly automated and provides a much less intensive method of storing training data and scheduling training courses. This system was developed by using SharePoint Designer and laying out the data structure for the interaction between different lists of data about the employees. The automation of data population inside of the lists was accomplished by implementing SharePoint workflows which essentially lay out the logic for how data is connected and calculated between certain lists. The resulting training system is constructed from a combination of five lists of data with a single list acting as the user-friendly interface. This interface is populated with the courses required for each employee and includes past and future information about course requirements. The employees of NCCIPS now have the ability to view, log, and schedule their training information and courses with much more ease. This system will relieve a significant amount of manual input and serve as a powerful informational resource for the employees of NCCIPS in the future.

Schmidtchen, Bryce↗