Engineering topics

Buck, Bill K.

Publications and source records attributed to Buck, Bill K..

4 records

NASA NTRS2019

Simulation and Flight Test Environments for the TASAR Traffic Aware Planner

The Traffic Aware Planner (TAP) software is a flight deck decision support tool that enhances the flight crew’s ability to make flight-optimizing route change requests while airborne. The software provides conflict-free, optimized trajectory suggestions during en route flight to produce time- and fuel-savings compared to the current trajectory. The TAP software requires evaluation in an operational environment with real pilot users to validate projected benefits. To this end, a set of developmental test environments have been developed to mature the software and mitigate technical risk prior to entering operational evaluation. The unique attributes of each test environment were leveraged to provide a range of purpose- and case-dependent TAP software tests. This paper describes the elements of a testing environment, discusses several environments of varying fidelity used to test the TAP software, and provides a review of two case studies highlighting the vital role testing played in the TAP software development process.

Barney, Terique L.↗

NASA NTRS2009

A Methodology for Determining Statistical Performance Compliance for Airborne Doppler Radar with Forward-Looking Turbulence Detection Capability

The objective of the research developed and presented in this document was to statistically assess turbulence hazard detection performance employing airborne pulse Doppler radar systems. The FAA certification methodology for forward looking airborne turbulence radars will require estimating the probabilities of missed and false hazard indications under operational conditions. Analytical approaches must be used due to the near impossibility of obtaining sufficient statistics experimentally. This report describes an end-to-end analytical technique for estimating these probabilities for Enhanced Turbulence (E-Turb) Radar systems under noise-limited conditions, for a variety of aircraft types, as defined in FAA TSO-C134. This technique provides for one means, but not the only means, by which an applicant can demonstrate compliance to the FAA directed ATDS Working Group performance requirements. Turbulence hazard algorithms were developed that derived predictive estimates of aircraft hazards from basic radar observables. These algorithms were designed to prevent false turbulence indications while accurately predicting areas of elevated turbulence risks to aircraft, passengers, and crew; and were successfully flight tested on a NASA B757-200 and a Delta Air Lines B737-800. Application of this defined methodology for calculating the probability of missed and false hazard indications taking into account the effect of the various algorithms used, is demonstrated for representative transport aircraft and radar performance characteristics.

Bowles, Roland L.↗

NASA NTRS2007

In-Service Evaluation of the Turbulence Auto-PIREP System and Enhanced Turbulence Radar Technologies

From August 2003 to December 2006, In-Service Evaluations (ISE) of the Turbulence Auto-PIREP System (TAPS) and Enhanced Turbulence (E-Turb) Radar, technologies developed in NASA's Turbulence Prediction and Warning System (TPAWS) element of its Aviation Safety and Security Program (AvSSP), were conducted. NASA and AeroTech Research established an industry team comprising AeroTech, Delta Air Lines, Rockwell Collins, and ARINC to conduct the ISEs. The technologies were installed on Delta aircraft and their effectiveness was evaluated in day-to-day operations. This report documents the establishment and conduct of the ISEs and presents results and feedback from various users.

Prince, Jason B.↗

NASA NTRS2004

Development of an Aircraft Approach and Departure Atmospheric Profile Generation Algorithm

In support of NASA Virtual Airspace Modeling and Simulation (VAMS) project, an effort was initiated to develop and test techniques for extracting meteorological data from landing and departing aircraft, and for building altitude based profiles for key meteorological parameters from these data. The generated atmospheric profiles will be used as inputs to NASA s Aircraft Vortex Spacing System (AVOLSS) Prediction Algorithm (APA) for benefits and trade analysis. A Wake Vortex Advisory System (WakeVAS) is being developed to apply weather and wake prediction and sensing technologies with procedures to reduce current wake separation criteria when safe and appropriate to increase airport operational efficiency. The purpose of this report is to document the initial theory and design of the Aircraft Approach Departure Atmospheric Profile Generation Algorithm.

Buck, Bill K.↗