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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 NTRS1995

Performance of the 0.3-meter transonic cryogenic tunnel with air, nitrogen, and sulfur hexafluoride media under closed loop automatic control

The NASA Langley 0.3-m Transonic Cryogenic Tunnel was modified in 1994, to operate with any one of the three test gas media viz., air, cryogenic nitrogen gas, or sulfur hexafluoride gas. This document provides the initial test results with respect to the tunnel performance and tunnel control, as a part of the commissioning activities on the microcomputer based controller. The tunnel can provide precise and stable control of temperature to less than or equal to +/- 0.3 K in the range 80-320 K in cyro mode or 300-320 K in air/SF6 mode, pressure to +/- 0.01 psia in the range 15-88 psia and Mach number to +/- O.0015 in the range 0.150 to transonic Mach numbers up to 1.000. A new heat exchanger has been included in the tunnel circuit and is performing adequately. The tunnel airfoil testing benefits considerably by precise control of tunnel states and helps in generating high quality aerodynamic test data from the 0.3-m TCT.

Balakrishna, S.↗
NASA NTRSDate not supplied

Benefits of using Electronic Data Sheets (EDS) with coreFlight Systems (cFS) - A Project Example

Recently there has been interest in the incorporation of core Flight Systems (cFS) with Spacecraft Onboard Interface Services (SOIS) Electronic Data Sheets (EDS) in the spaceflight software community. The Regenerative Fuel Cell project at the Glenn Research Center is using cFS architecture with EDS support for its monitoring and control software. The presentation will outline the benefits to using cFS with EDS support: First, EDS establishes a single source of truth for the definitions of data structures used throughout an entire mission that may otherwise be programmed in different languages and designed with different processor architectures. Not only does this help with inter-application communication via the software bus, but it also greatly simplifies communication between systems. An EDS Application Programming Interface (API) library allows the conversion of EDS data structures to and from native data structures. Second, bindings for other programming languages (e.g. Lua, Python, JSON) have been written to allow the creation and manipulation of EDS data objects within those languages. The RFC project uses Lua scripts to automatically generate binary configuration files at build time to be loaded into our cFS programs. We also use Python bindings in a graphical user interface (GUI) to allow an operator to send commands and view telemetry messages sent from cFS instances. Finally, using Lua scripts we can set up specific simulation scenarios to perform automatic functional testing. During the development of the RFC software, the software team put together a generic python GUI called “cFS-EDS-GroundStation” that provides a basic interface to an instance of cFS with EDS support. The GUI includes a basic telecommand and telemetry system that reads directly from the generated EDS databases. In the telecommand system, dropdown menus are populated with all user commands that are defined in EDS. In the telemetry system, telemetry messages are automatically decoded, written to the screen, and saved to a binary file. Additional Python scripts have been written to convert the binary data files into a comma separated value (CSV) format for further processing. We will demonstrate the basic use of the cFS-EDS-GroundStation software including adding additional commands and telemetry payload values in EDS and see them appear automatically in the cFS-EDS-Groundstation software. About the RFC project: The Regenerative Fuel Cell project is tasked with developing and demonstrating a power system consisting of a fuel cell and electrolyzer to provide power during a lunar day/night cycle. During the night, the fuel cell takes Hydrogen and Oxygen gasses and converts them into electricity, water, and heat. During the day, the electrolyzer takes input power (e.g. from a photovoltaic array) and converts water back into Hydrogen and Oxygen gasses.

Mathew Mccaskey↗
DOE OSTI2025

Multi-objective automatic discovery of optimized metamaterials for varying velocity impact protection

Mechanical metamaterials have demonstrated exceptional impact performance while remaining lightweight. Impact resistance has traditionally been investigated using quasi-static simulations, often with the assumption that performance will translate to high-velocity impact scenarios. However, critical crash protection parameters—such as peak stress and absorbed energy—are highly sensitive to impact velocity, leading to inconsistent performance under dynamic loading. To address this, we introduce a strain-rate-aware, active deep learning framework that enables multi-objective optimization of impact protection metrics across a wide range of impact velocities. Our framework captures the strain-rate sensitivity of architected lattices by learning to control spatial gradation in cellular metamaterials, resulting in over 200 % enhancement in impact protection relative to state-of-the-art designs such as Voronoi and re-entrant lattices. We demonstrate its practical utility by designing next-generation lattice structures for automotive bumper systems that satisfy multiple, velocity-specific safety criteria—capabilities beyond those of conventional designs. More than just a predictive tool, this framework marks the first step towards enabling adaptable impact-resistant structures across dynamic regimes.

Deep learning↗
NASA NTRS1990

Douglas flight deck design philosophy

The systems experience gained from 17 years of DC-10 operation was used during the design of the MD-11 to automate system operation and reduce crew workload. All functions, from preflight to shutdown at the termination of flight, require little input from the crew. The MD-11 aircraft systems are monitored for proper operation by the Aircraft Systems Controllers (ASC). In most cases, system reconfiguration as a result of a malfunction is automated. Manual input is required for irreversible actions such as engine shutdown, fuel dump, fire agent discharge, or Integrated Drive Generator (IDG) disconnect. During normal operations, when the cockpit is configured for flight, all annunciators on the overhead panel will be extinguished. This Dark Cockpit immediately confirms to the crew that the panels are correctly configured and that no abnormalities are present. Primary systems annunciations are shown in text on the Alert Area of the Engine and Alert Display (EAD). This eliminates the need to scan the overhead. The MD-11 aircraft systems can be manually controlled from the overhead area of the cockpit. The center portion of the overhead panel is composed of the primary aircraft systems panels, which include FUEL, AIR, Electrical (ELEC) and Hydraulic (HYD) systems, which are easily accessible from both flight crew positions. Each Aircraft Systems Controller (ASC) has two automatic channels and a manual mode. All rectangular lights are annunciators. All square lights are combined switches and annunciators called switch/lights. Red switch/lights on the overhead (Level 3 alerts) are for conditions requiring immediate crew action. Amber (Level 2 or Level 1 alerts) indicates a fault or switch out of position requiring awareness or crew interaction. Overhead switches used in normal operating conditions will illuminate blue when in use (Level 0 alerts) such as WING ANTI-ICE - ON. An overhead switch/light with BLACK LETTERING on an amber or red background indicates a system failure and that crew interaction is required. A switch/light with blue or amber lettering and a BLACK BACKGROUND indicates a switch out of normal position and that crew action is necessary only if the system is in manual operation.

Oldale, Paul↗
NASA NTRS1993

Intelligent neuroprocessors for in-situ launch vehicle propulsion systems health management

Efficacy of existing on-board propulsion systems health management systems (HMS) are severely impacted by computational limitations (e.g., low sampling rates); paradigmatic limitations (e.g., low-fidelity logic/parameter redlining only, false alarms due to noisy/corrupted sensor signatures, preprogrammed diagnostics only); and telemetry bandwidth limitations on space/ground interactions. Ultra-compact/light, adaptive neural networks with massively parallel, asynchronous, fast reconfigurable and fault-tolerant information processing properties have already demonstrated significant potential for inflight diagnostic analyses and resource allocation with reduced ground dependence. In particular, they can automatically exploit correlation effects across multiple sensor streams (plume analyzer, flow meters, vibration detectors, etc.) so as to detect anomaly signatures that cannot be determined from the exploitation of single sensor. Furthermore, neural networks have already demonstrated the potential for impacting real-time fault recovery in vehicle subsystems by adaptively regulating combustion mixture/power subsystems and optimizing resource utilization under degraded conditions. A class of high-performance neuroprocessors, developed at JPL, that have demonstrated potential for next-generation HMS for a family of space transportation vehicles envisioned for the next few decades, including HLLV, NLS, and space shuttle is presented. Of fundamental interest are intelligent neuroprocessors for real-time plume analysis, optimizing combustion mixture-ratio, and feedback to hydraulic, pneumatic control systems. This class includes concurrently asynchronous reprogrammable, nonvolatile, analog neural processors with high speed, high bandwidth electronic/optical I/O interfaced, with special emphasis on NASA's unique requirements in terms of performance, reliability, ultra-high density ultra-compactness, ultra-light weight devices, radiation hardened devices, power stringency, and long life terms.

Gulati, S.↗
NASA NTRS2013

Acceptability of Flight Deck-Based Interval Management Crew Procedures

The Interval Management for Near-term Operations Validation of Acceptability (IM-NOVA) experiment was conducted at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) in support of the NASA Next Generation Air Transportation System (NextGen) Airspace Systems Program's Air Traffic Management Technology Demonstration - 1 (ATD-1). ATD-1 is intended to showcase an integrated set of technologies that provide an efficient arrival solution for managing aircraft using NextGen surveillance, navigation, procedures, and automation for both airborne and ground-based systems. The goal of the IM-NOVA experiment was to assess if procedures outlined by the ATD-1 Concept of Operations, when used with a minimum set of Flight deck-based Interval Management (FIM) equipment and a prototype crew interface, were acceptable to and feasible for use by flight crews in a voice communications environment. To investigate an integrated arrival solution using ground-based air traffic control tools and aircraft automatic dependent surveillance broadcast (ADS-B) tools, the LaRC FIM system and the Traffic Management Advisor with Terminal Metering and Controller Managed Spacing tools developed at the NASA Ames Research Center (ARC) were integrated in LaRC's Air Traffic Operations Laboratory. Data were collected from 10 crews of current, qualified 757/767 pilots asked to fly a high-fidelity, fixed based simulator during scenarios conducted within an airspace environment modeled on the Dallas-Fort Worth (DFW) Terminal Radar Approach Control area. The aircraft simulator was equipped with the Airborne Spacing for Terminal Area Routes algorithm and a FIM crew interface consisting of electronic flight bags and ADS-B guidance displays. Researchers used "pseudo-pilot" stations to control 24 simulated aircraft that provided multiple air traffic flows into DFW, and recently retired DFW air traffic controllers served as confederate Center, Feeder, Final, and Tower controllers. Pilot participant feedback indicated that the procedures used by flight crews to receive and execute interval management (IM) clearances in a voice communications environment were logical, easy to follow, did not contain any missing or extraneous steps, and required the use of an acceptable level of workload. The majority of the pilot participants found the IM concept, in addition to the proposed FIM crew procedures, to be acceptable and indicated that the ATD-1 procedures can be successfully executed in a near-term NextGen environment.

Murdock, Jennifer L.↗
NASA NTRS1990

State reduction for semi-Markov reliability models

Semi-Markov processes have proved to be an effective and convenient tool to construct models of systems that achieve reliability by redundancy and reconfiguration. These models are able to depict complex system architectures and to capture the dynamics of fault arrival and system recovery. A disadvantage of this approach is that the models can be extremely large, which poses both a model construction and a computational problem. Techniques are needed to reduce the model size. Because these systems are used in critical applications where failure can be expensive, there must be an analytically derived bound for the error produced by the model reduction technique. Automatic model generation programs have been written to help the reliability analyst produce models of complex systems. Because of the importance of these programs, the model reduction technique needs to be precise and easily implemented. This paper presents a model reduction technique called trimming that can be applied to a popular class of systems. An error bound for the trimming procedure is derived that uses readily available system parameters. The trimming procedure is precisely described and appears easy to implement in a model generation program.

Reduced order systems↗
NASA NTRS2009

General Purpose Data-Driven Monitoring for Space Operations

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault and anomaly detection algorithms and diagnosis tools with executive and adaptive planning functions contained in the flight software on-board the Air Force Research Laboratory TacSat-3 satellite. The TVSM software package will be uploaded after launch to monitor spacecraft subsystems such as power and guidance, navigation, and control (GN&C). It will analyze data in real-time to demonstrate detection of faults and unusual conditions, diagnose problems, and react to threats to spacecraft health and mission goals. The experiment will demonstrate the feasibility and effectiveness of integrated system health management (ISHM) technologies with both ground and on-board experiments.

Iverson, David L.↗
NASA NTRS1977

The navigation system of the JPL robot

The control structure of the JPL research robot and the operations of the navigation subsystem are discussed. The robot functions as a network of interacting concurrent processes distributed among several computers and coordinated by a central executive. The results of scene analysis are used to create a segmented terrain model in which surface regions are classified by traversibility. The model is used by a path planning algorithm, PATH, which uses tree search methods to find the optimal path to a goal. In PATH, the search space is defined dynamically as a consequence of node testing. Maze-solving and the use of an associative data base for context dependent node generation are also discussed. Execution of a planned path is accomplished by a feedback guidance process with automatic error recovery.

Thompson, A. M.↗
NASA NTRS2013

SequenceL: Automated Parallel Algorithms Derived from CSP-NT Computational Laws

With the introduction of new parallel architectures like the cell and multicore chips from IBM, Intel, AMD, and ARM, as well as the petascale processing available for highend computing, a larger number of programmers will need to write parallel codes. Adding the parallel control structure to the sequence, selection, and iterative control constructs increases the complexity of code development, which often results in increased development costs and decreased reliability. SequenceL is a high-level programming language that is, a programming language that is closer to a human s way of thinking than to a machine s. Historically, high-level languages have resulted in decreased development costs and increased reliability, at the expense of performance. In recent applications at JSC and in industry, SequenceL has demonstrated the usual advantages of high-level programming in terms of low cost and high reliability. SequenceL programs, however, have run at speeds typically comparable with, and in many cases faster than, their counterparts written in C and C++ when run on single-core processors. Moreover, SequenceL is able to generate parallel executables automatically for multicore hardware, gaining parallel speedups without any extra effort from the programmer beyond what is required to write the sequen tial/singlecore code. A SequenceL-to-C++ translator has been developed that automatically renders readable multithreaded C++ from a combination of a SequenceL program and sample data input. The SequenceL language is based on two fundamental computational laws, Consume-Simplify- Produce (CSP) and Normalize-Trans - pose (NT), which enable it to automate the creation of parallel algorithms from high-level code that has no annotations of parallelism whatsoever. In our anecdotal experience, SequenceL development has been in every case less costly than development of the same algorithm in sequential (that is, single-core, single process) C or C++, and an order of magnitude less costly than development of comparable parallel code. Moreover, SequenceL not only automatically parallelizes the code, but since it is based on CSP-NT, it is provably race free, thus eliminating the largest quality challenge the parallelized software developer faces.

Cooke, Daniel↗
NASA NTRS2008

Wind Tunnel Testing of Powered Lift, All-Wing STOL Model

Short take-off and landing (STOL) systems can offer significant capabilities to warfighters and, for civil operators thriving on maximizing efficiencies they can improve airspace use while containing noise within airport environments. In order to provide data for next generation systems, a wind tunnel test of an all-wing cruise efficient, short take-off and landing (CE STOL) configuration was conducted in the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) 14- by 22-foot Subsonic Wind Tunnel. The test s purpose was to mature the aerodynamic aspects of an integrated powered lift system within an advanced mobility configuration capable of CE STOL. The full-span model made use of steady flap blowing and a lifting centerbody to achieve high lift coefficients. The test occurred during April through June of 2007 and included objectives for advancing the state-of-the-art of powered lift testing through gathering force and moment data, on-body pressure data, and off-body flow field measurements during automatically controlled blowing conditions. Data were obtained for variations in model configuration, angles of attack and sideslip, blowing coefficient, and height above ground. The database produced by this effort is being used to advance design techniques and computational tools for developing systems with integrated powered lift technologies.

Collins, Scott W.↗
NASA NTRS2013

Precision Departure Release Capability (PDRC) Final Report

After takeoff, aircraft must merge into en route (Center) airspace traffic flows that may be subject to constraints that create localized demand/capacity imbalances. When demand exceeds capacity, Traffic Management Coordinators (TMCs) and Frontline Managers (FLMs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves a Call for Release (CFR) procedure wherein the Tower must call the Center to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool, based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release time is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that improves tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions and departure runway assignments to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept reduces uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs and FLMs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station in Dallas/Fort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations. This paper presents research results from the PDRC research activity. Companion papers present the Concept of Operations and a Technology Description.

tactical departure scheduling↗
NASA NTRS2013

Precision Departure Release Capability (PDRC): NASA to FAA Research Transition

After takeoff, aircraft must merge into en route (Center) airspace traffic flows which may be subject to constraints that create localized demand-capacity imbalances. When demand exceeds capacity, Traffic Management Coordinators (TMCs) and Frontline Managers (FLMs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves use of a Call for Release (CFR) procedure wherein the Tower must call the Center to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release time is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that improves tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions and departure runway assignments to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept reduces uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs and FLMs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station in Dallas-Fort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations.

ATM↗
NASA NTRSDate not supplied

Q-Law for Rapid Assessment of Low Thrust Cislunar Trajectories Via Automatic Differentiation

Q-Law is a Lyapunov-based control law used to determine optimal controls for a low thrust trajectory. One major issue with its use is the difficult derivatives re-quired for calculating optimal controls at a given time. In this paper, an implementation of Q-Law with automatic differentiation via a Python package called JAX is applied. With automatic differentiation, the difficult derivatives for Q-Law’s optimal controls are calculated with ease, and derivatives of final states with respect to Q-Law’s weights are found enabling gradient-based optimization of Q-Law for the first time. Different search and optimization methods for finding optimal weights are then compared using the LEO to GEO problem, and it was found that gradient-free methods like design of experiments and genetic algorithm produced the best results, but they took the longest time to get a solution, while the gradient-based method found a locally optimal result in a much faster time. Overall, the run time for a single propagation is manageable and well-suited for a mission designer to use as an initial guess generator for trajectory optimization, or for simple orbit transfer analysis.

Nathan Steffen↗
NASA NTRS2013

Precision Departure Release Capability (PDRC) Technology Description

After takeoff, aircraft must merge into en route (Center) airspace traffic flows which may be subject to constraints that create localized demand-capacity imbalances. When demand exceeds capacity, Traffic Management Coordinators (TMCs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves use of a Call for Release (CFR) procedure wherein the Tower must call the Center TMC to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System (NextGen) plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that uses this technology to improve tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept helps reduce uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station (NTX) in Dallas-Fort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations. This paper presents the Technology Description. Companion papers include the Final Report and a Concept of Operations.

tactical departure scheduling↗
NASA NTRS2013

Precision Departure Release Capability (PDRC) Concept of Operations

After takeoff, aircraft must merge into en route (Center) airspace traffic flows which may be subject to constraints that create localized demandcapacity imbalances. When demand exceeds capacity Traffic Management Coordinators (TMCs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves use of a Call for Release (CFR) procedure wherein the Tower must call the Center TMC to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System (NextGen) plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that uses this technology to improve tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept helps reduce uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station (NTX) in DallasFort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations. This paper presents the Concept of Operations. Companion papers include the Final Report and a Technology Description. ? SUBJECT:

tactical departure scheduling↗
NASA NTRS2011

Development of Meandering Winding Magnetometer (MWM (Register Trademark)) Eddy Current Sensors for the Health Monitoring, Modeling and Damage Detection of High Temperature Composite Materials

The increased use of high-temperature composite materials in modern and next generation aircraft and spacecraft have led to the need for improved nondestructive evaluation and health monitoring techniques. Such technologies are desirable to improve quality control, damage detection, stress evaluation and temperature measurement capabilities. Novel eddy current sensors and sensor arrays, such as Meandering Winding Magnetometers (MWMs) have provided alternate or complimentary techniques to ultrasound and thermography for both nondestructive evaluation (NDE) and structural health monitoring (SHM). This includes imaging of composite material quality, damage detection and .the monitoring of fiber temperatures and multidirectional stresses. Historically, implementation of MWM technology for the inspection of the Space Shuttle Orbiter Reinforced Carbon-Carbon Composite (RCC) leading edge panels was developed by JENTEK Sensors and was subsequently transitioned by NASA as an operational pre and post flight in-situ inspection at the Kennedy Space Center. A manual scanner, which conformed'automatically to the curvature of the RCC panels was developed and used as a secondary technique if a defect was found during an infrared thermography screening, During a recent proof of concept study on composite overwrapped pressure vessels (COPV's), three different MWM sensors were tested at three orientations to demonstrate the ability of the technology to measure stresses at various fiber orientations and depths. These results showed excellent correlation with actual surface strain gage measurements. Recent advancements of this technology have been made applying MWM sensor technology for scanning COPVs for mechanical damage. This presentation will outline the recent advance~ in the MWM.technology and the development of MWM techniques for NDE and SHM of carbon wra~ped composite overwrapped pressure vessels (COPVs) including the measurement of internal stresses via a surface mounted sensor array. In addition, this paper will outline recent efforts to produce sensors capable of making real-time measurements at temperatures up to 850 C, and discuss previous results demonstrating capability to monitor carbon fiber temperature changes within a composite material.

Russell, Richard↗
NASA NTRS1998

X-33 Telemetry Best Source Selection, Processing, Display, and Simulation Model Comparison

The X-33 program requires the use of multiple telemetry ground stations to cover the launch, ascent, transition, descent, and approach phases for the flights from Edwards AFB to landings at Dugway Proving Grounds, UT and Malmstrom AFB, MT. This paper will discuss the X-33 telemetry requirements and design, including information on fixed and mobile telemetry systems, best source selection, and support for Range Safety Officers. A best source selection system will be utilized to automatically determine the best source based on the frame synchronization status of the incoming telemetry streams. These systems will be used to select the best source at the landing sites and at NASA Dryden Flight Research Center to determine the overall best source between the launch site, intermediate sites, and landing site sources. The best source at the landing sites will be decommutated to display critical flight safety parameters for the Range Safety Officers. The overall best source will be sent to the Lockheed Martin's Operational Control Center at Edwards AFB for performance monitoring by X-33 program personnel and for monitoring of critical flight safety parameters by the primary Range Safety Officer. The real-time telemetry data (received signal strength, etc.) from each of the primary ground stations will also be compared during each nu'ssion with simulation data generated using the Dynamic Ground Station Analysis software program. An overall assessment of the accuracy of the model will occur after each mission. Acknowledgment: The work described in this paper was NASA supported through cooperative agreement NCC8-115 with Lockheed Martin Skunk Works.

Burkes, Darryl A.↗