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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 NTRS1987

Automating the parallel processing of fluid and structural dynamics calculations

The NASA Lewis Research Center is actively involved in the development of expert system technology to assist users in applying parallel processing to computational fluid and structural dynamic analysis. The goal of this effort is to eliminate the necessity for the physical scientist to become a computer scientist in order to effectively use the computer as a research tool. Programming and operating software utilities have previously been developed to solve systems of ordinary nonlinear differential equations on parallel scalar processors. Current efforts are aimed at extending these capabilties to systems of partial differential equations, that describe the complex behavior of fluids and structures within aerospace propulsion systems. This paper presents some important considerations in the redesign, in particular, the need for algorithms and software utilities that can automatically identify data flow patterns in the application program and partition and allocate calculations to the parallel processors. A library-oriented multiprocessing concept for integrating the hardware and software functions is described.

Arpasi, Dale J.↗
NASA NTRS2015

TTEthernet for Integrated Spacecraft Networks

Aerospace projects have traditionally employed federated avionics architectures, in which each computer system is designed to perform one specific function (e.g. navigation). There are obvious downsides to this approach, including excessive weight (from so much computing hardware), and inefficient processor utilization (since modern processors are capable of performing multiple tasks). There has therefore been a push for integrated modular avionics (IMA), in which common computing platforms can be leveraged for different purposes. This consolidation of multiple vehicle functions to shared computing platforms can significantly reduce spacecraft cost, weight, and design complexity. However, the application of IMA principles introduces significant challenges, as the data network must accommodate traffic of mixed criticality and performance levels - potentially all related to the same shared computer hardware. Because individual network technologies are rarely so competent, the development of truly integrated network architectures often proves unreasonable. Several different types of networks are utilized - each suited to support a specific vehicle function. Critical functions are typically driven by precise timing loops, requiring networks with strict guarantees regarding message latency (i.e. determinism) and fault-tolerance. Alternatively, non-critical systems generally employ data networks prioritizing flexibility and high performance over reliable operation. Switched Ethernet has seen widespread success filling this role in terrestrial applications. Its high speed, flexibility, and the availability of inexpensive commercial off-the-shelf (COTS) components make it desirable for inclusion in spacecraft platforms. Basic Ethernet configurations have been incorporated into several preexisting aerospace projects, including both the Space Shuttle and International Space Station (ISS). However, classical switched Ethernet cannot provide the high level of network determinism required by real-time spacecraft applications. Even with modern advancements, the uncoordinated (i.e. event-driven) nature of Ethernet communication unavoidably leads to message contention within network switches. The arbitration process used to resolve such conflicts introduces variation in the time it takes for messages to be forwarded. TTEthernet1 introduces decentralized clock synchronization to switched Ethernet, enabling message transmission according to a time-triggered (TT) paradigm. A network planning tool is used to allocate each device a finite amount of time in which it may transmit a frame. Each time slot is repeated sequentially to form a periodic communication schedule that is then loaded onto each TTEthernet device (e.g. switches and end systems). Each network participant references the synchronized time in order to dispatch messages at predetermined instances. This schedule guarantees that no contention exists between time-triggered Ethernet frames in the network switches, therefore eliminating the need for arbitration (and the timing variation it causes). Besides time-triggered messaging, TTEthernet networks may provide two additional traffic classes to support communication of different criticality levels. In the rate-constrained (RC) traffic class, the frame payload size and rate of transmission along each communication channel are limited to predetermined maximums. The network switches can therefore be configured to accommodate the known worst-case traffic pattern, and buffer overflows can be eliminated. The best-effort (BE) traffic class behaves akin to classical Ethernet. No guarantees are provided regarding transmission latency or successful message delivery. TTEthernet coordinates transmission of all three traffic classes over the same physical connections, therefore accommodating the full spectrum of traffic criticality levels required in IMA architectures. Common computing platforms (e.g. LRUs) can share networking resources in such a way that failures in non-critical systems (using BE or RC communication modes) cannot impact flight-critical functions (using TT communication). Furthermore, TTEthernet hardware (e.g. switches, cabling) can be shared by both TTEthernet and classical Ethernet traffic.

Loveless, Andrew↗
NASA NTRS1994

Simplifying operations with an uplink/downlink integration toolkit

The Operations Engineering Lab (OEL) at JPL has developed a simple, generic toolkit to integrate the uplink/downlink processes, (often called closing the loop), in JPL's Multimission Ground Data System. This toolkit provides capabilities for integrating telemetry verification points with predicted spacecraft commands and ground events in the Mission Sequence Of Events (SOE) document. In the JPL ground data system, the uplink processing functions and the downlink processing functions are separate subsystems that are not well integrated because of the nature of planetary missions with large one-way light times for spacecraft-to-ground communication. Our new closed-loop monitoring tool allows an analyst or mission controller to view and save uplink commands and ground events with their corresponding downlinked telemetry values regardless of the delay in downlink telemetry and without requiring real-time intervention by the user. An SOE document is a time-ordered list of all the planned ground and spacecraft events, including all commands, sequence loads, ground events, significant mission activities, spacecraft status, and resource allocations. The SOE document is generated by expansion and integration of spacecraft sequence files, ground station allocations, navigation files, and other ground event files. This SOE generation process has been automated within the OEL and includes a graphical, object-oriented SOE editor and real-time viewing tool running under X/Motif. The SOE toolkit was used as the framework for the integrated implementation. The SOE is used by flight engineers to coordinate their operations tasks, serving as a predict data set in ground operations and mission control. The closed-loop SOE toolkit allows simple, automated integration of predicted uplink events with correlated telemetry points in a single SOE document for on-screen viewing and archiving. It automatically interfaces with existing real-time or non real-time sources of information, to display actual values from the telemetry data stream. This toolkit was designed to greatly simplify the user's ability to access and view telemetry data, and also provide a means to view this data in the context of the commands and ground events that are used to interpret it. A closed-loop system can prove especially useful in small missions with limited resources requiring automated monitoring tools. This paper will discuss the toolkit implementation, including design trade-offs and future plans for enhancing the automated capabilities.

Murphy, Susan C.↗
NASA NTRSDate not supplied

MBSE Applications for the MSR SRC Mars Ascent Vehicle

The objective of the NASA Mars Sample Return (MSR) Campaign is to collect samples from the surface of Mars and return them to Earth for scientific research. The Mars Ascent Vehicle (MAV) will be integrated into a larger Mars Sample Retrieval Lander (SRL) for transit to and storage on Mars. After all Martian samples have been collected and loaded into the MAV payload assembly, MAV will deliver the samples from the Martian surface to Mars orbit. A separate spacecraft, the Earth Return Orbiter (ERO) will retrieve the samples from Mars orbit and return them to Earth. To address common systems engineering challenges associated with using traditional systems engineering practices on complex projects, the MAV systems engineering team has explored implementation of Model-Based Systems Engineering (MBSE) tools and languages. This paper describes the current state of implementation and development of the MAV MBSE model with the Systems Modeling Language (SysML) within the scope of the MAV Systems Requirement Cycle (SRC) systems engineering workflow. The MAV MBSE model has been developed within Magic Draw – a SysML editor commonly used to implement MBSE. The MAV MBSE model has been used to develop mission phase functional flow diagrams for the Concept of Operations, decompose mission to vehicle subsystem functions, develop a functional decomposition, derive functional requirements, trace requirements up to customer-imposed requirements, trace requirements within MAV requirement space, identify requirements trace gaps, define and map the physical design space architecture, allocate requirements to subsystems, develop validation items, define assembly, integration, and test (AI&T) operations, and trace these items across driving goals to develop an integrated digital thread of systems engineering information used to drive design specifications, decision making, and ultimately design verification and validation. Findings and results associated with implementing MBSE in these ways, alongside traditional methods will be discussed.

MBSE↗
NASA NTRSDate not supplied

MBSE Applications for the MSR SRC Mars Ascent Vehicle

The objective of the NASA Mars Sample Return (MSR) Campaign is to collect samples from the surface of Mars and return them to Earth for scientific research. The Mars Ascent Vehicle (MAV) will be integrated into a larger Mars Sample Retrieval Lander (SRL) for transit to and storage on Mars. After all Martian samples have been collected and loaded into the MAV payload assembly, MAV will deliver the samples from the Martian surface to Mars orbit. A separate spacecraft, the Earth Return Orbiter (ERO) will retrieve the samples from Mars orbit and return them to Earth. To address common systems engineering challenges associated with using traditional systems engineering practices on complex projects, the MAV systems engineering team has explored implementation of Model-Based Systems Engineering (MBSE) tools and languages. This paper describes the current state of implementation and development of the MAV MBSE model with the Systems Modeling Language (SysML) within the scope of the MAV Systems Requirement Cycle (SRC) systems engineering workflow. The MAV MBSE model has been developed within Magic Draw – a SysML editor commonly used to implement MBSE. The MAV MBSE model has been used to develop mission phase functional flow diagrams for the Concept of Operations, decompose mission to vehicle subsystem functions, develop a functional decomposition, derive functional requirements, trace requirements up to customer-imposed requirements, trace requirements within MAV requirement space, identify requirements trace gaps, define and map the physical design space architecture, allocate requirements to subsystems, develop validation items, define assembly, integration, and test (AI&T) operations, and trace these items across driving goals to develop an integrated digital thread of systems engineering information used to drive design specifications, decision making, and ultimately design verification and validation. Findings and results associated with implementing MBSE in these ways, alongside traditional methods will be discussed.

MBSE↗
NASA NTRS2002

Autocommander: A Supervisory Controller for Integrated Guidance and Control for the 2nd Generation Reusable Launch Vehicle

This paper presents a hierarchical architecture for integrated guidance and control that achieves risk and cost reduction for NASA's 2d generation reusable launch vehicle (RLV). Guidance, attitude control, and control allocation subsystems that heretofore operated independently will now work cooperatively under the coordination of a top-level autocommander. In addition to delivering improved performance from a flight mechanics perspective, the autocommander is intended to provide an autonomous supervisory control capability for traditional mission management under nominal conditions, G&C reconfiguration in response to effector saturation, and abort mode decision-making upon vehicle malfunction. This high-level functionality is to be implemented through the development of a relational database that is populated with the broad range of vehicle and mission specific data and translated into a discrete event system model for analysis, simulation, and onboard implementation. A Stateflow Autocoder software tool that translates the database into the Stateflow component of a Matlab/Simulink simulation is also presented.

Fisher, J. E.↗
NASA NTRS2013

Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing

A chance-constrained dynamic programming algorithm was developed that is capable of making optimal sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard dynamic programming (DP) provides a general framework for optimal sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.

Ono, Masahiro↗
NASA NTRS2007

NASA Tech Briefs, July 2007

Topics covered include: Miniature Intelligent Sensor Module; "Smart" Sensor Module; Portable Apparatus for Electrochemical Sensing of Ethylene; Increasing Linear Dynamic Range of a CMOS Image Sensor; Flight Qualified Micro Sun Sensor; Norbornene-Based Polymer Electrolytes for Lithium Cells; Making Single-Source Precursors of Ternary Semiconductors; Water-Free Proton-Conducting Membranes for Fuel Cells; Mo/Ti Diffusion Bonding for Making Thermoelectric Devices; Photodetectors on Coronagraph Mask for Pointing Control; High-Energy-Density, Low-Temperature Li/CFx Primary Cells; G4-FETs as Universal and Programmable Logic Gates; Fabrication of Buried Nanochannels From Nanowire Patterns; Diamond Smoothing Tools; Infrared Imaging System for Studying Brain Function; Rarefying Spectra of Whispering-Gallery-Mode Resonators; Large-Area Permanent-Magnet ECR Plasma Source; Slot-Antenna/Permanent-Magnet Device for Generating Plasma; Fiber-Optic Strain Gauge With High Resolution And Update Rate; Broadband Achromatic Telecentric Lens; Temperature-Corrected Model of Turbulence in Hot Jet Flows; Enhanced Elliptic Grid Generation; Automated Knowledge Discovery From Simulators; Electro-Optical Modulator Bias Control Using Bipolar Pulses; Generative Representations for Automated Design of Robots; Mars-Approach Navigation Using In Situ Orbiters; Efficient Optimization of Low-Thrust Spacecraft Trajectories; Cylindrical Asymmetrical Capacitors for Use in Outer Space; Protecting Against Faults in JPL Spacecraft; Algorithm Optimally Allocates Actuation of a Spacecraft; and Radar Interferometer for Topographic Mapping of Glaciers and Ice Sheets.

Source record↗
NASA NTRS2016

Addressing Uniqueness and Unison of Reliability and Safety for a Better Integration

Over time, it has been observed that Safety and Reliability have not been clearly differentiated, which leads to confusion, inefficiency, and, sometimes, counter-productive practices in executing each of these two disciplines. It is imperative to address this situation to help Reliability and Safety disciplines improve their effectiveness and efficiency. The paper poses an important question to address, "Safety and Reliability - Are they unique or unisonous?" To answer the question, the paper reviewed several most commonly used analyses from each of the disciplines, namely, FMEA, reliability allocation and prediction, reliability design involvement, system safety hazard analysis, Fault Tree Analysis, and Probabilistic Risk Assessment. The paper pointed out uniqueness and unison of Safety and Reliability in their respective roles, requirements, approaches, and tools, and presented some suggestions for enhancing and improving the individual disciplines, as well as promoting the integration of the two. The paper concludes that Safety and Reliability are unique, but compensating each other in many aspects, and need to be integrated. Particularly, the individual roles of Safety and Reliability need to be differentiated, that is, Safety is to ensure and assure the product meets safety requirements, goals, or desires, and Reliability is to ensure and assure maximum achievability of intended design functions. With the integration of Safety and Reliability, personnel can be shared, tools and analyses have to be integrated, and skill sets can be possessed by the same person with the purpose of providing the best value to a product development.

Huang, Zhaofeng↗
NASA NTRS2013

Analysis of Traffic Conflicts in a Mixed-Airspace Evaluation of Airborne Separation Assurance

A pair of human-in-the-loop simulation evaluations of a distributed air/ground separation assurance system have been conducted to investigate the function allocation between humans and automation systems as well as ground-based and airborne agents in the Next Generation Air Transportation System and beyond. This paper focuses on an analysis of certain critical conflicts observed between self-separating aircraft and ground-managed traffic in the same airspace. The principal cause of each conflict is identified and potential mitigations are discussed, such as: the sharing of trajectory intent information between the ground and the air; more cautious trajectory planning by the self-separating aircraft; and more equitable rules-of-the-road between the self-separating aircraft and ground-managed aircraft. This analysis will inform the ongoing design of an airborne separation assurance automation tool.

Lewis, Timothy A.↗
NASA NTRS2009

The Integrated Medical Model - Optimizing In-flight Space Medical Systems to Reduce Crew Health Risk and Mission Impacts

The Integrated Medical Model (IMM) is a decision support tool used by medical system planners and designers as they prepare for exploration planning activities of the Constellation program (CxP). IMM provides an evidence-based approach to help optimize the allocation of in-flight medical resources for a specified level of risk within spacecraft operational constraints. Eighty medical conditions and associated resources are represented in IMM. Nine conditions are due to Space Adaptation Syndrome. The IMM helps answer fundamental medical mission planning questions such as What medical conditions can be expected? What type and quantity of medical resources are most likely to be used?", and "What is the probability of crew death or evacuation due to medical events?" For a specified mission and crew profile, the IMM effectively characterizes the sequence of events that could potentially occur should a medical condition happen. The mathematical relationships among mission and crew attributes, medical conditions and incidence data, in-flight medical resources, potential clinical and crew health end states are established to generate end state probabilities. A Monte Carlo computational method is used to determine the probable outcomes and requires up to 25,000 mission trials to reach convergence. For each mission trial, the pharmaceuticals and supplies required to diagnose and treat prevalent medical conditions are tracked and decremented. The uncertainty of patient response to treatment is bounded via a best-case, worst-case, untreated case algorithm. A Crew Health Index (CHI) metric, developed to account for functional impairment due to a medical condition, provides a quantified measure of risk and enables risk comparisons across mission scenarios. The use of historical in-flight medical data, terrestrial surrogate data as appropriate, and space medicine subject matter expertise has enabled the development of a probabilistic, stochastic decision support tool capable of optimizing in-flight medical systems based on crew and mission parameters. This presentation will illustrate how to apply quantitative risk assessment methods to optimize the mass and volume of space-based medical systems for a space flight mission given the level of crew health and mission risk.

Kerstman, Eric↗
NASA NTRS2007

Collaborative Resource Allocation

Collaborative Resource Allocation Networking Environment (CRANE) Version 0.5 is a prototype created to prove the newest concept of using a distributed environment to schedule Deep Space Network (DSN) antenna times in a collaborative fashion. This program is for all space-flight and terrestrial science project users and DSN schedulers to perform scheduling activities and conflict resolution, both synchronously and asynchronously. Project schedulers can, for the first time, participate directly in scheduling their tracking times into the official DSN schedule, and negotiate directly with other projects in an integrated scheduling system. A master schedule covers long-range, mid-range, near-real-time, and real-time scheduling time frames all in one, rather than the current method of separate functions that are supported by different processes and tools. CRANE also provides private workspaces (both dynamic and static), data sharing, scenario management, user control, rapid messaging (based on Java Message Service), data/time synchronization, workflow management, notification (including emails), conflict checking, and a linkage to a schedule generation engine. The data structure with corresponding database design combines object trees with multiple associated mortal instances and relational database to provide unprecedented traceability and simplify the existing DSN XML schedule representation. These technologies are used to provide traceability, schedule negotiation, conflict resolution, and load forecasting from real-time operations to long-range loading analysis up to 20 years in the future. CRANE includes a database, a stored procedure layer, an agent-based middle tier, a Web service wrapper, a Windows Integrated Analysis Environment (IAE), a Java application, and a Web page interface.

Wang, Yeou-Fang↗
NASA NTRS2009

Influence Diagram Use With Respect to Technology Planning and Investment

Influence diagrams are relatively simple, but powerful, tools for assessing the impact of choices or resource allocations on goals or requirements. They are very general and can be used on a wide range of problems. They can be used for any problem that has defined goals, a set of factors that influence the goals or the other factors, and a set of inputs. Influence diagrams show the relationship among a set of results and the attributes that influence them and the inputs that influence the attributes. If the results are goals or requirements of a program, then the influence diagram can be used to examine how the requirements are affected by changes to technology investment. This paper uses an example to show how to construct and interpret influence diagrams, how to assign weights to the inputs and attributes, how to assign weights to the transfer functions (influences), and how to calculate the resulting influences of the inputs on the results. A study is also presented as an example of how using influence diagrams can help in technology planning and investment. The Space Propulsion Synergy Team (SPST) used this technique to examine the impact of R&D spending on the Life Cycle Cost (LCC) of a space transportation system. The question addressed was the effect on the recurring and the non-recurring portions of LCC of the proportion of R&D resources spent to impact technology objectives versus the proportion spent to impact operational dependability objectives. The goals, attributes, and the inputs were established. All of the linkages (influences) were determined. The weighting of each of the attributes and each of the linkages was determined. Finally the inputs were varied and the impacts on the LCC determined and are presented. The paper discusses how each of these was accomplished both for credibility and as an example for future studies using influence diagrams for technology planning and investment planning.

Levack, Daniel J. H.↗
NASA NTRS1990

Resource Allocation Planning Helper (RALPH): Lessons learned

The current task of Resource Allocation Process includes the planning and apportionment of JPL's Ground Data System composed of the Deep Space Network and Mission Control and Computing Center facilities. The addition of the data driven, rule based planning system, RALPH, has expanded the planning horizon from 8 weeks to 10 years and has resulted in large labor savings. Use of the system has also resulted in important improvements in science return through enhanced resource utilization. In addition, RALPH has been instrumental in supporting rapid turn around for an increased volume of special what if studies. The status of RALPH is briefly reviewed and important lessons learned from the creation of an highly functional design team are focused on through an evolutionary design and implementation period in which an AI shell was selected, prototyped, and ultimately abandoned, and through the fundamental changes to the very process that spawned the tool kit. Principal topics include proper integration of software tools within the planning environment, transition from prototype to delivered to delivered software, changes in the planning methodology as a result of evolving software capabilities and creation of the ability to develop and process generic requirements to allow planning flexibility.

Durham, Ralph↗
NASA NTRSDate not supplied

Medical System Foundation Overview for Long-Duration Lunar Orbit and Surface Operations Missions

The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has developed a Medical System Foundation for Level of Care IV, as defined by NASA’s space flight human-system standards, for long-duration lunar orbit and surface operation missions by employing a systems engineering approach using model-based systems engineering tools. This Foundation model includes a concept of operations; functional decomposition; clinical content (medical conditions, capabilities, and resources); associated functional, interface and non-functional technical requirements; and traces to the current versions of NASA standards documents and parent-level (Program- and Vehicle habitat system level) requirements. Collectively, these components constitute a foundation that serves as a starting point for a medical system that meets the Level of Care IV requirement. The Foundation was developed by a multidisciplinary team consisting of systems engineers, scientists, and clinicians across NASA, and information is presented in an easily accessible format that is understandable across disciplines. Stakeholders can use the Foundation to analyze the traces between medical capabilities, medical conditions, medical resources, and requirements and to identify medical system interfaces with other vehicle systems/subsystems. It can also be used as a basis for performing trades on risks vs. medical system mass and volume allocation. This discussion will focus on the processes through which the Medical System Foundation was developed, how the Foundation builds a bridge between the medical and engineering domains and facilitates communication between these communities, and how these processes can be applied more broadly to a crew health and performance system and other system domains. The presentation also discusses Foundation modifications based on the recently updated versions of the NASA 3001 Standards.

S. Lumpkins↗
NASA NTRS2012

Design and Evaluation of Nextgen Aircraft Separation Assurance Concepts

To support the development and evaluation of future function allocation concepts for separation assurance systems for the Next Generation Air Transportation System, this paper presents the design and human-in-the-loop evaluation of three feasible function allocation concepts that allocate primary aircraft separation assurance responsibilities and workload to: 1) pilots; 2) air traffic controllers (ATC); and 3) automation. The design of these concepts also included rules of the road, separation assurance burdens for aircraft of different equipage levels, and utilization of advanced weather displays paired with advanced conflict detection and resolution automation. Results of the human-in-the-loop simulation show that: a) all the concepts are robust with respect to weather perturbation; b) concept 1 (pilots) had highest throughput, closest to assigned spacing, and fewest violations of speed and altitude restrictions; c) the energy of the aircraft during the descent phase was better managed in concepts 1 and 2 (pilots and ATC) than in concept 3 (automation), in which the situation awareness of pilots and controllers was lowest, and workload of pilots was highest. The paper also discusses further development of these concepts and their augmentation and integration with future air traffic management tools and systems that are being considered for NextGen.

Johnson, Walter↗
NASA NTRS2022

PAAV Concept Document

The Pathfinding for Airspace with Autonomous Vehicles (PAAV) Concept Document, version 1.0, lays out the key challenges and potential solutions for the use of uncrewed aircraft (UA) technology for future regional air cargo operations. The challenges and solutions described in this document were informed by communications with the UA industry community (e.g., RTCA, the Federal Aviation Administration, and regional air cargo business operators), as well as the PAAV team’s research activities during the last two years including four tabletop exercises, a human-in-the-loop simulation study, a numerical simulation study, a functional allocation study, and flight data analysis (Appendix A). This document first describes the expected operational context of PAAV (Section 2), such as the flight mission, baseline UAS components, nominal operations, m:N operations (i.e., "m" remote pilots per "N" aircraft), and off-nominal operations. This context sets the scope for the PAAV concept development work. PAAV concept development assumes that UA operations will be increasingly autonomous. Thus, near- and far-term assumptions are defined (Section 3). PAAV identified seven key challenges for UA operations (Section 4): - Flight route planning - Separation and flow management - Traffic pattern integration - Contingency management - Taxi, takeoff, and landing - m:N operations - Communications operations The following 13 potential solutions to these challenges are then described (Section 5): - Scalable communications architecture - Data link - Designated UAS corridors - Crew planning for m:N operations - Flight route optimization - Traffic load-level control - Trajectory solutions with data link - Automated hazard avoidance for m:N operations - Traffic pattern integration (TPI) tool - Standard lost command and control (C2) link (LC2L) procedures - Automated hazard avoidance under LC2L - Auto-taxi, auto-takeoff, and auto-land - Ground control station (GCS) user interface for m:N operations The document attempts to link each of these solutions to one or more of the challenge areas. Novel solutions involving numerous automation technologies are needed to mitigate traffic and airspace management challenges, especially for realizing m:N operations and ensuring safety under LC2L conditions. The purpose of this document is to help understand alternatives and tradeoffs among potential solutions and provide a foundation for a cohesive PAAV concept that will be described and refined in subsequent concept versions.

Unmanned aircraft, uncrewed aircraft, regional air↗
NASA NTRS2014

An Overview of Current Capabilities and Research Activities in the Airspace Operations Laboratory at NASA Ames Research Center

The Airspace Operations Laboratory at NASA Ames conducts research to provide a better understanding of roles, responsibilities, and requirements for human operators and automation in future air traffic management (ATM) systems. The research encompasses developing, evaluating, and integrating operational concepts and technologies for near-, mid-, and far-term air traffic operations. Current research threads include efficient arrival operations, function allocation in separation assurance and efficient airspace and trajectory management. The AOL has developed powerful air traffic simulation capabilities, most notably the Multi Aircraft Control System (MACS) that is used for many air traffic control simulations at NASA and its partners in government, academia and industry. Several additional NASA technologies have been integrated with the AOL's primary simulation capabilities where appropriate. Using this environment, large and small-scale system-level evaluations can be conducted to help make near-term improvements and transition NASA technologies to the FAA, such as the technologies developed under NASA's Air Traffic Management Demonstration-1 (ATD-1). The AOL's rapid prototyping and flexible simulation capabilities have proven a highly effective environment to progress the initiation of trajectory-based operations and support the mid-term implementation of NextGen. Fundamental questions about accuracy requirements have been investigated as well as realworld problems on how to improve operations in some of the most complex airspaces in the US. This includes using advanced trajectory-based operations and prototype tools for coordinating arrivals to converging runways at Newark airport and coordinating departures and arrivals in the San Francisco and the New York metro areas. Looking beyond NextGen, the AOL has started exploring hybrid human/automation control strategies as well as highly autonomous operations in the air traffic control domain. Initial results indicate improved capacity, low operator workload, good situation awareness and acceptability for controllers teaming with autonomous air traffic systems. While much research and development needs to be conducted to make such concepts a reality, these approaches have the potential to truly transform the airspace system towards increased mobility, safe and efficient growth in global operations and enabling many of the new vehicles and operations that are expected over the next decades. This paper describes how the AOL currently contributes to the ongoing air transportation transformation.

simulation↗