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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Embedded CLIPS for SDI BM/C3 simulation and analysis

Nichols Research Corporation is developing the BM/C3 Requirements Analysis Tool (BRAT) for the U.S. Army Strategic Defense Command. BRAT uses embedded CLIPS/Ada to model the decision making processes used by the human commander of a defense system. Embedding CLlPS/Ada in BRAT allows the user to explore the role of the human in Command and Control (C2) and the use of expert systems for automated C2. BRAT models assert facts about the current state of the system, the simulated scenario, and threat information into CLIPS/Ada. A user-defined rule set describes the decision criteria for the commander. We have extended CLIPS/Ada with user-defined functions that allow the firing of a rule to invoke a system action such as weapons release or a change in strategy. The use of embedded CLIPS/Ada will provide a powerful modeling tool for our customer at minimal cost.

Gossage, Brett↗
NASA NTRS2006

Planning to Explore: Using a Coordinated Multisource Infrastructure to Overcome Present and Future Space Flight Planning Challenges

Few human endeavors present as much of a planning and scheduling challenge as space flight, particularly manned space flight. Just on the operational side of it, efforts of thousands of people across hundreds of organizations need to be coordinated. Numerous tasks of varying complexity and nature, from scientific to construction, need to be accomplished within limited mission time frames. Resources need to be carefully managed and contingencies worked out, often on a very short notice. From the beginning of the NASA space program, planning has been done by large teams of domain experts working months, sometimes years, to put together a single mission. This approach, while proven very reliable up to now, is becoming increasingly harder to sustain. Elevated levels of NASA space activities, from deployment of the new Crew Exploration Vehicle (CEV) and completion of the International Space Station (ISS), to the planned lunar missions and permanent lunar bases, will put an even greater strain on this largely manual process. While several attempts to automate it have been made in the past, none have fully succeeded. In this paper we describe the current NASA planning methods, outline their advantages and disadvantages, discuss the planning challenges of upcoming missions and propose a distributed planning/scheduling framework (CMMD) aimed at unifying and optimizing the planning effort. CMMD will not attempt to make the process completely automated, but rather serve in a decision support capacity for human managers and planners. It will help manage information gathering, creation of partial and consolidated schedules, inter-team negotiations, contingencies investigation, and rapid re-planning when the situation demands it. The fist area of CMMD application will be planning for Extravehicular Activities (EVA) and associated logistics. Other potential applications, not only in the space flight domain, and future research efforts will be discussed as well.

Balaban, Edward↗
NASA NTRS2017

Real-Time Radar-Based Tracking and State Estimation of Multiple Non-Conformant Aircraft

In this study, a novel solution for automated tracking of multiple unknown aircraft is proposed. Many current methods use transponders to self-report state information and augment track identification. While conformant aircraft typically report transponder information to alert surrounding aircraft of its state, vehicles may exist in the airspace that are non-compliant and need to be accurately tracked using alternative methods. In this study, a multi-agent tracking solution is presented that solely utilizes primary surveillance radar data to estimate aircraft state information. Main research challenges include state estimation, track management, data association, and establishing persistent track validity. In an effort to realize these challenges, techniques such as Maximum a Posteriori estimation, Kalman filtering, degree of membership data association, and Nearest Neighbor Spanning Tree clustering are implemented for this application.

RADAR tracking↗
NASA NTRS2013

Evaluation of the Terminal Area Precision Scheduling and Spacing System for Performance-Based Navigation Arrivals

The growth of global demand for air transportation has put increasing strain on the nation's air traffic management system. To relieve this strain, the International Civil Aviation Organization has urged all nations to adopt Performance-Based Navigation (PBN), which can help to reduce air traffic congestion, decrease aviation fuel consumption, and protect the environment. NASA has developed a Terminal Area Precision Scheduling and Spacing (TAPSS) system that can support increased use of PBN during periods of high traffic, while supporting fuel-efficient, continuous descent approaches. In the original development of this system, arrival aircraft are assigned fuel-efficient Area Navigation (RNAV) Standard Terminal Arrival Routes before their initial descent from cruise, with routing defined to a specific runway. The system also determines precise schedules for these aircraft that facilitate continuous descent through the assigned routes. To meet these schedules, controllers are given a set of advisory tools to precisely control aircraft. The TAPSS system has been evaluated in a series of human-in-the-loop (HITL) air traffic simulations during 2010 and 2011. Results indicated increased airport arrival throughput up to 10 over current operations, and maintained fuel-efficient aircraft decent profiles from the initial descent to landing with reduced controller workload. This paper focuses on results from a joint NASA and FAA HITL simulation conducted in 2012. Due to the FAA rollout of the advance terminal area PBN procedures at mid-sized airports first, the TAPSS system was modified to manage arrival aircraft as they entered Terminal Radar Approach Control (TRACON). Dallas-Love Field airport (DAL) was selected by the FAA as a representative mid-sized airport within a constrained TRACON airspace due to the close proximity of a major airport, in this case Dallas-Ft Worth International Airport, one of the busiest in the world. To address this constraint, RNAV routes and Required Navigation Performance with the particular capability known as Radius-to-Fix (RNP-RF) approaches to a short final were used. The purpose of this simulation was to get feedback on how current operations could benefit with the TAPSS system and also to evaluate the efficacy of the advisory tools to support the broader use of PBN in the US National Airspace System. For this NASA-FAA joint experiment, an Air Traffic Control laboratory at NASA Ames was arranged to simulate arrivals into DAL in Instrument Meteorological Conditions utilizing parallel dependent approaches, with two feeder positions that handed off traffic to one final position. Four FAA controllers participated, alternately covering these three positions. All participants were Full-Performance Level terminal controllers and members of the National Air Traffic Controllers Association. During the simulation, PBN arrival operations were compared and contrasted in three conditions. They were the Baseline, where none of the TAPSS systems TRACON controller decision support advisories were provided, the Limited Advisories, reflecting the existing but dormant capabilities of the current terminal automation equipment with providing a subset of the TAPSS systems advisories; numerical delay, landing sequence, and runway assignment information, and the Full Advisories, with providing the following in addition to the ones in the Limited condition; trajectory slot markers, timelines of estimated times of arrivals and sched

Performance based navigation↗
NASA NTRS2017

Biosensor Integration Development ExMC/Canadian Space Agency Collaboration

In support of the NASA Human Research Program Exploration Medical Capability (ExMC) Element, NASA Ames Research Center (ARC) established a collaborative effort with the Canadian Space Agency (CSA). The collaboration focuses on leveraging CSA capability in the areas of biosensors and decision support that will augment future development of such components for Exploration Missions. The CSA advancement of biosensors enables NASA to focus on the integration and data management associated with these types of components through the system currently under development by the Medical Data Architecture (MDA) project. This approach has enabled the establishment of a successful collaborative working relationship between ExMC and CSA.Applying lessons learned from the fiscal year 2016 (FY16) Human Exploration Research Analog (HERA) campaign, CSA and NASA ARC developed a solution to provide real-time feedback to researchers who monitor the collection of vital signs data from a wearable Astroskin garment. The advances in the interfaces included the development of an iPad application (by CSA) to wirelessly forward the vital signs data to the MDA system, which collected the vital signs data through a receiver developed by NASA ARC. The development of these interfaces aims to provide communications between the Astroskin and the MDA system such that data may be seamlessly collected, stored and retrieved by the MDA. The first steps towards this goal were demonstrated in FY16. In FY17, ExMC will complete the first in a series of test beds that establishes a system to automate collection and management of vital sign data from the Astroskin, and other sources of data, to provide information for a crewmember to make medical decisions. In addition, the MDA Test Bed 1 will enable CSA to evaluate and optimize biosensor advancement and facilitate decision support algorithm development.

Vital signs↗
NASA NTRS2017

Biosensor Integration Development ExMC/Canadian Space Agency Collaboration

In support of the NASA Human Research Program Exploration Medical Capability (ExMC) Element, NASA Ames Research Center (ARC) established a collaborative effort with the Canadian Space Agency (CSA). The collaboration focuses on leveraging CSA capability in the areas of biosensors and decision support that will augment future development of such components for Exploration Missions. The CSA advancement of biosensors enables NASA to focus on the integration and data management associated with these types of components through the system currently under development by the Medical Data Architecture (MDA) project. This approach has enabled the establishment of a successful collaborative working relationship between ExMC and CSA.Applying lessons learned from the fiscal year 2016 (FY16) Human Exploration Research Analog (HERA) campaign, CSA and NASA ARC developed a solution to provide real-time feedback to researchers who monitor the collection of vital signs data from a wearable Astroskin garment. The advances in the interfaces included the development of an iPad application (by CSA) to wirelessly forward the vital signs data to the MDA system, which collected the vital signs data through a receiver developed by NASA ARC. The development of these interfaces aims to provide communications between the Astroskin and the MDA system such that data may be seamlessly collected, stored and retrieved by the MDA. The first steps towards this goal were demonstrated in FY16. In FY17, ExMC will complete the first in a series of test beds that establishes a system to automate collection and management of vital sign data from the Astroskin, and other sources of data, to provide information for a crewmember to make medical decisions. In addition, the MDA Test Bed 1 will enable CSA to evaluate and optimize biosensor advancement and facilitate decision support algorithm development.

Astroskin↗
NASA NTRSDate not supplied

The Genesis Non-flight Implant Sample Archive

Introduction: For the past 20 years the Genesis science community has been analyzing solar wind captured in sample collectors now curated at Johnson Space Center (JSC). Non-flown flight like collector materials (non-flight) considered reference material was always allocated by the JSC Genesis team for testing experimental procedures. However, to expedite Genesis science, distribution of non-flown reference materials were also provided by, D. S. Burnett (Genesis PI, Caltech) and A. J. G. Jurewicz (ASU) who were funded to aid all Genesis PIs by providing engineering test materials archived at Caltech pre-flight as well as ion implants into these materials [1]. Implanted materials (non-flight reference, flight-like semiconductor materials, and NIST SRM glass) received from the Caltech collection during a pilot project are being used to develop an accession procedure for the purpose of making these materials available to researchers in the future. These implant samples are important because they can be utilized as measurement standards [2]. This is a work in progress and this work reports progress in documentation and imaging. The pilot program received 63 implanted reference materials with known implanted ions. Genesis Non-Flight Database: The existing non-flight material database was modified to allow for the description of implant sessions and to allow correlation of the implant information to individual specimens. An implant session has three main components: a known ion, a known dose (ion/cm2), and a known energy (keV). Procedure: Laboratory Procedure. Upon receiving non-flight analytical standards (independently calibrated implants), or implant samples (nominally calibrated implants), they will be imaged in their current containers to capture any information written before being brought into the Genesis Sample Laboratory. Documentation is provided by the donor and used for correlating the data between the implant sessions and implant samples. This information is not verified by Genesis Curation. The microscope used to image samples in the laboratory has an automated stage with a stainless-steel plate to hold samples and a camera that utilizes the software Surveyor to take photomosaic images of the implant samples. The camera attached to the microscope is a QICAM High Performance IEEE 1394 FireWire Digital CCD Camera. This setup, shown in Fig. 1, allows for photomosaics of small-scale samples with a 10x objective or 25x objective. Examples of images taken with this microscope setup are shown in Fig.2 and Fig. 3. After imaging, samples get stored in a clean fluoroware container or polypropylene vial depending on sample size for long term storage. Database Procedure. The Genesis Non-Flight Database currently allows for the addition of implant sessions. The required fields for adding an implant session are the implant session ion, the implant session dose, and the implant session energy. There are also fields for the date and vendor of the sessions as well as a field for if the session was calibrated or not. Once an implant session has been inserted into the database, additional documentation from the session can be attached. The database will automatically assign an Implant Session Number. After inserting an implant session, the implanted samples can be inserted. The fields required for an implant sample are the material of the sample and the size of the sample. The Generic name for the implant sample with be automatically generated by the database once it has been inserted. Implant sample numbers begin with 3X to distinguish from flown Genesis sample numbers. There are also fields for processors to add the location (room, cabinet, tray) and container type (fluoroware, polypropylene vial). Once an implant session and an associated sample(s) have been inserted into the database the sample can be then tied to all associated implant sessions. An implant sample can be tied to multiple implant sessions. Future work: For curation, future work consists of creating an online catalogue for implant samples as well as updating the database with more samples as we receive them. For the scientific community these implant samples have many potential uses. For Genesis research, they are directly applicable for testing and, in some cases, as analytical standards. For non-Genesis research, implants (especially calibrated implants) could be used for calibrating other, unique planetary materials [1].

C D Calva↗
NASA NTRS2012

Physics Mining of Multi-Source Data Sets

Powerful new parallel data mining algorithms can produce diagnostic and prognostic numerical models and analyses from observational data. These techniques yield higher-resolution measures than ever before of environmental parameters by fusing synoptic imagery and time-series measurements. These techniques are general and relevant to observational data, including raster, vector, and scalar, and can be applied in all Earth- and environmental science domains. Because they can be highly automated and are parallel, they scale to large spatial domains and are well suited to change and gap detection. This makes it possible to analyze spatial and temporal gaps in information, and facilitates within-mission replanning to optimize the allocation of observational resources. The basis of the innovation is the extension of a recently developed set of algorithms packaged into MineTool to multi-variate time-series data. MineTool is unique in that it automates the various steps of the data mining process, thus making it amenable to autonomous analysis of large data sets. Unlike techniques such as Artificial Neural Nets, which yield a blackbox solution, MineTool's outcome is always an analytical model in parametric form that expresses the output in terms of the input variables. This has the advantage that the derived equation can then be used to gain insight into the physical relevance and relative importance of the parameters and coefficients in the model. This is referred to as physics-mining of data. The capabilities of MineTool are extended to include both supervised and unsupervised algorithms, handle multi-type data sets, and parallelize it.

Helly, John↗
NASA NTRS1991

Results of prototype software development for automation of shuttle proximity operations

The effort involves demonstration of expert system technology application to Shuttle rendezvous operations in a high-fidelity, real-time simulation environment. The JSC Systems Engineering Simulator (SES) served as the test bed for the demonstration. Rendezvous applications were focused on crew procedures and monitoring of sensor health and trajectory status. Proximity operations applications were focused on monitoring, crew advisory, and control of the approach trajectory. Guidance, Navigation, and Control areas of emphasis included the approach, transition and stationkeeping guidance, and laser docking sensor navigation. Operator interface displays for monitor and control functions were developed. A rule-based expert system was developed to manage the relative navigation system/sensors for nominal operations and simple failure contingencies. Testing resulted in the following findings; (1) the developed guidance is applicable for operations with LVLH stabilized targets; (2) closing rates less than 0.05 feet per second are difficult to maintain due to the Shuttle translational/rotational cross-coupling; (3) automated operations result in reduced propellant consumption and plume impingement effects on the target as compared to manual operations; and (4) braking gates are beneficial for trajectory management. A versatile guidance design was demonstrated. An accurate proximity operations sensor/navigation system to provide relative attitude information within 30 feet is required and redesign of the existing Shuttle digital autopilot should be considered to reduce the cross-coupling effects. This activity has demonstrated the feasibility of automated Shuttle proximity operations with the Space Station Freedom. Indications are that berthing operations as well as docking can be supported.

Hiers, Hal↗
NASA NTRS2003

Intelligent Machines in the 21st Century: Automating the Processes of Inference and Inquiry

The last century saw the application of Boolean algebra toward the construction of computing machines, which work by applying logical transformations to information contained in their memory. The development of information theory and the generalization of Boolean algebra to Bayesian inference have enabled these computing machines. in the last quarter of the twentieth century, to be endowed with the ability to learn by making inferences from data. This revolution is just beginning as new computational techniques continue to make difficult problems more accessible. However, modern intelligent machines work by inferring knowledge using only their pre-programmed prior knowledge and the data provided. They lack the ability to ask questions, or request data that would aid their inferences. Recent advances in understanding the foundations of probability theory have revealed implications for areas other than logic. Of relevance to intelligent machines, we identified the algebra of questions as the free distributive algebra, which now allows us to work with questions in a way analogous to that which Boolean algebra enables us to work with logical statements. In this paper we describe this logic of inference and inquiry using the mathematics of partially ordered sets and the scaffolding of lattice theory, discuss the far-reaching implications of the methodology, and demonstrate its application with current examples in machine learning. Automation of both inference and inquiry promises to allow robots to perform science in the far reaches of our solar system and in other star systems by enabling them to not only make inferences from data, but also decide which question to ask, experiment to perform, or measurement to take given what they have learned and what they are designed to understand.

Knuth, Kevin H.↗
NASA NTRS2016

Airspace Technology Demonstration 3 (ATD-3): Dynamic Weather Routes (DWR) Technology Transfer Document Summary Version 1.0

Airspace Technology Demonstration #3 (ATD-3) is part of NASA's Airspace Operations and Safety Program (AOSP) - specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multiyear research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the first of three Research Transition Products (RTPs) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. This transfer consists of NASA's legacy Dynamic Weather Routes (DWR) work for efficient routing for en-route weather avoidance. DWR is a ground-based trajectory automation system that continuously and automatically analyzes active airborne aircraft in en route airspace to identify opportunities for simple corrections to flight plan routes that can save significant flying time, at least five minutes wind-corrected, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions. The key benefit of the DWR concept is to let automation continuously and automatically analyze active flights to find those where simple route corrections can save significant time and fuel. Operators are busy during weather events. It is more effective to let automation find the opportunities for high-value route corrections.

ATD-3↗
NASA NTRSDate not supplied

Cognitive Engineering in Training: Monitoring and Pilot-Automation Coordination in Complex Environments

This paper reports our investigation of flight path monitoring in aviation. We interviewed experienced pilots to understand the knowledge and skills underlying effective monitoring and we developed an example learning environment to improve these skills. We explore how design of pilot training and learning, like the design of interfaces and of the underlying automation, benefits from cognitive engineering methods and perspective. In aviation, monitoring and managing flight path are critical activities. The influences on flight path are complex and come from the autoflight system, from control actions by the pilot, and from external factors, including weather and Air Traffic Control (ATC). Indeed, inadequate flight path monitoring is a current aviation concern as it has been implicated in accidents and incidents. Effective piloting depends on strategies for noticing, understanding, and anticipating these influences to monitor and manage flight path. Lack of such skills reduces pilots' ability to maintain safety margin and resilience. Although flightdeck automation is intended to aid pilot understanding and prediction, the Fight Management Systems (FMS) can mislead as well as aid the pilot's understanding and projection of what will happen. In dynamic conditions, FMS predictions may be based on old or incomplete information. Understanding such vulnerabilities is an important part of pilot-autoflight coordination. The learning environment we developed is designed to help pilots proactively monitor and manage flight path. We consider how a broad cognitive engineering approach might inform the "what" and "how" of learning in dynamic work domains.

pilot-monitoring↗
NASA NTRS1998

Automated Fluid Feature Extraction from Transient Simulations

In the past, feature extraction and identification were interesting concepts, but not required to understand the underlying physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of much interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one 'snap-shot' of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense. The following is a list of the important physical phenomena found in transient (and steady-state) fluid flow: Shocks; Vortex ores; Regions of Recirculation; Boundary Layers; Wakes.

Haimes, Robert↗
NASA NTRS1999

Automated Fluid Feature Extraction from Transient Simulations

In the past, feature extraction and identification were interesting concepts, but not required to understand the underlying physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of much interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one "snap-shot" of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense. The following is a list of the important physical phenomena found in transient (and steady-state) fluid flow: (1) Shocks, (2) Vortex cores, (3) Regions of recirculation, (4) Boundary layers, (5) Wakes. Three papers and an initial specification for the (The Fluid eXtraction tool kit) FX Programmer's guide were included. The papers, submitted to the AIAA Computational Fluid Dynamics Conference, are entitled : (1) Using Residence Time for the Extraction of Recirculation Regions, (2) Shock Detection from Computational Fluid Dynamics results and (3) On the Velocity Gradient Tensor and Fluid Feature Extraction.

Haimes, Robert↗
NASA NTRS1972

High-pressure oxygen impact tester

To extend the compatibility evaluation of candidate materials in oxygen, a high-pressure oxygen impact tester has been designed, developed, and installed at NASA/MSFC, Huntsville, Alabama. The tester has an operating range from ambient to 69,000 newton/sq m (10,000 psig) pressures and from the normal boiling point of liquid oxygen to 394 K (121 C) temperatures. The tester was designed to deliver 97.63 joules (72 ft-lb) of impact energy; however, variable height and weight can be achieved for threshold analysis. The system is completely remote and highly automated to furnish safe, reliable operation. High-frequency, fast-response instrumentation capabilities are provided to ensure maximum information output with the hope of minimizing the number of tests required for material acceptance.

Raniere, F. D.↗