Search NASA⌕ Search

SEARCH · Search NASA

Results for “Community Based Rules”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

National Campaign (NC)-1 Strategic Conflict Management Simulation (X4) Community Based Rules

Projected demand for transportation services in the urban environment has led to the development of several Concepts of Operation for Urban Air Mobility, or UAM. UAM is a concept for the transportation of people and goods in the metropolitan environment using small, efficient aircraft over short distances as part of an expanding multimodal transportation network. UAM will leverage emerging technologies including electric Vertical Takeoff and Landing (eVTOL) aircraft, increasing levels of automation and a new operational paradigm in dense airspace where a set of agreed-upon rules govern the procedures and interactions defining a cooperative environment in which operators are entrusted with a range of functions typically conducted by Air Traffic Control (ATC). These rules, proposed in the FAA NextGen Office’s UAM Concept of Operations [1], were originally termed Community Based Rules or Community Business Rules (CBRs), and will in the future termed Cooperative Operating Practices (COPs); this document uses the original term, CBR. CBRs are a set of rules, developed by the UAM community and (where necessary) approved by the FAA that govern the interactions between UAM entities and limit the need for ATC services including, but not limited to, separation control by ATC, addressing a fundamental challenge to scaling UAM operations. UAM community development of CBRs is anticipated to accelerate the adoption of new practices while retaining the regulatory authority of the FAA within required domains (e.g., NAS safety, security and equal access). However, there currently exists no agreed industry forum or defined procedures for CBR development. Investigation of best practices for the development of UAM CBRs was identified by NASA and the FAA NextGen Office as a research need. In collaboration with seven industry partners, NASA participated in a series of simulations that investigated elements of the envisioned UAM operations, with a primary focus on Strategic Conflict Management (SCM). The development and conduct of cooperative UAM simulations with seven industry partners provided a unique opportunity to investigate CBR development practices. Development of CBRs for the UAM SCM simulations was conducted in parallel with simulation capability development and was closely related to requirements definition for the simulations. As such, the CBR development effort presented herein had two objectives: explore CBR development practices in collaboration with the industry partners and develop an initial set of UAM CBRs to support simulation requirements definition and development. Consensus was achieved among NASA and the industry partners on 24 CBRs that were developed to support the cooperative simulation operations across five topic areas: General (related to test requirements), Operational Intent, Conformance Monitoring, Demand Capacity Balancing, and Airspace Constraint Management. Additional topic areas and CBRs were discussed but were deemed outside the scope of the simulation; these are included in the appendices. A collaborative, iterative process was employed for developing the CBRs engaging both NASA and Industry; because CBR development is envisioned to be community-driven, opportunities were sought that provided industry partners leadership roles in developing CBRs. The following key observations and recommendations may aid the UAM industry in future CBR development efforts: - The lack of a defined process proved challenging initially. Stakeholder engagement in the early stages of CBR development was intermittent and may have been due to the lack of a clear definition of roles and responsibilities of those involved in the effort. - Industry leadership of CBR topic areas proved successful. Discussions in these topic areas were engaging, with alternate viewpoints freely discussed and detailed CBRs resulting. This points to the importance of identifying the best-suited leadership in technical areas for CBR development. - Discussions within a CBR topic area were typically dominated by only a few participants. Whereas all industry partners contributed to CBR development, within each topic area, technical leadership was evident even when not formally established. This observation may indicate that smaller, focused groups may be more effective in initial CBR development than an open forum or large standards development effort (although both maybe required prior to FAA review and approval for some CBRs). - Identifying suitable forums for initial UAM CBR development and identifying the most effective industry participants and leadership will be crucial for successful CBR development. Although the operational need for UAM CBRs may not be immediate, establishing the forums and leadership to define the processes for CBR development is a prudent early step to UAM realization.

Community Based Rules↗
NASA NTRS2022

UAM Research – X4: Introduction to Community Based Rules (CBRs)

Recent advances in technology have enabled industry development of new and innovative vehicle types, offering lower operating costs and highly automated functionality that facilitates the introduction of new types of operations. These include low-altitude airspace operations with small Unmanned Aircraft Systems (UASs), short distance urban and intercity operations, and high- altitude Upper Class E operations. These and other new operations are expected to result in a much higher operational tempo than is currently experienced across the National Airspace System (NAS). The projected increase in operations, as well as the introduction of new aircraft form factors and supporting technologies—including increasing autonomy—will present challenges to the existing Air Traffic Management (ATM) system, which is currently unable to cost-effectively scale and deliver needed services. In response to these challenges and opportunities, a highly automated, cooperative environment incorporating a federated network has been envisioned and described through multiple operational concepts, depicting the future operating environment as part of the NAS. Foundational to the success of this future operating environment is the establishment of common business rules and understandings across relevant stakeholders, referred to as Community Based Rules (CBRs). Development, adoption, and implementation of CBRs will require collaboration across multiple stakeholders, including operators, support services (industry), and the Federal Aviation Administration (FAA), to identify and resolve a broad range of questions and challenges. Examples of these questions include “what rules are needed?”, “how are they expressed?”, and “how will they be managed?” This document identifies and describes an initial set of questions and considerations to be examined as efforts begin to create the innovative, automated, cooperative operating environment of the future. The goal is to establish a common frame of reference to support discussions and decisions regarding the future implementation of CBRs as part of the NAS.

Community Based Rules↗
NASA NTRS2022

National Campaign (NC)-1 Strategic Conflict Management Simulation (X4) Final Report

Urban Air Mobility (UAM) enables highly automated, cooperative, passenger or cargo-carrying air transportation services in and around urban areas. UAM is a subset of the Advanced Air Mobility (AAM) concept under development by the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), and industry. The Strategic Conflict Management (SCM) Simulation, dubbed “X4”, was conducted between July 2021 and June 2022 by NASA with the FAA and industry to evolve the Provider of Services for UAM (PSU) that will be needed to ensure initial UAM operations can scale in the National Airspace System (NAS). The FAA UAM Concept of Operations (ConOps) v1 [1] served as an initial guiding document for the X4 airspace management system design to ensure the architecture supports testing of services provided by third-party service providers. To that end, the X4 architecture leveraged concepts and technologies developed for Unmanned Aircraft System (UAS) Traffic Management (UTM) while also developing and testing new capabilities and services needed for UAM. The architecture included an initial prototype of the FAA-Industry Exchange Protocol (FIDXP), third-party services such as the PSUs, and Discovery and Synchronization Service (DSS), and other new services such as Demand-Capacity Balancing (DCB) to facilitate UAM strategic conflict management. During X4, NASA led discussions and collaborated with seven industry airspace partners to develop initial airspace management concepts for UAM that drove what would be tested and evaluated during the simulations. The initial capabilities defined for PSU leveraged UTM UAS Service Supplier (USS) as a starting point and evolved to meet UAM requirements. These discussions were also an opportunity for NASA to collaborate with industry to develop a set of initial Community-Based Rules (CBRs). These CBRs enabled how UAM traffic would be cooperatively managed among UAM operators. The collaborative, iterative process of developing CBRs with industry during X4 provided insight into the challenges involved and identified the need for a suitable and effective forum for future CBR development. In parallel with these discussions, NASA conducted a series of seven software sprints and two collaborative simulations with the airspace partners that built up in complexity. Over the course of the year, all seven partners successfully completed all the sprints by demonstrating the required capabilities. They also participated in the two collaborative simulations to demonstrate how multiple PSUs could work together in a collaborative, more complex environment with higher traffic density. The X4 simulation accomplished NASA's objectives and helped advance the development of the seven participating PSUs. The lessons learned provided insight into key elements of the UAM Notional Architecture from the FAA ConOps v1 [1] and UTM technologies when applied to UAM: - Having a Concept of Use (ConUse) defined prior to the activity would accelerate the time and effort from concept development to testing. - While the UAM Notional Architecture provided a starting point for a federated architecture that support services provided by third-party providers, the USS and PSU differed in their capability definitions for operational intent submission and sharing, conformance monitoring, airspace authorization, strategic conflict management, airspace constraints and dynamic replanning. - While existing DSS developed for UTM provided a way for PSU and other UAM services (such as DCB) to discover relevant operations from each other, additional complexity and challenges were found during X4 testing and illuminated the need for a more suitable solution for UAM. Industry can leverage the results of this demonstration to accelerate UAM requirements, CBRs, and standards development. The FAA and other government municipalities and agencies will be able to leverage results to inform future policies and identify additional gaps that require further analysis, moving toward operationalization of UAM.

Urban Air Mobility↗
NASA NTRS1987

Traditional versus rule-based programming techniques: Application to the control of optional flight information

To the software design community, the concern over the costs associated with a program's execution time and implementation is great. It is always desirable, and sometimes imperative, that the proper programming technique is chosen which minimizes all costs for a given application or type of application. A study is described that compared cost-related factors associated with traditional programming techniques to rule-based programming techniques for a specific application. The results of this study favored the traditional approach regarding execution efficiency, but favored the rule-based approach regarding programmer productivity (implementation ease). Although this study examined a specific application, the results should be widely applicable.

Ricks, Wendell R.↗
NASA NTRS1991

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components

This annual report summarizes the work completed during the third year of technical effort on the referenced contract. Principal developments continue to focus on the Probabilistic Finite Element Method (PFEM) which has been under development for three years. Essentially all of the linear capabilities within the PFEM code are in place. Major progress in the application or verifications phase was achieved. An EXPERT module architecture was designed and partially implemented. EXPERT is a user interface module which incorporates an expert system shell for the implementation of a rule-based interface utilizing the experience and expertise of the user community. The Fast Probability Integration (FPI) Algorithm continues to demonstrate outstanding performance characteristics for the integration of probability density functions for multiple variables. Additionally, an enhanced Monte Carlo simulation algorithm was developed and demonstrated for a variety of numerical strategies.

Source record↗
NASA NTRS1986

An expert system for ground support of the Hubble space telescope

The Hubble Space Telescope is an orbiting optical observatory due to be launched by the Space Shuttle in late 1987. It is a complex, multi-instrument observatory whose resources will be available to the world-wide astronomical community. The 'Transformation' system is a hybrid system which utilizes a rule-based expert system to convert scientific proposals into pre-optimized linked hierarchies of spacecraft activities. These activities are generated in a format that can be directly scheduled by the planning and scheduling component of the Space Telescope ground support system. The Transformation system will be described in detail in this paper, with particular attention given to the rule base.

Rosenthal, Don↗
NASA NTRS1991

Automated implementation of rule-based expert systems with neural networks for time-critical applications

In fault diagnosis, control and real-time monitoring, both timing and accuracy are critical for operators or machines to reach proper solutions or appropriate actions. Expert systems are becoming more popular in the manufacturing community for dealing with such problems. In recent years, neural networks have revived and their applications have spread to many areas of science and engineering. A method of using neural networks to implement rule-based expert systems for time-critical applications is discussed here. This method can convert a given rule-based system into a neural network with fixed weights and thresholds. The rules governing the translation are presented along with some examples. We also present the results of automated machine implementation of such networks from the given rule-base. This significantly simplifies the translation process to neural network expert systems from conventional rule-based systems. Results comparing the performance of the proposed approach based on neural networks vs. the classical approach are given. The possibility of very large scale integration (VLSI) realization of such neural network expert systems is also discussed.

Ramamoorthy, P. A.↗
NASA NTRS1995

Making intelligent systems team players. A guide to developing intelligent monitoring systems

This reference guide for developers of intelligent monitoring systems is based on lessons learned by developers of the DEcision Support SYstem (DESSY), an expert system that monitors Space Shuttle telemetry data in real time. DESSY makes inferences about commands, state transitions, and simple failures. It performs failure detection rather than in-depth failure diagnostics. A listing of rules from DESSY and cue cards from DESSY subsystems are included to give the development community a better understanding of the selected model system. The G-2 programming tool used in developing DESSY provides an object-oriented, rule-based environment, but many of the principles in use here can be applied to any type of monitoring intelligent system. The step-by-step instructions and examples given for each stage of development are in G-2, but can be used with other development tools. This guide first defines the authors' concept of real-time monitoring systems, then tells prospective developers how to determine system requirements, how to build the system through a combined design/development process, and how to solve problems involved in working with real-time data. It explains the relationships among operational prototyping, software evolution, and the user interface. It also explains methods of testing, verification, and validation. It includes suggestions for preparing reference documentation and training users.

Land, Sherry A.↗
NASA NTRS2020

UAS Service Supplier Network Performance

This report summarizes the performance of Unmanned Aircraft System (UAS) Service Suppliers (USS) in the Technical Capability Level 4 (TCL4) flight test performed by NASA and its partners in support of the UAS Traffic Management (UTM) concept. TCL4 is the final in a series of TCL demonstrations of a traffic management system for small UAS (sUAS). All demonstrations have been executed in collaboration with industry partners. The [FAA 2018] UTM Concept of Operations document describes UTM as:...the manner in which the FAA will support operations for predominantly sUAS operating in low altitude airspace. UTM utilizes industry’s ability to supply services under FAA’s regulatory authority where these services do not currently exist. It is a community-based traffic management system, where the Operators are responsible for the coordination, execution, and management of operations, with rules of the road established by FAA. UTM is designed to support the demand and expectations for a broad spectrum of operations with ever-increasing complexity and risk. UTM should be considered a collection of services rather than a monolithic application. The following section describes the architecture at a high level. For further insight, the FAA’s concept document [FAA 2018] or NASA’s earlier concept publication [NASA 2016] should be consulted.

Rios, Joseph L.↗
NASA NTRS1993

TARGET: Rapid Capture of Process Knowledge

TARGET (Task Analysis/Rule Generation Tool) represents a new breed of tool that blends graphical process flow modeling capabilities with the function of a top-down reporting facility. Since NASA personnel frequently perform tasks that are primarily procedural in nature, TARGET models mission or task procedures and generates hierarchical reports as part of the process capture and analysis effort. Historically, capturing knowledge has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent the expert's knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some types of knowledge, procedural knowledge has received relatively little attention. In essence, TARGET is one of the first tools of its kind, commercial or institutional, that is designed to support this type of knowledge capture undertaking. This paper will describe the design and development of TARGET for the acquisition and representation of procedural knowledge. The strategies employed by TARGET to support use by knowledge engineers, subject matter experts, programmers and managers will be discussed. This discussion includes the method by which the tool employs its graphical user interface to generate a task hierarchy report. Next, the approach to generate production rules for incorporation in and development of a CLIPS based expert system will be elaborated. TARGET also permits experts to visually describe procedural tasks as a common medium for knowledge refinement by the expert community and knowledge engineer making knowledge consensus possible. The paper briefly touches on the verification and validation issues facing the CLIPS rule generation aspects of TARGET. A description of efforts to support TARGET's interoperability issues on PCs, Macintoshes and UNIX workstations concludes the paper.

Ortiz, C. J.↗
NASA NTRS2016

Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation

A major focus of the commercial aviation community is discovery of unknown safety events in flight operations data. Data-driven unsupervised anomaly detection methods are better at capturing unknown safety events compared to rule-based methods which only look for known violations. However, not all statistical anomalies that are discovered by these unsupervised anomaly detection methods are operationally significant (e.g., represent a safety concern). Subject Matter Experts (SMEs) have to spend significant time reviewing these statistical anomalies individually to identify a few operationally significant ones. In this paper we propose an active learning algorithm that incorporates SME feedback in the form of rationales to build a classifier that can distinguish between uninteresting and operationally significant anomalies. Experimental evaluation on real aviation data shows that our approach improves detection of operationally significant events by as much as 75% compared to the state-of-the-art. The learnt classifier also generalizes well to additional validation data sets.

anomaly detection↗
NASA NTRS2016

Estimating Snow Water Storage in North America Using CLM4, DART, and Snow Radiance Data Assimilation

This paper addresses continental-scale snow estimates in North America using a recently developed snow radiance assimilation (RA) system. A series of RA experiments with the ensemble adjustment Kalman filter are conducted by assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature T(sub B) at 18.7- and 36.5-GHz vertical polarization channels. The overall RA performance in estimating snow depth for North America is improved by simultaneously updating the Community Land Model, version 4 (CLM4), snow/soil states and radiative transfer model (RTM) parameters involved in predicting T(sub B) based on their correlations with the prior T(sub B) (i.e., rule-based RA), although degradations are also observed. The RA system exhibits a more mixed performance for snow cover fraction estimates. Compared to the open-loop run (0.171m RMSE), the overall snow depth estimates are improved by 1.6% (0.168m RMSE) in the rule-based RA whereas the default RA (without a rule) results in a degradation of 3.6% (0.177mRMSE). Significant improvement of the snow depth estimates in the rule-based RA as observed for tundra snow class (11.5%, p < 0.05) and bare soil land-cover type (13.5%, p < 0.05). However, the overall improvement is not significant (p = 0.135) because snow estimates are degraded or marginally improved for other snow classes and land covers, especially the taiga snow class and forest land cover (7.1% and 7.3% degradations, respectively). The current RA system needs to be further refined to enhance snow estimates for various snow types and forested regions.

snow depth↗
NASA NTRS1990

In defense of compilation: A response to Davis' form and content in model-based reasoning

In a recent paper entitled 'Form and Content in Model Based Reasoning', Randy Davis argues that model based reasoning research aimed at compiling task specific rules from underlying device models is mislabeled, misguided, and diversionary. Some of Davis' claims are examined and his basic conclusions are challenged about the value of compilation research to the model based reasoning community. In particular, Davis' claim is refuted that model based reasoning is exempt from the efficiency benefits provided by knowledge compilation techniques. In addition, several misconceptions are clarified about the role of representational form in compilation. It is concluded that techniques have the potential to make a substantial contribution to solving tractability problems in model based reasoning.

Keller, Richard↗
NASA NTRS1991

Advanced CLIPS capabilities

The C Language Integrated Production System (CLIPS) is a forward chaining rule based language developed by NASA. CLIPS was designed specifically to provide high portability, low cost, and easy integration with external systems. The current release of CLIPS, version 4.3, is being used by over 2500 users throughout the public and private community. The primary addition to the next release of CLIPS, version 5.0, will be the CLIPS Object Oriented Language (COOL). The major capabilities of COOL are: class definition with multiple inheritance and no restrictions on the number, types, or cardinality of slots; message passing which allows procedural code bundled with an object to be executed; and query functions which allow groups of instances to be examined and manipulated. In addition to COOL, numerous other enhancements were added to CLIPS including: generic functions (which allow different pieces of procedural code to be executed depending upon the types or classes of the arguments); integer and double precision data type support; multiple conflict resolution strategies; global variables; logical dependencies; type checking on facts; full ANSI compiler support; and incremental reset for rules.

Riley, Gary↗
NASA NTRS1996

A System Concept for Facilitating User Preferences in En Route Airspace

The Federal Aviation Administration is trying to make its air traffic management system more responsive to the needs of the aviation community by exploring the concept of 'free flight' for aircraft flying under instrument flight rules. A logical first step toward free flight could be made without significantly altering current air traffic control (ATC) procedures or requiring new airborne equipment by designing a ground-based system to be highly responsive to 'user preference' in en route airspace while providing for an orderly transition to the terminal area. To facilitate user preference in all en route environments, a system based on an extension of the Center/TRACON Automation System (CTAS) is proposed in this document. The new system would consist of two integrated components. An airspace tool (AT) focuses on unconstrained en route aircraft (e.g., not transitioning to the terminal airspace), taking advantage of the relatively unconstrained nature of their flights and using long-range trajectory prediction to provide cost-effective conflict resolution advisories to sector controllers. A sector tool (ST) generates efficient advisories for all aircraft, with a focus on supporting controllers in analyzing and resolving complex, highly constrained traffic situations. When combined, the integrated AT/ST system supports user preference in any air route traffic control center sector. The system should also be useful in evaluating advanced free-flight concepts by serving as a test bed for future research. This document provides an overview of the design concept, explains its anticipated benefits, and recommends a development strategy that leads to a deployable system.

Vivona, R. A.↗
NASA NTRS2016

A Survey of Solver-Related Geometry and Meshing Issues

There is a concern in the computational fluid dynamics community that mesh generation is a significant bottleneck in the CFD workflow. This is one of several papers that will help set the stage for a moderated panel discussion addressing this issue. Although certain general "rules of thumb" and a priori mesh metrics can be used to ensure that some base level of mesh quality is achieved, inadequate consideration is often given to the type of solver or particular flow regime on which the mesh will be utilized. This paper explores how an analyst may want to think differently about a mesh based on considerations such as if a flow is compressible vs. incompressible or hypersonic vs. subsonic or if the solver is node-centered vs. cell-centered. This paper is a high-level investigation intended to provide general insight into how considering the nature of the solver or flow when performing mesh generation has the potential to increase the accuracy and/or robustness of the solution and drive the mesh generation process to a state where it is no longer a hindrance to the analysis process.

Masters, James↗
NASA NTRS1994

Optimal pattern distributions in Rete-based production systems

Since its introduction into the AI community in the early 1980's, the Rete algorithm has been widely used. This algorithm has formed the basis for many AI tools, including NASA's CLIPS. One drawback of Rete-based implementation, however, is that the network structures used internally by the Rete algorithm make it sensitive to the arrangement of individual patterns within rules. Thus while rules may be more or less arbitrarily placed within source files, the distribution of individual patterns within these rules can significantly affect the overall system performance. Some heuristics have been proposed to optimize pattern placement, however, these suggestions can be conflicting. This paper describes a systematic effort to measure the effect of pattern distribution on production system performance. An overview of the Rete algorithm is presented to provide context. A description of the methods used to explore the pattern ordering problem area are presented, using internal production system metrics such as the number of partial matches, and coarse-grained operating system data such as memory usage and time. The results of this study should be of interest to those developing and optimizing software for Rete-based production systems.

Scott, Stephen L.↗
NASA NTRS2002

Science opportunity analyzer - a multi-mission tool for planning

For many years the diverse scientific community that supports JPL's wide variety ofinterplanetary space missions has needed a tool in order to plan and develop their experiments. The tool needs to be easily adapted to various mission types and portable to the user community. The Science Opportunity Analyzer, SOA, now in its third year of development, is intended to meet this need. SOA is a java-based application that is designed to enable scientists to identify and analyze opportunities for science observations from spacecraft. It differs from other planning tools in that it does not require an in-depth knowledge of the spacecraft command system or operation modes to begin high level planning. Users can, however, develop increasingly detailed levels of design. SOA consists of six major functions: Opportunity Search, Visualization, Observation Design, Constraint Checking, Data Output and Communications. Opportunity Search is a GUI driven interface to existing search engines that can be used to identify times when a spacecraft is in a specific geometrical relationship with other bodies in the solar system. This function can be used for advanced mission planning as well as for making last minute adjustments to mission sequences in response to trajectory modifications. Visualization is a key aspect of SOA. The user can view observation opportunities in either a 3D representation or as a 2D map projection. The user is given extensive flexibility to customize what is displayed in the view. Observation Design allows the user to orient the spacecraft and visualize the projection of the instrument field of view for that orientation using the same views as Opportunity Search. Constraint Checking is provided to validate various geometrical and physical aspects of an observation design. The user has the ability to easily create custom rules or to use official project-generated flight rules. This capability may also allow scientists to easily impact the cost to science if flight rule changes occur. Data Output generates information based on the spacecraft's trajectory, opportunity search results or based on a created observation. The data can be viewed either in tabular format or as a graph. Finally, SOA is unique in that it is designed to be able to communicate with a variety of existing planning and sequencing tools. From the very beginning SOA was designed with the user in mind. Extensive surveys of the potential user community were conducted in order to develop the software requirements. Throughout the development period, close ties have been maintained with the science community to insure that the tool maintains its user focus. Although development is still in its early stages, SOA is already developing a user community on the Cassini project, which is depending on this tool for their science planning. There are other tools at JPL that do various pieces of what SOA can do; however, there is no other tool which combines all these functions and presents them to the user in such a convenient, cohesive, and easy to use fashion.

SOA science planning mission operations sequence s↗