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At least 199 records · Page 11

All sources NASA NTRS DOE OSTI

NASA NTRS1989

The fault monitoring and diagnosis knowledge-based system for space power systems: AMPERES, phase 1

The objective is to develop a real time fault monitoring and diagnosis knowledge-based system (KBS) for space power systems which can save costly operational manpower and can achieve more reliable space power system operation. The proposed KBS was developed using the Autonomously Managed Power System (AMPS) test facility currently installed at NASA Marshall Space Flight Center (MSFC), but the basic approach taken for this project could be applicable for other space power systems. The proposed KBS is entitled Autonomously Managed Power-System Extendible Real-time Expert System (AMPERES). In Phase 1 the emphasis was put on the design of the overall KBS, the identification of the basic research required, the initial performance of the research, and the development of a prototype KBS. In Phase 2, emphasis is put on the completion of the research initiated in Phase 1, and the enhancement of the prototype KBS developed in Phase 1. This enhancement is intended to achieve a working real time KBS incorporated with the NASA space power system test facilities. Three major research areas were identified and progress was made in each area. These areas are real time data acquisition and its supporting data structure; sensor value validations; development of inference scheme for effective fault monitoring and diagnosis, and its supporting knowledge representation scheme.

Lee, S. C.↗

DOE OSTI2014

SU-E-T-357: Semi-Automated Knowledge-Based Radiation Therapy (KBRT) Planning for Head-And-Neck Cancer (HNC): Can KBRT Plans Achieve Better Results Than Manual Planning?

Purpose: Knowledge Based Radiation Therapy Treatment (KBRT) planning can be used to semi-automatically generate IMRT plans for new patients using constraints derived from previously manually-planned, geometrically similar patients. We investigate whether KBRT plans can achieve greater dose sparing than manual plans using optimized, organspecific constraint weighting factors. Methods: KBRT planning of HNC radiotherapy cases geometrically matched each new (query) case to one of the 105 clinically approved plans in our database. The dose distribution of the planned match was morphed to fit the querys geometry. Dose-volume constraints extracted from the morphed dose distribution were used to run the IMRT optimization with no user input. In the first version, all constraints were multiplied by a weighting factor of 0.7. The weighting factors were then systematically optimized (in order of OARs with increasing separation from the target) to maximize sparing to each OAR without compromising other OARs. The optimized, second version plans were compared against the first version plans and the clinically approved plans for 45 unilateral/bilateral target cases using the dose metrics: mean, median and maximum (brainstem and cord) doses. Results: Compared to the first version, the second version significantly reduced mean/median contralateral parotid doses (>2Gy) for bilateral cases. Other changes between the two versions were not clinically meaningful. Compared to the original clinical plans, both bilateral and unilateral plans in the second version had lower average dose metrics for 5 of the 6 OARs. Compared to the original plans, the second version achieved dose sparing that was at least as good for all OARs and better for the ipsilateral parotid (bilateral) and oral cavity (bilateral/unilateral). Differences in planning target volume coverage metrics were not clinically significant. Conclusion: HNC-KBRT planning generated IMRT plans with at least equivalent dose sparing to manually generated plans; greater dose sparing was achieved in selected OARs.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1990

Compiling knowledge-based systems from KEE to Ada

The dominant technology for developing AI applications is to work in a multi-mechanism, integrated, knowledge-based system (KBS) development environment. Unfortunately, systems developed in such environments are inappropriate for delivering many applications - most importantly, they carry the baggage of the entire Lisp environment and are not written in conventional languages. One resolution of this problem would be to compile applications from complex environments to conventional languages. Here the first efforts to develop a system for compiling KBS developed in KEE to Ada (trademark). This system is called KATYDID, for KEE/Ada Translation Yields Development Into Delivery. KATYDID includes early prototypes of a run-time KEE core (object-structure) library module for Ada, and translation mechanisms for knowledge structures, rules, and Lisp code to Ada. Using these tools, part of a simple expert system was compiled (not quite automatically) to run in a purely Ada environment. This experience has given us various insights on Ada as an artificial intelligence programming language, potential solutions of some of the engineering difficulties encountered in early work, and inspiration on future system development.

Filman, Robert E.↗

DOE OSTI2025

Enhancing EV Motor Design Through Knowledge-Based AI and Hierarchical Fuzzy Logic Model

This work presents a novel approach to optimizing electric vehicle motor design through the integration of Knowledge-Based Artificial Intelligence (KB-AI) and Hierarchical Fuzzy Logic. Traditional motor design processes are time-intensive, relying heavily on iterative simulations and domain-specific expertise. These processes are further complicated by the nonlinear relationships between key design parameters. The proposed framework addresses these challenges by systematically encoding expert knowledge from scientific literature into a fuzzy logic system, allowing for the efficient handling of complex design variables. The hierarchical fuzzy logic model reduces computational complexity by decomposing the nonlinear relationships into manageable rule sets while maintaining design accuracy. The proposed methodology was applied to the design of a 100 kW motor, yielding optimal values for key parameters. This resulted in a compact motor design with a volume of 2.2 liters, showcasing the framework’s ability to deliver high-performance, application-specific motor configurations.

Kumar, Praveen [ORNL] (ORCID:0000000291877857)↗

NASA NTRS1988

Development of a component centered fault monitoring and diagnosis knowledge based system for space power system

The overall approach currently being taken in the development of AMPERES (Autonomously Managed Power System Extendable Real-time Expert System), a knowledge-based expert system for fault monitoring and diagnosis of space power systems, is discussed. The system architecture, knowledge representation, and fault monitoring and diagnosis strategy are examined. A 'component-centered' approach developed in this project is described. Critical issues requiring further study are identified.

Lee, S. C.↗

NASA NTRS1993

The Knowledge-Based Software Assistant: Beyond CASE

This paper will outline the similarities and differences between two paradigms of software development. Both support the whole software life cycle and provide automation for most of the software development process, but have different approaches. The CASE approach is based on a set of tools linked by a central data repository. This tool-based approach is data driven and views software development as a series of sequential steps, each resulting in a product. The Knowledge-Based Software Assistant (KBSA) approach, a radical departure from existing software development practices, is knowledge driven and centers around a formalized software development process. KBSA views software development as an incremental, iterative, and evolutionary process with development occurring at the specification level.

Carozzoni, Joseph A.↗

NASA NTRS1987

Knowledge based jet engine diagnostics

A fielded expert system automates equipment fault isolation and recommends corrective maintenance action for Air Force jet engines. The knowledge based diagnostics tool was developed as an expert system interface to the Comprehensive Engine Management System, Increment IV (CEMS IV), the standard Air Force base level maintenance decision support system. XMAM (trademark), the Expert Maintenance Tool, automates procedures for troubleshooting equipment faults, provides a facility for interactive user training, and fits within a diagnostics information feedback loop to improve the troubleshooting and equipment maintenance processes. The application of expert diagnostics to the Air Force A-10A aircraft TF-34 engine equipped with the Turbine Engine Monitoring System (TEMS) is presented.

Jellison, Timothy G.↗

DOE OSTI2017

Highly Efficient Training, Refinement, and Validation of a Knowledge-based Planning Quality-Control System for Radiation Therapy Clinical Trials

Purpose: To demonstrate an efficient method for training and validation of a knowledge-based planning (KBP) system as a radiation therapy clinical trial plan quality-control system. Methods and Materials: We analyzed 86 patients with stage IB through IVA cervical cancer treated with intensity modulated radiation therapy at 2 institutions according to the standards of the INTERTECC (International Evaluation of Radiotherapy Technology Effectiveness in Cervical Cancer, National Clinical Trials Network identifier: 01554397) protocol. The protocol used a planning target volume and 2 primary organs at risk: pelvic bone marrow (PBM) and bowel. Secondary organs at risk were rectum and bladder. Initial unfiltered dose-volume histogram (DVH) estimation models were trained using all 86 plans. Refined training sets were created by removing sub-optimal plans from the unfiltered sample, and DVH estimation models… and DVH estimation models were constructed by identifying 30 of 86 plans emphasizing PBM sparing (comparing protocol-specified dosimetric cutpoints V{sub 10} (percentage volume of PBM receiving at least 10 Gy dose) and V{sub 20} (percentage volume of PBM receiving at least 20 Gy dose) with unfiltered predictions) and another 30 of 86 plans emphasizing bowel sparing (comparing V{sub 40} (absolute volume of bowel receiving at least 40 Gy dose) and V{sub 45} (absolute volume of bowel receiving at least 45 Gy dose), 9 in common with the PBM set). To obtain deliverable KBP plans, refined models must inform patient-specific optimization objectives and/or priorities (an auto-planning “routine”). Four candidate routines emphasizing different tradeoffs were composed, and a script was developed to automatically re-plan multiple patients with each routine. After selection of the routine that best met protocol objectives in the 51-patient training sample (KBP{sub FINAL}), protocol-specific DVH metrics and normal tissue complication probability were compared for original versus KBP{sub FINAL} plans across the 35-patient validation set. Paired t tests were used to test differences between planning sets. Results: KBP{sub FINAL} plans outperformed manual planning across the validation set in all protocol-specific DVH cutpoints. The mean normal tissue complication probability for gastrointestinal toxicity was lower for KBP{sub FINAL} versus validation-set plans (48.7% vs 53.8%, P<.001). Similarly, the estimated mean white blood cell count nadir was higher (2.77 vs 2.49 k/mL, P<.001) with KBP{sub FINAL} plans, indicating lowered probability of hematologic toxicity. Conclusions: This work demonstrates that a KBP system can be efficiently trained and refined for use in radiation therapy clinical trials with minimal effort. This patient-specific plan quality control resulted in improvements on protocol-specific dosimetric endpoints.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2021

Developing a Fundamental Knowledge Base for the Interaction of Ruthenium with Natural and Engineered Iron-Bearing Materials

The intent of this project is to build a fundamental knowledge base concerning the redox coupling between Ru and Fe in heterogeneous systems with predictive applications towards the fate, speciation, and transport of Ru in the environment and its capture using available technologies. RuNOCl 3 and Fe 3+ are redox active over a broad range of pH. Initial assessment of effect of redox coupling between Ru and Fe indicates that Fe(III) in ferrihydrite can oxidize Ru 2+ in RuNOCl3 to Ru(IV) during coprecipitation at ambient conditions and alkaline pH. Further, evidence suggests that Ru(IV) is incorporated in the structure of fh. Likewise, Fe 3+ (aq) also reduces Ru 2+ in RuNOCl 3 in the homogenous system at acidic pH although the kinetics of reaction appear to be slow. Rufh annealed to 500 0C transforms to Ru(III) doped hematite. AIMD informed EXAFS indicates that Ru substitutes for Fe(III) in regular octahedral sites of hematite but requires three distinct configurations involving edge-sharing protonated Fe vacancies and straight substitution with no local defects. Fe 2+ (aq) appears to oxidize at the surface of RuO 2 , but the amount is too low to reasonably expect detectable reduced Ru. Future experiments at higher pH are warranted to make Fe 2+ (aq) less stable (i.e., make more redox active). We also demonstrated that we can functionalize Si aerogels with Fe(II) and Fe(III) but likely need to go to higher T to make Feo nanoparticles.

36 MATERIALS SCIENCE↗

NASA NTRS1987

HSTDEK: Developing a methodology for construction of large-scale, multi-use knowledge bases

The primary research objectives of the Hubble Space Telescope Design/Engineering Knowledgebase (HSTDEK) are to develop a methodology for constructing and maintaining large scale knowledge bases which can be used to support multiple applications. To insure the validity of its results, this research is being persued in the context of a real world system, the Hubble Space Telescope. The HSTDEK objectives are described in detail. The history and motivation of the project are briefly described. The technical challenges faced by the project are outlined.

Freeman, Michael S.↗

NASA NTRS1992

Knowledge based imaging for terrain analysis

A planetary rover will have various vision based requirements for navigation, terrain characterization, and geological sample analysis. In this paper we describe a knowledge-based controller and sensor development system for terrain analysis. The sensor system consists of a laser ranger and a CCD camera. The controller, under the input of high-level commands, performs such functions as multisensor data gathering, data quality monitoring, and automatic extraction of sample images meeting various criteria. In addition to large scale terrain analysis, the system's ability to extract useful geological information from rock samples is illustrated. Image and data compression strategies are also discussed in light of the requirements of earth bound investigators.

Holben, Rick↗

NASA NTRS1988

Workshop on Verification and Validation of Knowledge Based Systems. I - Overview and meeting summary

An overview is presented of a workshop held on May 14-15, 1987. Presentations included overviews of knowledge-based system (KBS) fundamentals, introductions to verification and validation (V&V) methods currently being used, and theoretical V&V work. The findings of three working groups are considered, involving: (1) KBS V&V feasibility within current NASA software constraints, (2) V&V methods suited to KBS constraints, and future KBS V&V research goals.

Richardson, Keith↗

NASA NTRS1989

Knowledge-based control of an adaptive interface

The analysis, development strategy, and preliminary design for an intelligent, adaptive interface is reported. The design philosophy couples knowledge-based system technology with standard human factors approaches to interface development for computer workstations. An expert system has been designed to drive the interface for application software. The intelligent interface will be linked to application packages, one at a time, that are planned for multiple-application workstations aboard Space Station Freedom. Current requirements call for most Space Station activities to be conducted at the workstation consoles. One set of activities will consist of standard data management services (DMS). DMS software includes text processing, spreadsheets, data base management, etc. Text processing was selected for the first intelligent interface prototype because text-processing software can be developed initially as fully functional but limited with a small set of commands. The program's complexity then can be increased incrementally. The intelligent interface includes the operator's behavior and three types of instructions to the underlying application software are included in the rule base. A conventional expert-system inference engine searches the data base for antecedents to rules and sends the consequents of fired rules as commands to the underlying software. Plans for putting the expert system on top of a second application, a database management system, will be carried out following behavioral research on the first application. The intelligent interface design is suitable for use with ground-based workstations now common in government, industrial, and educational organizations.

Lachman, Roy↗

NASA NTRS1996

Intelligent Tools for Planning Knowledge base Development and Verification

A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintaining the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems.

errors↗

NASA NTRS1996

Static and Completion Analysis for Planning Knowledge Base Development and Verification

anaylsis techniques↗

DOE OSTI2015

SU-E-J-244: Development and Validation of a Knowledge Based Planning Model for External Beam Radiation Therapy of Locally Advanced Non-Small Cell Lung Cancer

Purpose: The study aims to develop and validate a knowledge based planning (KBP) model for external beam radiation therapy of locally advanced non-small cell lung cancer (LA-NSCLC). Methods: RapidPlan™ technology was used to develop a lung KBP model. Plans from 65 patients with LA-NSCLC were used to train the model. 25 patients were treated with VMAT, and the other patients were treated with IMRT. Organs-at-risk (OARs) included right lung, left lung, heart, esophagus, and spinal cord. DVH and geometric distribution DVH were extracted from the treated plans. The model was trained using principal component analysis and step-wise multiple regression. Box plot and regression plot tools were used to identify geometric outliers and dosimetry outliers and help fine-tune the model. The validation was performed by (a) comparing predicted DVH boundaries to actual DVHs of 63 patients and (b) using an independent set of treatment planning data. Results: 63 out of 65 plans were included in the final KBP model with PTV volume ranging from 102.5cc to 1450.2cc. Total treatment dose prescription varied from 50Gy to 70Gy based on institutional guidelines. One patient was excluded due to geometric outlier where 2.18cc of spinal cord was included in PTV. The other patient was excluded due to dosimetric outlier where the dose sparing to spinal cord was heavily enforced in the clinical plan. Target volume, OAR volume, OAR overlap volume percentage to target, and OAR out-of-field volume were included in the trained model. Lungs and heart had two principal component scores of GEDVH, whereas spinal cord and esophagus had three in the final model. Predicted DVH band (mean ±1 standard deviation) represented 66.2±3.6% of all DVHs. Conclusion: A KBP model was developed and validated for radiotherapy of LA-NSCLC in a commercial treatment planning system. The clinical implementation may improve the consistency of IMRT/VMAT planning.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1994

Matrix Failure Modes and Effects Analysis as a Knowledge Base for a Real Time Automated Diagnosis Expert System

Failure Modes and Effects Analysis contain a wealth of information that can be used to create the knowledge base required for building automated diagnostic Expert systems. A real time monitoring and diagnosis expert system based on an actual NASA project's matrix failure modes and effects analysis was developed. This Expert system Was developed at NASA Ames Research Center. This system was first used as a case study to monitor the Research Animal Holding Facility (RAHF), a Space Shuttle payload that is used to house and monitor animals in orbit so the effects of space flight and microgravity can be studied. The techniques developed for the RAHF monitoring and diagnosis Expert system are general enough to be used for monitoring and diagnosis of a variety of other systems that undergo a Matrix FMEA. This automated diagnosis system was successfully used on-line and validated on the Space Shuttle flight STS-58, mission SLS-2 in October 1993.

Herrin, Stephanie↗

NASA NTRS1989

Knowledge-based machine vision systems for space station automation

Computer vision techniques which have the potential for use on the space station and related applications are assessed. A knowledge-based vision system (expert vision system) and the development of a demonstration system for it are described. This system implements some of the capabilities that would be necessary in a machine vision system for the robot arm of the laboratory module in the space station. A Perceptics 9200e image processor, on a host VAXstation, was used to develop the demonstration system. In order to use realistic test images, photographs of actual space shuttle simulator panels were used. The system's capabilities of scene identification and scene matching are discussed.

Ranganath, Heggere S.↗