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Results for “behavioral model”

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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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

TMC Behavior Modeling and Life Prediction Under Multiaxial Stresses

The goal of this program was to manufacture and burst test small diameter SCS-6/Ti-6Al-4V composite rings for use in the design of an advanced titanium matrix composite (TMC) impeller. The Textron Specialty Metals grooved foil-fiber process was successfully used to make high quality TMC rings. A novel spin test arbor with "soft touch" fingers to retain the TMC ring was designed and manufactured. The design of the arbor took into account its use for cyclic experiments as well as ring burst tests. Spin testing of the instrumented ring was performed at ambient, 149C (300F), and 316C (600F) temperatures. Assembly vibration was encountered during spin testing but this was overcome through simple modification of the arbor. A spin-to-burst test was successfully completed at 316C (600F). The rotational speed of the TMC ring at burst was close to that predicted. In addition to the spin test program, a number of SCS-6/Ti-6Al-4V test panels were made. Neat Ti-6Al-4V panels also were made.

Merrick, H. F.↗
NASA NTRS2002

Human performance cognitive-behavioral modeling: a benefit for occupational safety

Human Performance Modeling (HPM) is a computer-aided job analysis software methodology used to generate predictions of complex human-automation integration and system flow patterns with the goal of improving operator and system safety. The use of HPM tools has recently been increasing due to reductions in computational cost, augmentations in the tools' fidelity, and usefulness in the generated output. An examination of an Air Man-machine Integration Design and Analysis System (Air MIDAS) model evaluating complex human-automation integration currently underway at NASA Ames Research Center will highlight the importance to occupational safety of considering both cognitive and physical aspects of performance when researching human error.

Occupational Health↗
NASA NTRS2020

Behavior modeling for cybersecurity

In this paper, we elaborate on the key actors within the context of the cyber world at the Jet Propulsion Laboratory and use Bayesian Belief Networks to represent the causal and probabilistic relationships between the various elements that affect an actor and the likelihood of exploits and adverse consequences that can occur due to an exploit. We assess the effectiveness of each of the mitigative methods and the sensitivity of the system to each of the aggravating as well as mitigative factors. We use a combination of objective incident data and Subject Matter Expert knowledge as input to these models.

King, James↗
NASA NTRS1978

Winter Simulation Conference, Miami Beach, Fla., December 4-6, 1978, Proceedings. Volumes 1 & 2

The papers report on the various aspects of simulation such as random variate generation, simulation optimization, ranking and selection of alternatives, model management, documentation, data bases, and instructional methods. Simulation studies in a wide variety of fields are described, including system design and scheduling, government and social systems, agriculture, computer systems, the military, transportation, corporate planning, ecosystems, health care, manufacturing and industrial systems, computer networks, education, energy, production planning and control, financial models, behavioral models, information systems, and inventory control.

Highland, H. J.↗
NASA NTRS1946

Correlation Tests of the Ditching Behavior of an Army B-24D Airplane and a 1/16-size Model

Behaviors of both model and full-scale airplanes were ascertained by making visual observations, by recording time histories of decelerations, and by taking motion picture records of ditchings. Results are presented in form of sequence photographs and time-history curves for attitudes, vertical and horizontal displacements, and longitudinal decelerations. Time-history curves for attitudes and horizontal and vertical displacements for model and full-scale tests were in agreement; maximum longitudinal decelerations for both ditchings did not occur at same part of run; full-scale maximum deceleration was 50 percent greater.

Jarvis, George A.↗
NASA NTRS1991

Acquisition and production of skilled behavior in dynamic decision-making tasks: Modeling strategic behavior in human-automation interaction: Why and aid can (and should) go unused

Advances in computer and control technology offer the opportunity for task-offload aiding in human-machine systems. A task-offload aid (e.g., an autopilot, an intelligent assistant) can be selectively engaged by the human operator to dynamically delegate tasks to an automated system. Successful design and performance prediction in such systems requires knowledge of the factors influencing the strategy the operator develops and uses for managing interaction with the task-offload aid. A model is presented that shows how such strategies can be predicted as a function of three task context properties (frequency and duration of secondary tasks and costs of delaying secondary tasks) and three aid design properties (aid engagement and disengagement times, aid performance relative to human performance). Sensitivity analysis indicates how each of these contextual and design factors affect the optimal aid aid usage strategy and attainable system performance. The model is applied to understanding human-automation interaction in laboratory experiments on human supervisory control behavior. The laboratory task allowed subjects freedom to determine strategies for using an autopilot in a dynamic, multi-task environment. Modeling results suggested that many subjects may indeed have been acting appropriately by not using the autopilot in the way its designers intended. Although autopilot function was technically sound, this aid was not designed with due regard to the overall task context in which it was placed. These results demonstrate the need for additional research on how people may strategically manage their own resources, as well as those provided by automation, in an effort to keep workload and performance at acceptable levels.

Kirlik, Alex↗
NASA NTRS1991

Modeling the behavioral substrates of associate learning and memory - Adaptive neural models

Three adaptive single-neuron models based on neural analogies of behavior modification episodes are proposed, which attempt to bridge the gap between psychology and neurophysiology. The proposed models capture the predictive nature of Pavlovian conditioning, which is essential to the theory of adaptive/learning systems. The models learn to anticipate the occurrence of a conditioned response before the presence of a reinforcing stimulus when training is complete. Furthermore, each model can find the most nonredundant and earliest predictor of reinforcement. The behavior of the models accounts for several aspects of basic animal learning phenomena in Pavlovian conditioning beyond previous related models. Computer simulations show how well the models fit empirical data from various animal learning paradigms.

Lee, Chuen-Chien↗
NASA NTRS1988

Modeling creep behavior of fiber composites

A micromechanical model for the creep behavior of fiber composites is developed based on a typical cell consisting of a fiber and the surrounding matrix. The fiber is assumed to be linearly elastic and the matrix nonlinearly viscous. The creep strain rate in the matrix is assumed to be a function of stress. The nominal stress-strain relations are derived in the form of differential equations which are solved numerically for off-axis specimens under uniaxial loading. A potential function and the associated effective stress and effective creep strain rates are introduced to simplify the orthotropic relations.

Chen, J. L.↗
NASA NTRS2005

Human Performance Models of Pilot Behavior

Five modeling teams from industry and academia were chosen by the NASA Aviation Safety and Security Program to develop human performance models (HPM) of pilots performing taxi operations and runway instrument approaches with and without advanced displays. One representative from each team will serve as a panelist to discuss their team s model architecture, augmentations and advancements to HPMs, and aviation-safety related lessons learned. Panelists will discuss how modeling results are influenced by a model s architecture and structure, the role of the external environment, specific modeling advances and future directions and challenges for human performance modeling in aviation.

Foyle, David C.↗
NASA NTRS1979

Mathematical concepts for modeling human behavior in complex man-machine systems

Many human behavior (e.g., manual control) models have been found to be inadequate for describing processes in certain real complex man-machine systems. An attempt is made to find a way to overcome this problem by examining the range of applicability of existing mathematical models with respect to the hierarchy of human activities in real complex tasks. Automobile driving is chosen as a baseline scenario, and a hierarchy of human activities is derived by analyzing this task in general terms. A structural description leads to a block diagram and a time-sharing computer analogy.

Johannsen, G.↗
NASA NTRS1991

Modeling methods for the design and evaluation of fault-tolerant systems

The authors describe an approach for using directed graph simulation models, behavioral simulation models, and semi-Markov analytic models to implement early- to mid-design analysis activities specified by the SDIO BM/C3 Processor and Algorithm Working Group. The use of the models was demonstrated for a mission scenario requiring parallel, reliable computations with a maximum probability of system failure between 10-4 and 10-2 over a 5-year-preengagement phase and between 10-7 and 10-5 over a half-hour engagement phase.

Scheper, Charlotte O.↗
NASA NTRS2009

Towards Behavioral Reflexion Models

Software architecture has become essential in the struggle to manage today s increasingly large and complex systems. Software architecture views are created to capture important system characteristics on an abstract and, thus, comprehensible level. As the system is implemented and later maintained, it often deviates from the original design specification. Such deviations can have implication for the quality of the system, such as reliability, security, and maintainability. Software architecture compliance checking approaches, such as the reflexion model technique, have been proposed to address this issue by comparing the implementation to a model of the systems architecture design. However, architecture compliance checking approaches focus solely on structural characteristics and ignore behavioral conformance. This is especially an issue in Systems-of- Systems. Systems-of-Systems (SoS) are decompositions of large systems, into smaller systems for the sake of flexibility. Deviations of the implementation to its behavioral design often reduce the reliability of the entire SoS. An approach is needed that supports the reasoning about behavioral conformance on architecture level. In order to address this issue, we have developed an approach for comparing the implementation of a SoS to an architecture model of its behavioral design. The approach follows the idea of reflexion models and adopts it to support the compliance checking of behaviors. In this paper, we focus on sequencing properties as they play an important role in many SoS. Sequencing deviations potentially have a severe impact on the SoS correctness and qualities. The desired behavioral specification is defined in UML sequence diagram notation and behaviors are extracted from the SoS implementation. The behaviors are then mapped to the model of the desired behavior and the two are compared. Finally, a reflexion model is constructed that shows the deviations between behavioral design and implementation. This paper discusses the approach and shows how it can be applied to investigate reliability issues in SoS.

Ackermann, Christopher↗
NASA NTRS2010

Modeling Pilot Behavior for Assessing Integrated Alert and Notification Systems on Flight Decks

Numerous new flight deck configurations for caution, warning, and alerts can be conceived; yet testing them with human-in-the-Ioop experiments to evaluate each one would not be practical. New sensors, instruments, and displays are being put into cockpits every day and this is particularly true as we enter the dawn of the Next Generation Air Transportation System (NextGen). By modeling pilot behavior in a computer simulation, an unlimited number of unique caution, warning, and alert configurations can be evaluated 24/7 by a computer. These computer simulations can then identify the most promising candidate formats to further evaluate in higher fidelity, but more costly, Human-in-the-Ioop (HITL) simulations. Evaluations using batch simulations with human performance models saves time, money, and enables a broader consideration of possible caution, warning, and alerting configurations for future flight decks.

Cover, Mathew↗