Nineteen sixty-seven behavioral model of man - His chains revealed
Dynamic characteristics of physical-chemical systems in human behavior, and structural nature of brain
DYNAMIC PROPERTY↗
SEARCH · Engineering Papers
Results for “Behavior modeling”
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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Constraint-Based Off-Nominal Behavior Modeling for Europa Clipper
The risk analysis for the Europa Clipper mission evaluates the probability of mission failure based on the failure rates of individual components and dependencies among them. The probabilities are calculated by integrating over the intervals of time within which a fault occurs, accounting for an infinite number of cases. The response of the spacecraft to different faults can result in different schedules of activities, changing the intervals of integration. Europa currently uses models of spacecraft systems and components to simulate individual flight scenarios. The goal is to develop a framework for integrating, automating, and improving this modeling process. We describe an approach to generating the schedules for the different fault cases and determining the intervals for faults. It is not enough to just simulate individual cases because we are working with continuous variables that generate an infinite number of possible futures. Instead, we determine time windows within which certain faults can occur and use these time windows as bounds for integration. We found that determining these time windows is a constraint optimization problem. In order to represent these problems, we employ a language based on ontologies of behavior and scenarios. The language enables us to specify constraints in a simple, declarative syntax. A constraint-based analysis engine uses the declarative specification to identify bounds on system parameters and fill in details of behavior. For example, we created a detailed model of power generation, power use, and the corresponding effects on the battery in order to determine when an undervoltage fault can occur. An undervoltage during a trajectory correction maneuver requires that thrusting be interrupted for just enough time to recharge the battery such that the maneuver can be completed within battery limits. This behavior is generated based on the model to minimize the interruption time. For certain scenarios the constraint optimization problems were simple enough to be solved by hand, but the framework made the process substantially faster. It also produced solutions to other problems that we could not solve by hand or with existing tools and allowed us to generate and run many scenarios at once. The scenario language and engine greatly simplified the process of identifying time bounds and separating cases.
Everline, Chester J.↗
Session 3: Irradiation and Thermal Stesses - NRC Graphite Behavior Model
Graphite anisotropic microstructure Graphite crystal structure and basal planes Response to irradiation and temperature C-axis and a-axis behavior The effect of porosity Nano-and micro-length scale Microscopic to macroscopic response Material property changes Defect length-scale factors Internal stress build-up Irradiation induced dimensional change Temperature effects Stress increases & property changes
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
CORSAIR: A Framework for Human Mobility Prediction through Visit Characterization and Spatial Behavior Modeling
The rapid advancement of location acquisition technologies has led to the daily collection of vast amounts of mobile trajectory data, facilitating in-depth research on human mobility and enabling more accurate mobility prediction models. However, existing methodologies often fall short in capturing the intricate dynamics of human navigation and spatial behavior. This paper addresses this gap by exploring the multifaceted relationships between individuals and their environments, considering the diverse influences of personal preferences and experiences. Some places hold sentimental value and are visited frequently, while others serve as transient points of passage. To model these differences, we introduce CORSAIR, a novel visit characterization framework that leverages visitation patterns and dwell times to delineate an individual’s relationship with specific places. CORSAIR classifies visits into seven distinct types: casual, occasional, routine, special, anchor, important, and resettling. Also, we show that explicitly recognizing these distinct visit types and incorporating nuanced visit intents into mobility prediction models leads to a substantial improvement in prediction accuracy. This distinction allows for more precise modeling of the individual’s transitions, enhancing the personalization and relevance of location-based services. Our findings suggest that a deeper understanding of the complexities of individual-environment interactions is crucial for developing effective predictive tools in mobility research.
Amichi, Licia [ORNL] (ORCID:0000000177631394)↗
Assessing High Burnup U-19Pu-10Zr Fuel Performance against Historical and Modeled Behavior
Advancing the deployment of sodium-cooled fast reactors (SFRs) requires thorough testing of metallic fuel pins under accident conditions to establish safe operational limits of high burnup fuel. To conduct transient testing, a comprehensive understanding of steady-state fuel behavior obtained through both experimental characterization and accurate predictive capabilities is needed. This study comparatively assesses the steady-state irradiation performance of two high burnup U-19Pu-10Zr fuel pins, DP-36 and DP-40, irradiated under prototypic fast reactor conditions in preparation for planned safety testing at the Transient Reactor Test Facility. Since DP-40 was designated for use in the test and DP-36 serves as its sibling pin, non-destructive, engineering-scale post-irradiation examinations (PIE) were conducted on both pins while destructive examinations were performed exclusively on DP-36. The results were then assessed against historical performance data from similar fuel pins irradiated in the Experimental Breeder Reactor-II. Additionally, the steady-state irradiation of each pin was modeled using the BISON fuel performance code to assess the accuracy of current modeling capabilities in predicting the baseline irradiation behavior. Non-destructive examinations included neutron radiography to measure fuel column elongation, gamma scanning to verify pin integrity and fission product migration, and profilometry to assess dimensional changes. Benchmarking against existing PIE data revealed consistent patterns in axial fuel column growth and cladding diametral strain, though both pins exhibited longer low-density “fluff” structures, which can have implications for core reactivity and source term calculations. Destructive examinations on DP-36 included fission gas release analysis and sectioning for optical microscopy, which showed more complex constituent redistribution patterns than the traditionally accepted 3-ring model. The axial evolution of fractional areas and porosities of each of the redistributed zones were quantified and presented. Modeling comparisons showed agreement in fractional fission gas release but consistently overestimated axial and radial swelling and disagreed with measured axial porosity patterns. These conservative overpredictions suggested that the pins would appear closer to failure or operational limits at the start of transient tests, potentially leading to higher strain accumulation during the transient. While conservative estimates provide safety margins, they can negatively impact fuel economics. A review of the swelling models identified areas for improvement in the gaseous swelling, solid swelling, and fuel hot-pressing models when applied to ternary fuel. The results of this study highlight the critical importance of conducting pre-test characterization on both test and sibling pins to accurately capture steady-state fuel behavior, providing a precise baseline for post-test evaluations and essential inputs for transient modeling of the planned experiments. The analysis also revealed significant data gaps that require further investigation to enhance the understanding and prediction of fuel swelling and pore dynamics. Collecting comprehensive data across different irradiation conditions, burnup levels, and fuel compositions are essential for refining existing models and developing mechanistic models for both binary and ternary metallic fuels, ultimately improving the integration of modeling and experimental approaches in accident testing.
11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Graphite Material Behavior: NRC Graphite Behavior Model
Introduction to graphite Fabrication of graphite Unique features of nuclear grade graphite Providing the properties As-fabricated material properties of interest Thermal diff, thermal stability, mechanical strength, etc. General graphite behavior and degradation Microstructure: key to behavior Crystallographic structure Basal plane (covalent) bonding Porosity and pore microstructure Degradation Irradiation behavior Oxidation behavior Molten salt issues
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Behavioral Models of Differential Amplifiers with Hammerstein Model
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Thieme, Ethan Connor↗
Electric Vehicle Charging Data Falsification Attacks Utilizing Behavioral Models
A charging station (CS) and its associated electric vehicle supply equipment (EVSE) and charging electric vehicle (EV) interactions are potential targets for data falsification attacks since CSs are typically unmanned public facilities that are connected to the internet and EVs incorporate the vulnerable CAN bus network, which are both susceptible to remote attacks. The research question being addressed is how is the EV owner and CS negatively affected by CAN bus EV battery current sensor and battery temperature sensor data falsification attacks. Negative effects include economic losses from reduced life span of the battery, battery thermal runaway and fire (and potential loss of surrounding structure), and reduced utilization of the CS due to delayed departure time (longer charging times).
25 ENERGY STORAGE↗
Behavioral Models Of Operational Amplifiers with a Hammerstein Structure
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Thieme, Ethan Connor [Sandia National Laboratories↗
A generalized behavioral model for rotating short period comets with spectral orbital elements and axial orientation
A generalized model for short period comets is developed which integrates in a fairly rigorous manner the isolation history of regions on rotating comets with specified axial orientation and the complex feedback processes involving heat, gas and dust transport, dust mantle development and coma opacity. Attention is focused on development, reconfiguration and partial or complete launching of dust mantles and the reciprocal effects of these three processes on ice surface temperature and gas and dust production. The dust mantle controls the H2O flux not only by its effect on the temperature at the ice interface but (dominantly) by its dynamic stability which strongly influences vapor diffusivity. The model includes the effects of latitude, rotation and spin axis orientation are included and applied to an initially homogeneous sphere of H2O ice and silicate using the orbital parameters of comet Encke. Numerous variations of the model, using combinations of grain size distribution, dust-to-ice ratio, latitude and spin axis orientation, are presented and discussed. Resulted for a similar nonrotating, constant Sun orientation models are also included.
Fanale, F. P.↗
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.↗
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's Use of Human Behavior Models for Concept Development and Evaluation
Overview of NASA's use of computational approaches and methods to support research goals, of human performance models, with a focus on examples of the methods used in Code TH and TI at NASA Ames, followed by an in depth review of MIDAS' current FAA work.
Gore, Brian F.↗
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↗
Graphite Oxidation Behavior: NRC Graphite Behavior Model
Graphite microstructure and oxidation Graphite crystal structure and basal planes Reactive surface area sites Zig-zag and Arm-chair Pore microstructure effects Interconnectivity Reactivity and oxygen transport Oxygen-graphitereaction Not C-O reaction! Temperature effects Oxygen diffusion to graphite Diffusion into the microstructure High temperature vs low temperature diffusion Oxidation: It’s a gradient of factors
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
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.↗
Real-World Driving Features for Identifying Intelligent Driver Model Parameters
Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver. It stands to reason that determining the parameter values from real-world driving data would serve the purpose of representing a real-world driver. Although the published literature is replete with techniques and consequences of using real-world driving data to determine parameter values for parametric driver models, none have explored them in the context of using shorter driving features where the parameter values may change over the course of a single trip for the same driver. In this study we consider the “intelligent driver model” (IDM) as our driver behavior model and use real-world driving data from the Transportation Secure Data Center (TSDC) maintained at the National Renewable Energy Laboratory (NREL). The TSDC includes real-world travel data from across the United States, from which NREL has created a wide range of driving routes consisting of road features such as speed limits, stop locations, and turn locations. The real-world driving data are categorized into different driving regimes and extracted into driving features. The driving features are then used to calibrate the parameter values for the IDM. The distribution of the parameters and the relationships among them are reported. The insights obtained from this study enable judicious usage of IDM or similar parametric driver models to represent baseline human driver behavior in simulations.
27 ARPA - Advanced Research Projects Agency-Energy↗