Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, Brian; Wood, Richard T.

1997-01-01

A method for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system.

Design and implementation of space physics multi-model application integration based on web

NASA Astrophysics Data System (ADS)

Jiang, Wenping; Zou, Ziming

With the development of research on space environment and space science, how to develop network online computing environment of space weather, space environment and space physics models for Chinese scientific community is becoming more and more important in recent years. Currently, There are two software modes on space physics multi-model application integrated system (SPMAIS) such as C/S and B/S. the C/S mode which is traditional and stand-alone, demands a team or workshop from many disciplines and specialties to build their own multi-model application integrated system, that requires the client must be deployed in different physical regions when user visits the integrated system. Thus, this requirement brings two shortcomings: reducing the efficiency of researchers who use the models to compute; inconvenience of accessing the data. Therefore, it is necessary to create a shared network resource access environment which could help users to visit the computing resources of space physics models through the terminal quickly for conducting space science research and forecasting spatial environment. The SPMAIS develops high-performance, first-principles in B/S mode based on computational models of the space environment and uses these models to predict "Space Weather", to understand space mission data and to further our understanding of the solar system. the main goal of space physics multi-model application integration system (SPMAIS) is to provide an easily and convenient user-driven online models operating environment. up to now, the SPMAIS have contained dozens of space environment models , including international AP8/AE8 IGRF T96 models and solar proton prediction model geomagnetic transmission model etc. which are developed by Chinese scientists. another function of SPMAIS is to integrate space observation data sets which offers input data for models online high-speed computing. In this paper, service-oriented architecture (SOA) concept that divides system into independent modules according to different business needs is applied to solve the problem of the independence of the physical space between multiple models. The classic MVC(Model View Controller) software design pattern is concerned to build the architecture of space physics multi-model application integrated system. The JSP+servlet+javabean technology is used to integrate the web application programs of space physics multi-model. It solves the problem of multi-user requesting the same job of model computing and effectively balances each server computing tasks. In addition, we also complete follow tasks: establishing standard graphical user interface based on Java Applet application program; Designing the interface between model computing and model computing results visualization; Realizing three-dimensional network visualization without plug-ins; Using Java3D technology to achieve a three-dimensional network scene interaction; Improved ability to interact with web pages and dynamic execution capabilities, including rendering three-dimensional graphics, fonts and color control. Through the design and implementation of the SPMAIS based on Web, we provide an online computing and application runtime environment of space physics multi-model. The practical application improves that researchers could be benefit from our system in space physics research and engineering applications.

Physical Uncertainty Bounds (PUB)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vaughan, Diane Elizabeth; Preston, Dean L.

2015-03-19

This paper introduces and motivates the need for a new methodology for determining upper bounds on the uncertainties in simulations of engineered systems due to limited fidelity in the composite continuum-level physics models needed to simulate the systems. We show that traditional uncertainty quantification methods provide, at best, a lower bound on this uncertainty. We propose to obtain bounds on the simulation uncertainties by first determining bounds on the physical quantities or processes relevant to system performance. By bounding these physics processes, as opposed to carrying out statistical analyses of the parameter sets of specific physics models or simply switchingmore » out the available physics models, one can obtain upper bounds on the uncertainties in simulated quantities of interest.« less

Technical Manual for the SAM Physical Trough Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wagner, M. J.; Gilman, P.

2011-06-01

NREL, in conjunction with Sandia National Lab and the U.S Department of Energy, developed the System Advisor Model (SAM) analysis tool for renewable energy system performance and economic analysis. This paper documents the technical background and engineering formulation for one of SAM's two parabolic trough system models in SAM. The Physical Trough model calculates performance relationships based on physical first principles where possible, allowing the modeler to predict electricity production for a wider range of component geometries than is possible in the Empirical Trough model. This document describes the major parabolic trough plant subsystems in detail including the solar field,more » power block, thermal storage, piping, auxiliary heating, and control systems. This model makes use of both existing subsystem performance modeling approaches, and new approaches developed specifically for SAM.« less

A proposed application programming interface for a physical volume repository

NASA Technical Reports Server (NTRS)

Jones, Merritt; Williams, Joel; Wrenn, Richard

1996-01-01

The IEEE Storage System Standards Working Group (SSSWG) has developed the Reference Model for Open Storage Systems Interconnection, Mass Storage System Reference Model Version 5. This document, provides the framework for a series of standards for application and user interfaces to open storage systems. More recently, the SSSWG has been developing Application Programming Interfaces (APIs) for the individual components defined by the model. The API for the Physical Volume Repository is the most fully developed, but work is being done on APIs for the Physical Volume Library and for the Mover also. The SSSWG meets every other month, and meetings are open to all interested parties. The Physical Volume Repository (PVR) is responsible for managing the storage of removable media cartridges and for mounting and dismounting these cartridges onto drives. This document describes a model which defines a Physical Volume Repository, and gives a brief summary of the Application Programming Interface (API) which the IEEE Storage Systems Standards Working Group (SSSWG) is proposing as the standard interface for the PVR.

Integrating 3D geological information with a national physically-based hydrological modelling system

NASA Astrophysics Data System (ADS)

Lewis, Elizabeth; Parkin, Geoff; Kessler, Holger; Whiteman, Mark

2016-04-01

Robust numerical models are an essential tool for informing flood and water management and policy around the world. Physically-based hydrological models have traditionally not been used for such applications due to prohibitively large data, time and computational resource requirements. Given recent advances in computing power and data availability, a robust, physically-based hydrological modelling system for Great Britain using the SHETRAN model and national datasets has been created. Such a model has several advantages over less complex systems. Firstly, compared with conceptual models, a national physically-based model is more readily applicable to ungauged catchments, in which hydrological predictions are also required. Secondly, the results of a physically-based system may be more robust under changing conditions such as climate and land cover, as physical processes and relationships are explicitly accounted for. Finally, a fully integrated surface and subsurface model such as SHETRAN offers a wider range of applications compared with simpler schemes, such as assessments of groundwater resources, sediment and nutrient transport and flooding from multiple sources. As such, SHETRAN provides a robust means of simulating numerous terrestrial system processes which will add physical realism when coupled to the JULES land surface model. 306 catchments spanning Great Britain have been modelled using this system. The standard configuration of this system performs satisfactorily (NSE > 0.5) for 72% of catchments and well (NSE > 0.7) for 48%. Many of the remaining 28% of catchments that performed relatively poorly (NSE < 0.5) are located in the chalk in the south east of England. As such, the British Geological Survey 3D geology model for Great Britain (GB3D) has been incorporated, for the first time in any hydrological model, to pave the way for improvements to be made to simulations of catchments with important groundwater regimes. This coupling has involved development of software to allow for easy incorporation of geological information into SHETRAN for any model setup. The addition of more realistic subsurface representation following this approach is shown to greatly improve model performance in areas dominated by groundwater processes. The resulting modelling system has great potential to be used as a resource at national, regional and local scales in an array of different applications, including climate change impact assessments, land cover change studies and integrated assessments of groundwater and surface water resources.

Quasi-dynamic earthquake fault systems with rheological heterogeneity

NASA Astrophysics Data System (ADS)

Brietzke, G. B.; Hainzl, S.; Zoeller, G.; Holschneider, M.

2009-12-01

Seismic risk and hazard estimates mostly use pure empirical, stochastic models of earthquake fault systems tuned specifically to the vulnerable areas of interest. Although such models allow for reasonable risk estimates, such models cannot allow for physical statements of the described seismicity. In contrary such empirical stochastic models, physics based earthquake fault systems models allow for a physical reasoning and interpretation of the produced seismicity and system dynamics. Recently different fault system earthquake simulators based on frictional stick-slip behavior have been used to study effects of stress heterogeneity, rheological heterogeneity, or geometrical complexity on earthquake occurrence, spatial and temporal clustering of earthquakes, and system dynamics. Here we present a comparison of characteristics of synthetic earthquake catalogs produced by two different formulations of quasi-dynamic fault system earthquake simulators. Both models are based on discretized frictional faults embedded in an elastic half-space. While one (1) is governed by rate- and state-dependent friction with allowing three evolutionary stages of independent fault patches, the other (2) is governed by instantaneous frictional weakening with scheduled (and therefore causal) stress transfer. We analyze spatial and temporal clustering of events and characteristics of system dynamics by means of physical parameters of the two approaches.

On the Role of Mathematics in Physics

ERIC Educational Resources Information Center

Quale, Andreas

2011-01-01

I examine the association between the observable physical world and the mathematical models of theoretical physics. These models will exhibit many entities that have no counterpart in the physical world, but which are still necessary for the mathematical description of physical systems. Moreover, when the model is applied to the analysis of a…

Parametric model of servo-hydraulic actuator coupled with a nonlinear system: Experimental validation

NASA Astrophysics Data System (ADS)

Maghareh, Amin; Silva, Christian E.; Dyke, Shirley J.

2018-05-01

Hydraulic actuators play a key role in experimental structural dynamics. In a previous study, a physics-based model for a servo-hydraulic actuator coupled with a nonlinear physical system was developed. Later, this dynamical model was transformed into controllable canonical form for position tracking control purposes. For this study, a nonlinear device is designed and fabricated to exhibit various nonlinear force-displacement profiles depending on the initial condition and the type of materials used as replaceable coupons. Using this nonlinear system, the controllable canonical dynamical model is experimentally validated for a servo-hydraulic actuator coupled with a nonlinear physical system.

Evaluation of snow modeling with Noah and Noah-MP land surface models in NCEP GFS/CFS system

NASA Astrophysics Data System (ADS)

Dong, J.; Ek, M. B.; Wei, H.; Meng, J.

2017-12-01

Land surface serves as lower boundary forcing in global forecast system (GFS) and climate forecast system (CFS), simulating interactions between land and the atmosphere. Understanding the underlying land model physics is a key to improving weather and seasonal prediction skills. With the upgrades in land model physics (e.g., release of newer versions of a land model), different land initializations, changes in parameterization schemes used in the land model (e.g., land physical parametrization options), and how the land impact is handled (e.g., physics ensemble approach), it always prompts the necessity that climate prediction experiments need to be re-conducted to examine its impact. The current NASA LIS (version 7) integrates NOAA operational land surface and hydrological models (NCEP's Noah, versions from 2.7.1 to 3.6 and the future Noah-MP), high-resolution satellite and observational data, and land DA tools. The newer versions of the Noah LSM used in operational models have a variety of enhancements compared to older versions, where the Noah-MP allows for different physics parameterization options and the choice could have large impact on physical processes underlying seasonal predictions. These impacts need to be reexamined before implemented into NCEP operational systems. A set of offline numerical experiments driven by the GFS forecast forcing have been conducted to evaluate the impact of snow modeling with daily Global Historical Climatology Network (GHCN).

Physical Models that Provide Guidance in Visualization Deconstruction in an Inorganic Context

ERIC Educational Resources Information Center

Schiltz, Holly K.; Oliver-Hoyo, Maria T.

2012-01-01

Three physical model systems have been developed to help students deconstruct the visualization needed when learning symmetry and group theory. The systems provide students with physical and visual frames of reference to facilitate the complex visualization involved in symmetry concepts. The permanent reflection plane demonstration presents an…

Building Mental Models by Dissecting Physical Models

ERIC Educational Resources Information Center

Srivastava, Anveshna

2016-01-01

When students build physical models from prefabricated components to learn about model systems, there is an implicit trade-off between the physical degrees of freedom in building the model and the intensity of instructor supervision needed. Models that are too flexible, permitting multiple possible constructions require greater supervision to…

Advanced Ground Systems Maintenance Physics Models for Diagnostics Project

NASA Technical Reports Server (NTRS)

Harp, Janicce Leshay

2014-01-01

The project will use high-fidelity physics models and simulations to simulate real-time operations of cryogenic and systems and calculate the status/health of the systems. The project enables the delivery of system health advisories to ground system operators. The capability will also be used to conduct planning and analysis of cryogenic system operations.

Modeling Physical Systems Using Vensim PLE Systems Dynamics Software

ERIC Educational Resources Information Center

Widmark, Stephen

2012-01-01

Many physical systems are described by time-dependent differential equations or systems of such equations. This makes it difficult for students in an introductory physics class to solve many real-world problems since these students typically have little or no experience with this kind of mathematics. In my high school physics classes, I address…

Can We Practically Bring Physics-based Modeling Into Operational Analytics Tools?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Granderson, Jessica; Bonvini, Marco; Piette, Mary Ann

We present that analytics software is increasingly used to improve and maintain operational efficiency in commercial buildings. Energy managers, owners, and operators are using a diversity of commercial offerings often referred to as Energy Information Systems, Fault Detection and Diagnostic (FDD) systems, or more broadly Energy Management and Information Systems, to cost-effectively enable savings on the order of ten to twenty percent. Most of these systems use data from meters and sensors, with rule-based and/or data-driven models to characterize system and building behavior. In contrast, physics-based modeling uses first-principles and engineering models (e.g., efficiency curves) to characterize system and buildingmore » behavior. Historically, these physics-based approaches have been used in the design phase of the building life cycle or in retrofit analyses. Researchers have begun exploring the benefits of integrating physics-based models with operational data analytics tools, bridging the gap between design and operations. In this paper, we detail the development and operator use of a software tool that uses hybrid data-driven and physics-based approaches to cooling plant FDD and optimization. Specifically, we describe the system architecture, models, and FDD and optimization algorithms; advantages and disadvantages with respect to purely data-driven approaches; and practical implications for scaling and replicating these techniques. Finally, we conclude with an evaluation of the future potential for such tools and future research opportunities.« less

Minding the Cyber-Physical Gap: Model-Based Analysis and Mitigation of Systemic Perception-Induced Failure.

PubMed

Mordecai, Yaniv; Dori, Dov

2017-07-17

The cyber-physical gap (CPG) is the difference between the 'real' state of the world and the way the system perceives it. This discrepancy often stems from the limitations of sensing and data collection technologies and capabilities, and is inevitable at some degree in any cyber-physical system (CPS). Ignoring or misrepresenting such limitations during system modeling, specification, design, and analysis can potentially result in systemic misconceptions, disrupted functionality and performance, system failure, severe damage, and potential detrimental impacts on the system and its environment. We propose CPG-Aware Modeling & Engineering (CPGAME), a conceptual model-based approach to capturing, explaining, and mitigating the CPG. CPGAME enhances the systems engineer's ability to cope with CPGs, mitigate them by design, and prevent erroneous decisions and actions. We demonstrate CPGAME by applying it for modeling and analysis of the 1979 Three Miles Island 2 nuclear accident, and show how its meltdown could be mitigated. We use ISO-19450:2015-Object Process Methodology as our conceptual modeling framework.

Terminator field-aligned current system: A new finding from model-assimilated data set (MADS)

NASA Astrophysics Data System (ADS)

Zhu, L.; Schunk, R. W.; Scherliess, L.; Sojka, J. J.; Gardner, L. C.; Eccles, J. V.; Rice, D.

2013-12-01

Physics-based data assimilation models have been recognized by the space science community as the most accurate approach to specify and forecast the space weather of the solar-terrestrial environment. The model-assimilated data sets (MADS) produced by these models constitute an internally consistent time series of global three-dimensional fields whose accuracy can be estimated. Because of its internal consistency of physics and completeness of descriptions on the status of global systems, the MADS has also been a powerful tool to identify the systematic errors in measurements, reveal the missing physics in physical models, and discover the important dynamical physical processes that are inadequately observed or missed by measurements due to observational limitations. In the past years, we developed a data assimilation model for the high-latitude ionospheric plasma dynamics and electrodynamics. With a set of physical models, an ensemble Kalman filter, and the ingestion of data from multiple observations, the data assimilation model can produce a self-consistent time-series of the complete descriptions of the global high-latitude ionosphere, which includes the convection electric field, horizontal and field-aligned currents, conductivity, as well as 3-D plasma densities and temperatures, In this presentation, we will show a new field-aligned current system discovered from the analysis of the MADS produced by our data assimilation model. This new current system appears and develops near the ionospheric terminator. The dynamical features of this current system will be described and its connection to the active role of the ionosphere in the M-I coupling will be discussed.

Modelling Systems of Classical/Quantum Identical Particles by Focusing on Algorithms

ERIC Educational Resources Information Center

Guastella, Ivan; Fazio, Claudio; Sperandeo-Mineo, Rosa Maria

2012-01-01

A procedure modelling ideal classical and quantum gases is discussed. The proposed approach is mainly based on the idea that modelling and algorithm analysis can provide a deeper understanding of particularly complex physical systems. Appropriate representations and physical models able to mimic possible pseudo-mechanisms of functioning and having…

Multi-views storage model and access methods of conversation history in converged IP messaging system

NASA Astrophysics Data System (ADS)

Lu, Meilian; Yang, Dong; Zhou, Xing

2013-03-01

Based on the analysis of the requirements of conversation history storage in CPM (Converged IP Messaging) system, a Multi-views storage model and access methods of conversation history are proposed. The storage model separates logical views from physical storage and divides the storage into system managed region and user managed region. It simultaneously supports conversation view, system pre-defined view and user-defined view of storage. The rationality and feasibility of multi-view presentation, the physical storage model and access methods are validated through the implemented prototype. It proves that, this proposal has good scalability, which will help to optimize the physical data storage structure and improve storage performance.

Statistical inference of empirical constituents in partitioned analysis from integral-effect experiments: An application in thermo-mechanical coupling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stevens, Garrison N.; Atamturktur, Sez; Brown, D. Andrew

Rapid advancements in parallel computing over the last two decades have enabled simulations of complex, coupled systems through partitioning. In partitioned analysis, independently developed constituent models communicate, representing dependencies between multiple physical phenomena that occur in the full system. Figure 1 schematically demonstrates a coupled system with two constituent models, each resolving different physical behavior. In this figure, the constituent model, denoted as the “consumer,” relies upon some input parameter that is being provided by the constituent model acting as a “feeder”. The role of the feeder model is to map operating conditions (i.e. those that are stimulating the process)more » to consumer inputs, thus providing functional inputs to the consumer model*. Problems arise if the feeder model cannot be built–a challenge that is prevalent for highly complex systems in extreme operational conditions that push the limits of our understanding of underlying physical behavior. Often, these are also the situations where separate-effect experiments isolating the physical phenomena are not available; meaning that experimentally determining the unknown constituent behavior is not possible (Bauer and Holland, 1995; Unal et al., 2013), and that integral-effect experiments that reflect the behavior of the complete system tend to be the only available observations. In this paper, the authors advocate for the usefulness of integral-effect experiments in furthering a model developer’s knowledge of the physics principles governing the system behavior of interest.« less

Statistical inference of empirical constituents in partitioned analysis from integral-effect experiments: An application in thermo-mechanical coupling

DOE PAGES

Stevens, Garrison N.; Atamturktur, Sez; Brown, D. Andrew; ...

2018-04-16

Rapid advancements in parallel computing over the last two decades have enabled simulations of complex, coupled systems through partitioning. In partitioned analysis, independently developed constituent models communicate, representing dependencies between multiple physical phenomena that occur in the full system. Figure 1 schematically demonstrates a coupled system with two constituent models, each resolving different physical behavior. In this figure, the constituent model, denoted as the “consumer,” relies upon some input parameter that is being provided by the constituent model acting as a “feeder”. The role of the feeder model is to map operating conditions (i.e. those that are stimulating the process)more » to consumer inputs, thus providing functional inputs to the consumer model*. Problems arise if the feeder model cannot be built–a challenge that is prevalent for highly complex systems in extreme operational conditions that push the limits of our understanding of underlying physical behavior. Often, these are also the situations where separate-effect experiments isolating the physical phenomena are not available; meaning that experimentally determining the unknown constituent behavior is not possible (Bauer and Holland, 1995; Unal et al., 2013), and that integral-effect experiments that reflect the behavior of the complete system tend to be the only available observations. In this paper, the authors advocate for the usefulness of integral-effect experiments in furthering a model developer’s knowledge of the physics principles governing the system behavior of interest.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campbell, Philip LaRoche

At the end of his life, Stephen Jay Kline, longtime professor of mechanical engineering at Stanford University, completed a book on how to address complex systems. The title of the book is 'Conceptual Foundations of Multi-Disciplinary Thinking' (1995), but the topic of the book is systems. Kline first establishes certain limits that are characteristic of our conscious minds. Kline then establishes a complexity measure for systems and uses that complexity measure to develop a hierarchy of systems. Kline then argues that our minds, due to their characteristic limitations, are unable to model the complex systems in that hierarchy. Computers aremore » of no help to us here. Our attempts at modeling these complex systems are based on the way we successfully model some simple systems, in particular, 'inert, naturally-occurring' objects and processes, such as what is the focus of physics. But complex systems overwhelm such attempts. As a result, the best we can do in working with these complex systems is to use a heuristic, what Kline calls the 'Guideline for Complex Systems.' Kline documents the problems that have developed due to 'oversimple' system models and from the inappropriate application of a system model from one domain to another. One prominent such problem is the Procrustean attempt to make the disciplines that deal with complex systems be 'physics-like.' Physics deals with simple systems, not complex ones, using Kline's complexity measure. The models that physics has developed are inappropriate for complex systems. Kline documents a number of the wasteful and dangerous fallacies of this type.« less

Simulating the Rayleigh-Taylor instability with the Ising model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ball, Justin R.; Elliott, James B.

2011-08-26

The Ising model, implemented with the Metropolis algorithm and Kawasaki dynamics, makes a system with its own physics, distinct from the real world. These physics are sophisticated enough to model behavior similar to the Rayleigh-Taylor instability and by better understanding these physics, we can learn how to modify the system to better re ect reality. For example, we could add a v x and a v y to each spin and modify the exchange rules to incorporate them, possibly using two body scattering laws to construct a more realistic system.

Tinamit: Making coupled system dynamics models accessible to stakeholders

NASA Astrophysics Data System (ADS)

Malard, Julien; Inam Baig, Azhar; Rojas Díaz, Marcela; Hassanzadeh, Elmira; Adamowski, Jan; Tuy, Héctor; Melgar-Quiñonez, Hugo

2017-04-01

Model coupling is increasingly used as a method of combining the best of two models when representing socio-environmental systems, though barriers to successful model adoption by stakeholders are particularly present with the use of coupled models, due to their high complexity and typically low implementation flexibility. Coupled system dynamics - physically-based modelling is a promising method to improve stakeholder participation in environmental modelling while retaining a high level of complexity for physical process representation, as the system dynamics components are readily understandable and can be built by stakeholders themselves. However, this method is not without limitations in practice, including 1) inflexible and complicated coupling methods, 2) difficult model maintenance after the end of the project, and 3) a wide variety of end-user cultures and languages. We have developed the open-source Python-language software tool Tinamit to overcome some of these limitations to the adoption of stakeholder-based coupled system dynamics - physically-based modelling. The software is unique in 1) its inclusion of both a graphical user interface (GUI) and a library of available commands (API) that allow users with little or no coding abilities to rapidly, effectively, and flexibly couple models, 2) its multilingual support for the GUI, allowing users to couple models in their preferred language (and to add new languages as necessary for their community work), and 3) its modular structure allowing for very easy model coupling and modification without the direct use of code, and to which programming-savvy users can easily add support for new types of physically-based models. We discuss how the use of Tinamit for model coupling can greatly increase the accessibility of coupled models to stakeholders, using an example of a stakeholder-built system dynamics model of soil salinity issues in Pakistan coupled with the physically-based soil salinity and water flow model SAHYSMOD. Different socioeconomic and environmental policies for soil salinity remediation are tested within the coupled model, allowing for the identification of the most efficient actions from an environmental and a farmer economy standpoint while taking into account the complex feedbacks between socioeconomics and the physical environment.

Graph modeling systems and methods

DOEpatents

Neergaard, Mike

2015-10-13

An apparatus and a method for vulnerability and reliability modeling are provided. The method generally includes constructing a graph model of a physical network using a computer, the graph model including a plurality of terminating vertices to represent nodes in the physical network, a plurality of edges to represent transmission paths in the physical network, and a non-terminating vertex to represent a non-nodal vulnerability along a transmission path in the physical network. The method additionally includes evaluating the vulnerability and reliability of the physical network using the constructed graph model, wherein the vulnerability and reliability evaluation includes a determination of whether each terminating and non-terminating vertex represents a critical point of failure. The method can be utilized to evaluate wide variety of networks, including power grid infrastructures, communication network topologies, and fluid distribution systems.

Development and evaluation of a physics-based windblown dust emission scheme implemented in the CMAQ modeling system

EPA Science Inventory

A new windblown dust emission treatment was incorporated in the Community Multiscale Air Quality (CMAQ) modeling system. This new model treatment has been built upon previously developed physics-based parameterization schemes from the literature. A distinct and novel feature of t...

Modeling and simulation of high dimensional stochastic multiscale PDE systems at the exascale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zabaras, Nicolas J.

2016-11-08

Predictive Modeling of multiscale and Multiphysics systems requires accurate data driven characterization of the input uncertainties, and understanding of how they propagate across scales and alter the final solution. This project develops a rigorous mathematical framework and scalable uncertainty quantification algorithms to efficiently construct realistic low dimensional input models, and surrogate low complexity systems for the analysis, design, and control of physical systems represented by multiscale stochastic PDEs. The work can be applied to many areas including physical and biological processes, from climate modeling to systems biology.

Systems Models for Transportation Problems : Part 2. The Social Physics for Modern Societies - the Role of the Cities

DOT National Transportation Integrated Search

1977-09-01

The objective of the research was to make use of a physically based social systems model, developed earlier, to study the determinants of city sizes and their national interactions. In particular, information on the role of a transportation system in...

Model-based reasoning in the physics laboratory: Framework and initial results

NASA Astrophysics Data System (ADS)

Zwickl, Benjamin M.; Hu, Dehui; Finkelstein, Noah; Lewandowski, H. J.

2015-12-01

[This paper is part of the Focused Collection on Upper Division Physics Courses.] We review and extend existing frameworks on modeling to develop a new framework that describes model-based reasoning in introductory and upper-division physics laboratories. Constructing and using models are core scientific practices that have gained significant attention within K-12 and higher education. Although modeling is a broadly applicable process, within physics education, it has been preferentially applied to the iterative development of broadly applicable principles (e.g., Newton's laws of motion in introductory mechanics). A significant feature of the new framework is that measurement tools (in addition to the physical system being studied) are subjected to the process of modeling. Think-aloud interviews were used to refine the framework and demonstrate its utility by documenting examples of model-based reasoning in the laboratory. When applied to the think-aloud interviews, the framework captures and differentiates students' model-based reasoning and helps identify areas of future research. The interviews showed how students productively applied similar facets of modeling to the physical system and measurement tools: construction, prediction, interpretation of data, identification of model limitations, and revision. Finally, we document students' challenges in explicitly articulating assumptions when constructing models of experimental systems and further challenges in model construction due to students' insufficient prior conceptual understanding. A modeling perspective reframes many of the seemingly arbitrary technical details of measurement tools and apparatus as an opportunity for authentic and engaging scientific sense making.

Minding the Cyber-Physical Gap: Model-Based Analysis and Mitigation of Systemic Perception-Induced Failure

PubMed Central

2017-01-01

The cyber-physical gap (CPG) is the difference between the ‘real’ state of the world and the way the system perceives it. This discrepancy often stems from the limitations of sensing and data collection technologies and capabilities, and is inevitable at some degree in any cyber-physical system (CPS). Ignoring or misrepresenting such limitations during system modeling, specification, design, and analysis can potentially result in systemic misconceptions, disrupted functionality and performance, system failure, severe damage, and potential detrimental impacts on the system and its environment. We propose CPG-Aware Modeling & Engineering (CPGAME), a conceptual model-based approach to capturing, explaining, and mitigating the CPG. CPGAME enhances the systems engineer’s ability to cope with CPGs, mitigate them by design, and prevent erroneous decisions and actions. We demonstrate CPGAME by applying it for modeling and analysis of the 1979 Three Miles Island 2 nuclear accident, and show how its meltdown could be mitigated. We use ISO-19450:2015—Object Process Methodology as our conceptual modeling framework. PMID:28714910

Development of physical and mathematical models for the Porous Ceramic Tube Plant Nutrification System (PCTPNS)

NASA Technical Reports Server (NTRS)

Tsao, D. Teh-Wei; Okos, M. R.; Sager, J. C.; Dreschel, T. W.

1992-01-01

A physical model of the Porous Ceramic Tube Plant Nutrification System (PCTPNS) was developed through microscopic observations of the tube surface under various operational conditions. In addition, a mathematical model of this system was developed which incorporated the effects of the applied suction pressure, surface tension, and gravitational forces as well as the porosity and physical dimensions of the tubes. The flow of liquid through the PCTPNS was thus characterized for non-biological situations. One of the key factors in the verification of these models is the accurate and rapid measurement of the 'wetness' or holding capacity of the ceramic tubes. This study evaluated a thermistor based moisture sensor device and recommendations for future research on alternative sensing devices are proposed. In addition, extensions of the physical and mathematical models to include the effects of plant physiology and growth are also discussed for future research.

Proposed standards for peer-reviewed publication of computer code

USDA-ARS?s Scientific Manuscript database

Computer simulation models are mathematical abstractions of physical systems. In the area of natural resources and agriculture, these physical systems encompass selected interacting processes in plants, soils, animals, or watersheds. These models are scientific products and have become important i...

On Mechanical Transitions in Biologically Motivated Soft Matter Systems

NASA Astrophysics Data System (ADS)

Fogle, Craig

The notion of phase transitions as a characterization of a change in physical properties pervades modern physics. Such abrupt and fundamental changes in the behavior of physical systems are evident in condensed matter system and also occur in nuclear and subatomic settings. While this concept is less prevalent in the field of biology, recent advances have pointed to its relevance in a number of settings. Recent studies have modeled both the cell cycle and cancer as phase transition in physical systems. In this dissertation we construct simplified models for two biological systems. As described by those models, both systems exhibit phase transitions. The first model is inspired by the shape transition in the nuclei of neutrophils during differentiation. During differentiation the nucleus transitions from spherical to a shape often described as "beads on a string." As a simplified model of this system, we investigate the spherical-to-wrinkled transition in an elastic core bounded to a fluid shell system. We find that this model exhibits a first-order phase transition, and the shape that minimizes the energy of the system scales as (micror3/kappa). . The second system studied is motivated by the dynamics of globular proteins. These proteins may undergoes conformational changes with large displacements relative to their size. Transitions between conformational states are not possible if the dynamics are governed strictly by linear elasticity. We construct a model consisting of an predominantly elastic region near the energetic minimum of the system and a non-linear softening of the system at a critical displacement. We find that this simple model displays very rich dynamics include a sharp dynamical phase transition and driving-force-dependent symmetry breaking.

Advanced Ground Systems Maintenance Physics Models For Diagnostics Project

NASA Technical Reports Server (NTRS)

Perotti, Jose M.

2015-01-01

The project will use high-fidelity physics models and simulations to simulate real-time operations of cryogenic and systems and calculate the status/health of the systems. The project enables the delivery of system health advisories to ground system operators. The capability will also be used to conduct planning and analysis of cryogenic system operations. This project will develop and implement high-fidelity physics-based modeling techniques tosimulate the real-time operation of cryogenics and other fluids systems and, when compared to thereal-time operation of the actual systems, provide assessment of their state. Physics-modelcalculated measurements (called “pseudo-sensors”) will be compared to the system real-timedata. Comparison results will be utilized to provide systems operators with enhanced monitoring ofsystems' health and status, identify off-nominal trends and diagnose system/component failures.This capability can also be used to conduct planning and analysis of cryogenics and other fluidsystems designs. This capability will be interfaced with the ground operations command andcontrol system as a part of the Advanced Ground Systems Maintenance (AGSM) project to helpassure system availability and mission success. The initial capability will be developed for theLiquid Oxygen (LO2) ground loading systems.

Towards Co-Engineering Communicating Autonomous Cyber-Physical Systems

NASA Technical Reports Server (NTRS)

Bujorianu, Marius C.; Bujorianu, Manuela L.

2009-01-01

In this paper, we sketch a framework for interdisciplinary modeling of space systems, by proposing a holistic view. We consider different system dimensions and their interaction. Specifically, we study the interactions between computation, physics, communication, uncertainty and autonomy. The most comprehensive computational paradigm that supports a holistic perspective on autonomous space systems is given by cyber-physical systems. For these, the state of art consists of collaborating multi-engineering efforts that prompt for an adequate formal foundation. To achieve this, we propose a leveraging of the traditional content of formal modeling by a co-engineering process.

The SAM framework: modeling the effects of management factors on human behavior in risk analysis.

PubMed

Murphy, D M; Paté-Cornell, M E

1996-08-01

Complex engineered systems, such as nuclear reactors and chemical plants, have the potential for catastrophic failure with disastrous consequences. In recent years, human and management factors have been recognized as frequent root causes of major failures in such systems. However, classical probabilistic risk analysis (PRA) techniques do not account for the underlying causes of these errors because they focus on the physical system and do not explicitly address the link between components' performance and organizational factors. This paper describes a general approach for addressing the human and management causes of system failure, called the SAM (System-Action-Management) framework. Beginning with a quantitative risk model of the physical system, SAM expands the scope of analysis to incorporate first the decisions and actions of individuals that affect the physical system. SAM then links management factors (incentives, training, policies and procedures, selection criteria, etc.) to those decisions and actions. The focus of this paper is on four quantitative models of action that describe this last relationship. These models address the formation of intentions for action and their execution as a function of the organizational environment. Intention formation is described by three alternative models: a rational model, a bounded rationality model, and a rule-based model. The execution of intentions is then modeled separately. These four models are designed to assess the probabilities of individual actions from the perspective of management, thus reflecting the uncertainties inherent to human behavior. The SAM framework is illustrated for a hypothetical case of hazardous materials transportation. This framework can be used as a tool to increase the safety and reliability of complex technical systems by modifying the organization, rather than, or in addition to, re-designing the physical system.

Understanding Probabilistic Interpretations of Physical Systems: A Prerequisite to Learning Quantum Physics.

ERIC Educational Resources Information Center

Bao, Lei; Redish, Edward F.

2002-01-01

Explains the critical role of probability in making sense of quantum physics and addresses the difficulties science and engineering undergraduates experience in helping students build a model of how to think about probability in physical systems. (Contains 17 references.) (Author/YDS)

A new method of search design of refrigerating systems containing a liquid and gaseous working medium based on the graph model of the physical operating principle

NASA Astrophysics Data System (ADS)

Yakovlev, A. A.; Sorokin, V. S.; Mishustina, S. N.; Proidakova, N. V.; Postupaeva, S. G.

2017-01-01

The article describes a new method of search design of refrigerating systems, the basis of which is represented by a graph model of the physical operating principle based on thermodynamical description of physical processes. The mathematical model of the physical operating principle has been substantiated, and the basic abstract theorems relatively semantic load applied to nodes and edges of the graph have been represented. The necessity and the physical operating principle, sufficient for the given model and intended for the considered device class, were demonstrated by the example of a vapour-compression refrigerating plant. The example of obtaining a multitude of engineering solutions of a vapour-compression refrigerating plant has been considered.

Automatic determination of fault effects on aircraft functionality

NASA Technical Reports Server (NTRS)

Feyock, Stefan

1989-01-01

The problem of determining the behavior of physical systems subsequent to the occurrence of malfunctions is discussed. It is established that while it was reasonable to assume that the most important fault behavior modes of primitive components and simple subsystems could be known and predicted, interactions within composite systems reached levels of complexity that precluded the use of traditional rule-based expert system techniques. Reasoning from first principles, i.e., on the basis of causal models of the physical system, was required. The first question that arises is, of course, how the causal information required for such reasoning should be represented. The bond graphs presented here occupy a position intermediate between qualitative and quantitative models, allowing the automatic derivation of Kuipers-like qualitative constraint models as well as state equations. Their most salient feature, however, is that entities corresponding to components and interactions in the physical system are explicitly represented in the bond graph model, thus permitting systematic model updates to reflect malfunctions. Researchers show how this is done, as well as presenting a number of techniques for obtaining qualitative information from the state equations derivable from bond graph models. One insight is the fact that one of the most important advantages of the bond graph ontology is the highly systematic approach to model construction it imposes on the modeler, who is forced to classify the relevant physical entities into a small number of categories, and to look for two highly specific types of interactions among them. The systematic nature of bond graph model construction facilitates the process to the point where the guidelines are sufficiently specific to be followed by modelers who are not domain experts. As a result, models of a given system constructed by different modelers will have extensive similarities. Researchers conclude by pointing out that the ease of updating bond graph models to reflect malfunctions is a manifestation of the systematic nature of bond graph construction, and the regularity of the relationship between bond graph models and physical reality.

Dynamic inverse models in human-cyber-physical systems

NASA Astrophysics Data System (ADS)

Robinson, Ryan M.; Scobee, Dexter R. R.; Burden, Samuel A.; Sastry, S. Shankar

2016-05-01

Human interaction with the physical world is increasingly mediated by automation. This interaction is characterized by dynamic coupling between robotic (i.e. cyber) and neuromechanical (i.e. human) decision-making agents. Guaranteeing performance of such human-cyber-physical systems will require predictive mathematical models of this dynamic coupling. Toward this end, we propose a rapprochement between robotics and neuromechanics premised on the existence of internal forward and inverse models in the human agent. We hypothesize that, in tele-robotic applications of interest, a human operator learns to invert automation dynamics, directly translating from desired task to required control input. By formulating the model inversion problem in the context of a tracking task for a nonlinear control system in control-a_ne form, we derive criteria for exponential tracking and show that the resulting dynamic inverse model generally renders a portion of the physical system state (i.e., the internal dynamics) unobservable from the human operator's perspective. Under stability conditions, we show that the human can achieve exponential tracking without formulating an estimate of the system's state so long as they possess an accurate model of the system's dynamics. These theoretical results are illustrated using a planar quadrotor example. We then demonstrate that the automation can intervene to improve performance of the tracking task by solving an optimal control problem. Performance is guaranteed to improve under the assumption that the human learns and inverts the dynamic model of the altered system. We conclude with a discussion of practical limitations that may hinder exact dynamic model inversion.

Galactic evolution. I - Single-zone models. [encompassing stellar evolution and gas-star dynamic theories

NASA Technical Reports Server (NTRS)

Thuan, T. X.; Hart, M. H.; Ostriker, J. P.

1975-01-01

The two basic approaches of physical theory required to calculate the evolution of a galactic system are considered, taking into account stellar evolution theory and the dynamics of a gas-star system. Attention is given to intrinsic (stellar) physics, extrinsic (dynamical) physics, and computations concerning the fractionation of an initial mass of gas into stars. The characteristics of a 'standard' model and its variants are discussed along with the results obtained with the aid of these models.

Probabilistic short-term forecasting of eruption rate at Kīlauea Volcano using a physics-based model

NASA Astrophysics Data System (ADS)

Anderson, K. R.

2016-12-01

Deterministic models of volcanic eruptions yield predictions of future activity conditioned on uncertainty in the current state of the system. Physics-based eruption models are well-suited for deterministic forecasting as they can relate magma physics with a wide range of observations. Yet, physics-based eruption forecasting is strongly limited by an inadequate understanding of volcanic systems, and the need for eruption models to be computationally tractable. At Kīlauea Volcano, Hawaii, episodic depressurization-pressurization cycles of the magma system generate correlated, quasi-exponential variations in ground deformation and surface height of the active summit lava lake. Deflations are associated with reductions in eruption rate, or even brief eruptive pauses, and thus partly control lava flow advance rates and associated hazard. Because of the relatively well-understood nature of Kīlauea's shallow magma plumbing system, and because more than 600 of these events have been recorded to date, they offer a unique opportunity to refine a physics-based effusive eruption forecasting approach and apply it to lava eruption rates over short (hours to days) time periods. A simple physical model of the volcano ascribes observed data to temporary reductions in magma supply to an elastic reservoir filled with compressible magma. This model can be used to predict the evolution of an ongoing event, but because the mechanism that triggers events is unknown, event durations are modeled stochastically from previous observations. A Bayesian approach incorporates diverse data sets and prior information to simultaneously estimate uncertain model parameters and future states of the system. Forecasts take the form of probability distributions for eruption rate or cumulative erupted volume at some future time. Results demonstrate the significant uncertainties that still remain even for short-term eruption forecasting at a well-monitored volcano - but also the value of a physics-based, mixed deterministic-probabilistic eruption forecasting approach in reducing and quantifying these uncertainties.

Physical and numerical studies of a fracture system model

NASA Astrophysics Data System (ADS)

Piggott, Andrew R.; Elsworth, Derek

1989-03-01

Physical and numerical studies of transient flow in a model of discretely fractured rock are presented. The physical model is a thermal analogue to fractured media flow consisting of idealized disc-shaped fractures. The numerical model is used to predict the behavior of the physical model. The use of different insulating materials to encase the physical model allows the effects of differing leakage magnitudes to be examined. A procedure for determining appropriate leakage parameters is documented. These parameters are used in forward analysis to predict the thermal response of the physical model. Knowledge of the leakage parameters and of the temporal variation of boundary conditions are shown to be essential to an accurate prediction. Favorable agreement is illustrated between numerical and physical results. The physical model provides a data source for the benchmarking of alternative numerical algorithms.

Cyber-Physical Test Platform for Microgrids: Combining Hardware, Hardware-in-the-Loop, and Network-Simulator-in-the-Loop

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, Austin; Chakraborty, Sudipta; Wang, Dexin

This paper presents a cyber-physical testbed, developed to investigate the complex interactions between emerging microgrid technologies such as grid-interactive power sources, control systems, and a wide variety of communication platforms and bandwidths. The cyber-physical testbed consists of three major components for testing and validation: real time models of a distribution feeder model with microgrid assets that are integrated into the National Renewable Energy Laboratory's (NREL) power hardware-in-the-loop (PHIL) platform; real-time capable network-simulator-in-the-loop (NSIL) models; and physical hardware including inverters and a simple system controller. Several load profiles and microgrid configurations were tested to examine the effect on system performance withmore » increasing channel delays and router processing delays in the network simulator. Testing demonstrated that the controller's ability to maintain a target grid import power band was severely diminished with increasing network delays and laid the foundation for future testing of more complex cyber-physical systems.« less

Physics of the Circulatory System.

ERIC Educational Resources Information Center

Van Heuvelen, Alan

1989-01-01

Discusses some calculations and demonstrations illustrating the role of physics in cardiovascular system. Describes a model for the system, work done by the heart, pressure in blood vessel, and gravitational effects. (YP)

The Design and Semi-Physical Simulation Test of Fault-Tolerant Controller for Aero Engine

NASA Astrophysics Data System (ADS)

Liu, Yuan; Zhang, Xin; Zhang, Tianhong

2017-11-01

A new fault-tolerant control method for aero engine is proposed, which can accurately diagnose the sensor fault by Kalman filter banks and reconstruct the signal by real-time on-board adaptive model combing with a simplified real-time model and an improved Kalman filter. In order to verify the feasibility of the method proposed, a semi-physical simulation experiment has been carried out. Besides the real I/O interfaces, controller hardware and the virtual plant model, semi-physical simulation system also contains real fuel system. Compared with the hardware-in-the-loop (HIL) simulation, semi-physical simulation system has a higher degree of confidence. In order to meet the needs of semi-physical simulation, a rapid prototyping controller with fault-tolerant control ability based on NI CompactRIO platform is designed and verified on the semi-physical simulation test platform. The result shows that the controller can realize the aero engine control safely and reliably with little influence on controller performance in the event of fault on sensor.

Modeling Physical Systems Using Vensim PLE Systems Dynamics Software

NASA Astrophysics Data System (ADS)

Widmark, Stephen

2012-02-01

Many physical systems are described by time-dependent differential equations or systems of such equations. This makes it difficult for students in an introductory physics class to solve many real-world problems since these students typically have little or no experience with this kind of mathematics. In my high school physics classes, I address this problem by having my students use a variety of software solutions to model physical systems described by differential equations. These include spreadsheets, applets, software my students themselves create, and systems dynamics software. For the latter, cost is often the main issue in choosing a solution for use in a public school and so I researched no-cost software. I found Sphinx SD,2OptiSim,3 Systems Dynamics,4 Simile (Trial Edition),5 and Vensim PLE.6 In evaluating each of these solutions, I looked for the fewest restrictions in the license for educational use, ease of use by students, power, and versatility. In my opinion, Vensim PLE best fulfills these criteria.7

Parameterized reduced-order models using hyper-dual numbers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fike, Jeffrey A.; Brake, Matthew Robert

2013-10-01

The goal of most computational simulations is to accurately predict the behavior of a real, physical system. Accurate predictions often require very computationally expensive analyses and so reduced order models (ROMs) are commonly used. ROMs aim to reduce the computational cost of the simulations while still providing accurate results by including all of the salient physics of the real system in the ROM. However, real, physical systems often deviate from the idealized models used in simulations due to variations in manufacturing or other factors. One approach to this issue is to create a parameterized model in order to characterize themore » effect of perturbations from the nominal model on the behavior of the system. This report presents a methodology for developing parameterized ROMs, which is based on Craig-Bampton component mode synthesis and the use of hyper-dual numbers to calculate the derivatives necessary for the parameterization.« less

Microphysics in Multi-scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2012-01-01

Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.

Subsystem functional and the missing ingredient of confinement physics in density functionals.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Armiento, Rickard Roberto; Mattsson, Ann Elisabet; Hao, Feng

2010-08-01

The subsystem functional scheme is a promising approach recently proposed for constructing exchange-correlation density functionals. In this scheme, the physics in each part of real materials is described by mapping to a characteristic model system. The 'confinement physics,' an essential physical ingredient that has been left out in present functionals, is studied by employing the harmonic-oscillator (HO) gas model. By performing the potential {yields} density and the density {yields} exchange energy per particle mappings based on two model systems characterizing the physics in the interior (uniform electron-gas model) and surface regions (Airy gas model) of materials for the HO gases,more » we show that the confinement physics emerges when only the lowest subband of the HO gas is occupied by electrons. We examine the approximations of the exchange energy by several state-of-the-art functionals for the HO gas, and none of them produces adequate accuracy in the confinement dominated cases. A generic functional that incorporates the description of the confinement physics is needed.« less

A Framework to Learn Physics from Atomically Resolved Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vlcek, L.; Maksov, A.; Pan, M.

Here, we present a generalized framework for physics extraction, i.e., knowledge, from atomically resolved images, and show its utility by applying it to a model system of segregation of chalcogen atoms in an FeSe 0.45Te 0.55 superconductor system. We emphasize that the framework can be used for any imaging data for which a generative physical model exists. Consider that a generative physical model can produce a very large number of configurations, not all of which are observable. By applying a microscope function to a sub-set of this generated data, we form a simulated dataset on which statistics can be computed.

Characterization of structural connections using free and forced response test data

NASA Technical Reports Server (NTRS)

Lawrence, Charles; Huckelbridge, Arthur A.

1989-01-01

The accurate prediction of system dynamic response often has been limited by deficiencies in existing capabilities to characterize connections adequately. Connections between structural components often are complex mechanically, and difficult to accurately model analytically. Improved analytical models for connections are needed to improve system dynamic preditions. A procedure for identifying physical connection properties from free and forced response test data is developed, then verified utilizing a system having both a linear and nonlinear connection. Connection properties are computed in terms of physical parameters so that the physical characteristics of the connections can better be understood, in addition to providing improved input for the system model. The identification procedure is applicable to multi-degree of freedom systems, and does not require that the test data be measured directly at the connection locations.

Experiments with a Regional Vector-Vorticity Model, and Comparison with Other Models

NASA Astrophysics Data System (ADS)

Konor, C. S.; Dazlich, D. A.; Jung, J.; Randall, D. A.

2017-12-01

The Vector-Vorticity Model (VVM) is an anelastic model with a unique dynamical core that predicts the three-dimensional vorticity instead of the three-dimensional momentum. The VVM is used in the CRMs of the Global Quasi-3D Multiscale Modeling Framework, which is discussed by Joon-Hee Jung and collaborators elsewhere in this session. We are updating the physics package of the VVM, replacing it with the physics package of the System for Atmosphere Modeling (SAM). The new physics package includes a double-moment microphysics, Mellor-Yamada turbulence, Monin-Obukov surface fluxes, and the RRTMG radiation parameterization. We briefly describe the VVM and show results from standard test cases, including TWP-ICE. We compare the results with those obtained using the earlier physics. We also show results from experiments on convection aggregation in radiative-convective equilibrium, and compare with those obtained using both SAM and the Regional Atmospheric Modeling System (RAMS).

Quantitative Diagnosis of Continuous-Valued, Stead-State Systems

NASA Technical Reports Server (NTRS)

Rouquette, N.

1995-01-01

Quantitative diagnosis involves numerically estimating the values of unobservable parameters that best explain the observed parameter values. We consider quantitative diagnosis for continuous, lumped- parameter, steady-state physical systems because such models are easy to construct and the diagnosis problem is considerably simpler than that for corresponding dynamic models. To further tackle the difficulties of numerically inverting a simulation model to compute a diagnosis, we propose to decompose a physical system model in terms of feedback loops. This decomposition reduces the dimension of the problem and consequently decreases the diagnosis search space. We illustrate this approach on a model of thermal control system studied in earlier research.

Markov Task Network: A Framework for Service Composition under Uncertainty in Cyber-Physical Systems.

PubMed

Mohammed, Abdul-Wahid; Xu, Yang; Hu, Haixiao; Agyemang, Brighter

2016-09-21

In novel collaborative systems, cooperative entities collaborate services to achieve local and global objectives. With the growing pervasiveness of cyber-physical systems, however, such collaboration is hampered by differences in the operations of the cyber and physical objects, and the need for the dynamic formation of collaborative functionality given high-level system goals has become practical. In this paper, we propose a cross-layer automation and management model for cyber-physical systems. This models the dynamic formation of collaborative services pursuing laid-down system goals as an ontology-oriented hierarchical task network. Ontological intelligence provides the semantic technology of this model, and through semantic reasoning, primitive tasks can be dynamically composed from high-level system goals. In dealing with uncertainty, we further propose a novel bridge between hierarchical task networks and Markov logic networks, called the Markov task network. This leverages the efficient inference algorithms of Markov logic networks to reduce both computational and inferential loads in task decomposition. From the results of our experiments, high-precision service composition under uncertainty can be achieved using this approach.

Regional Assessment of Storm-triggered Shall Landslide Risks using the SLIDE (SLope-Infiltration-Distributed Equilibrium) Model

NASA Astrophysics Data System (ADS)

Hong, Y.; Kirschbaum, D. B.; Fukuoka, H.

2011-12-01

The key to advancing the predictability of rainfall-triggered landslides is to use physically based slope-stability models that simulate the dynamical response of the subsurface moisture to spatiotemporal variability of rainfall in complex terrains. An early warning system applying such physical models has been developed to predict rainfall-induced shallow landslides over Java Island in Indonesia and Honduras. The prototyped early warning system integrates three major components: (1) a susceptibility mapping or hotspot identification component based on a land surface geospatial database (topographical information, maps of soil properties, and local landslide inventory etc.); (2) a satellite-based precipitation monitoring system (http://trmm.gsfc.nasa.gov) and a precipitation forecasting model (i.e. Weather Research Forecast); and (3) a physically-based, rainfall-induced landslide prediction model SLIDE (SLope-Infiltration-Distributed Equilibrium). The system utilizes the modified physical model to calculate a Factor of Safety (FS) that accounts for the contribution of rainfall infiltration and partial saturation to the shear strength of the soil in topographically complex terrains. The system's prediction performance has been evaluated using a local landslide inventory. In Java Island, Indonesia, evaluation of SLIDE modeling results by local news reports shows that the system successfully predicted landslides in correspondence to the time of occurrence of the real landslide events. Further study of SLIDE is implemented in Honduras where Hurricane Mitch triggered widespread landslides in 1998. Results shows within the approximately 1,200 square kilometers study areas, the values of hit rates reached as high as 78% and 75%, while the error indices were 35% and 49%. Despite positive model performance, the SLIDE model is limited in the early warning system by several assumptions including, using general parameter calibration rather than in situ tests and neglecting geologic information. Advantages and limitations of this model will be discussed with respect to future applications of landslide assessment and prediction over large scales. In conclusion, integration of spatially distributed remote sensing precipitation products and in-situ datasets and physical models in this prototype system enable us to further develop a regional early warning tool in the future for forecasting storm-induced landslides.

Hunting Solomonoff's Swans: Exploring the Boundary Between Physics and Statistics in Hydrological Modeling

NASA Astrophysics Data System (ADS)

Nearing, G. S.

2014-12-01

Statistical models consistently out-perform conceptual models in the short term, however to account for a nonstationary future (or an unobserved past) scientists prefer to base predictions on unchanging and commutable properties of the universe - i.e., physics. The problem with physically-based hydrology models is, of course, that they aren't really based on physics - they are based on statistical approximations of physical interactions, and we almost uniformly lack an understanding of the entropy associated with these approximations. Thermodynamics is successful precisely because entropy statistics are computable for homogeneous (well-mixed) systems, and ergodic arguments explain the success of Newton's laws to describe systems that are fundamentally quantum in nature. Unfortunately, similar arguments do not hold for systems like watersheds that are heterogeneous at a wide range of scales. Ray Solomonoff formalized the situation in 1968 by showing that given infinite evidence, simultaneously minimizing model complexity and entropy in predictions always leads to the best possible model. The open question in hydrology is about what happens when we don't have infinite evidence - for example, when the future will not look like the past, or when one watershed does not behave like another. How do we isolate stationary and commutable components of watershed behavior? I propose that one possible answer to this dilemma lies in a formal combination of physics and statistics. In this talk I outline my recent analogue (Solomonoff's theorem was digital) of Solomonoff's idea that allows us to quantify the complexity/entropy tradeoff in a way that is intuitive to physical scientists. I show how to formally combine "physical" and statistical methods for model development in a way that allows us to derive the theoretically best possible model given any given physics approximation(s) and available observations. Finally, I apply an analogue of Solomonoff's theorem to evaluate the tradeoff between model complexity and prediction power.

Study on perception and control layer of mine CPS with mixed logic dynamic approach

NASA Astrophysics Data System (ADS)

Li, Jingzhao; Ren, Ping; Yang, Dayu

2017-01-01

Mine inclined roadway transportation system of mine cyber physical system is a hybrid system consisting of a continuous-time system and a discrete-time system, which can be divided into inclined roadway signal subsystem, error-proofing channel subsystems, anti-car subsystems, and frequency control subsystems. First, to ensure stable operation, improve efficiency and production safety, this hybrid system model with n inputs and m outputs is constructed and analyzed in detail, then its steady schedule state to be solved. Second, on the basis of the formal modeling for real-time systems, we use hybrid toolbox for system security verification. Third, the practical application of mine cyber physical system shows that the method for real-time simulation of mine cyber physical system is effective.

Physical factors that influence patients' privacy perception toward a psychiatric behavioral monitoring system: a qualitative study.

PubMed

Zakaria, Nasriah; Ramli, Rusyaizila

2018-01-01

Psychiatric patients have privacy concerns when it comes to technology intervention in the hospital setting. In this paper, we present scenarios for psychiatric behavioral monitoring systems to be placed in psychiatric wards to understand patients' perception regarding privacy. Psychiatric behavioral monitoring refers to systems that are deemed useful in measuring clinical outcomes, but little research has been done on how these systems will impact patients' privacy. We conducted a case study in one teaching hospital in Malaysia. We investigated the physical factors that influence patients' perceived privacy with respect to a psychiatric monitoring system. The eight physical factors identified from the information system development privacy model, a comprehensive model for designing a privacy-sensitive information system, were adapted in this research. Scenario-based interviews were conducted with 25 patients in a psychiatric ward for 3 months. Psychiatric patients were able to share how physical factors influence their perception of privacy. Results show how patients responded to each of these dimensions in the context of a psychiatric behavioral monitoring system. Some subfactors under physical privacy are modified to reflect the data obtained in the interviews. We were able to capture the different physical factors that influence patient privacy.

Design of Soil Salinity Policies with Tinamit, a Flexible and Rapid Tool to Couple Stakeholder-Built System Dynamics Models with Physically-Based Models

NASA Astrophysics Data System (ADS)

Malard, J. J.; Baig, A. I.; Hassanzadeh, E.; Adamowski, J. F.; Tuy, H.; Melgar-Quiñonez, H.

2016-12-01

Model coupling is a crucial step to constructing many environmental models, as it allows for the integration of independently-built models representing different system sub-components to simulate the entire system. Model coupling has been of particular interest in combining socioeconomic System Dynamics (SD) models, whose visual interface facilitates their direct use by stakeholders, with more complex physically-based models of the environmental system. However, model coupling processes are often cumbersome and inflexible and require extensive programming knowledge, limiting their potential for continued use by stakeholders in policy design and analysis after the end of the project. Here, we present Tinamit, a flexible Python-based model-coupling software tool whose easy-to-use API and graphical user interface make the coupling of stakeholder-built SD models with physically-based models rapid, flexible and simple for users with limited to no coding knowledge. The flexibility of the system allows end users to modify the SD model as well as the linking variables between the two models themselves with no need for recoding. We use Tinamit to couple a stakeholder-built socioeconomic model of soil salinization in Pakistan with the physically-based soil salinity model SAHYSMOD. As climate extremes increase in the region, policies to slow or reverse soil salinity buildup are increasing in urgency and must take both socioeconomic and biophysical spheres into account. We use the Tinamit-coupled model to test the impact of integrated policy options (economic and regulatory incentives to farmers) on soil salinity in the region in the face of future climate change scenarios. Use of the Tinamit model allowed for rapid and flexible coupling of the two models, allowing the end user to continue making model structure and policy changes. In addition, the clear interface (in contrast to most model coupling code) makes the final coupled model easily accessible to stakeholders with limited technical background.

Modeling the dynamics of multipartite quantum systems created departing from two-level systems using general local and non-local interactions

NASA Astrophysics Data System (ADS)

Delgado, Francisco

2017-12-01

Quantum information is an emergent area merging physics, mathematics, computer science and engineering. To reach its technological goals, it is requiring adequate approaches to understand how to combine physical restrictions, computational approaches and technological requirements to get functional universal quantum information processing. This work presents the modeling and the analysis of certain general type of Hamiltonian representing several physical systems used in quantum information and establishing a dynamics reduction in a natural grammar for bipartite processing based on entangled states.

A Model-Based Prognostics Approach Applied to Pneumatic Valves

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Goebel, Kai

2011-01-01

Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain knowledge of the system, its components, and how they fail by casting the underlying physical phenomena in a physics-based model that is derived from first principles. Uncertainty cannot be avoided in prediction, therefore, algorithms are employed that help in managing these uncertainties. The particle filtering algorithm has become a popular choice for model-based prognostics due to its wide applicability, ease of implementation, and support for uncertainty management. We develop a general model-based prognostics methodology within a robust probabilistic framework using particle filters. As a case study, we consider a pneumatic valve from the Space Shuttle cryogenic refueling system. We develop a detailed physics-based model of the pneumatic valve, and perform comprehensive simulation experiments to illustrate our prognostics approach and evaluate its effectiveness and robustness. The approach is demonstrated using historical pneumatic valve data from the refueling system.

Comparing the Hydrologic and Watershed Processes between a Full Scale Stochastic Model Versus a Scaled Physical Model of Bell Canyon

NASA Astrophysics Data System (ADS)

Hernandez, K. F.; Shah-Fairbank, S.

2016-12-01

The San Dimas Experimental Forest has been designated as a research area by the United States Forest Service for use as a hydrologic testing facility since 1933 to investigate watershed hydrology of the 27 square mile land. Incorporation of a computer model provides validity to the testing of the physical model. This study focuses on San Dimas Experimental Forest's Bell Canyon, one of the triad of watersheds contained within the Big Dalton watershed of the San Dimas Experimental Forest. A scaled physical model was constructed of Bell Canyon to highlight watershed characteristics and each's effect on runoff. The physical model offers a comprehensive visualization of a natural watershed and can vary the characteristics of rainfall intensity, slope, and roughness through interchangeable parts and adjustments to the system. The scaled physical model is validated and calibrated through a HEC-HMS model to assure similitude of the system. Preliminary results of the physical model suggest that a 50-year storm event can be represented by a peak discharge of 2.2 X 10-3 cfs. When comparing the results to HEC-HMS, this equates to a flow relationship of approximately 1:160,000, which can be used to model other return periods. The completion of the Bell Canyon physical model can be used for educational instruction in the classroom, outreach in the community, and further research using the model as an accurate representation of the watershed present in the San Dimas Experimental Forest.

Physical Analytics: An emerging field with real-world applications and impact

NASA Astrophysics Data System (ADS)

Hamann, Hendrik

2015-03-01

In the past most information on the internet has been originated by humans or computers. However with the emergence of cyber-physical systems, vast amount of data is now being created by sensors from devices, machines etc digitizing the physical world. While cyber-physical systems are subject to active research around the world, the vast amount of actual data generated from the physical world has attracted so far little attention from the engineering and physics community. In this presentation we use examples to highlight the opportunities in this new subject of ``Physical Analytics'' for highly inter-disciplinary research (including physics, engineering and computer science), which aims understanding real-world physical systems by leveraging cyber-physical technologies. More specifically, the convergence of the physical world with the digital domain allows applying physical principles to everyday problems in a much more effective and informed way than what was possible in the past. Very much like traditional applied physics and engineering has made enormous advances and changed our lives by making detailed measurements to understand the physics of an engineered device, we can now apply the same rigor and principles to understand large-scale physical systems. In the talk we first present a set of ``configurable'' enabling technologies for Physical Analytics including ultralow power sensing and communication technologies, physical big data management technologies, numerical modeling for physical systems, machine learning based physical model blending, and physical analytics based automation and control. Then we discuss in detail several concrete applications of Physical Analytics ranging from energy management in buildings and data centers, environmental sensing and controls, precision agriculture to renewable energy forecasting and management.

Assessment of physical activity of the human body considering the thermodynamic system.

PubMed

Hochstein, Stefan; Rauschenberger, Philipp; Weigand, Bernhard; Siebert, Tobias; Schmitt, Syn; Schlicht, Wolfgang; Převorovská, Světlana; Maršík, František

2016-01-01

Correctly dosed physical activity is the basis of a vital and healthy life, but the measurement of physical activity is certainly rather empirical resulting in limited individual and custom activity recommendations. Certainly, very accurate three-dimensional models of the cardiovascular system exist, however, requiring the numeric solution of the Navier-Stokes equations of the flow in blood vessels. These models are suitable for the research of cardiac diseases, but computationally very expensive. Direct measurements are expensive and often not applicable outside laboratories. This paper offers a new approach to assess physical activity using thermodynamical systems and its leading quantity of entropy production which is a compromise between computation time and precise prediction of pressure, volume, and flow variables in blood vessels. Based on a simplified (one-dimensional) model of the cardiovascular system of the human body, we develop and evaluate a setup calculating entropy production of the heart to determine the intensity of human physical activity in a more precise way than previous parameters, e.g. frequently used energy considerations. The knowledge resulting from the precise real-time physical activity provides the basis for an intelligent human-technology interaction allowing to steadily adjust the degree of physical activity according to the actual individual performance level and thus to improve training and activity recommendations.

Exploring cluster Monte Carlo updates with Boltzmann machines

NASA Astrophysics Data System (ADS)

Wang, Lei

2017-11-01

Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.

Federating Cyber and Physical Models for Event-Driven Situational Awareness

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stephan, Eric G.; Pawlowski, Ronald A.; Sridhar, Siddharth

The purpose of this paper is to describe a novel method to improve electric power system monitoring and control software application interoperability. This method employs the concept of federation, which is defined as the use of existing models that represent aspects of a system in specific domains (such as physical and cyber security domains) and building interface to link all of domain models.

Physics-based Space Weather Forecasting in the Project for Solar-Terrestrial Environment Prediction (PSTEP) in Japan

NASA Astrophysics Data System (ADS)

Kusano, K.

2016-12-01

Project for Solar-Terrestrial Environment Prediction (PSTEP) is a Japanese nation-wide research collaboration, which was recently launched. PSTEP aims to develop a synergistic interaction between predictive and scientific studies of the solar-terrestrial environment and to establish the basis for next-generation space weather forecasting using the state-of-the-art observation systems and the physics-based models. For this project, we coordinate the four research groups, which develop (1) the integration of space weather forecast system, (2) the physics-based solar storm prediction, (3) the predictive models of magnetosphere and ionosphere dynamics, and (4) the model of solar cycle activity and its impact on climate, respectively. In this project, we will build the coordinated physics-based model to answer the fundamental questions concerning the onset of solar eruptions and the mechanism for radiation belt dynamics in the Earth's magnetosphere. In this paper, we will show the strategy of PSTEP, and discuss about the role and prospect of the physics-based space weather forecasting system being developed by PSTEP.

Microphysics in the Multi-Scale Modeling Systems with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2011-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the microphysics developments of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the heavy precipitation processes will be presented.

Agent autonomy approach to probabilistic physics-of-failure modeling of complex dynamic systems with interacting failure mechanisms

NASA Astrophysics Data System (ADS)

Gromek, Katherine Emily

A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.

Students' Use of the Energy Model to Account for Changes in Physical Systems

ERIC Educational Resources Information Center

Papadouris, Nico; Constantinou, Constantinos P.; Kyratsi, Theodora

2008-01-01

The aim of this study is to explore the ways in which students, aged 11-14 years, account for certain changes in physical systems and the extent to which they draw on an energy model as a common framework for explaining changes observed in diverse systems. Data were combined from two sources: interviews with 20 individuals and an open-ended…

An undergraduate course, and new textbook, on ``Physical Models of Living Systems''

NASA Astrophysics Data System (ADS)

Nelson, Philip

2015-03-01

I'll describe an intermediate-level course on ``Physical Models of Living Systems.'' The only prerequisite is first-year university physics and calculus. The course is a response to rapidly growing interest among undergraduates in several science and engineering departments. Students acquire several research skills that are often not addressed in traditional courses, including: basic modeling skills, probabilistic modeling skills, data analysis methods, computer programming using a general-purpose platform like MATLAB or Python, dynamical systems, particularly feedback control. These basic skills, which are relevant to nearly any field of science or engineering, are presented in the context of case studies from living systems, including: virus dynamics; bacterial genetics and evolution of drug resistance; statistical inference; superresolution microscopy; synthetic biology; naturally evolved cellular circuits. Publication of a new textbook by WH Freeman and Co. is scheduled for December 2014. Supported in part by EF-0928048 and DMR-0832802.

The Mathematics of High School Physics

NASA Astrophysics Data System (ADS)

Kanderakis, Nikos

2016-10-01

In the seventeenth and eighteenth centuries, mathematicians and physical philosophers managed to study, via mathematics, various physical systems of the sublunar world through idealized and simplified models of these systems, constructed with the help of geometry. By analyzing these models, they were able to formulate new concepts, laws and theories of physics and then through models again, to apply these concepts and theories to new physical phenomena and check the results by means of experiment. Students' difficulties with the mathematics of high school physics are well known. Science education research attributes them to inadequately deep understanding of mathematics and mainly to inadequate understanding of the meaning of symbolic mathematical expressions. There seem to be, however, more causes of these difficulties. One of them, not independent from the previous ones, is the complex meaning of the algebraic concepts used in school physics (e.g. variables, parameters, functions), as well as the complexities added by physics itself (e.g. that equations' symbols represent magnitudes with empirical meaning and units instead of pure numbers). Another source of difficulties is that the theories and laws of physics are often applied, via mathematics, to simplified, and idealized physical models of the world and not to the world itself. This concerns not only the applications of basic theories but also all authentic end-of-the-chapter problems. Hence, students have to understand and participate in a complex interplay between physics concepts and theories, physical and mathematical models, and the real world, often without being aware that they are working with models and not directly with the real world.

Learning Physics-based Models in Hydrology under the Framework of Generative Adversarial Networks

NASA Astrophysics Data System (ADS)

Karpatne, A.; Kumar, V.

2017-12-01

Generative adversarial networks (GANs), that have been highly successful in a number of applications involving large volumes of labeled and unlabeled data such as computer vision, offer huge potential for modeling the dynamics of physical processes that have been traditionally studied using simulations of physics-based models. While conventional physics-based models use labeled samples of input/output variables for model calibration (estimating the right parametric forms of relationships between variables) or data assimilation (identifying the most likely sequence of system states in dynamical systems), there is a greater opportunity to explore the full power of machine learning (ML) methods (e.g, GANs) for studying physical processes currently suffering from large knowledge gaps, e.g. ground-water flow. However, success in this endeavor requires a principled way of combining the strengths of ML methods with physics-based numerical models that are founded on a wealth of scientific knowledge. This is especially important in scientific domains like hydrology where the number of data samples is small (relative to Internet-scale applications such as image recognition where machine learning methods has found great success), and the physical relationships are complex (high-dimensional) and non-stationary. We will present a series of methods for guiding the learning of GANs using physics-based models, e.g., by using the outputs of physics-based models as input data to the generator-learner framework, and by using physics-based models as generators trained using validation data in the adversarial learning framework. These methods are being developed under the broad paradigm of theory-guided data science that we are developing to integrate scientific knowledge with data science methods for accelerating scientific discovery.

A glacier runoff extension to the Precipitation Runoff Modeling System

Treesearch

A. E. Van Beusekom; R. J. Viger

2016-01-01

A module to simulate glacier runoff, PRMSglacier, was added to PRMS (Precipitation Runoff Modeling System), a distributed-parameter, physical-process hydrological simulation code. The extension does not require extensive on-glacier measurements or computational expense but still relies on physical principles over empirical relations as much as is feasible while...

Physical Foundations for Socio-Economic Modeling for Transportation Planning : Part 1. Interaction Between Urban Centers as a Potential Process.

DOT National Transportation Integrated Search

1977-09-01

The objective of this research is to make use of a physically based social system model to study the determinants of city sizes and their interactions in a nation. In particular, it was required that attention be paid to how new transportation system...

Thermostatted kinetic equations as models for complex systems in physics and life sciences.

PubMed

Bianca, Carlo

2012-12-01

Statistical mechanics is a powerful method for understanding equilibrium thermodynamics. An equivalent theoretical framework for nonequilibrium systems has remained elusive. The thermodynamic forces driving the system away from equilibrium introduce energy that must be dissipated if nonequilibrium steady states are to be obtained. Historically, further terms were introduced, collectively called a thermostat, whose original application was to generate constant-temperature equilibrium ensembles. This review surveys kinetic models coupled with time-reversible deterministic thermostats for the modeling of large systems composed both by inert matter particles and living entities. The introduction of deterministic thermostats allows to model the onset of nonequilibrium stationary states that are typical of most real-world complex systems. The first part of the paper is focused on a general presentation of the main physical and mathematical definitions and tools: nonequilibrium phenomena, Gauss least constraint principle and Gaussian thermostats. The second part provides a review of a variety of thermostatted mathematical models in physics and life sciences, including Kac, Boltzmann, Jager-Segel and the thermostatted (continuous and discrete) kinetic for active particles models. Applications refer to semiconductor devices, nanosciences, biological phenomena, vehicular traffic, social and economics systems, crowds and swarms dynamics. Copyright © 2012 Elsevier B.V. All rights reserved.

Propulsion Physics Under the Changing Density Field Model

NASA Technical Reports Server (NTRS)

Robertson, Glen A.

2011-01-01

To grow as a space faring race, future spaceflight systems will requires new propulsion physics. Specifically a propulsion physics model that does not require mass ejection without limiting the high thrust necessary to accelerate within or beyond our solar system and return within a normal work period or lifetime. In 2004 Khoury and Weltman produced a density dependent cosmology theory they called Chameleon Cosmology, as at its nature, it is hidden within known physics. This theory represents a scalar field within and about an object, even in the vacuum. Whereby, these scalar fields can be viewed as vacuum energy fields with definable densities that permeate all matter; having implications to dark matter/energy with universe acceleration properties; implying a new force mechanism for propulsion physics. Using Chameleon Cosmology, the author has developed a new propulsion physics model, called the Changing Density Field (CDF) Model. This model relates to density changes in these density fields, where the density field density changes are related to the acceleration of matter within an object. These density changes in turn change how an object couples to the surrounding density fields. Whereby, thrust is achieved by causing a differential in the coupling to these density fields about an object. Since the model indicates that the density of the density field in an object can be changed by internal mass acceleration, even without exhausting mass, the CDF model implies a new propellant-less propulsion physics model

THE MOVEMENT SYSTEM IN EDUCATION.

PubMed

Hoogenboom, Barbara J; Sulavik, Mark

2017-11-01

Although many physical therapists have begun to focus on movement and function in clinical practice, a significant number continue to focus on impairments or pathoanatomic models to direct interventions. This paradigm may be driven by the current models used to direct and guide curricula used for physical therapist education. The methods by which students are educated may contribute to a focus on independent systems, rather than viewing the body as a functional whole. Students who enter practice must be able to integrate information across multiple systems that affect a patient or client's movement and function. Such integration must be taught to students and it is the responsibility of those in physical therapist education to embrace and teach the next generation of students this identifying professional paradigm of the movement system. The purpose of this clinical commentary is to describe the current state of the movement system in physical therapy education, suggest strategies for enhancing movement system focus in entry level education, and envision the future of physical therapy education related to the movement system. Contributions by a student author offer depth and perspective to the ideas and suggestions presented. 5.

Near Identifiability of Dynamical Systems

NASA Technical Reports Server (NTRS)

Hadaegh, F. Y.; Bekey, G. A.

1987-01-01

Concepts regarding approximate mathematical models treated rigorously. Paper presents new results in analysis of structural identifiability, equivalence, and near equivalence between mathematical models and physical processes they represent. Helps establish rigorous mathematical basis for concepts related to structural identifiability and equivalence revealing fundamental requirements, tacit assumptions, and sources of error. "Structural identifiability," as used by workers in this field, loosely translates as meaning ability to specify unique mathematical model and set of model parameters that accurately predict behavior of corresponding physical system.

Diagnosis by integrating model-based reasoning with knowledge-based reasoning

NASA Technical Reports Server (NTRS)

Bylander, Tom

1988-01-01

Our research investigates how observations can be categorized by integrating a qualitative physical model with experiential knowledge. Our domain is diagnosis of pathologic gait in humans, in which the observations are the gait motions, muscle activity during gait, and physical exam data, and the diagnostic hypotheses are the potential muscle weaknesses, muscle mistimings, and joint restrictions. Patients with underlying neurological disorders typically have several malfunctions. Among the problems that need to be faced are: the ambiguity of the observations, the ambiguity of the qualitative physical model, correspondence of the observations and hypotheses to the qualitative physical model, the inherent uncertainty of experiential knowledge, and the combinatorics involved in forming composite hypotheses. Our system divides the work so that the knowledge-based reasoning suggests which hypotheses appear more likely than others, the qualitative physical model is used to determine which hypotheses explain which observations, and another process combines these functionalities to construct a composite hypothesis based on explanatory power and plausibility. We speculate that the reasoning architecture of our system is generally applicable to complex domains in which a less-than-perfect physical model and less-than-perfect experiential knowledge need to be combined to perform diagnosis.

Model-Based Anomaly Detection for a Transparent Optical Transmission System

NASA Astrophysics Data System (ADS)

Bengtsson, Thomas; Salamon, Todd; Ho, Tin Kam; White, Christopher A.

In this chapter, we present an approach for anomaly detection at the physical layer of networks where detailed knowledge about the devices and their operations is available. The approach combines physics-based process models with observational data models to characterize the uncertainties and derive the alarm decision rules. We formulate and apply three different methods based on this approach for a well-defined problem in optical network monitoring that features many typical challenges for this methodology. Specifically, we address the problem of monitoring optically transparent transmission systems that use dynamically controlled Raman amplification systems. We use models of amplifier physics together with statistical estimation to derive alarm decision rules and use these rules to automatically discriminate between measurement errors, anomalous losses, and pump failures. Our approach has led to an efficient tool for systematically detecting anomalies in the system behavior of a deployed network, where pro-active measures to address such anomalies are key to preventing unnecessary disturbances to the system's continuous operation.

A perspective on bridging scales and design of models using low-dimensional manifolds and data-driven model inference

PubMed Central

Zenil, Hector; Kiani, Narsis A.; Ball, Gordon; Gomez-Cabrero, David

2016-01-01

Systems in nature capable of collective behaviour are nonlinear, operating across several scales. Yet our ability to account for their collective dynamics differs in physics, chemistry and biology. Here, we briefly review the similarities and differences between mathematical modelling of adaptive living systems versus physico-chemical systems. We find that physics-based chemistry modelling and computational neuroscience have a shared interest in developing techniques for model reductions aiming at the identification of a reduced subsystem or slow manifold, capturing the effective dynamics. By contrast, as relations and kinetics between biological molecules are less characterized, current quantitative analysis under the umbrella of bioinformatics focuses on signal extraction, correlation, regression and machine-learning analysis. We argue that model reduction analysis and the ensuing identification of manifolds bridges physics and biology. Furthermore, modelling living systems presents deep challenges as how to reconcile rich molecular data with inherent modelling uncertainties (formalism, variables selection and model parameters). We anticipate a new generative data-driven modelling paradigm constrained by identified governing principles extracted from low-dimensional manifold analysis. The rise of a new generation of models will ultimately connect biology to quantitative mechanistic descriptions, thereby setting the stage for investigating the character of the model language and principles driving living systems. This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’. PMID:27698038

Workshop on data acquisition and trigger system simulations for high energy physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1992-12-31

This report discusses the following topics: DAQSIM: A data acquisition system simulation tool; Front end and DCC Simulations for the SDC Straw Tube System; Simulation of Non-Blocklng Data Acquisition Architectures; Simulation Studies of the SDC Data Collection Chip; Correlation Studies of the Data Collection Circuit & The Design of a Queue for this Circuit; Fast Data Compression & Transmission from a Silicon Strip Wafer; Simulation of SCI Protocols in Modsim; Visual Design with vVHDL; Stochastic Simulation of Asynchronous Buffers; SDC Trigger Simulations; Trigger Rates, DAQ & Online Processing at the SSC; Planned Enhancements to MODSEM II & SIMOBJECT -- anmore » Overview -- R.; DAGAR -- A synthesis system; Proposed Silicon Compiler for Physics Applications; Timed -- LOTOS in a PROLOG Environment: an Algebraic language for Simulation; Modeling and Simulation of an Event Builder for High Energy Physics Data Acquisition Systems; A Verilog Simulation for the CDF DAQ; Simulation to Design with Verilog; The DZero Data Acquisition System: Model and Measurements; DZero Trigger Level 1.5 Modeling; Strategies Optimizing Data Load in the DZero Triggers; Simulation of the DZero Level 2 Data Acquisition System; A Fast Method for Calculating DZero Level 1 Jet Trigger Properties and Physics Input to DAQ Studies.« less

Integrated Formulation of Beacon-Based Exception Analysis for Multimissions

NASA Technical Reports Server (NTRS)

Mackey, Ryan; James, Mark; Park, Han; Zak, Mickail

2003-01-01

Further work on beacon-based exception analysis for multimissions (BEAM), a method of real-time, automated diagnosis of a complex electromechanical systems, has greatly expanded its capability and suitability of application. This expanded formulation, which fully integrates physical models and symbolic analysis, is described. The new formulation of BEAM expands upon previous advanced techniques for analysis of signal data, utilizing mathematical modeling of the system physics, and expert-system reasoning,

Coarse-grained component concurrency in Earth system modeling: parallelizing atmospheric radiative transfer in the GFDL AM3 model using the Flexible Modeling System coupling framework

NASA Astrophysics Data System (ADS)

Balaji, V.; Benson, Rusty; Wyman, Bruce; Held, Isaac

2016-10-01

Climate models represent a large variety of processes on a variety of timescales and space scales, a canonical example of multi-physics multi-scale modeling. Current hardware trends, such as Graphical Processing Units (GPUs) and Many Integrated Core (MIC) chips, are based on, at best, marginal increases in clock speed, coupled with vast increases in concurrency, particularly at the fine grain. Multi-physics codes face particular challenges in achieving fine-grained concurrency, as different physics and dynamics components have different computational profiles, and universal solutions are hard to come by. We propose here one approach for multi-physics codes. These codes are typically structured as components interacting via software frameworks. The component structure of a typical Earth system model consists of a hierarchical and recursive tree of components, each representing a different climate process or dynamical system. This recursive structure generally encompasses a modest level of concurrency at the highest level (e.g., atmosphere and ocean on different processor sets) with serial organization underneath. We propose to extend concurrency much further by running more and more lower- and higher-level components in parallel with each other. Each component can further be parallelized on the fine grain, potentially offering a major increase in the scalability of Earth system models. We present here first results from this approach, called coarse-grained component concurrency, or CCC. Within the Geophysical Fluid Dynamics Laboratory (GFDL) Flexible Modeling System (FMS), the atmospheric radiative transfer component has been configured to run in parallel with a composite component consisting of every other atmospheric component, including the atmospheric dynamics and all other atmospheric physics components. We will explore the algorithmic challenges involved in such an approach, and present results from such simulations. Plans to achieve even greater levels of coarse-grained concurrency by extending this approach within other components, such as the ocean, will be discussed.

Physical factors that influence patients’ privacy perception toward a psychiatric behavioral monitoring system: a qualitative study

PubMed Central

Zakaria, Nasriah; Ramli, Rusyaizila

2018-01-01

Background Psychiatric patients have privacy concerns when it comes to technology intervention in the hospital setting. In this paper, we present scenarios for psychiatric behavioral monitoring systems to be placed in psychiatric wards to understand patients’ perception regarding privacy. Psychiatric behavioral monitoring refers to systems that are deemed useful in measuring clinical outcomes, but little research has been done on how these systems will impact patients’ privacy. Methods We conducted a case study in one teaching hospital in Malaysia. We investigated the physical factors that influence patients’ perceived privacy with respect to a psychiatric monitoring system. The eight physical factors identified from the information system development privacy model, a comprehensive model for designing a privacy-sensitive information system, were adapted in this research. Scenario-based interviews were conducted with 25 patients in a psychiatric ward for 3 months. Results Psychiatric patients were able to share how physical factors influence their perception of privacy. Results show how patients responded to each of these dimensions in the context of a psychiatric behavioral monitoring system. Conclusion Some subfactors under physical privacy are modified to reflect the data obtained in the interviews. We were able to capture the different physical factors that influence patient privacy. PMID:29343963

Model-Based Diagnostics for Propellant Loading Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew John; Foygel, Michael; Smelyanskiy, Vadim N.

2011-01-01

The loading of spacecraft propellants is a complex, risky operation. Therefore, diagnostic solutions are necessary to quickly identify when a fault occurs, so that recovery actions can be taken or an abort procedure can be initiated. Model-based diagnosis solutions, established using an in-depth analysis and understanding of the underlying physical processes, offer the advanced capability to quickly detect and isolate faults, identify their severity, and predict their effects on system performance. We develop a physics-based model of a cryogenic propellant loading system, which describes the complex dynamics of liquid hydrogen filling from a storage tank to an external vehicle tank, as well as the influence of different faults on this process. The model takes into account the main physical processes such as highly nonequilibrium condensation and evaporation of the hydrogen vapor, pressurization, and also the dynamics of liquid hydrogen and vapor flows inside the system in the presence of helium gas. Since the model incorporates multiple faults in the system, it provides a suitable framework for model-based diagnostics and prognostics algorithms. Using this model, we analyze the effects of faults on the system, derive symbolic fault signatures for the purposes of fault isolation, and perform fault identification using a particle filter approach. We demonstrate the detection, isolation, and identification of a number of faults using simulation-based experiments.

Towards using musculoskeletal models for intelligent control of physically assistive robots.

PubMed

Carmichael, Marc G; Liu, Dikai

2011-01-01

With the increasing number of robots being developed to physically assist humans in tasks such as rehabilitation and assistive living, more intelligent and personalized control systems are desired. In this paper we propose the use of a musculoskeletal model to estimate the strength of the user, from which information can be utilized to improve control schemes in which robots physically assist humans. An optimization model is developed utilizing a musculoskeletal model to estimate human strength in a specified dynamic state. Results of this optimization as well as methods of using it to observe muscle-based weaknesses in task space are presented. Lastly potential methods and problems in incorporating this model into a robot control system are discussed.

Selection of fire spread model for Russian fire behavior prediction system

Treesearch

Alexandra V. Volokitina; Kevin C. Ryan; Tatiana M. Sofronova; Mark A. Sofronov

2010-01-01

Mathematical modeling of fire behavior prediction is only possible if the models are supplied with an information database that provides spatially explicit input parameters for modeled area. Mathematical models can be of three kinds: 1) physical; 2) empirical; and 3) quasi-empirical (Sullivan, 2009). Physical models (Grishin, 1992) are of academic interest only because...

Using Discrete Event Simulation to Model Attacker Interactions with Cyber and Physical Security Systems

DOE PAGES

Perkins, Casey; Muller, George

2015-10-08

The number of connections between physical and cyber security systems is rapidly increasing due to centralized control from automated and remotely connected means. As the number of interfaces between systems continues to grow, the interactions and interdependencies between them cannot be ignored. Historically, physical and cyber vulnerability assessments have been performed independently. This independent evaluation omits important aspects of the integrated system, where the impacts resulting from malicious or opportunistic attacks are not easily known or understood. Here, we describe a discrete event simulation model that uses information about integrated physical and cyber security systems, attacker characteristics and simple responsemore » rules to identify key safeguards that limit an attacker's likelihood of success. Key features of the proposed model include comprehensive data generation to support a variety of sophisticated analyses, and full parameterization of safeguard performance characteristics and attacker behaviours to evaluate a range of scenarios. Lastly, we also describe the core data requirements and the network of networks that serves as the underlying simulation structure.« less

Using Discrete Event Simulation to Model Attacker Interactions with Cyber and Physical Security Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perkins, Casey; Muller, George

The number of connections between physical and cyber security systems is rapidly increasing due to centralized control from automated and remotely connected means. As the number of interfaces between systems continues to grow, the interactions and interdependencies between them cannot be ignored. Historically, physical and cyber vulnerability assessments have been performed independently. This independent evaluation omits important aspects of the integrated system, where the impacts resulting from malicious or opportunistic attacks are not easily known or understood. Here, we describe a discrete event simulation model that uses information about integrated physical and cyber security systems, attacker characteristics and simple responsemore » rules to identify key safeguards that limit an attacker's likelihood of success. Key features of the proposed model include comprehensive data generation to support a variety of sophisticated analyses, and full parameterization of safeguard performance characteristics and attacker behaviours to evaluate a range of scenarios. Lastly, we also describe the core data requirements and the network of networks that serves as the underlying simulation structure.« less

Physics Based Modeling in Design and Development for U.S. Defense Held in Denver, Colorado on November 14-17, 2011. Volume 2: Audio and Movie Files

DTIC Science & Technology

2011-11-17

Mr. Frank Salvatore, High Performance Technologies FIXED AND ROTARY WING AIRCRAFT 13274 - “CREATE-AV DaVinci : Model-Based Engineering for Systems... Tools for Reliability Improvement and Addressing Modularity Issues in Evaluation and Physical Testing”, Dr. Richard Heine, Army Materiel Systems

Resilient control of cyber-physical systems against intelligent attacker: a hierarchal stackelberg game approach

NASA Astrophysics Data System (ADS)

Yuan, Yuan; Sun, Fuchun; Liu, Huaping

2016-07-01

This paper is concerned with the resilient control under denial-of-service attack launched by the intelligent attacker. The resilient control system is modelled as a multi-stage hierarchical game with a corresponding hierarchy of decisions made at cyber and physical layer, respectively. Specifically, the interaction in the cyber layer between different security agents is modelled as a static infinite Stackelberg game, while in the underlying physical layer the full-information H∞ minimax control with package drops is modelled as a different Stackelberg game. Both games are solved sequentially, which is consistent with the actual situations. Finally, the proposed method is applied to the load frequency control of the power system, which demonstrates its effectiveness.

Real time polymer nanocomposites-based physical nanosensors: theory and modeling.

PubMed

Bellucci, Stefano; Shunin, Yuri; Gopeyenko, Victor; Lobanova-Shunina, Tamara; Burlutskaya, Nataly; Zhukovskii, Yuri

2017-09-01

Functionalized carbon nanotubes and graphene nanoribbons nanostructures, serving as the basis for the creation of physical pressure and temperature nanosensors, are considered as tools for ecological monitoring and medical applications. Fragments of nanocarbon inclusions with different morphologies, presenting a disordered system, are regarded as models for nanocomposite materials based on carbon nanoсluster suspension in dielectric polymer environments (e.g., epoxy resins). We have formulated the approach of conductivity calculations for carbon-based polymer nanocomposites using the effective media cluster approach, disordered systems theory and conductivity mechanisms analysis, and obtained the calibration dependences. Providing a proper description of electric responses in nanosensoring systems, we demonstrate the implementation of advanced simulation models suitable for real time control nanosystems. We also consider the prospects and prototypes of the proposed physical nanosensor models providing the comparisons with experimental calibration dependences.

Real time polymer nanocomposites-based physical nanosensors: theory and modeling

NASA Astrophysics Data System (ADS)

Bellucci, Stefano; Shunin, Yuri; Gopeyenko, Victor; Lobanova-Shunina, Tamara; Burlutskaya, Nataly; Zhukovskii, Yuri

2017-09-01

Functionalized carbon nanotubes and graphene nanoribbons nanostructures, serving as the basis for the creation of physical pressure and temperature nanosensors, are considered as tools for ecological monitoring and medical applications. Fragments of nanocarbon inclusions with different morphologies, presenting a disordered system, are regarded as models for nanocomposite materials based on carbon nanoсluster suspension in dielectric polymer environments (e.g., epoxy resins). We have formulated the approach of conductivity calculations for carbon-based polymer nanocomposites using the effective media cluster approach, disordered systems theory and conductivity mechanisms analysis, and obtained the calibration dependences. Providing a proper description of electric responses in nanosensoring systems, we demonstrate the implementation of advanced simulation models suitable for real time control nanosystems. We also consider the prospects and prototypes of the proposed physical nanosensor models providing the comparisons with experimental calibration dependences.

Retrieving hydrological connectivity from empirical causality in karst systems

NASA Astrophysics Data System (ADS)

Delforge, Damien; Vanclooster, Marnik; Van Camp, Michel; Poulain, Amaël; Watlet, Arnaud; Hallet, Vincent; Kaufmann, Olivier; Francis, Olivier

2017-04-01

Because of their complexity, karst systems exhibit nonlinear dynamics. Moreover, if one attempts to model a karst, the hidden behavior complicates the choice of the most suitable model. Therefore, both intense investigation methods and nonlinear data analysis are needed to reveal the underlying hydrological connectivity as a prior for a consistent physically based modelling approach. Convergent Cross Mapping (CCM), a recent method, promises to identify causal relationships between time series belonging to the same dynamical systems. The method is based on phase space reconstruction and is suitable for nonlinear dynamics. As an empirical causation detection method, it could be used to highlight the hidden complexity of a karst system by revealing its inner hydrological and dynamical connectivity. Hence, if one can link causal relationships to physical processes, the method should show great potential to support physically based model structure selection. We present the results of numerical experiments using karst model blocks combined in different structures to generate time series from actual rainfall series. CCM is applied between the time series to investigate if the empirical causation detection is consistent with the hydrological connectivity suggested by the karst model.

The Binary System Laboratory Activities Based on Students Mental Model

NASA Astrophysics Data System (ADS)

Albaiti, A.; Liliasari, S.; Sumarna, O.; Martoprawiro, M. A.

2017-09-01

Generic science skills (GSS) are required to develop student conception in learning binary system. The aim of this research was to know the improvement of students GSS through the binary system labotoratory activities based on their mental model using hypothetical-deductive learning cycle. It was a mixed methods embedded experimental model research design. This research involved 15 students of a university in Papua, Indonesia. Essay test of 7 items was used to analyze the improvement of students GSS. Each items was designed to interconnect macroscopic, sub-microscopic and symbolic levels. Students worksheet was used to explore students mental model during investigation in laboratory. The increase of students GSS could be seen in their N-Gain of each GSS indicators. The results were then analyzed descriptively. Students mental model and GSS have been improved from this study. They were interconnect macroscopic and symbolic levels to explain binary systems phenomena. Furthermore, they reconstructed their mental model with interconnecting the three levels of representation in Physical Chemistry. It necessary to integrate the Physical Chemistry Laboratory into a Physical Chemistry course for effectiveness and efficiency.

Upon Generating Discrete Expanding Integrable Models of the Toda Lattice Systems and Infinite Conservation Laws

NASA Astrophysics Data System (ADS)

Zhang, Yufeng; Zhang, Xiangzhi; Wang, Yan; Liu, Jiangen

2017-01-01

With the help of R-matrix approach, we present the Toda lattice systems that have extensive applications in statistical physics and quantum physics. By constructing a new discrete integrable formula by R-matrix, the discrete expanding integrable models of the Toda lattice systems and their Lax pairs are generated, respectively. By following the constructing formula again, we obtain the corresponding (2+1)-dimensional Toda lattice systems and their Lax pairs, as well as their (2+1)-dimensional discrete expanding integrable models. Finally, some conservation laws of a (1+1)-dimensional generalised Toda lattice system and a new (2+1)-dimensional lattice system are generated, respectively.

The Monash University Interactive Simple Climate Model

NASA Astrophysics Data System (ADS)

Dommenget, D.

2013-12-01

The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

Cyber-Physical Human Systems: Putting People in the Loop.

PubMed

Sowe, Sulayman K; Zettsu, Koji; Simmon, Eric; de Vaulx, Frederic; Bojanova, Irena

2016-01-01

This article outlines the challenge to understand how to integrate people into a new generation of cyber-physical-human systems (CPHSs) and proposes a human service capability description model to help.

Modeling North Atlantic Nor'easters With Modern Wave Forecast Models

NASA Astrophysics Data System (ADS)

Perrie, Will; Toulany, Bechara; Roland, Aron; Dutour-Sikiric, Mathieu; Chen, Changsheng; Beardsley, Robert C.; Qi, Jianhua; Hu, Yongcun; Casey, Michael P.; Shen, Hui

2018-01-01

Three state-of-the-art operational wave forecast model systems are implemented on fine-resolution grids for the Northwest Atlantic. These models are: (1) a composite model system consisting of SWAN implemented within WAVEWATCHIII® (the latter is hereafter, WW3) on a nested system of traditional structured grids, (2) an unstructured grid finite-volume wave model denoted "SWAVE," using SWAN physics, and (3) an unstructured grid finite element wind wave model denoted as "WWM" (for "wind wave model") which uses WW3 physics. Models are implemented on grid systems that include relatively large domains to capture the wave energy generated by the storms, as well as including fine-resolution nearshore regions of the southern Gulf of Maine with resolution on the scale of 25 m to simulate areas where inundation and coastal damage have occurred, due to the storms. Storm cases include three intense midlatitude cases: a spring Nor'easter storm in May 2005, the Patriot's Day storm in 2007, and the Boxing Day storm in 2010. Although these wave model systems have comparable overall properties in terms of their performance and skill, it is found that there are differences. Models that use more advanced physics, as presented in recent versions of WW3, tuned to regional characteristics, as in the Gulf of Maine and the Northwest Atlantic, can give enhanced results.

A Goddard Multi-Scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2010-01-01

A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. In this talk, I will present: (1) A brief review on GCE model and its applications on the impact of the aerosol on deep precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications). We are also performing the inline tracer calculation to comprehend the physical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems. In addition, high - resolution (spatial. 2km, and temporal, I minute) visualization showing the model results will be presented.

Biomechanically based simulation of brain deformations for intraoperative image correction: coupling of elastic and fluid models

NASA Astrophysics Data System (ADS)

Hagemann, Alexander; Rohr, Karl; Stiehl, H. Siegfried

2000-06-01

In order to improve the accuracy of image-guided neurosurgery, different biomechanical models have been developed to correct preoperative images w.r.t. intraoperative changes like brain shift or tumor resection. All existing biomechanical models simulate different anatomical structures by using either appropriate boundary conditions or by spatially varying material parameter values, while assuming the same physical model for all anatomical structures. In general, this leads to physically implausible results, especially in the case of adjacent elastic and fluid structures. Therefore, we propose a new approach which allows to couple different physical models. In our case, we simulate rigid, elastic, and fluid regions by using the appropriate physical description for each material, namely either the Navier equation or the Stokes equation. To solve the resulting differential equations, we derive a linear matrix system for each region by applying the finite element method (FEM). Thereafter, the linear matrix systems are linked together, ending up with one overall linear matrix system. Our approach has been tested using synthetic as well as tomographic images. It turns out from experiments, that the integrated treatment of rigid, elastic, and fluid regions significantly improves the prediction results in comparison to a pure linear elastic model.

Physics-based statistical model and simulation method of RF propagation in urban environments

DOEpatents

Pao, Hsueh-Yuan; Dvorak, Steven L.

2010-09-14

A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.

The Modular Modeling System (MMS): User's Manual

USGS Publications Warehouse

Leavesley, G.H.; Restrepo, Pedro J.; Markstrom, S.L.; Dixon, M.; Stannard, L.G.

1996-01-01

The Modular Modeling System (MMS) is an integrated system of computer software that has been developed to provide the research and operational framework needed to support development, testing, and evaluation of physical-process algorithms and to facilitate integration of user-selected sets of algorithms into operational physical-process models. MMS uses a module library that contains modules for simulating a variety of water, energy, and biogeochemical processes. A model is created by selectively coupling the most appropriate modules from the library to create a 'suitable' model for the desired application. Where existing modules do not provide appropriate process algorithms, new modules can be developed. The MMS user's manual provides installation instructions and a detailed discussion of system concepts, module development, and model development and application using the MMS graphical user interface.

Development , Implementation and Evaluation of a Physics-Base Windblown Dust Emission Model

EPA Science Inventory

A physics-based windblown dust emission parametrization scheme is developed and implemented in the CMAQ modeling system. A distinct feature of the present model includes the incorporation of a newly developed, dynamic relation for the surface roughness length, which is important ...

Statistical physics of vehicular traffic and some related systems

NASA Astrophysics Data System (ADS)

Chowdhury, Debashish; Santen, Ludger; Schadschneider, Andreas

2000-05-01

In the so-called “microscopic” models of vehicular traffic, attention is paid explicitly to each individual vehicle each of which is represented by a “particle”; the nature of the “interactions” among these particles is determined by the way the vehicles influence each others’ movement. Therefore, vehicular traffic, modeled as a system of interacting “particles” driven far from equilibrium, offers the possibility to study various fundamental aspects of truly nonequilibrium systems which are of current interest in statistical physics. Analytical as well as numerical techniques of statistical physics are being used to study these models to understand rich variety of physical phenomena exhibited by vehicular traffic. Some of these phenomena, observed in vehicular traffic under different circumstances, include transitions from one dynamical phase to another, criticality and self-organized criticality, metastability and hysteresis, phase-segregation, etc. In this critical review, written from the perspective of statistical physics, we explain the guiding principles behind all the main theoretical approaches. But we present detailed discussions on the results obtained mainly from the so-called “particle-hopping” models, particularly emphasizing those which have been formulated in recent years using the language of cellular automata.

System Simulation Modeling: A Case Study Illustration of the Model Development Life Cycle

Treesearch

Janice K. Wiedenbeck; D. Earl Kline

1994-01-01

Systems simulation modeling techniques offer a method of representing the individual elements of a manufacturing system and their interactions. By developing and experimenting with simulation models, one can obtain a better understanding of the overall physical system. Forest products industries are beginning to understand the importance of simulation modeling to help...

Causal Modeling of Secondary Science Students' Intentions to Enroll in Physics.

ERIC Educational Resources Information Center

Crawley, Frank E.; Black, Carolyn B.

1992-01-01

Reports a study using the causal modeling method to verify underlying causes of student interest in enrolling in physics as predicted by the theory of planned behavior. Families were identified as major referents in the social support system for physics enrollment. Course and extracurricular conflicts and fear of failure were primary beliefs…

Synthetic Earthquake Statistics From Physical Fault Models for the Lower Rhine Embayment

NASA Astrophysics Data System (ADS)

Brietzke, G. B.; Hainzl, S.; Zöller, G.

2012-04-01

As of today, seismic risk and hazard estimates mostly use pure empirical, stochastic models of earthquake fault systems tuned specifically to the vulnerable areas of interest. Although such models allow for reasonable risk estimates they fail to provide a link between the observed seismicity and the underlying physical processes. Solving a state-of-the-art fully dynamic description set of all relevant physical processes related to earthquake fault systems is likely not useful since it comes with a large number of degrees of freedom, poor constraints on its model parameters and a huge computational effort. Here, quasi-static and quasi-dynamic physical fault simulators provide a compromise between physical completeness and computational affordability and aim at providing a link between basic physical concepts and statistics of seismicity. Within the framework of quasi-static and quasi-dynamic earthquake simulators we investigate a model of the Lower Rhine Embayment (LRE) that is based upon seismological and geological data. We present and discuss statistics of the spatio-temporal behavior of generated synthetic earthquake catalogs with respect to simplification (e.g. simple two-fault cases) as well as to complication (e.g. hidden faults, geometric complexity, heterogeneities of constitutive parameters).

Using Markov Models of Fault Growth Physics and Environmental Stresses to Optimize Control Actions

NASA Technical Reports Server (NTRS)

Bole, Brian; Goebel, Kai; Vachtsevanos, George

2012-01-01

A generalized Markov chain representation of fault dynamics is presented for the case that available modeling of fault growth physics and future environmental stresses can be represented by two independent stochastic process models. A contrived but representatively challenging example will be presented and analyzed, in which uncertainty in the modeling of fault growth physics is represented by a uniformly distributed dice throwing process, and a discrete random walk is used to represent uncertain modeling of future exogenous loading demands to be placed on the system. A finite horizon dynamic programming algorithm is used to solve for an optimal control policy over a finite time window for the case that stochastic models representing physics of failure and future environmental stresses are known, and the states of both stochastic processes are observable by implemented control routines. The fundamental limitations of optimization performed in the presence of uncertain modeling information are examined by comparing the outcomes obtained from simulations of an optimizing control policy with the outcomes that would be achievable if all modeling uncertainties were removed from the system.

Characterization of structural connections for multicomponent systems

NASA Technical Reports Server (NTRS)

Lawrence, Charles; Huckelbridge, Arthur A.

1988-01-01

This study explores combining Component Mode Synthesis methods for coupling structural components with Parameter Identification procedures for improving the analytical modeling of the connections. Improvements in the connection stiffness and damping properties are computed in terms of physical parameters so that the physical characteristics of the connections can be better understood, in addition to providing improved input for the system model.

An architecture for the development of real-time fault diagnosis systems using model-based reasoning

NASA Technical Reports Server (NTRS)

Hall, Gardiner A.; Schuetzle, James; Lavallee, David; Gupta, Uday

1992-01-01

Presented here is an architecture for implementing real-time telemetry based diagnostic systems using model-based reasoning. First, we describe Paragon, a knowledge acquisition tool for offline entry and validation of physical system models. Paragon provides domain experts with a structured editing capability to capture the physical component's structure, behavior, and causal relationships. We next describe the architecture of the run time diagnostic system. The diagnostic system, written entirely in Ada, uses the behavioral model developed offline by Paragon to simulate expected component states as reflected in the telemetry stream. The diagnostic algorithm traces causal relationships contained within the model to isolate system faults. Since the diagnostic process relies exclusively on the behavioral model and is implemented without the use of heuristic rules, it can be used to isolate unpredicted faults in a wide variety of systems. Finally, we discuss the implementation of a prototype system constructed using this technique for diagnosing faults in a science instrument. The prototype demonstrates the use of model-based reasoning to develop maintainable systems with greater diagnostic capabilities at a lower cost.

A new course and textbook on Physical Models of Living Systems, for science and engineering undergraduates

NASA Astrophysics Data System (ADS)

Nelson, Philip

2015-03-01

I'll describe an intermediate-level course on ``Physical Models of Living Systems.'' The only prerequisite is first-year university physics and calculus. The course is a response to rapidly growing interest among undergraduates in a broad range of science and engineering majors. Students acquire several research skills that are often not addressed in traditional courses: Basic modeling skills Probabilistic modeling skills Data analysis methods Computer programming using a general-purpose platform like MATLAB or Python Dynamical systems, particularly feedback control. These basic skills, which are relevant to nearly any field of science or engineering, are presented in the context of case studies from living systems, including: Virus dynamics Bacterial genetics and evolution of drug resistance Statistical inference Superresolution microscopy Synthetic biology Naturally evolved cellular circuits. Work supported by NSF Grants EF-0928048 and DMR-0832802.

Nature as a network of morphological infocomputational processes for cognitive agents

NASA Astrophysics Data System (ADS)

Dodig-Crnkovic, Gordana

2017-01-01

This paper presents a view of nature as a network of infocomputational agents organized in a dynamical hierarchy of levels. It provides a framework for unification of currently disparate understandings of natural, formal, technical, behavioral and social phenomena based on information as a structure, differences in one system that cause the differences in another system, and computation as its dynamics, i.e. physical process of morphological change in the informational structure. We address some of the frequent misunderstandings regarding the natural/morphological computational models and their relationships to physical systems, especially cognitive systems such as living beings. Natural morphological infocomputation as a conceptual framework necessitates generalization of models of computation beyond the traditional Turing machine model presenting symbol manipulation, and requires agent-based concurrent resource-sensitive models of computation in order to be able to cover the whole range of phenomena from physics to cognition. The central role of agency, particularly material vs. cognitive agency is highlighted.

Assessment of Energy Removal Impacts on Physical Systems: Hydrodynamic Model Domain Expansion and Refinement, and Online Dissemination of Model Results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Zhaoqing; Khangaonkar, Tarang; Wang, Taiping

In this report we describe the 1) the expansion of the PNNL hydrodynamic model domain to include the continental shelf along the coasts of Washington, Oregon, and Vancouver Island; and 2) the approach and progress in developing the online/Internet disseminations of model results and outreach efforts in support of the Puget Sound Operational Forecast System (PS-OPF). Submittal of this report completes the work on Task 2.1.2, Effects of Physical Systems, Subtask 2.1.2.1, Hydrodynamics, for fiscal year 2010 of the Environmental Effects of Marine and Hydrokinetic Energy project.

Next Generation Community Based Unified Global Modeling System Development and Operational Implementation Strategies at NCEP

NASA Astrophysics Data System (ADS)

Tallapragada, V.

2017-12-01

NOAA's Next Generation Global Prediction System (NGGPS) has provided the unique opportunity to develop and implement a non-hydrostatic global model based on Geophysical Fluid Dynamics Laboratory (GFDL) Finite Volume Cubed Sphere (FV3) Dynamic Core at National Centers for Environmental Prediction (NCEP), making a leap-step advancement in seamless prediction capabilities across all spatial and temporal scales. Model development efforts are centralized with unified model development in the NOAA Environmental Modeling System (NEMS) infrastructure based on Earth System Modeling Framework (ESMF). A more sophisticated coupling among various earth system components is being enabled within NEMS following National Unified Operational Prediction Capability (NUOPC) standards. The eventual goal of unifying global and regional models will enable operational global models operating at convective resolving scales. Apart from the advanced non-hydrostatic dynamic core and coupling to various earth system components, advanced physics and data assimilation techniques are essential for improved forecast skill. NGGPS is spearheading ambitious physics and data assimilation strategies, concentrating on creation of a Common Community Physics Package (CCPP) and Joint Effort for Data Assimilation Integration (JEDI). Both initiatives are expected to be community developed, with emphasis on research transitioning to operations (R2O). The unified modeling system is being built to support the needs of both operations and research. Different layers of community partners are also established with specific roles/responsibilities for researchers, core development partners, trusted super-users, and operations. Stakeholders are engaged at all stages to help drive the direction of development, resources allocations and prioritization. This talk presents the current and future plans of unified model development at NCEP for weather, sub-seasonal, and seasonal climate prediction applications with special emphasis on implementation of NCEP FV3 Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS) into operations by 2019.

Systems Thinking and Simulation Modeling to Inform Childhood Obesity Policy and Practice.

PubMed

Powell, Kenneth E; Kibbe, Debra L; Ferencik, Rachel; Soderquist, Chris; Phillips, Mary Ann; Vall, Emily Anne; Minyard, Karen J

In 2007, 31.7% of Georgia adolescents in grades 9-12 were overweight or obese. Understanding the impact of policies and interventions on obesity prevalence among young people can help determine statewide public health and policy strategies. This article describes a systems model, originally launched in 2008 and updated in 2014, that simulates the impact of policy interventions on the prevalence of childhood obesity in Georgia through 2034. In 2008, using information from peer-reviewed reports and quantitative estimates by experts in childhood obesity, physical activity, nutrition, and health economics and policy, a group of legislators, legislative staff members, and experts trained in systems thinking and system dynamics modeling constructed a model simulating the impact of policy interventions on the prevalence of childhood obesity in Georgia through 2034. Use of the 2008 model contributed to passage of a bill requiring annual fitness testing of schoolchildren and stricter enforcement of physical education requirements. We updated the model in 2014. With no policy change, the updated model projects that the prevalence of obesity among children and adolescents aged ≤18 in Georgia would hold at 18% from 2014 through 2034. Mandating daily school physical education (which would reduce prevalence to 12%) and integrating moderate to vigorous physical activity into elementary classrooms (which would reduce prevalence to 10%) would have the largest projected impact. Enacting all policies simultaneously would lower the prevalence of childhood obesity from 18% to 3%. Systems thinking, especially with simulation models, facilitates understanding of complex health policy problems. Using a simulation model to educate legislators, educators, and health experts about the policies that have the greatest short- and long-term impact should encourage strategic investment in low-cost, high-return policies.

Perspective: Reaches of chemical physics in biology.

PubMed

Gruebele, Martin; Thirumalai, D

2013-09-28

Chemical physics as a discipline contributes many experimental tools, algorithms, and fundamental theoretical models that can be applied to biological problems. This is especially true now as the molecular level and the systems level descriptions begin to connect, and multi-scale approaches are being developed to solve cutting edge problems in biology. In some cases, the concepts and tools got their start in non-biological fields, and migrated over, such as the idea of glassy landscapes, fluorescence spectroscopy, or master equation approaches. In other cases, the tools were specifically developed with biological physics applications in mind, such as modeling of single molecule trajectories or super-resolution laser techniques. In this introduction to the special topic section on chemical physics of biological systems, we consider a wide range of contributions, all the way from the molecular level, to molecular assemblies, chemical physics of the cell, and finally systems-level approaches, based on the contributions to this special issue. Chemical physicists can look forward to an exciting future where computational tools, analytical models, and new instrumentation will push the boundaries of biological inquiry.

Perspective: Reaches of chemical physics in biology

PubMed Central

Gruebele, Martin; Thirumalai, D.

2013-01-01

Chemical physics as a discipline contributes many experimental tools, algorithms, and fundamental theoretical models that can be applied to biological problems. This is especially true now as the molecular level and the systems level descriptions begin to connect, and multi-scale approaches are being developed to solve cutting edge problems in biology. In some cases, the concepts and tools got their start in non-biological fields, and migrated over, such as the idea of glassy landscapes, fluorescence spectroscopy, or master equation approaches. In other cases, the tools were specifically developed with biological physics applications in mind, such as modeling of single molecule trajectories or super-resolution laser techniques. In this introduction to the special topic section on chemical physics of biological systems, we consider a wide range of contributions, all the way from the molecular level, to molecular assemblies, chemical physics of the cell, and finally systems-level approaches, based on the contributions to this special issue. Chemical physicists can look forward to an exciting future where computational tools, analytical models, and new instrumentation will push the boundaries of biological inquiry. PMID:24089712

MPD Thruster Performance Analytic Models

NASA Technical Reports Server (NTRS)

Gilland, James; Johnston, Geoffrey

2003-01-01

Magnetoplasmadynamic (MPD) thrusters are capable of accelerating quasi-neutral plasmas to high exhaust velocities using Megawatts (MW) of electric power. These characteristics make such devices worthy of consideration for demanding, far-term missions such as the human exploration of Mars or beyond. Assessment of MPD thrusters at the system and mission level is often difficult due to their status as ongoing experimental research topics rather than developed thrusters. However, in order to assess MPD thrusters utility in later missions, some adequate characterization of performance, or more exactly, projected performance, and system level definition are required for use in analyses. The most recent physical models of self-field MPD thrusters have been examined, assessed, and reconfigured for use by systems and mission analysts. The physical models allow for rational projections of thruster performance based on physical parameters that can be measured in the laboratory. The models and their implications for the design of future MPD thrusters are presented.

MPD Thruster Performance Analytic Models

NASA Technical Reports Server (NTRS)

Gilland, James; Johnston, Geoffrey

2007-01-01

Magnetoplasmadynamic (MPD) thrusters are capable of accelerating quasi-neutral plasmas to high exhaust velocities using Megawatts (MW) of electric power. These characteristics make such devices worthy of consideration for demanding, far-term missions such as the human exploration of Mars or beyond. Assessment of MPD thrusters at the system and mission level is often difficult due to their status as ongoing experimental research topics rather than developed thrusters. However, in order to assess MPD thrusters utility in later missions, some adequate characterization of performance, or more exactly, projected performance, and system level definition are required for use in analyses. The most recent physical models of self-field MPD thrusters have been examined, assessed, and reconfigured for use by systems and mission analysts. The physical models allow for rational projections of thruster performance based on physical parameters that can be measured in the laboratory. The models and their implications for the design of future MPD thrusters are presented.

Challenges to modeling the Sun-Earth System: A Workshop Summary

NASA Technical Reports Server (NTRS)

Spann, James F.

2006-01-01

This special issue of the Journal of' Atmospheric and Solar-Terrestrial Physics is a compilation of 23 papers presented at The 2004 Huntsville Modeling Workshop: Challenges to Modeling thc San-Earth System held in Huntsville, AB on October 18-22, 2004. The title of the workshop appropriately captures the theme of what was presented and discussed by the 120 participants. Currently, end-to-end modeling of the Sun-Earth system is a major goal of the National Space Weather and NASA living with a star (LWS) programs. While profound advances have been made in modeling isolated regions of the Sun-Earth system, minimal progress has been achieved in modeling the end-to-end system. The transfer of mass, energy and momentum through the coupled Sun-Earth system spans a wide range of scales inn time and space. The uncertainty in the underlying physics responsible for coupling contiguous regions of the Sun-Earth system is recognized as a significant barrier to progress

Modeling reality

NASA Technical Reports Server (NTRS)

Denning, Peter J.

1990-01-01

Although powerful computers have allowed complex physical and manmade hardware systems to be modeled successfully, we have encountered persistent problems with the reliability of computer models for systems involving human learning, human action, and human organizations. This is not a misfortune; unlike physical and manmade systems, human systems do not operate under a fixed set of laws. The rules governing the actions allowable in the system can be changed without warning at any moment, and can evolve over time. That the governing laws are inherently unpredictable raises serious questions about the reliability of models when applied to human situations. In these domains, computers are better used, not for prediction and planning, but for aiding humans. Examples are systems that help humans speculate about possible futures, offer advice about possible actions in a domain, systems that gather information from the networks, and systems that track and support work flows in organizations.

Damage and Loss Estimation for Natural Gas Networks: The Case of Istanbul

NASA Astrophysics Data System (ADS)

Çaktı, Eser; Hancılar, Ufuk; Şeşetyan, Karin; Bıyıkoǧlu, Hikmet; Şafak, Erdal

2017-04-01

Natural gas networks are one of the major lifeline systems to support human, urban and industrial activities. The continuity of gas supply is critical for almost all functions of modern life. Under natural phenomena such as earthquakes and landslides the damages to the system elements may lead to explosions and fires compromising human life and damaging physical environment. Furthermore, the disruption in the gas supply puts human activities at risk and also results in economical losses. This study is concerned with the performance of one of the largest natural gas distribution systems in the world. Physical damages to Istanbul's natural gas network are estimated under the most recent probabilistic earthquake hazard models available, as well as under simulated ground motions from physics based models. Several vulnerability functions are used in modelling damages to system elements. A first-order assessment of monetary losses to Istanbul's natural gas distribution network is also attempted.

DAWN (Design Assistant Workstation) for advanced physical-chemical life support systems

NASA Technical Reports Server (NTRS)

Rudokas, Mary R.; Cantwell, Elizabeth R.; Robinson, Peter I.; Shenk, Timothy W.

1989-01-01

This paper reports the results of a project supported by the National Aeronautics and Space Administration, Office of Aeronautics and Space Technology (NASA-OAST) under the Advanced Life Support Development Program. It is an initial attempt to integrate artificial intelligence techniques (via expert systems) with conventional quantitative modeling tools for advanced physical-chemical life support systems. The addition of artificial intelligence techniques will assist the designer in the definition and simulation of loosely/well-defined life support processes/problems as well as assist in the capture of design knowledge, both quantitative and qualitative. Expert system and conventional modeling tools are integrated to provide a design workstation that assists the engineer/scientist in creating, evaluating, documenting and optimizing physical-chemical life support systems for short-term and extended duration missions.

Identifiability Of Systems With Modeling Errors

NASA Technical Reports Server (NTRS)

Hadaegh, Yadolah " fred" ; Bekey, George A.

1988-01-01

Advances in theory of modeling errors reported. Recent paper on errors in mathematical models of deterministic linear or weakly nonlinear systems. Extends theoretical work described in NPO-16661 and NPO-16785. Presents concrete way of accounting for difference in structure between mathematical model and physical process or system that it represents.

The Community WRF-Hydro Modeling System Version 4 Updates: Merging Toward Capabilities of the National Water Model

NASA Astrophysics Data System (ADS)

McAllister, M.; Gochis, D.; Dugger, A. L.; Karsten, L. R.; McCreight, J. L.; Pan, L.; Rafieeinasab, A.; Read, L. K.; Sampson, K. M.; Yu, W.

2017-12-01

The community WRF-Hydro modeling system is publicly available and provides researchers and operational forecasters a flexible and extensible capability for performing multi-scale, multi-physics options for hydrologic modeling that can be run independent or fully-interactive with the WRF atmospheric model. The core WRF-Hydro physics model contains very high-resolution descriptions of terrestrial hydrologic process representations such as land-atmosphere exchanges of energy and moisture, snowpack evolution, infiltration, terrain routing, channel routing, basic reservoir representation and hydrologic data assimilation. Complementing the core physics components of WRF-Hydro are an ecosystem of pre- and post-processing tools that facilitate the preparation of terrain and meteorological input data, an open-source hydrologic model evaluation toolset (Rwrfhydro), hydrologic data assimilation capabilities with DART and advanced model visualization capabilities. The National Center for Atmospheric Research (NCAR), through collaborative support from the National Science Foundation and other funding partners, provides community support for the entire WRF-Hydro system through a variety of mechanisms. This presentation summarizes the enhanced user support capabilities that are being developed for the community WRF-Hydro modeling system. These products and services include a new website, open-source code repositories, documentation and user guides, test cases, online training materials, live, hands-on training sessions, an email list serve, and individual user support via email through a new help desk ticketing system. The WRF-Hydro modeling system and supporting tools which now include re-gridding scripts and model calibration have recently been updated to Version 4 and are merging toward capabilities of the National Water Model.

Progress on Implementing Additional Physics Schemes into MPAS-A v5.1 for Next Generation Air Quality Modeling

EPA Science Inventory

The U.S. Environmental Protection Agency (USEPA) has a team of scientists developing a next generation air quality modeling system employing the Model for Prediction Across Scales – Atmosphere (MPAS-A) as its meteorological foundation. Several preferred physics schemes and ...

A Model-Based Approach to Support Validation of Medical Cyber-Physical Systems.

PubMed

Silva, Lenardo C; Almeida, Hyggo O; Perkusich, Angelo; Perkusich, Mirko

2015-10-30

Medical Cyber-Physical Systems (MCPS) are context-aware, life-critical systems with patient safety as the main concern, demanding rigorous processes for validation to guarantee user requirement compliance and specification-oriented correctness. In this article, we propose a model-based approach for early validation of MCPS, focusing on promoting reusability and productivity. It enables system developers to build MCPS formal models based on a library of patient and medical device models, and simulate the MCPS to identify undesirable behaviors at design time. Our approach has been applied to three different clinical scenarios to evaluate its reusability potential for different contexts. We have also validated our approach through an empirical evaluation with developers to assess productivity and reusability. Finally, our models have been formally verified considering functional and safety requirements and model coverage.

A Model-Based Approach to Support Validation of Medical Cyber-Physical Systems

PubMed Central

Silva, Lenardo C.; Almeida, Hyggo O.; Perkusich, Angelo; Perkusich, Mirko

2015-01-01

Medical Cyber-Physical Systems (MCPS) are context-aware, life-critical systems with patient safety as the main concern, demanding rigorous processes for validation to guarantee user requirement compliance and specification-oriented correctness. In this article, we propose a model-based approach for early validation of MCPS, focusing on promoting reusability and productivity. It enables system developers to build MCPS formal models based on a library of patient and medical device models, and simulate the MCPS to identify undesirable behaviors at design time. Our approach has been applied to three different clinical scenarios to evaluate its reusability potential for different contexts. We have also validated our approach through an empirical evaluation with developers to assess productivity and reusability. Finally, our models have been formally verified considering functional and safety requirements and model coverage. PMID:26528982

PREFACE: Physics and Mathematics of Nonlinear Phenomena 2013 (PMNP2013)

NASA Astrophysics Data System (ADS)

Konopelchenko, B. G.; Landolfi, G.; Martina, L.; Vitolo, R.

2014-03-01

Modern theory of nonlinear integrable equations is nowdays an important and effective tool of study for numerous nonlinear phenomena in various branches of physics from hydrodynamics and optics to quantum filed theory and gravity. It includes the study of nonlinear partial differential and discrete equations, regular and singular behaviour of their solutions, Hamitonian and bi- Hamitonian structures, their symmetries, associated deformations of algebraic and geometrical structures with applications to various models in physics and mathematics. The PMNP 2013 conference focused on recent advances and developments in Continuous and discrete, classical and quantum integrable systems Hamiltonian, critical and geometric structures of nonlinear integrable equations Integrable systems in quantum field theory and matrix models Models of nonlinear phenomena in physics Applications of nonlinear integrable systems in physics The Scientific Committee of the conference was formed by Francesco Calogero (University of Rome `La Sapienza', Italy) Boris A Dubrovin (SISSA, Italy) Yuji Kodama (Ohio State University, USA) Franco Magri (University of Milan `Bicocca', Italy) Vladimir E Zakharov (University of Arizona, USA, and Landau Institute for Theoretical Physics, Russia) The Organizing Committee: Boris G Konopelchenko, Giulio Landolfi, Luigi Martina, Department of Mathematics and Physics `E De Giorgi' and the Istituto Nazionale di Fisica Nucleare, and Raffaele Vitolo, Department of Mathematics and Physics `E De Giorgi'. A list of sponsors, speakers, talks, participants and the conference photograph are given in the PDF. Conference photograph

The Australian Computational Earth Systems Simulator

NASA Astrophysics Data System (ADS)

Mora, P.; Muhlhaus, H.; Lister, G.; Dyskin, A.; Place, D.; Appelbe, B.; Nimmervoll, N.; Abramson, D.

2001-12-01

Numerical simulation of the physics and dynamics of the entire earth system offers an outstanding opportunity for advancing earth system science and technology but represents a major challenge due to the range of scales and physical processes involved, as well as the magnitude of the software engineering effort required. However, new simulation and computer technologies are bringing this objective within reach. Under a special competitive national funding scheme to establish new Major National Research Facilities (MNRF), the Australian government together with a consortium of Universities and research institutions have funded construction of the Australian Computational Earth Systems Simulator (ACcESS). The Simulator or computational virtual earth will provide the research infrastructure to the Australian earth systems science community required for simulations of dynamical earth processes at scales ranging from microscopic to global. It will consist of thematic supercomputer infrastructure and an earth systems simulation software system. The Simulator models and software will be constructed over a five year period by a multi-disciplinary team of computational scientists, mathematicians, earth scientists, civil engineers and software engineers. The construction team will integrate numerical simulation models (3D discrete elements/lattice solid model, particle-in-cell large deformation finite-element method, stress reconstruction models, multi-scale continuum models etc) with geophysical, geological and tectonic models, through advanced software engineering and visualization technologies. When fully constructed, the Simulator aims to provide the software and hardware infrastructure needed to model solid earth phenomena including global scale dynamics and mineralisation processes, crustal scale processes including plate tectonics, mountain building, interacting fault system dynamics, and micro-scale processes that control the geological, physical and dynamic behaviour of earth systems. ACcESS represents a part of Australia's contribution to the APEC Cooperation for Earthquake Simulation (ACES) international initiative. Together with other national earth systems science initiatives including the Japanese Earth Simulator and US General Earthquake Model projects, ACcESS aims to provide a driver for scientific advancement and technological breakthroughs including: quantum leaps in understanding of earth evolution at global, crustal, regional and microscopic scales; new knowledge of the physics of crustal fault systems required to underpin the grand challenge of earthquake prediction; new understanding and predictive capabilities of geological processes such as tectonics and mineralisation.

Toward experimental validation of a model for human sensorimotor learning and control in teleoperation

NASA Astrophysics Data System (ADS)

Roth, Eatai; Howell, Darrin; Beckwith, Cydney; Burden, Samuel A.

2017-05-01

Humans, interacting with cyber-physical systems (CPS), formulate beliefs about the system's dynamics. It is natural to expect that human operators, tasked with teleoperation, use these beliefs to control the remote robot. For tracking tasks in the resulting human-cyber-physical system (HCPS), theory suggests that human operators can achieve exponential tracking (in stable systems) without state estimation provided they possess an accurate model of the system's dynamics. This internalized inverse model, however, renders a portion of the system state unobservable to the human operator—the zero dynamics. Prior work shows humans can track through observable linear dynamics, thus we focus on nonlinear dynamics rendered unobservable through tracking control. We propose experiments to assess the human operator's ability to learn and invert such models, and distinguish this behavior from that achieved by pure feedback control.

The Challenge of Grounding Planning in Simulation with an Interactive Model Development Environment

NASA Technical Reports Server (NTRS)

Clement, Bradley J.; Frank, Jeremy D.; Chachere, John M.; Smith, Tristan B.; Swanson, Keith J.

2011-01-01

A principal obstacle to fielding automated planning systems is the difficulty of modeling. Physical systems are modeled conventionally based on specification documents and the modeler's understanding of the system. Thus, the model is developed in a way that is disconnected from the system's actual behavior and is vulnerable to manual error. Another obstacle to fielding planners is testing and validation. For a space mission, generated plans must be validated often by translating them into command sequences that are run in a simulation testbed. Testing in this way is complex and onerous because of the large number of possible plans and states of the spacecraft. Though, if used as a source of domain knowledge, the simulator can ease validation. This paper poses a challenge: to ground planning models in the system physics represented by simulation. A proposed, interactive model development environment illustrates the integration of planning and simulation to meet the challenge. This integration reveals research paths for automated model construction and validation.

A study of amplitude information-frequency characteristics for underwater active electrolocation system.

PubMed

Peng, Jiegang

2015-11-04

Weakly electric fish sense their surroundings in complete darkness by their active electrolocation system. For biologists, the active electrolocation system has been investigated for near 60 years. And for engineers, bio-inspired active electrolocation sensor has been investigated for about 20 years. But how the amplitude information response will be affected by frequencies of detecting electric fields in the active electrolocation system was rarely investigated. In this paper, an electrolocation experiment system has been built. The amplitude information-frequency characteristics (AIFC) of the electrolocation system for sinusoidal electric fields of varying frequencies have been investigated. We find that AIFC of the electrolocation system have relevance to the material properties and geometric features of the probed object and conductivity of surrounding water. Detect frequency dead zone (DFDZ) and frequency inflection point (FIP) of AIFC for the electrolocation system were found. The analysis model of the electrolocation system has been investigated for many years, but DFDZ and FIP of AIFC can be difficult to explain by those models. In order to explain those AIFC phenomena for the electrolocation system, a simple relaxation model based on Cole-Cole model which is not only a mathematical explanation but it is a physical one for the electrolocation system was advanced. We also advance a hypothesis for physical mechanism of weakly electrical fish electrolocation system. It may have reference value for physical mechanism of weakly electrical fish active electrolocation system.

Alternative model for administration and analysis of research-based assessments

NASA Astrophysics Data System (ADS)

Wilcox, Bethany R.; Zwickl, Benjamin M.; Hobbs, Robert D.; Aiken, John M.; Welch, Nathan M.; Lewandowski, H. J.

2016-06-01

Research-based assessments represent a valuable tool for both instructors and researchers interested in improving undergraduate physics education. However, the historical model for disseminating and propagating conceptual and attitudinal assessments developed by the physics education research (PER) community has not resulted in widespread adoption of these assessments within the broader community of physics instructors. Within this historical model, assessment developers create high quality, validated assessments, make them available for a wide range of instructors to use, and provide minimal (if any) support to assist with administration or analysis of the results. Here, we present and discuss an alternative model for assessment dissemination, which is characterized by centralized data collection and analysis. This model provides a greater degree of support for both researchers and instructors in order to more explicitly support adoption of research-based assessments. Specifically, we describe our experiences developing a centralized, automated system for an attitudinal assessment we previously created to examine students' epistemologies and expectations about experimental physics. This system provides a proof of concept that we use to discuss the advantages associated with centralized administration and data collection for research-based assessments in PER. We also discuss the challenges that we encountered while developing, maintaining, and automating this system. Ultimately, we argue that centralized administration and data collection for standardized assessments is a viable and potentially advantageous alternative to the default model characterized by decentralized administration and analysis. Moreover, with the help of online administration and automation, this model can support the long-term sustainability of centralized assessment systems.

Use of system identification techniques for improving airframe finite element models using test data

NASA Technical Reports Server (NTRS)

Hanagud, Sathya V.; Zhou, Weiyu; Craig, James I.; Weston, Neil J.

1991-01-01

A method for using system identification techniques to improve airframe finite element models was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Continuous system modeling

NASA Technical Reports Server (NTRS)

Cellier, Francois E.

1991-01-01

A comprehensive and systematic introduction is presented for the concepts associated with 'modeling', involving the transition from a physical system down to an abstract description of that system in the form of a set of differential and/or difference equations, and basing its treatment of modeling on the mathematics of dynamical systems. Attention is given to the principles of passive electrical circuit modeling, planar mechanical systems modeling, hierarchical modular modeling of continuous systems, and bond-graph modeling. Also discussed are modeling in equilibrium thermodynamics, population dynamics, and system dynamics, inductive reasoning, artificial neural networks, and automated model synthesis.

REVIEWS OF TOPICAL PROBLEMS: Application of cybernetic methods in physics

NASA Astrophysics Data System (ADS)

Fradkov, Aleksandr L.

2005-02-01

Basic aspects of the subject and methodology for a new and rapidly developing area of research that has emerged at the intersection of physics and control theory (cybernetics) and emphasizes the application of cybernetic methods to the study of physical systems are reviewed. Speed-gradient and Hamiltonian solutions for energy control problems in conservative and dissipative systems are presented. Application examples such as the Kapitza pendulum, controlled overcoming of a potential barrier, and controlling coupled oscillators and molecular systems are presented. A speed-gradient approach to modeling the dynamics of physical systems is discussed.

Lattice hydrodynamic model based traffic control: A transportation cyber-physical system approach

NASA Astrophysics Data System (ADS)

Liu, Hui; Sun, Dihua; Liu, Weining

2016-11-01

Lattice hydrodynamic model is a typical continuum traffic flow model, which describes the jamming transition of traffic flow properly. Previous studies in lattice hydrodynamic model have shown that the use of control method has the potential to improve traffic conditions. In this paper, a new control method is applied in lattice hydrodynamic model from a transportation cyber-physical system approach, in which only one lattice site needs to be controlled in this control scheme. The simulation verifies the feasibility and validity of this method, which can ensure the efficient and smooth operation of the traffic flow.

Potential effects of alterations to the hydrologic system on the distribution of salinity in the Biscayne aquifer in Broward County, Florida

USGS Publications Warehouse

Hughes, Joseph D.; Sifuentes, Dorothy F.; White, Jeremy T.

2016-03-15

Model accuracy and use are limited by uncertainty in the physical properties and boundary conditions of the system, uncertainty in historical and future conditions, and generalizations made in the mathematical relationships used to describe the physical processes of groundwater flow and transport. Because of these limitations, model results should be considered in relative rather than absolute terms. Nonetheless, model results do provide useful information on the relative scale of response of the system to changes in pumping distribution, sea-level rise, and mitigation activities.

A piezoelectric transformer

NASA Technical Reports Server (NTRS)

Won, C. C.

1993-01-01

This work describes a modeling and design method whereby a piezoelectric system is formulated by two sets of second-order equations, one for the mechanical system, and the other for the electrical system, coupled through the piezoelectric effect. The solution to this electromechanical coupled system gives a physical interpretation of the piezoelectric effect as a piezoelectric transformer that is a part of the piezoelectric system, which transfers the applied mechanical force into a force-controlled current source, and short circuit mechanical compliance into capacitance. It also transfers the voltage source into a voltage-controlled relative velocity input, and free motional capacitance into mechanical compliance. The formulation and interpretation simplify the modeling of smart structures and lead to physical insight that aids the designer. Due to its physical realization, the smart structural system can be unconditional stable and effectively control responses. This new concept has been demonstrated in three numerical examples for a simple piezoelectric system.

Training Administrators in Anasynthesis

ERIC Educational Resources Information Center

Silvern, Leonard C.

1971-01-01

The author discusses the application of physical and mathematical systems to non-physical social systems; specifically education and cinema, the process of analysis, synthesis, modeling and simulation. The author describes the course he has developed to instruct students in anasynthesis. (Author/RR)

A 3-D Approach for Teaching and Learning about Surface Water Systems through Computational Thinking, Data Visualization and Physical Models

NASA Astrophysics Data System (ADS)

Caplan, B.; Morrison, A.; Moore, J. C.; Berkowitz, A. R.

2017-12-01

Understanding water is central to understanding environmental challenges. Scientists use `big data' and computational models to develop knowledge about the structure and function of complex systems, and to make predictions about changes in climate, weather, hydrology, and ecology. Large environmental systems-related data sets and simulation models are difficult for high school teachers and students to access and make sense of. Comp Hydro, a collaboration across four states and multiple school districts, integrates computational thinking and data-related science practices into water systems instruction to enhance development of scientific model-based reasoning, through curriculum, assessment and teacher professional development. Comp Hydro addresses the need for 1) teaching materials for using data and physical models of hydrological phenomena, 2) building teachers' and students' comfort or familiarity with data analysis and modeling, and 3) infusing the computational knowledge and practices necessary to model and visualize hydrologic processes into instruction. Comp Hydro teams in Baltimore, MD and Fort Collins, CO are integrating teaching about surface water systems into high school courses focusing on flooding (MD) and surface water reservoirs (CO). This interactive session will highlight the successes and challenges of our physical and simulation models in helping teachers and students develop proficiency with computational thinking about surface water. We also will share insights from comparing teacher-led vs. project-led development of curriculum and our simulations.

A Novel Approach to Develop the Lower Order Model of Multi-Input Multi-Output System

NASA Astrophysics Data System (ADS)

Rajalakshmy, P.; Dharmalingam, S.; Jayakumar, J.

2017-10-01

A mathematical model is a virtual entity that uses mathematical language to describe the behavior of a system. Mathematical models are used particularly in the natural sciences and engineering disciplines like physics, biology, and electrical engineering as well as in the social sciences like economics, sociology and political science. Physicists, Engineers, Computer scientists, and Economists use mathematical models most extensively. With the advent of high performance processors and advanced mathematical computations, it is possible to develop high performing simulators for complicated Multi Input Multi Ouptut (MIMO) systems like Quadruple tank systems, Aircrafts, Boilers etc. This paper presents the development of the mathematical model of a 500 MW utility boiler which is a highly complex system. A synergistic combination of operational experience, system identification and lower order modeling philosophy has been effectively used to develop a simplified but accurate model of a circulation system of a utility boiler which is a MIMO system. The results obtained are found to be in good agreement with the physics of the process and with the results obtained through design procedure. The model obtained can be directly used for control system studies and to realize hardware simulators for boiler testing and operator training.

A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

NASA Astrophysics Data System (ADS)

Tao, W. K.

2017-12-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

Virtual design and optimization studies for industrial silicon microphones applying tailored system-level modeling

NASA Astrophysics Data System (ADS)

Kuenzig, Thomas; Dehé, Alfons; Krumbein, Ulrich; Schrag, Gabriele

2018-05-01

Maxing out the technological limits in order to satisfy the customers’ demands and obtain the best performance of micro-devices and-systems is a challenge of today’s manufacturers. Dedicated system simulation is key to investigate the potential of device and system concepts in order to identify the best design w.r.t. the given requirements. We present a tailored, physics-based system-level modeling approach combining lumped with distributed models that provides detailed insight into the device and system operation at low computational expense. The resulting transparent, scalable (i.e. reusable) and modularly composed models explicitly contain the physical dependency on all relevant parameters, thus being well suited for dedicated investigation and optimization of MEMS devices and systems. This is demonstrated for an industrial capacitive silicon microphone. The performance of such microphones is determined by distributed effects like viscous damping and inhomogeneous capacitance variation across the membrane as well as by system-level phenomena like package-induced acoustic effects and the impact of the electronic circuitry for biasing and read-out. The here presented model covers all relevant figures of merit and, thus, enables to evaluate the optimization potential of silicon microphones towards high fidelity applications. This work was carried out at the Technical University of Munich, Chair for Physics of Electrotechnology. Thomas Kuenzig is now with Infineon Technologies AG, Neubiberg.

Top-down models in biology: explanation and control of complex living systems above the molecular level.

PubMed

Pezzulo, Giovanni; Levin, Michael

2016-11-01

It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering. © 2016 The Author(s).

Top-down models in biology: explanation and control of complex living systems above the molecular level

PubMed Central

2016-01-01

It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering. PMID:27807271

Systems engineering in the Large Synoptic Survey Telescope project: an application of model based systems engineering

NASA Astrophysics Data System (ADS)

Claver, C. F.; Selvy, Brian M.; Angeli, George; Delgado, Francisco; Dubois-Felsmann, Gregory; Hascall, Patrick; Lotz, Paul; Marshall, Stuart; Schumacher, German; Sebag, Jacques

2014-08-01

The Large Synoptic Survey Telescope project was an early adopter of SysML and Model Based Systems Engineering practices. The LSST project began using MBSE for requirements engineering beginning in 2006 shortly after the initial release of the first SysML standard. Out of this early work the LSST's MBSE effort has grown to include system requirements, operational use cases, physical system definition, interfaces, and system states along with behavior sequences and activities. In this paper we describe our approach and methodology for cross-linking these system elements over the three classical systems engineering domains - requirement, functional and physical - into the LSST System Architecture model. We also show how this model is used as the central element to the overall project systems engineering effort. More recently we have begun to use the cross-linked modeled system architecture to develop and plan the system verification and test process. In presenting this work we also describe "lessons learned" from several missteps the project has had with MBSE. Lastly, we conclude by summarizing the overall status of the LSST's System Architecture model and our plans for the future as the LSST heads toward construction.

An evidential reasoning extension to quantitative model-based failure diagnosis

NASA Technical Reports Server (NTRS)

Gertler, Janos J.; Anderson, Kenneth C.

1992-01-01

The detection and diagnosis of failures in physical systems characterized by continuous-time operation are studied. A quantitative diagnostic methodology has been developed that utilizes the mathematical model of the physical system. On the basis of the latter, diagnostic models are derived each of which comprises a set of orthogonal parity equations. To improve the robustness of the algorithm, several models may be used in parallel, providing potentially incomplete and/or conflicting inferences. Dempster's rule of combination is used to integrate evidence from the different models. The basic probability measures are assigned utilizing quantitative information extracted from the mathematical model and from online computation performed therewith.

The browning value changes and spectral analysis on the Maillard reaction product from glucose and methionine model system

NASA Astrophysics Data System (ADS)

Al-Baarri, A. N.; Legowo, A. M.; Widayat

2018-01-01

D-glucose has been understood to provide the various effect on the reactivity in Maillard reaction resulting in the changes in physical performance of food product. Therefore this research was done to analyse physical appearance of Maillard reaction product made of D-glucose and methionine as a model system. The changes in browning value and spectral analysis model system were determined. The glucose-methionine model system was produced through the heating treatment at 50°C and RH 70% for 24 hours. The data were collected for every three hour using spectrophotometer. As result, browning value was elevated with the increase of heating time and remarkably high if compare to the D-glucose only. Furthermore, the spectral analysis showed that methionine turned the pattern of peak appearance. As conclusion, methionine raised the browning value and changed the pattern of spectral analysis in Maillard reaction model system.

When does a physical system compute?

PubMed

Horsman, Clare; Stepney, Susan; Wagner, Rob C; Kendon, Viv

2014-09-08

Computing is a high-level process of a physical system. Recent interest in non-standard computing systems, including quantum and biological computers, has brought this physical basis of computing to the forefront. There has been, however, no consensus on how to tell if a given physical system is acting as a computer or not; leading to confusion over novel computational devices, and even claims that every physical event is a computation. In this paper, we introduce a formal framework that can be used to determine whether a physical system is performing a computation. We demonstrate how the abstract computational level interacts with the physical device level, in comparison with the use of mathematical models in experimental science. This powerful formulation allows a precise description of experiments, technology, computation and simulation, giving our central conclusion: physical computing is the use of a physical system to predict the outcome of an abstract evolution . We give conditions for computing, illustrated using a range of non-standard computing scenarios. The framework also covers broader computing contexts, where there is no obvious human computer user. We introduce the notion of a 'computational entity', and its critical role in defining when computing is taking place in physical systems.

When does a physical system compute?

PubMed Central

Horsman, Clare; Stepney, Susan; Wagner, Rob C.; Kendon, Viv

2014-01-01

Computing is a high-level process of a physical system. Recent interest in non-standard computing systems, including quantum and biological computers, has brought this physical basis of computing to the forefront. There has been, however, no consensus on how to tell if a given physical system is acting as a computer or not; leading to confusion over novel computational devices, and even claims that every physical event is a computation. In this paper, we introduce a formal framework that can be used to determine whether a physical system is performing a computation. We demonstrate how the abstract computational level interacts with the physical device level, in comparison with the use of mathematical models in experimental science. This powerful formulation allows a precise description of experiments, technology, computation and simulation, giving our central conclusion: physical computing is the use of a physical system to predict the outcome of an abstract evolution. We give conditions for computing, illustrated using a range of non-standard computing scenarios. The framework also covers broader computing contexts, where there is no obvious human computer user. We introduce the notion of a ‘computational entity’, and its critical role in defining when computing is taking place in physical systems. PMID:25197245

How device-independent approaches change the meaning of physical theory

NASA Astrophysics Data System (ADS)

Grinbaum, Alexei

2017-05-01

Dirac sought an interpretation of mathematical formalism in terms of physical entities and Einstein insisted that physics should describe ;the real states of the real systems;. While Bell inequalities put into question the reality of states, modern device-independent approaches do away with the idea of entities: physical theory may contain no physical systems. Focusing on the correlations between operationally defined inputs and outputs, device-independent methods promote a view more distant from the conventional one than Einstein's 'principle theories' were from 'constructive theories'. On the examples of indefinite causal orders and almost quantum correlations, we ask a puzzling question: if physical theory is not about systems, then what is it about? Device-independent models suggest that physical theory can be 'about' languages.

Optimization and Control of Cyber-Physical Vehicle Systems

PubMed Central

Bradley, Justin M.; Atkins, Ella M.

2015-01-01

A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined. PMID:26378541

Optimization and Control of Cyber-Physical Vehicle Systems.

PubMed

Bradley, Justin M; Atkins, Ella M

2015-09-11

A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined.

A Preliminary Evaluation of the GFS Physics in the Navy Global Environmental Model

NASA Astrophysics Data System (ADS)

Liu, M.; Langland, R.; Martini, M.; Viner, K.

2017-12-01

Global extended long-range weather forecast is a goal in the near future at Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). In an effort to improve the performance of the Navy Global Environmental Model (NAVGEM) operated at FNMOC, and to gain more understanding of the impact of atmospheric physics in the long-range forecast, the physics package of the Global Forecast System (GFS) of the National Centers for Environmental Prediction is being evaluated in the framework of NAVGEM. That is GFS physics being transported by NAVGEM Semi-Lagrangian Semi-Implicit advection, and update-cycled by the 4D-variational data assimilation along with the assimilated land surface data of NASA's Land Information System. The output of free long runs of 10-day GFS physics forecast in a summer and a winter season are evaluated through the comparisons with the output of NAVGEM physics long forecast, and through the validations with observations and with the European Center's analyses data. It is found that the GFS physics is able to effectively reduce some of the modeling biases of NAVGEM, especially wind speed of the troposphere and land surface temperature that is an important surface boundary condition. The bias corrections increase with forecast leads, reaching maximum at 240 hours. To further understand the relative roles of physics and dynamics in extended long-range forecast, the tendencies of physics components and advection are also calculated and analyzed to compare their forces of magnitudes in the integration of winds, temperature, and moisture. The comparisons reveal the strength and limitation of GFS physics in the overall improvement of NAVGEM prediction system.

Gray-Box Approach for Thermal Modelling of Buildings for Applications in District Heating and Cooling Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saurav, Kumar; Chandan, Vikas

District-heating-and-cooling (DHC) systems are a proven energy solution that has been deployed for many years in a growing number of urban areas worldwide. They comprise a variety of technologies that seek to develop synergies between the production and supply of heat, cooling, domestic hot water and electricity. Although the benefits of DHC systems are significant and have been widely acclaimed, yet the full potential of modern DHC systems remains largely untapped. There are several opportunities for development of energy efficient DHC systems, which will enable the effective exploitation of alternative renewable resources, waste heat recovery, etc., in order to increasemore » the overall efficiency and facilitate the transition towards the next generation of DHC systems. This motivated the need for modelling these complex systems. Large-scale modelling of DHC-networks is challenging, as it has several components such as buildings, pipes, valves, heating source, etc., interacting with each other. In this paper, we focus on building modelling. In particular, we present a gray-box methodology for thermal modelling of buildings. Gray-box modelling is a hybrid of data driven and physics based models where, coefficients of the equations from physics based models are learned using data. This approach allows us to capture the dynamics of the buildings more effectively as compared to pure data driven approach. Additionally, this approach results in a simpler models as compared to pure physics based models. We first develop the individual components of the building such as temperature evolution, flow controller, etc. These individual models are then integrated in to the complete gray-box model for the building. The model is validated using data collected from one of the buildings at Lule{\\aa}, a city on the coast of northern Sweden.« less

New Educational Modules Using a Cyber-Distribution System Testbed

DOE PAGES

Xie, Jing; Bedoya, Juan Carlos; Liu, Chen-Ching; ...

2018-03-30

At Washington State University (WSU), a modern cyber-physical system testbed has been implemented based on an industry grade distribution management system (DMS) that is integrated with remote terminal units (RTUs), smart meters, and a solar photovoltaic (PV). In addition, the real model from the Avista Utilities distribution system in Pullman, WA, is modeled in DMS. The proposed testbed environment allows students and instructors to utilize these facilities for innovations in learning and teaching. For power engineering education, this testbed helps students understand the interaction between a cyber system and a physical distribution system through industrial level visualization. The testbed providesmore » a distribution system monitoring and control environment for students. Compared with a simulation based approach, the testbed brings the students' learning environment a step closer to the real world. The educational modules allow students to learn the concepts of a cyber-physical system and an electricity market through an integrated testbed. Furthermore, the testbed provides a platform in the study mode for students to practice working on a real distribution system model. Here, this paper describes the new educational modules based on the testbed environment. Three modules are described together with the underlying educational principles and associated projects.« less

New Educational Modules Using a Cyber-Distribution System Testbed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Jing; Bedoya, Juan Carlos; Liu, Chen-Ching

At Washington State University (WSU), a modern cyber-physical system testbed has been implemented based on an industry grade distribution management system (DMS) that is integrated with remote terminal units (RTUs), smart meters, and a solar photovoltaic (PV). In addition, the real model from the Avista Utilities distribution system in Pullman, WA, is modeled in DMS. The proposed testbed environment allows students and instructors to utilize these facilities for innovations in learning and teaching. For power engineering education, this testbed helps students understand the interaction between a cyber system and a physical distribution system through industrial level visualization. The testbed providesmore » a distribution system monitoring and control environment for students. Compared with a simulation based approach, the testbed brings the students' learning environment a step closer to the real world. The educational modules allow students to learn the concepts of a cyber-physical system and an electricity market through an integrated testbed. Furthermore, the testbed provides a platform in the study mode for students to practice working on a real distribution system model. Here, this paper describes the new educational modules based on the testbed environment. Three modules are described together with the underlying educational principles and associated projects.« less

Integration of Advanced Probabilistic Analysis Techniques with Multi-Physics Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cetiner, Mustafa Sacit; none,; Flanagan, George F.

2014-07-30

An integrated simulation platform that couples probabilistic analysis-based tools with model-based simulation tools can provide valuable insights for reactive and proactive responses to plant operating conditions. The objective of this work is to demonstrate the benefits of a partial implementation of the Small Modular Reactor (SMR) Probabilistic Risk Assessment (PRA) Detailed Framework Specification through the coupling of advanced PRA capabilities and accurate multi-physics plant models. Coupling a probabilistic model with a multi-physics model will aid in design, operations, and safety by providing a more accurate understanding of plant behavior. This represents the first attempt at actually integrating these two typesmore » of analyses for a control system used for operations, on a faster than real-time basis. This report documents the development of the basic communication capability to exchange data with the probabilistic model using Reliability Workbench (RWB) and the multi-physics model using Dymola. The communication pathways from injecting a fault (i.e., failing a component) to the probabilistic and multi-physics models were successfully completed. This first version was tested with prototypic models represented in both RWB and Modelica. First, a simple event tree/fault tree (ET/FT) model was created to develop the software code to implement the communication capabilities between the dynamic-link library (dll) and RWB. A program, written in C#, successfully communicates faults to the probabilistic model through the dll. A systems model of the Advanced Liquid-Metal Reactor–Power Reactor Inherently Safe Module (ALMR-PRISM) design developed under another DOE project was upgraded using Dymola to include proper interfaces to allow data exchange with the control application (ConApp). A program, written in C+, successfully communicates faults to the multi-physics model. The results of the example simulation were successfully plotted.« less

The Spinal Cord Injury- Functional Index: Item Banks to Measure Physical Functioning of Individuals with Spinal Cord Injury

PubMed Central

Tulsky, David S.; Jette, Alan; Kisala, Pamela A.; Kalpakjian, Claire; Dijkers, Marcel P.; Whiteneck, Gale; Ni, Pengsheng; Kirshblum, Steven; Charlifue, Susan; Heinemann, Allen W.; Forchheimer, Martin; Slavin, Mary; Houlihan, Bethlyn; Tate, Denise; Dyson-Hudson, Trevor; Fyffe, Denise; Williams, Steve; Zanca, Jeanne

2012-01-01

Objective To develop a comprehensive set of patient reported items to assess multiple aspects of physical functioning relevant to the lives of people with spinal cord injury (SCI) and to evaluate the underlying structure of physical functioning. Design Cross-sectional Setting Inpatient and community Participants Item pools of physical functioning were developed, refined and field tested in a large sample of 855 individuals with traumatic spinal cord injury stratified by diagnosis, severity, and time since injury Interventions None Main Outcome Measure SCI-FI measurement system Results Confirmatory factor analysis (CFA) indicated that a 5-factor model, including basic mobility, ambulation, wheelchair mobility, self care, and fine motor, had the best model fit and was most closely aligned conceptually with feedback received from individuals with SCI and SCI clinicians. When just the items making up basic mobility were tested in CFA, the fit statistics indicate strong support for a unidimensional model. Similar results were demonstrated for each of the other four factors indicating unidimensional models. Conclusions Though unidimensional or 2-factor (mobility and upper extremity) models of physical functioning make up outcomes measures in the general population, the underlying structure of physical function in SCI is more complex. A 5-factor solution allows for comprehensive assessment of key domain areas of physical functioning. These results informed the structure and development of the SCI-FI measurement system of physical functioning. PMID:22609299

Final Report Collaborative Project. Improving the Representation of Coastal and Estuarine Processes in Earth System Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bryan, Frank; Dennis, John; MacCready, Parker

This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation. The main computational objectives were: 1. To develop computationally efficient, but physically based, parameterizations of estuary and continental shelf mixing processes for use in an Earth System Model (CESM). 2. Tomore » develop a two-way nested regional modeling framework in order to dynamically downscale the climate response of particular coastal ocean regions and to upscale the impact of the regional coastal processes to the global climate in an Earth System Model (CESM). 3. To develop computational infrastructure to enhance the efficiency of data transfer between specific sources and destinations, i.e., a point-to-point communication capability, (used in objective 1) within POP, the ocean component of CESM.« less

Analysis of the 20th November 2003 Extreme Geomagnetic Storm using CTIPe Model and GNSS Data

NASA Astrophysics Data System (ADS)

Fernandez-Gomez, I.; Borries, C.; Codrescu, M.

2016-12-01

The ionospheric instabilities produced by solar activity generate disturbances in ionospheric density (ionospheric storms) with important terrestrial consequences such as disrupting communications and positioning. During the 20th November 2003 extreme geomagnetic storm, significant perturbations were produced in the ionosphere - thermosphere system. In this work, we replicate how this system responded to the onset of this particular storm, using the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics physics based model. CTIPe simulates the changes in the neutral winds, temperature, composition and electron densities. Although modelling the ionosphere under this conditions is a challenging task due to energy flow uncertainties, the model reproduces some of the storm features necessary to interpret the physical mechanisms behind the Total Electron Content (TEC) increase and the dramatic changes in composition during this event.Corresponding effects are observed in the TEC simulations from other physics based models and from observations derived from Global Navigation Satellite System (GNSS) and ground-based measurements.The study illustrates the necessity of using both, measurements and models, to have a complete understanding of the processes that are most likely responsible for the observed effects.

Feasibility of self-correcting quantum memory and thermal stability of topological order

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoshida, Beni, E-mail: rouge@mit.edu

2011-10-15

Recently, it has become apparent that the thermal stability of topologically ordered systems at finite temperature, as discussed in condensed matter physics, can be studied by addressing the feasibility of self-correcting quantum memory, as discussed in quantum information science. Here, with this correspondence in mind, we propose a model of quantum codes that may cover a large class of physically realizable quantum memory. The model is supported by a certain class of gapped spin Hamiltonians, called stabilizer Hamiltonians, with translation symmetries and a small number of ground states that does not grow with the system size. We show that themore » model does not work as self-correcting quantum memory due to a certain topological constraint on geometric shapes of its logical operators. This quantum coding theoretical result implies that systems covered or approximated by the model cannot have thermally stable topological order, meaning that systems cannot be stable against both thermal fluctuations and local perturbations simultaneously in two and three spatial dimensions. - Highlights: > We define a class of physically realizable quantum codes. > We determine their coding and physical properties completely. > We establish the connection between topological order and self-correcting memory. > We find they do not work as self-correcting quantum memory. > We find they do not have thermally stable topological order.« less

Modeling of Electrocardiograph Telediagnosing System Based on Petri Net

NASA Astrophysics Data System (ADS)

Hu, Wensong; Li, Ming; Li, Lan

This paper analyzed the characteristics of the electrocardiograph telediagnosing system. Firstly, we introduce the system and Petri nets. Secondly, we built a topological diagram of this system. Then we use Petri nets to show the physical process of this system. Finally, we verified the model of the electrocardiograph telediagnosing system. With the help of model based on Petri nets, we analyzed the system performance and feasibility.

The Physics of Colour Vision.

ERIC Educational Resources Information Center

Goldman, Martin

1985-01-01

An elementary physical model of cone receptor cells is explained and applied to complexities of human color vision. One-, two-, and three-receptor systems are considered, with the later shown to be the best model for the human eye. Color blindness is also discussed. (DH)

An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud

PubMed Central

Dinh, Thanh; Kim, Younghan

2016-01-01

This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud. PMID:27367689

An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud.

PubMed

Dinh, Thanh; Kim, Younghan

2016-06-28

This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud.

A formulation of multidimensional growth models for the assessment and forecast of technology attributes

NASA Astrophysics Data System (ADS)

Danner, Travis W.

Developing technology systems requires all manner of investment---engineering talent, prototypes, test facilities, and more. Even for simple design problems the investment can be substantial; for complex technology systems, the development costs can be staggering. The profitability of a corporation in a technology-driven industry is crucially dependent on maximizing the effectiveness of research and development investment. Decision-makers charged with allocation of this investment are forced to choose between the further evolution of existing technologies and the pursuit of revolutionary technologies. At risk on the one hand is excessive investment in an evolutionary technology which has only limited availability for further improvement. On the other hand, the pursuit of a revolutionary technology may mean abandoning momentum and the potential for substantial evolutionary improvement resulting from the years of accumulated knowledge. The informed answer to this question, evolutionary or revolutionary, requires knowledge of the expected rate of improvement and the potential a technology offers for further improvement. This research is dedicated to formulating the assessment and forecasting tools necessary to acquire this knowledge. The same physical laws and principles that enable the development and improvement of specific technologies also limit the ultimate capability of those technologies. Researchers have long used this concept as the foundation for modeling technological advancement through extrapolation by analogy to biological growth models. These models are employed to depict technology development as it asymptotically approaches limits established by the fundamental principles on which the technological approach is based. This has proven an effective and accurate approach to modeling and forecasting simple single-attribute technologies. With increased system complexity and the introduction of multiple system objectives, however, the usefulness of this modeling technique begins to diminish. With the introduction of multiple objectives, researchers often abandon technology growth models for scoring models and technology frontiers. While both approaches possess advantages over current growth models for the assessment of multi-objective technologies, each lacks a necessary dimension for comprehensive technology assessment. By collapsing multiple system metrics into a single, non-intuitive technology measure, scoring models provide a succinct framework for multi-objective technology assessment and forecasting. Yet, with no consideration of physical limits, scoring models provide no insight as to the feasibility of a particular combination of system capabilities. They only indicate that a given combination of system capabilities yields a particular score. Conversely, technology frontiers are constructed with the distinct objective of providing insight into the feasibility of system capability combinations. Yet again, upper limits to overall system performance are ignored. Furthermore, the data required to forecast subsequent technology frontiers is often inhibitive. In an attempt to reincorporate the fundamental nature of technology advancement as bound by physical principles, researchers have sought to normalize multi-objective systems whereby the variability of a single system objective is eliminated as a result of changes in the remaining objectives. This drastically limits the applicability of the resulting technology model because it is only applicable for a single setting of all other system attributes. Attempts to maintain the interaction between the growth curves of each technical objective of a complex system have thus far been limited to qualitative and subjective consideration. This research proposes the formulation of multidimensional growth models as an approach to simulating the advancement of multi-objective technologies towards their upper limits. Multidimensional growth models were formulated by noticing and exploiting the correlation between technology growth models and technology frontiers. Both are frontiers in actuality. The technology growth curve is a frontier between capability levels of a single attribute and time, while a technology frontier is a frontier between the capability levels of two or more attributes. Multidimensional growth models are formulated by exploiting the mathematical significance of this correlation. The result is a model that can capture both the interaction between multiple system attributes and their expected rates of improvement over time. The fundamental nature of technology development is maintained, and interdependent growth curves are generated for each system metric with minimal data requirements. Being founded on the basic nature of technology advancement, relative to physical limits, the availability for further improvement can be determined for a single metric relative to other system measures of merit. A by-product of this modeling approach is a single n-dimensional technology frontier linking all n system attributes with time. This provides an environment capable of forecasting future system capability in the form of advancing technology frontiers. The ability of a multidimensional growth model to capture the expected improvement of a specific technological approach is dependent on accurately identifying the physical limitations to each pertinent attribute. This research investigates two potential approaches to identifying those physical limits, a physics-based approach and a regression-based approach. The regression-based approach has found limited acceptance among forecasters, although it does show potential for estimating upper limits with a specified degree of uncertainty. Forecasters have long favored physics-based approaches for establishing the upper limit to unidimensional growth models. The task of accurately identifying upper limits has become increasingly difficult with the extension of growth models into multiple dimensions. A lone researcher may be able to identify the physical limitation to a single attribute of a simple system; however, as system complexity and the number of attributes increases, the attention of researchers from multiple fields of study is required. Thus, limit identification is itself an area of research and development requiring some level of investment. Whether estimated by physics or regression-based approaches, predicted limits will always have some degree of uncertainty. This research takes the approach of quantifying the impact of that uncertainty on model forecasts rather than heavily endorsing a single technique to limit identification. In addition to formulating the multidimensional growth model, this research provides a systematic procedure for applying that model to specific technology architectures. Researchers and decision-makers are able to investigate the potential for additional improvement within that technology architecture and to estimate the expected cost of each incremental improvement relative to the cost of past improvements. In this manner, multidimensional growth models provide the necessary information to set reasonable program goals for the further evolution of a particular technological approach or to establish the need for revolutionary approaches in light of the constraining limits of conventional approaches.

Persuasive Technology in Mobile Applications Promoting Physical Activity: a Systematic Review.

PubMed

Matthews, John; Win, Khin Than; Oinas-Kukkonen, Harri; Freeman, Mark

2016-03-01

Persuasive technology in mobile applications can be used to influence the behaviour of users. A framework known as the Persuasive Systems Design model has been developed for designing and evaluating systems that influence the attitudes or behaviours of users. This paper reviews the current state of mobile applications for health behavioural change with an emphasis on applications that promote physical activity. The inbuilt persuasive features of mobile applications were evaluated using the Persuasive Systems Design model. A database search was conducted to identify relevant articles. Articles were then reviewed using the Persuasive Systems Design model as a framework for analysis. Primary task support, dialogue support, and social support were found to be moderately represented in the selected articles. However, system credibility support was found to have only low levels of representation as a persuasive systems design feature in mobile applications for supporting physical activity. To ensure that available mobile technology resources are best used to improve the wellbeing of people, it is important that the design principles that influence the effectiveness of persuasive technology be understood.

Use of system identification techniques for improving airframe finite element models using test data

NASA Technical Reports Server (NTRS)

Hanagud, Sathya V.; Zhou, Weiyu; Craig, James I.; Weston, Neil J.

1993-01-01

A method for using system identification techniques to improve airframe finite element models using test data was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in the total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all of the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Atmospheric cloud physics thermal systems analysis

NASA Technical Reports Server (NTRS)

1977-01-01

Engineering analyses performed on the Atmospheric Cloud Physics (ACPL) Science Simulator expansion chamber and associated thermal control/conditioning system are reported. Analyses were made to develop a verified thermal model and to perform parametric thermal investigations to evaluate systems performance characteristics. Thermal network representations of solid components and the complete fluid conditioning system were solved simultaneously using the Systems Improved Numerical Differencing Analyzer (SINDA) computer program.

Passive simulation of the nonlinear port-Hamiltonian modeling of a Rhodes Piano

NASA Astrophysics Data System (ADS)

Falaize, Antoine; Hélie, Thomas

2017-03-01

This paper deals with the time-domain simulation of an electro-mechanical piano: the Fender Rhodes. A simplified description of this multi-physical system is considered. It is composed of a hammer (nonlinear mechanical component), a cantilever beam (linear damped vibrating component) and a pickup (nonlinear magneto-electronic transducer). The approach is to propose a power-balanced formulation of the complete system, from which a guaranteed-passive simulation is derived to generate physically-based realistic sound synthesis. Theses issues are addressed in four steps. First, a class of Port-Hamiltonian Systems is introduced: these input-to-output systems fulfill a power balance that can be decomposed into conservative, dissipative and source parts. Second, physical models are proposed for each component and are recast in the port-Hamiltonian formulation. In particular, a finite-dimensional model of the cantilever beam is derived, based on a standard modal decomposition applied to the Euler-Bernoulli model. Third, these systems are interconnected, providing a nonlinear finite-dimensional Port-Hamiltonian System of the piano. Fourth, a passive-guaranteed numerical method is proposed. This method is built to preserve the power balance in the discrete-time domain, and more precisely, its decomposition structured into conservative, dissipative and source parts. Finally, simulations are performed for a set of physical parameters, based on empirical but realistic values. They provide a variety of audio signals which are perceptively relevant and qualitatively similar to some signals measured on a real instrument.

Physical and Hydrological Meaning of the Spectral Information from Hydrodynamic Signals at Karst Springs

NASA Astrophysics Data System (ADS)

Dufoyer, A.; Lecoq, N.; Massei, N.; Marechal, J. C.

2017-12-01

Physics-based modeling of karst systems remains almost impossible without enough accurate information about the inner physical characteristics. Usually, the only available hydrodynamic information is the flow rate at the karst outlet. Numerous works in the past decades have used and proven the usefulness of time-series analysis and spectral techniques applied to spring flow, precipitations or even physico-chemical parameters, for interpreting karst hydrological functioning. However, identifying or interpreting the karst systems physical features that control statistical or spectral characteristics of spring flow variations is still challenging, not to say sometimes controversial. The main objective of this work is to determine how the statistical and spectral characteristics of the hydrodynamic signal at karst springs can be related to inner physical and hydraulic properties. In order to address this issue, we undertake an empirical approach based on the use of both distributed and physics-based models, and on synthetic systems responses. The first step of the research is to conduct a sensitivity analysis of time-series/spectral methods to karst hydraulic and physical properties. For this purpose, forward modeling of flow through several simple, constrained and synthetic cases in response to precipitations is undertaken. It allows us to quantify how the statistical and spectral characteristics of flow at the outlet are sensitive to changes (i) in conduit geometries, and (ii) in hydraulic parameters of the system (matrix/conduit exchange rate, matrix hydraulic conductivity and storativity). The flow differential equations resolved by MARTHE, a computer code developed by the BRGM, allows karst conduits modeling. From signal processing on simulated spring responses, we hope to determine if specific frequencies are always modified, thanks to Fourier series and multi-resolution analysis. We also hope to quantify which parameters are the most variable with auto-correlation analysis: first results seem to show higher variations due to conduit conductivity than the ones due to matrix/conduit exchange rate. Future steps will be using another computer code, based on double-continuum approach and allowing turbulent conduit flow, and modeling a natural system.

A Baseline Patient Model to Support Testing of Medical Cyber-Physical Systems.

PubMed

Silva, Lenardo C; Perkusich, Mirko; Almeida, Hyggo O; Perkusich, Angelo; Lima, Mateus A M; Gorgônio, Kyller C

2015-01-01

Medical Cyber-Physical Systems (MCPS) are currently a trending topic of research. The main challenges are related to the integration and interoperability of connected medical devices, patient safety, physiologic closed-loop control, and the verification and validation of these systems. In this paper, we focus on patient safety and MCPS validation. We present a formal patient model to be used in health care systems validation without jeopardizing the patient's health. To determine the basic patient conditions, our model considers the four main vital signs: heart rate, respiratory rate, blood pressure and body temperature. To generate the vital signs we used regression models based on statistical analysis of a clinical database. Our solution should be used as a starting point for a behavioral patient model and adapted to specific clinical scenarios. We present the modeling process of the baseline patient model and show its evaluation. The conception process may be used to build different patient models. The results show the feasibility of the proposed model as an alternative to the immediate need for clinical trials to test these medical systems.

Coupling System Dynamics and Physically-based Models for Participatory Water Management - A Methodological Framework, with Two Case Studies: Water Quality in Quebec, and Soil Salinity in Pakistan

NASA Astrophysics Data System (ADS)

Boisvert-Chouinard, J.; Halbe, J.; Baig, A. I.; Adamowski, J. F.

2014-12-01

The principles of Integrated Water Resource Management outline the importance of stakeholder participation in water management processes, but in practice, there is a lack of meaningful engagement in water planning and implementation, and participation is often limited to public consultation and education. When models are used to support water planning, stakeholders are usually not involved in their development and use, and the models commonly fail to represent important feedbacks between socio-economic and physical processes. This paper presents the development of holistic models of the Du Chêne basin in Quebec, and the Rechna Doab basin in Pakistan, that simulate socio-economic and physical processes related to, respectively, water quality management, and soil salinity management. The models each consists of two sub-components: a System Dynamics (SD) model, and a physically based model. The SD component was developed in collaboration with key stakeholders in the basins. The Du Chêne SD model was coupled with a Soil and Water Assessment Tool (SWAT) model, while the Rechna Doab SD model was coupled with SahysMod, a soil salinity model. The coupled models were used to assess the environmental and socio-economic impacts of different management scenarios proposed by stakeholders. Results indicate that coupled SD - physically-based models can be used as effective tools for participatory water planning and implementation. The participatory modeling process provides a structure for meaningful stakeholder engagement, and the models themselves can be used to transparently and coherently assess and compare different management options.

Incorporating Prognostic Marine Nitrogen Fixers and Related Bio-Physical Feedbacks in an Earth System Model

NASA Astrophysics Data System (ADS)

Paulsen, H.; Ilyina, T.; Six, K. D.

2016-02-01

Marine nitrogen fixers play a fundamental role in the oceanic nitrogen and carbon cycles by providing a major source of `new' nitrogen to the euphotic zone that supports biological carbon export and sequestration. Furthermore, nitrogen fixers may regionally have a direct impact on ocean physics and hence the climate system as they form extensive surface mats which can increase light absorption and surface albedo and reduce the momentum input by wind. Resulting alterations in temperature and stratification may feed back on nitrogen fixers' growth itself.We incorporate nitrogen fixers as a prognostic 3D tracer in the ocean biogeochemical component (HAMOCC) of the Max Planck Institute Earth system model and assess for the first time the impact of related bio-physical feedbacks on biogeochemistry and the climate system.The model successfully reproduces recent estimates of global nitrogen fixation rates, as well as the observed distribution of nitrogen fixers, covering large parts of the tropical and subtropical oceans. First results indicate that including bio-physical feedbacks has considerable effects on the upper ocean physics in this region. Light absorption by nitrogen fixers leads locally to surface heating, subsurface cooling, and mixed layer depth shoaling in the subtropical gyres. As a result, equatorial upwelling is increased, leading to surface cooling at the equator. This signal is damped by the effect of the reduced wind stress due to the presence of cyanobacteria mats, which causes a reduction in the wind-driven circulation, and hence a reduction in equatorial upwelling. The increase in surface albedo due to nitrogen fixers has only inconsiderable effects. The response of nitrogen fixers' growth to the alterations in temperature and stratification varies regionally. Simulations with the fully coupled Earth system model are in progress to assess the implications of the biologically induced changes in upper ocean physics for the global climate system.

Physical Invariants of Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail

2010-01-01

A program of research is dedicated to development of a mathematical formalism that could provide, among other things, means by which living systems could be distinguished from non-living ones. A major issue that arises in this research is the following question: What invariants of mathematical models of the physics of systems are (1) characteristic of the behaviors of intelligent living systems and (2) do not depend on specific features of material compositions heretofore considered to be characteristic of life? This research at earlier stages has been reported, albeit from different perspectives, in numerous previous NASA Tech Briefs articles. To recapitulate: One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Mathematical models of motor dynamics are used to simulate the observable physical behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. At the time of reporting the information for this article, the focus of this research was upon the following aspects of the formalism: Intelligence is considered to be a means by which a living system preserves itself and improves its ability to survive and is further considered to manifest itself in feedback from the mental dynamics to the motor dynamics. Because of the feedback from the mental dynamics, the motor dynamics attains quantum-like properties: The trajectory of the physical aspect of the system in the space of dynamical variables splits into a family of different trajectories, and each of those trajectories can be chosen with a probability prescribed by the mental dynamics. From a slightly different perspective, the mechanism of decision-making is feedback from the mental dynamics to the motor dynamics, and this mechanism provides a quantum-like collapse of a random motion into an appropriate deterministic state, such that entropy undergoes a pronounced decrease. The existence of this mechanism is considered to be an invariant of intelligent behavior of living systems, regardless of the origins and material compositions of the systems.

A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors.

PubMed

Wu, Minglin; Zhang, Sheng; Dong, Yuhan

2016-10-20

In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution) and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden) can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects.

A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors

PubMed Central

Wu, Minglin; Zhang, Sheng; Dong, Yuhan

2016-01-01

In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution) and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden) can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects. PMID:27775625

SU-B-BRF-01: Professional Council Symposium: The Evolving US Healthcare Delivery Model, How Will the Medical Physics Profession Be Impacted and How Should We Respond?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halvorsen, P; Shine, K; White, G

The United States' healthcare delivery model is undergoing significant change. Insurance and reimbursement models are rapidly evolving, federal allocations are shifting from specialty services to preventive and generalpractice services, and Accountable Care Organizations are gaining in prominence. One area of focus is on the perceived over-utilization of expensive services such as advanced imaging and, in some cases, radiation therapy. Reimbursement incentives are increasingly aimed at quality metrics, leading to an increased interest in the core concepts of High Reliability Organizations. With the shift in federal resources away from specialty services and the increasing prominence of Accountable Care Organizations, we willmore » likely be challenged to re-assess our traditional model for delivering medical physics services. Medical physicists have a unique combination of education and training in physics principles, radiation physics applications in medicine, human anatomy, as well as safety analysis and quality control methods. An effective medical physicist recognizes that to advance the institution's mission, the medical physicist must join other professional leaders within the institution to provide clear direction and perspective for the entire team. To do that, we must first recognize the macro changes in our healthcare delivery system and candidly assess how the medical physics practice model can evolve in a prudent way to support the institution's objectives while maintaining the traditionally high level of quality and safety. This year's Professional Council Symposium will explore the many facets of the changing healthcare system and its potential impact on medical physics. Dr. Shine will provide an overview of the developing healthcare delivery and reimbursement models, with a focus on how the physician community has adapted to the changing objectives. Mr. White will describe recent changes in the reimbursement patterns for both imaging and radiation therapy services, the underlying imperatives that will influence additional changes in the near-term future, and the broader changes in the medical physics workforce that may arise due to many (often conflicting) directives and incentives both internal and external to the profession. Maintaining the integrity of the medical physics profession and the high quality of medical physics services will require a shared understanding of the changing practice environment and a firm commitment to protecting the key priorities of clinical medical physics as the healthcare system transitions to a new and very different model. To be effective as medical physicists, we must learn how to provide leadership in our respective institutions. Learning Objectives: Understand the macro changes occurring in the US healthcare delivery system. Understand the likely near-term, and possible longer-term, impact on the medical physics profession. Understand some strategies for providing leadership during this period of significant change.« less

Engineering the smart factory

NASA Astrophysics Data System (ADS)

Harrison, Robert; Vera, Daniel; Ahmad, Bilal

2016-10-01

The fourth industrial revolution promises to create what has been called the smart factory. The vision is that within such modular structured smart factories, cyber-physical systems monitor physical processes, create a virtual copy of the physical world and make decentralised decisions. This paper provides a view of this initiative from an automation systems perspective. In this context it considers how future automation systems might be effectively configured and supported through their lifecycles and how integration, application modelling, visualisation and reuse of such systems might be best achieved. The paper briefly describes limitations in current engineering methods, and new emerging approaches including the cyber physical systems (CPS) engineering tools being developed by the automation systems group (ASG) at Warwick Manufacturing Group, University of Warwick, UK.

Modeling of the radiation belt megnetosphere in decisional timeframes

DOEpatents

Koller, Josef; Reeves, Geoffrey D; Friedel, Reiner H.W.

2013-04-23

Systems and methods for calculating L* in the magnetosphere with essentially the same accuracy as with a physics based model at many times the speed by developing a surrogate trained to be a surrogate for the physics-based model. The trained model can then beneficially process input data falling within the training range of the surrogate model. The surrogate model can be a feedforward neural network and the physics-based model can be the TSK03 model. Operatively, the surrogate model can use parameters on which the physics-based model was based, and/or spatial data for the location where L* is to be calculated. Surrogate models should be provided for each of a plurality of pitch angles. Accordingly, a surrogate model having a closed drift shell can be used from the plurality of models. The feedforward neural network can have a plurality of input-layer units, there being at least one input-layer unit for each physics-based model parameter, a plurality of hidden layer units and at least one output unit for the value of L*.

Skill Assessment for Coupled Biological/Physical Models of Marine Systems.

PubMed

Stow, Craig A; Jolliff, Jason; McGillicuddy, Dennis J; Doney, Scott C; Allen, J Icarus; Friedrichs, Marjorie A M; Rose, Kenneth A; Wallhead, Philip

2009-02-20

Coupled biological/physical models of marine systems serve many purposes including the synthesis of information, hypothesis generation, and as a tool for numerical experimentation. However, marine system models are increasingly used for prediction to support high-stakes decision-making. In such applications it is imperative that a rigorous model skill assessment is conducted so that the model's capabilities are tested and understood. Herein, we review several metrics and approaches useful to evaluate model skill. The definition of skill and the determination of the skill level necessary for a given application is context specific and no single metric is likely to reveal all aspects of model skill. Thus, we recommend the use of several metrics, in concert, to provide a more thorough appraisal. The routine application and presentation of rigorous skill assessment metrics will also serve the broader interests of the modeling community, ultimately resulting in improved forecasting abilities as well as helping us recognize our limitations.

Energy evaluation of protection effectiveness of anti-vibration gloves.

PubMed

Hermann, Tomasz; Dobry, Marian Witalis

2017-09-01

This article describes an energy method of assessing protection effectiveness of anti-vibration gloves on the human dynamic structure. The study uses dynamic models of the human and the glove specified in Standard No. ISO 10068:2012. The physical models of human-tool systems were developed by combining human physical models with a power tool model. The combined human-tool models were then transformed into mathematical models from which energy models were finally derived. Comparative energy analysis was conducted in the domain of rms powers. The energy models of the human-tool systems were solved using numerical simulation implemented in the MATLAB/Simulink environment. The simulation procedure demonstrated the effectiveness of the anti-vibration glove as a method of protecting human operators of hand-held power tools against vibration. The desirable effect is achieved by lowering the flow of energy in the human-tool system when the anti-vibration glove is employed.

Cellular Gauge Symmetry and the Li Organization Principle: A Mathematical Addendum. Quantifying energetic dynamics in physical and biological systems through a simple geometric tool and geodetic curves.

PubMed

Yurkin, Alexander; Tozzi, Arturo; Peters, James F; Marijuán, Pedro C

2017-12-01

The present Addendum complements the accompanying paper "Cellular Gauge Symmetry and the Li Organization Principle"; it illustrates a recently-developed geometrical physical model able to assess electronic movements and energetic paths in atomic shells. The model describes a multi-level system of circular, wavy and zigzag paths which can be projected onto a horizontal tape. This model ushers in a visual interpretation of the distribution of atomic electrons' energy levels and the corresponding quantum numbers through rather simple tools, such as compasses, rulers and straightforward calculations. Here we show how this geometrical model, with the due corrections, among them the use of geodetic curves, might be able to describe and quantify the structure and the temporal development of countless physical and biological systems, from Langevin equations for random paths, to symmetry breaks occurring ubiquitously in physical and biological phenomena, to the relationships among different frequencies of EEG electric spikes. Therefore, in our work we explore the possible association of binomial distribution and geodetic curves configuring a uniform approach for the research of natural phenomena, in biology, medicine or the neurosciences. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Risk-Based Approach for Aerothermal/TPS Analysis and Testing

NASA Technical Reports Server (NTRS)

Wright, Michael J.; Grinstead, Jay H.; Bose, Deepak

2007-01-01

The current status of aerothermal and thermal protection system modeling for civilian entry missions is reviewed. For most such missions, the accuracy of our simulations is limited not by the tools and processes currently employed, but rather by reducible deficiencies in the underlying physical models. Improving the accuracy of and reducing the uncertainties in these models will enable a greater understanding of the system level impacts of a particular thermal protection system and of the system operation and risk over the operational life of the system. A strategic plan will be laid out by which key modeling deficiencies can be identified via mission-specific gap analysis. Once these gaps have been identified, the driving component uncertainties are determined via sensitivity analyses. A Monte-Carlo based methodology is presented for physics-based probabilistic uncertainty analysis of aerothermodynamics and thermal protection system material response modeling. These data are then used to advocate for and plan focused testing aimed at reducing key uncertainties. The results of these tests are used to validate or modify existing physical models. Concurrently, a testing methodology is outlined for thermal protection materials. The proposed approach is based on using the results of uncertainty/sensitivity analyses discussed above to tailor ground testing so as to best identify and quantify system performance and risk drivers. A key component of this testing is understanding the relationship between the test and flight environments. No existing ground test facility can simultaneously replicate all aspects of the flight environment, and therefore good models for traceability to flight are critical to ensure a low risk, high reliability thermal protection system design. Finally, the role of flight testing in the overall thermal protection system development strategy is discussed.

Integration of a three-dimensional process-based hydrological model into the Object Modeling System

USDA-ARS?s Scientific Manuscript database

The integration of a spatial process model into an environmental modelling framework can enhance the model’s capabilities. We present the integration of the GEOtop model into the Object Modeling System (OMS) version 3.0 and illustrate its application in a small watershed. GEOtop is a physically base...

Development of 3-axis precise positioning seismic physical modeling system in the simulation of marine seismic exploration

NASA Astrophysics Data System (ADS)

Kim, D.; Shin, S.; Ha, J.; Lee, D.; Lim, Y.; Chung, W.

2017-12-01

Seismic physical modeling is a laboratory-scale experiment that deals with the actual and physical phenomena that may occur in the field. In seismic physical modeling, field conditions are downscaled and used. For this reason, even a small error may lead to a big error in an actual field. Accordingly, the positions of the source and the receiver must be precisely controlled in scale modeling. In this study, we have developed a seismic physical modeling system capable of precisely controlling the 3-axis position. For automatic and precise position control of an ultrasonic transducer(source and receiver) in the directions of the three axes(x, y, and z), a motor was mounted on each of the three axes. The motor can automatically and precisely control the positions with positional precision of 2''; for the x and y axes and 0.05 mm for the z axis. As it can automatically and precisely control the positions in the directions of the three axes, it has an advantage in that simulations can be carried out using the latest exploration techniques, such as OBS and Broadband Seismic. For the signal generation section, a waveform generator that can produce a maximum of two sources was used, and for the data acquisition section, which receives and stores reflected signals, an A/D converter that can receive a maximum of four signals was used. As multiple sources and receivers could be used at the same time, the system was set up in such a way that diverse exploration methods, such as single channel, multichannel, and 3-D exploration, could be realized. A computer control program based on LabVIEW was created, so that it could control the position of the transducer, determine the data acquisition parameters, and check the exploration data and progress in real time. A marine environment was simulated using a water tank 1 m wide, 1 m long, and 0.9 m high. To evaluate the performance and applicability of the seismic physical modeling system developed in this study, single channel and multichannel explorations were carried out in the marine environment and the accuracy of the modeling system was verified by comparatively analyzing the exploration data and the numerical modeling data acquired.

Modelling and control issues of dynamically substructured systems: adaptive forward prediction taken as an example

PubMed Central

Tu, Jia-Ying; Hsiao, Wei-De; Chen, Chih-Ying

2014-01-01

Testing techniques of dynamically substructured systems dissects an entire engineering system into parts. Components can be tested via numerical simulation or physical experiments and run synchronously. Additional actuator systems, which interface numerical and physical parts, are required within the physical substructure. A high-quality controller, which is designed to cancel unwanted dynamics introduced by the actuators, is important in order to synchronize the numerical and physical outputs and ensure successful tests. An adaptive forward prediction (AFP) algorithm based on delay compensation concepts has been proposed to deal with substructuring control issues. Although the settling performance and numerical conditions of the AFP controller are improved using new direct-compensation and singular value decomposition methods, the experimental results show that a linear dynamics-based controller still outperforms the AFP controller. Based on experimental observations, the least-squares fitting technique, effectiveness of the AFP compensation and differences between delay and ordinary differential equations are discussed herein, in order to reflect the fundamental issues of actuator modelling in relevant literature and, more specifically, to show that the actuator and numerical substructure are heterogeneous dynamic components and should not be collectively modelled as a homogeneous delay differential equation. PMID:25104902

The management submodel of the Wind Erosion Prediction System

USDA-ARS?s Scientific Manuscript database

The Wind Erosion Prediction System (WEPS) is a process-based, daily time-step, computer model that predicts soil erosion via simulation of the physical processes controlling wind erosion. WEPS is comprised of several individual modules (submodels) that reflect different sets of physical processes, ...

Simple universal models capture all classical spin physics.

PubMed

De las Cuevas, Gemma; Cubitt, Toby S

2016-03-11

Spin models are used in many studies of complex systems because they exhibit rich macroscopic behavior despite their microscopic simplicity. Here, we prove that all the physics of every classical spin model is reproduced in the low-energy sector of certain "universal models," with at most polynomial overhead. This holds for classical models with discrete or continuous degrees of freedom. We prove necessary and sufficient conditions for a spin model to be universal and show that one of the simplest and most widely studied spin models, the two-dimensional Ising model with fields, is universal. Our results may facilitate physical simulations of Hamiltonians with complex interactions. Copyright © 2016, American Association for the Advancement of Science.

Simulation modelling for new gas turbine fuel controller creation.

NASA Astrophysics Data System (ADS)

Vendland, L. E.; Pribylov, V. G.; Borisov, Yu A.; Arzamastsev, M. A.; Kosoy, A. A.

2017-11-01

State of the art gas turbine fuel flow control systems are based on throttle principle. Major disadvantage of such systems is that they require high pressure fuel intake. Different approach to fuel flow control is to use regulating compressor. And for this approach because of controller and gas turbine interaction a specific regulating compressor is required. Difficulties emerge as early as the requirement definition stage. To define requirements for new object, his properties must be known. Simulation modelling helps to overcome these difficulties. At the requirement definition stage the most simplified mathematical model is used. Mathematical models will get more complex and detailed as we advance in planned work. If future adjusting of regulating compressor physical model to work with virtual gas turbine and physical control system is planned.

Statistical physics of the symmetric group.

PubMed

Williams, Mobolaji

2017-04-01

Ordered chains (such as chains of amino acids) are ubiquitous in biological cells, and these chains perform specific functions contingent on the sequence of their components. Using the existence and general properties of such sequences as a theoretical motivation, we study the statistical physics of systems whose state space is defined by the possible permutations of an ordered list, i.e., the symmetric group, and whose energy is a function of how certain permutations deviate from some chosen correct ordering. Such a nonfactorizable state space is quite different from the state spaces typically considered in statistical physics systems and consequently has novel behavior in systems with interacting and even noninteracting Hamiltonians. Various parameter choices of a mean-field model reveal the system to contain five different physical regimes defined by two transition temperatures, a triple point, and a quadruple point. Finally, we conclude by discussing how the general analysis can be extended to state spaces with more complex combinatorial properties and to other standard questions of statistical mechanics models.

Statistical physics of the symmetric group

NASA Astrophysics Data System (ADS)

Williams, Mobolaji

2017-04-01

Ordered chains (such as chains of amino acids) are ubiquitous in biological cells, and these chains perform specific functions contingent on the sequence of their components. Using the existence and general properties of such sequences as a theoretical motivation, we study the statistical physics of systems whose state space is defined by the possible permutations of an ordered list, i.e., the symmetric group, and whose energy is a function of how certain permutations deviate from some chosen correct ordering. Such a nonfactorizable state space is quite different from the state spaces typically considered in statistical physics systems and consequently has novel behavior in systems with interacting and even noninteracting Hamiltonians. Various parameter choices of a mean-field model reveal the system to contain five different physical regimes defined by two transition temperatures, a triple point, and a quadruple point. Finally, we conclude by discussing how the general analysis can be extended to state spaces with more complex combinatorial properties and to other standard questions of statistical mechanics models.

Current Status of Nuclear Physics Research

NASA Astrophysics Data System (ADS)

Bertulani, Carlos A.; Hussein, Mahir S.

2015-12-01

In this review, we discuss the current status of research in nuclear physics which is being carried out in different centers in the world. For this purpose, we supply a short account of the development in the area which evolved over the last nine decades, since the discovery of the neutron. The evolution of the physics of the atomic nucleus went through many stages as more data became available. We briefly discuss models introduced to discern the physics behind the experimental discoveries, such as the shell model, the collective model, the statistical model, the interacting boson model, etc., some of these models may be seemingly in conflict with each other, but this was shown to be only apparent. The richness of the ideas and abundance of theoretical models attests to the important fact that the nucleus is a really singular system in the sense that it evolves from two-body bound states such as the deuteron, to few-body bound states, such as 4He, 7Li, 9Be, etc. and up the ladder to heavier bound nuclei containing up to more than 200 nucleons. Clearly, statistical mechanics, usually employed in systems with very large number of particles, would seemingly not work for such finite systems as the nuclei, neither do other theories which are applicable to condensed matter. The richness of nuclear physics stems from these restrictions. New theories and models are presently being developed. Theories of the structure and reactions of neutron-rich and proton-rich nuclei, called exotic nuclei, halo nuclei, or Borromean nuclei, deal with the wealth of experimental data that became available in the last 35 years. Furthermore, nuclear astrophysics and stellar and Big Bang nucleosynthesis have become a more mature subject. Due to limited space, this review only covers a few selected topics, mainly those with which the authors have worked on. Our aimed potential readers of this review are nuclear physicists and physicists in other areas, as well as graduate students interested in pursuing a career in nuclear physics.

The morals of model-making.

PubMed

Sterrett, S G

2014-06-01

I address questions about values in model-making in engineering, specifically: Might the role of values be attributable solely to interests involved in specifying and using the model? Selected examples illustrate the surprisingly wide variety of things one must take into account in the model-making itself. The notions of system (as used in engineering thermodynamics), and physically similar systems (as used in the physical sciences) are important and powerful in determining what is relevant to an engineering model. Another example (windfarms) illustrates how an idea to completely re-characterize, or reframe, an engineering problem arose during model-making. I employ a qualitative analogue of the notion of physically similar systems. Historical cases can thus be drawn upon; I illustrate with a comparison between a geoengineering proposal to inject, or spray, sulfate aerosols, and two different historical cases involving the spraying of DDT (fire ant eradication; malaria eradication). The current geoengineering proposal is seen to be like the disastrous and counterproductive case, and unlike the successful case, of the spraying of DDT. I conclude by explaining my view that model-making in science is analogous to moral perception in action, drawing on a view in moral theory that has come to be called moral particularism.

Ordering, thermal excitations and phase transitions in dipolar coupled mono-domain magnet arrays

NASA Astrophysics Data System (ADS)

Kapaklis, Vassilios

2015-03-01

Magnetism has provided a fertile test bed for physical models, such as the Heisenberg and Ising models. Most of these investigations have focused on solid materials and relate to their atomic properties such as the atomic magnetic moments and their interactions. Recently, advances in nanotechnology have enabled the controlled patterning of nano-sized magnetic particles, which can be arranged in extended lattices. Tailoring the geometry and the magnetic material of these lattices, the magnetic interactions and magnetization reversal energy barriers can be tuned. This enables interesting interaction schemes to be examined on adjustable length and energy scales. As a result such nano-magnetic systems represent an ideal playground for the study of physical model systems, being facilitated by direct magnetic imaging techniques. One particularly interesting case is that of systems exhibiting frustration, where competing interactions cannot be simultaneously satisfied. This results in a degeneracy of the ground state and intricate thermodynamic properties. An archetypical frustrated physical system is water ice. Similar physics can be mirrored in nano-magnetic arrays, by tuning the arrangement of neighboring magnetic islands, referred to as artificial spin ice. Thermal excitations in such systems resemble magnetic monopoles. In this presentation key concepts related to nano-magnetism and artificial spin ice will be introduced and discussed, along with recent experimental and theoretical developments.

Game theoretic analysis of physical protection system design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Canion, B.; Schneider, E.; Bickel, E.

The physical protection system (PPS) of a fictional small modular reactor (SMR) facility have been modeled as a platform for a game theoretic approach to security decision analysis. To demonstrate the game theoretic approach, a rational adversary with complete knowledge of the facility has been modeled attempting a sabotage attack. The adversary adjusts his decisions in response to investments made by the defender to enhance the security measures. This can lead to a conservative physical protection system design. Since defender upgrades were limited by a budget, cost benefit analysis may be conducted upon security upgrades. One approach to cost benefitmore » analysis is the efficient frontier, which depicts the reduction in expected consequence per incremental increase in the security budget.« less

Enriching Triangle Mesh Animations with Physically Based Simulation.

PubMed

Li, Yijing; Xu, Hongyi; Barbic, Jernej

2017-10-01

We present a system to combine arbitrary triangle mesh animations with physically based Finite Element Method (FEM) simulation, enabling control over the combination both in space and time. The input is a triangle mesh animation obtained using any method, such as keyframed animation, character rigging, 3D scanning, or geometric shape modeling. The input may be non-physical, crude or even incomplete. The user provides weights, specified using a minimal user interface, for how much physically based simulation should be allowed to modify the animation in any region of the model, and in time. Our system then computes a physically-based animation that is constrained to the input animation to the amount prescribed by these weights. This permits smoothly turning physics on and off over space and time, making it possible for the output to strictly follow the input, to evolve purely based on physically based simulation, and anything in between. Achieving such results requires a careful combination of several system components. We propose and analyze these components, including proper automatic creation of simulation meshes (even for non-manifold and self-colliding undeformed triangle meshes), converting triangle mesh animations into animations of the simulation mesh, and resolving collisions and self-collisions while following the input.

Cyberspatial mechanics.

PubMed

Bayne, Jay S

2008-06-01

In support of a generalization of systems theory, this paper introduces a new approach in modeling complex distributed systems. It offers an analytic framework for describing the behavior of interactive cyberphysical systems (CPSs), which are networked stationary or mobile information systems responsible for the real-time governance of physical processes whose behaviors unfold in cyberspace. The framework is predicated on a cyberspace-time reference model comprising three spatial dimensions plus time. The spatial domains include geospatial, infospatial, and sociospatial references, the latter describing relationships among sovereign enterprises (rational agents) that choose voluntarily to organize and interoperate for individual and mutual benefit through geospatial (physical) and infospatial (logical) transactions. Of particular relevance to CPSs are notions of timeliness and value, particularly as they relate to the real-time governance of physical processes and engagements with other cooperating CPS. Our overarching interest, as with celestial mechanics, is in the formation and evolution of clusters of cyberspatial objects and the federated systems they form.

Coupling of a distributed stakeholder-built system dynamics socio-economic model with SAHYSMOD for sustainable soil salinity management - Part 1: Model development

NASA Astrophysics Data System (ADS)

Inam, Azhar; Adamowski, Jan; Prasher, Shiv; Halbe, Johannes; Malard, Julien; Albano, Raffaele

2017-08-01

Effective policies, leading to sustainable management solutions for land and water resources, require a full understanding of interactions between socio-economic and physical processes. However, the complex nature of these interactions, combined with limited stakeholder engagement, hinders the incorporation of socio-economic components into physical models. The present study addresses this challenge by integrating the physical Spatial Agro Hydro Salinity Model (SAHYSMOD) with a participatory group-built system dynamics model (GBSDM) that includes socio-economic factors. A stepwise process to quantify the GBSDM is presented, along with governing equations and model assumptions. Sub-modules of the GBSDM, describing agricultural, economic, water and farm management factors, are linked together with feedbacks and finally coupled with the physically based SAHYSMOD model through commonly used tools (i.e., MS Excel and a Python script). The overall integrated model (GBSDM-SAHYSMOD) can be used to help facilitate the role of stakeholders with limited expertise and resources in model and policy development and implementation. Following the development of the integrated model, a testing methodology was used to validate the structure and behavior of the integrated model. Model robustness under different operating conditions was also assessed. The model structure was able to produce anticipated real behaviours under the tested scenarios, from which it can be concluded that the formulated structures generate the right behaviour for the right reasons.

Review of incursive, hyperincursive and anticipatory systems-foundation of anticipation in electromagnetism

NASA Astrophysics Data System (ADS)

Dubois, Daniel M.

2000-05-01

The main purpose of this paper is to show that anticipation is not only a property of biosystems but is also a fundamental property of physical systems. In electromagnetism, the anticipation is related to the Lorentz transform. In this framework the anticipation is a strong anticipation because it is not based on a prediction from a model of the physical system but is embedded in the fundamental system. So, Robert Rosen's anticipatory systems deal with weak anticipation. Contrary to Robert Rosen's affirmation, anticipation is thus not a characteristic of living systems. Finality is implicitly embedded in any system and thus the final cause of Aristotle is implicitly embedded in any physical and biological systems, contrary to what Robert Rosen argued. This paper will review some incursive and hyperincursive systems giving rise to strong anticipation. Space-time incursive parabolic systems show non-local properties. Hyperincursive crisp systems are related to catastrophe theory. Finally it will be shown that incursive and hyperincursive anticipatory systems could model properties of biosystems like free will, game strategy, theorem creation, etc. Anticipation is not only related to predictions but to decisions: hyperincursive systems create multiple choices and a decision process selects one choice. So, anticipation is not a final goal, like in cybernetics and system science, but is a fundamental property of physical and biological systems.

PHYSICAL AND NUMERICAL MODELING OF ASD EXHAUST DISPERSION AROUND HOUSES

EPA Science Inventory

The report discusses the use of a wind tunnel to physically model the dispersion of exhaust plumes from active soil depressurization (ASD) radon mitigation systems in houses. he testing studied the effects of exhaust location (grade level vs. above the eave), as house height, roo...

Hierarchical multi-scale approach to validation and uncertainty quantification of hyper-spectral image modeling

NASA Astrophysics Data System (ADS)

Engel, Dave W.; Reichardt, Thomas A.; Kulp, Thomas J.; Graff, David L.; Thompson, Sandra E.

2016-05-01

Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensor level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.

Integrating Unified Gravity Wave Physics into the NOAA Next Generation Global Prediction System

NASA Astrophysics Data System (ADS)

Alpert, J. C.; Yudin, V.; Fuller-Rowell, T. J.; Akmaev, R. A.

2017-12-01

The Unified Gravity Wave Physics (UGWP) project for the Next Generation Global Prediction System (NGGPS) is a NOAA collaborative effort between the National Centers for Environmental Prediction (NCEP), Environemntal Modeling Center (EMC) and the University of Colorado, Cooperative Institute for Research in Environmental Sciences (CU-CIRES) to support upgrades and improvements of GW dynamics (resolved scales) and physics (sub-grid scales) in the NOAA Environmental Modeling System (NEMS)†. As envisioned the global climate, weather and space weather models of NEMS will substantially improve their predictions and forecasts with the resolution-sensitive (scale-aware) formulations planned under the UGWP framework for both orographic and non-stationary waves. In particular, the planned improvements for the Global Forecast System (GFS) model of NEMS are: calibration of model physics for higher vertical and horizontal resolution and an extended vertical range of simulations, upgrades to GW schemes, including the turbulent heating and eddy mixing due to wave dissipation and breaking, and representation of the internally-generated QBO. The main priority of the UGWP project is unified parameterization of orographic and non-orographic GW effects including momentum deposition in the middle atmosphere and turbulent heating and eddies due to wave dissipation and breaking. The latter effects are not currently represented in NOAA atmosphere models. The team has tested and evaluated four candidate GW solvers integrating the selected GW schemes into the NGGPS model. Our current work and planned activity is to implement the UGWP schemes in the first available GFS/FV3 (open FV3) configuration including adapted GFDL modification for sub-grid orography in GFS. Initial global model results will be shown for the operational and research GFS configuration for spectral and FV3 dynamical cores. †http://www.emc.ncep.noaa.gov/index.php?branch=NEMS

The quest for a new modelling framework in mathematical biology. Comment on "On the interplay between mathematics and biology: Hallmarks towards a new systems biology" by N. Bellomo et al.

NASA Astrophysics Data System (ADS)

Eftimie, Raluca

2015-03-01

One of the main unsolved problems of modern physics is finding a "theory of everything" - a theory that can explain, with the help of mathematics, all physical aspects of the universe. While the laws of physics could explain some aspects of the biology of living systems (e.g., the phenomenological interpretation of movement of cells and animals), there are other aspects specific to biology that cannot be captured by physics models. For example, it is generally accepted that the evolution of a cell-based system is influenced by the activation state of cells (e.g., only activated and functional immune cells can fight diseases); on the other hand, the evolution of an animal-based system can be influenced by the psychological state (e.g., distress) of animals. Therefore, the last 10-20 years have seen also a quest for a "theory of everything"-approach extended to biology, with researchers trying to propose mathematical modelling frameworks that can explain various biological phenomena ranging from ecology to developmental biology and medicine [1,2,6]. The basic idea behind this approach can be found in a few reviews on ecology and cell biology [6,7,9-11], where researchers suggested that due to the parallel between the micro-scale dynamics and the emerging macro-scale phenomena in both cell biology and in ecology, many mathematical methods used for ecological processes could be adapted to cancer modelling [7,9] or to modelling in immunology [11]. However, this approach generally involved the use of different models to describe different biological aspects (e.g., models for cell and animal movement, models for competition between cells or animals, etc.).

Direct modeling parameter signature analysis and failure mode prediction of physical systems using hybrid computer optimization

NASA Technical Reports Server (NTRS)

Drake, R. L.; Duvoisin, P. F.; Asthana, A.; Mather, T. W.

1971-01-01

High speed automated identification and design of dynamic systems, both linear and nonlinear, are discussed. Special emphasis is placed on developing hardware and techniques which are applicable to practical problems. The basic modeling experiment and new results are described. Using the improvements developed successful identification of several systems, including a physical example as well as simulated systems, was obtained. The advantages of parameter signature analysis over signal signature analysis in go-no go testing of operational systems were demonstrated. The feasibility of using these ideas in failure mode prediction in operating systems was also investigated. An improved digital controlled nonlinear function generator was developed, de-bugged, and completely documented.

Simulation of process identification and controller tuning for flow control system

NASA Astrophysics Data System (ADS)

Chew, I. M.; Wong, F.; Bono, A.; Wong, K. I.

2017-06-01

PID controller is undeniably the most popular method used in controlling various industrial processes. The feature to tune the three elements in PID has allowed the controller to deal with specific needs of the industrial processes. This paper discusses the three elements of control actions and improving robustness of controllers through combination of these control actions in various forms. A plant model is simulated using the Process Control Simulator in order to evaluate the controller performance. At first, the open loop response of the plant is studied by applying a step input to the plant and collecting the output data from the plant. Then, FOPDT of physical model is formed by using both Matlab-Simulink and PRC method. Then, calculation of controller’s setting is performed to find the values of Kc and τi that will give satisfactory control in closed loop system. Then, the performance analysis of closed loop system is obtained by set point tracking analysis and disturbance rejection performance. To optimize the overall physical system performance, a refined tuning of PID or detuning is further conducted to ensure a consistent resultant output of closed loop system reaction to the set point changes and disturbances to the physical model. As a result, the PB = 100 (%) and τi = 2.0 (s) is preferably chosen for setpoint tracking while PB = 100 (%) and τi = 2.5 (s) is selected for rejecting the imposed disturbance to the model. In a nutshell, selecting correlation tuning values is likewise depended on the required control’s objective for the stability performance of overall physical model.

Physical properties of inulin and inulin-orange juice: physical characterization and technological application.

PubMed

Saavedra-Leos, M Z; Leyva-Porras, C; Martínez-Guerra, E; Pérez-García, S A; Aguilar-Martínez, J A; Álvarez-Salas, C

2014-05-25

In this work two systems based on a carbohydrate polymer were studied: inulin as model system and inulin-orange juice as complex system. Both system were stored at different water activity conditions and subsequently characterized. Water adsorption isotherms type II were fitted by the GAB model and the water monolayer content was determined for each system. From thermal analyzes it was found that at low water activities (aw) systems were fully amorphous. As aw increased, crystallinity was developed. This behavior was corroborated by X-ray diffraction. In the inulin-orange juice system, crystallization appears at lower water activity caused by the intensification of the chemical interaction of the low molecular weight species contained in orange juice. Glass transition temperature (Tg), determined by modulated differential scanning calorimeter, decreased with aw. As water is adsorbed, the physical appearance of samples changed which could be observed by optical microscopy and effectively related with the microstructure found by scanning electron microscopy. Copyright © 2014 Elsevier Ltd. All rights reserved.

Physical and geometrical parameters of VCBS XIII: HIP 105947

NASA Astrophysics Data System (ADS)

Gumaan Masda, Suhail; Al-Wardat, Mashhoor Ahmed; Pathan, Jiyaulla Khan Moula Khan

2018-06-01

The best physical and geometrical parameters of the main sequence close visual binary system (CVBS), HIP 105947, are presented. These parameters have been constructed conclusively using Al-Wardat’s complex method for analyzing CVBSs, which is a method for constructing a synthetic spectral energy distribution (SED) for the entire binary system using individual SEDs for each component star. The model atmospheres are in its turn built using the Kurucz (ATLAS9) line-blanketed plane-parallel models. At the same time, the orbital parameters for the system are calculated using Tokovinin’s dynamical method for constructing the best orbits of an interferometric binary system. Moreover, the mass-sum of the components, as well as the Δθ and Δρ residuals for the system, is introduced. The combination of Al-Wardat’s and Tokovinin’s methods yields the best estimations of the physical and geometrical parameters. The positions of the components in the system on the evolutionary tracks and isochrones are plotted and the formation and evolution of the system are discussed.

COED Transactions, Vol. XI, No. 3, March 1979. LSSP: An Educational Aid to the Study of Linear System Dynamics.

ERIC Educational Resources Information Center

Mitchell, Eugene E., Ed.

The study of the dynamics of physical systems is of importance to all engineering students. LSSP, a Linear System Simulation Program, is used to study the behavior of physical phenomena and systems which may be represented to a good degree of approximation by linear models. Emphasis is placed upon the unity resulting from the mathematical…

Health monitoring system for transmission shafts based on adaptive parameter identification

NASA Astrophysics Data System (ADS)

Souflas, I.; Pezouvanis, A.; Ebrahimi, K. M.

2018-05-01

A health monitoring system for a transmission shaft is proposed. The solution is based on the real-time identification of the physical characteristics of the transmission shaft i.e. stiffness and damping coefficients, by using a physical oriented model and linear recursive identification. The efficacy of the suggested condition monitoring system is demonstrated on a prototype transient engine testing facility equipped with a transmission shaft capable of varying its physical properties. Simulation studies reveal that coupling shaft faults can be detected and isolated using the proposed condition monitoring system. Besides, the performance of various recursive identification algorithms is addressed. The results of this work recommend that the health status of engine dynamometer shafts can be monitored using a simple lumped-parameter shaft model and a linear recursive identification algorithm which makes the concept practically viable.

Design and fabrication of complete dentures using CAD/CAM technology

PubMed Central

Han, Weili; Li, Yanfeng; Zhang, Yue; lv, Yuan; Zhang, Ying; Hu, Ping; Liu, Huanyue; Ma, Zheng; Shen, Yi

2017-01-01

Abstract The aim of the study was to test the feasibility of using commercially available computer-aided design and computer-aided manufacturing (CAD/CAM) technology including 3Shape Dental System 2013 trial version, WIELAND V2.0.049 and WIELAND ZENOTEC T1 milling machine to design and fabricate complete dentures. The modeling process of full denture available in the trial version of 3Shape Dental System 2013 was used to design virtual complete dentures on the basis of 3-dimensional (3D) digital edentulous models generated from the physical models. The virtual complete dentures designed were exported to CAM software of WIELAND V2.0.049. A WIELAND ZENOTEC T1 milling machine controlled by the CAM software was used to fabricate physical dentitions and baseplates by milling acrylic resin composite plates. The physical dentitions were bonded to the corresponding baseplates to form the maxillary and mandibular complete dentures. Virtual complete dentures were successfully designed using the software through several steps including generation of 3D digital edentulous models, model analysis, arrangement of artificial teeth, trimming relief area, and occlusal adjustment. Physical dentitions and baseplates were successfully fabricated according to the designed virtual complete dentures using milling machine controlled by a CAM software. Bonding physical dentitions to the corresponding baseplates generated the final physical complete dentures. Our study demonstrated that complete dentures could be successfully designed and fabricated by using CAD/CAM. PMID:28072686

Federation of UML models for cyber physical use cases

DOE Office of Scientific and Technical Information (OSTI.GOV)

This method employs the concept of federation, which is defined as the use of existing models that represent aspects of a system in specific domains (such as physical and cyber security domains) and building interfaces to link all of domain models. Federation seeks to build on existing bodies of work. Some examples include the Common Information Models (CIM) maintained by the International Electrotechnical Commission Technical Committee 57 (IEC TC 57) for the electric power industry. Another relevant model is the CIM maintained by the Distributed Management Task Force (DMTF)? this CIM defines a representation of the managed elements in anmore » Information Technology (IT) environment. The power system is an example of a cyber-physical system, where the cyber systems, consisting of computing infrastructure such as networks and devices, play a critical role in the operation of the underlying physical electricity delivery system. Measurements from remote field devices are relayed to control centers through computer networks, and the data is processed to determine suitable control actions. Control decisions are then relayed back to field devices. It has been observed that threat actors may be able to successfully compromise this cyber layer in order to impact power system operation. Therefore, future control center applications must be wary of potentially compromised measurements coming from field devices. In order to ensure the integrity of the field measurements, these applications could make use of compromise indicators from alternate sources of information such as cyber security. Thus, modern control applications may require access to data from sources that are not defined in the local information model. In such cases, software application interfaces will require integration of data objects from cross-domain data models. When incorporating or federating different domains, it is important to have subject matter experts work together, recognizing that not everyone has the same knowledge, responsibilities, focus, or skill set.« less

Final Report, DOE Early Career Award: Predictive modeling of complex physical systems: new tools for statistical inference, uncertainty quantification, and experimental design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marzouk, Youssef

Predictive simulation of complex physical systems increasingly rests on the interplay of experimental observations with computational models. Key inputs, parameters, or structural aspects of models may be incomplete or unknown, and must be developed from indirect and limited observations. At the same time, quantified uncertainties are needed to qualify computational predictions in the support of design and decision-making. In this context, Bayesian statistics provides a foundation for inference from noisy and limited data, but at prohibitive computional expense. This project intends to make rigorous predictive modeling *feasible* in complex physical systems, via accelerated and scalable tools for uncertainty quantification, Bayesianmore » inference, and experimental design. Specific objectives are as follows: 1. Develop adaptive posterior approximations and dimensionality reduction approaches for Bayesian inference in high-dimensional nonlinear systems. 2. Extend accelerated Bayesian methodologies to large-scale {\\em sequential} data assimilation, fully treating nonlinear models and non-Gaussian state and parameter distributions. 3. Devise efficient surrogate-based methods for Bayesian model selection and the learning of model structure. 4. Develop scalable simulation/optimization approaches to nonlinear Bayesian experimental design, for both parameter inference and model selection. 5. Demonstrate these inferential tools on chemical kinetic models in reacting flow, constructing and refining thermochemical and electrochemical models from limited data. Demonstrate Bayesian filtering on canonical stochastic PDEs and in the dynamic estimation of inhomogeneous subsurface properties and flow fields.« less

Design of a Modular Monolithic Implicit Solver for Multi-Physics Applications

NASA Technical Reports Server (NTRS)

Carton De Wiart, Corentin; Diosady, Laslo T.; Garai, Anirban; Burgess, Nicholas; Blonigan, Patrick; Ekelschot, Dirk; Murman, Scott M.

2018-01-01

The design of a modular multi-physics high-order space-time finite-element framework is presented together with its extension to allow monolithic coupling of different physics. One of the main objectives of the framework is to perform efficient high- fidelity simulations of capsule/parachute systems. This problem requires simulating multiple physics including, but not limited to, the compressible Navier-Stokes equations, the dynamics of a moving body with mesh deformations and adaptation, the linear shell equations, non-re effective boundary conditions and wall modeling. The solver is based on high-order space-time - finite element methods. Continuous, discontinuous and C1-discontinuous Galerkin methods are implemented, allowing one to discretize various physical models. Tangent and adjoint sensitivity analysis are also targeted in order to conduct gradient-based optimization, error estimation, mesh adaptation, and flow control, adding another layer of complexity to the framework. The decisions made to tackle these challenges are presented. The discussion focuses first on the "single-physics" solver and later on its extension to the monolithic coupling of different physics. The implementation of different physics modules, relevant to the capsule/parachute system, are also presented. Finally, examples of coupled computations are presented, paving the way to the simulation of the full capsule/parachute system.

Results and Lessons Learned from a Coupled Social and Physical Hydrology Model: Testing Alternative Water Management Policies and Institutional Structures Using Agent-Based Modeling and Regional Hydrology

NASA Astrophysics Data System (ADS)

Murphy, J.; Lammers, R. B.; Prousevitch, A.; Ozik, J.; Altaweel, M.; Collier, N. T.; Kliskey, A. D.; Alessa, L.

2015-12-01

Water Management in the U.S. Southwest is under increasing scrutiny as many areas endure persistent drought. The impact of these prolonged dry conditions is a product of regional climate and hydrological conditions, but also of a highly engineered water management infrastructure and a complex web of social arrangements whereby water is allocated, shared, exchanged, used, re-used, and finally consumed. We coupled an agent-based model with a regional hydrological model to understand the dynamics in one richly studied and highly populous area: southern Arizona, U.S.A., including metropolitan Phoenix and Tucson. There, multiple management entities representing an array of municipalities and other water providers and customers, including private companies and Native American tribes are enmeshed in a complex legal and economic context in which water is bought, leased, banked, and exchanged in a variety of ways and on multiple temporal and physical scales. A recurrent question in the literature of adaptive management is the impact of management structure on overall system performance. To explore this, we constructed an agent-based model to capture this social complexity, and coupled this with a physical hydrological model that we used to drive the system under a variety of water stress scenarios and to assess the regional impact of the social system's performance. We report the outcomes of ensembles of runs in which varieties of alternative policy constraints and management strategies are considered. We hope to contribute to policy discussions in this area and connected and legislatively similar areas (such as California) as current conditions change and existing legal and policy structures are revised. Additionally, we comment on the challenges of integrating models that ostensibly are in different domains (physical and social) but that independently represent a system in which physical processes and human actions are closely intertwined and difficult to disentangle.

First orbital solution and evolutionary state for the newly discovered eclipsing binaries USNO-B1.0 1091-0130715 and GSC-03449-0680

NASA Astrophysics Data System (ADS)

Elkhateeb, M. M.; Nouh, M. I.; Nelson, R. H.

2015-02-01

A first photometric study for the newly discovered systems USNO-B1.0 1091-0130715 and GSC-03449-0680 was carried out by means of recent a windows interface version of the Wilson and Devinney code based on model atmospheres by Kurucz (1993). The accepted models reveal some absolute parameters for both systems, which are used in deriving the spectral type of the system components and their evolutionary status. Distances to each systems and physical properties were estimated. Comparisons of the computed physical parameters with stellar models are discussed. The components of the system USNO-B1.0 1091-0130715 and the primary of the system GSC-03449-0680 are found to be on or near the ZAMS track, while the secondary of GSC-03449-0680 system found to be severely under luminous and too cool compared to its ZAMS mass.

Experimental Uncertainty Associated with Traveling Wave Excitation

DTIC Science & Technology

2014-09-15

20 2.9 Schematic of the Lumped Model [6] . . . . . . . . . . . . . . . . . . . . . . . 21 2.10 Multiple Coupled Pendulum [7...model to describe the physical system, the authors chose to employ a coupled pendulum model to represent a rotor. This system is shown in Figure 2.10...System mistuning is introduced by altering pendulum lengths. All other system parameters are equal. A linear viscous proportional damping force is

Measurement methods to build up the digital optical twin

NASA Astrophysics Data System (ADS)

Prochnau, Marcel; Holzbrink, Michael; Wang, Wenxin; Holters, Martin; Stollenwerk, Jochen; Loosen, Peter

2018-02-01

The realization of the Digital Optical Twin (DOT), which is in short the digital representation of the physical state of an optical system, is particularly useful in the context of an automated assembly process of optical systems. During the assembly process, the physical system status of the optical system is continuously measured and compared with the digital model. In case of deviations between physical state and the digital model, the latter one is adapted to match the physical state. To reach the goal described above, in a first step measurement/characterization technologies concerning their suitability to generate a precise digital twin of an existing optical system have to be identified and evaluated. This paper gives an overview of possible characterization methods and, finally, shows first results of evaluated, compared methods (e.g. spot-radius, MTF, Zernike-polynomials), to create a DOT. The focus initially lies on the unequivocalness of the optimization results as well as on the computational time required for the optimization to reach the characterized system state. Possible sources of error are the measurement accuracy (to characterize the system) , execution time of the measurement, time needed to map the digital to the physical world (optimization step) as well as interface possibilities to integrate the measurement tool into an assembly cell. Moreover, it is to be discussed whether the used measurement methods are suitable for a `seamless' integration into an assembly cell.

Current Density and Continuity in Discretized Models

ERIC Educational Resources Information Center

Boykin, Timothy B.; Luisier, Mathieu; Klimeck, Gerhard

2010-01-01

Discrete approaches have long been used in numerical modelling of physical systems in both research and teaching. Discrete versions of the Schrodinger equation employing either one or several basis functions per mesh point are often used by senior undergraduates and beginning graduate students in computational physics projects. In studying…

Modeling physical and chemical climate of the northeastern United States for a geographic information system

Treesearch

Scott V. Ollinger; John D. Aber; Anthony C. Federer; Gary M. Lovett; Jennifer M. Ellis

1995-01-01

A model of physical and chemical climate was developed for New York and New England that can be used in a GIs for integration with ecosystem models. The variables included are monthly average maximum and minimum daily temperatures, precipitation, humidity, and solar radiation, as well as annual atmospheric deposition of sulfur and nitrogen. Equations generated from...

Advanced solar irradiances applied to satellite and ionospheric operational systems

NASA Astrophysics Data System (ADS)

Tobiska, W. Kent; Schunk, Robert; Eccles, Vince; Bouwer, Dave

Satellite and ionospheric operational systems require solar irradiances in a variety of time scales and spectral formats. We describe the development of a system using operational grade solar irradiances that are applied to empirical thermospheric density models and physics-based ionospheric models used by operational systems that require a space weather characterization. The SOLAR2000 (S2K) and SOLARFLARE (SFLR) models developed by Space Environment Technologies (SET) provide solar irradiances from the soft X-rays (XUV) through the Far Ultraviolet (FUV) spectrum. The irradiances are provided as integrated indices for the JB2006 empirical atmosphere density models and as line/band spectral irradiances for the physics-based Ionosphere Forecast Model (IFM) developed by the Space Environment Corporation (SEC). We describe the integration of these irradiances in historical, current epoch, and forecast modes through the Communication Alert and Prediction System (CAPS). CAPS provides real-time and forecast HF radio availability for global and regional users and global total electron content (TEC) conditions.

A Comprehensive Availability Modeling and Analysis of a Virtualized Servers System Using Stochastic Reward Nets

PubMed Central

Kim, Dong Seong; Park, Jong Sou

2014-01-01

It is important to assess availability of virtualized systems in IT business infrastructures. Previous work on availability modeling and analysis of the virtualized systems used a simplified configuration and assumption in which only one virtual machine (VM) runs on a virtual machine monitor (VMM) hosted on a physical server. In this paper, we show a comprehensive availability model using stochastic reward nets (SRN). The model takes into account (i) the detailed failures and recovery behaviors of multiple VMs, (ii) various other failure modes and corresponding recovery behaviors (e.g., hardware faults, failure and recovery due to Mandelbugs and aging-related bugs), and (iii) dependency between different subcomponents (e.g., between physical host failure and VMM, etc.) in a virtualized servers system. We also show numerical analysis on steady state availability, downtime in hours per year, transaction loss, and sensitivity analysis. This model provides a new finding on how to increase system availability by combining both software rejuvenations at VM and VMM in a wise manner. PMID:25165732

Synthetic observations of protostellar multiple systems

NASA Astrophysics Data System (ADS)

Lomax, O.; Whitworth, A. P.

2018-04-01

Observations of protostars are often compared with synthetic observations of models in order to infer the underlying physical properties of the protostars. The majority of these models have a single protostar, attended by a disc and an envelope. However, observational and numerical evidence suggests that a large fraction of protostars form as multiple systems. This means that fitting models of single protostars to observations may be inappropriate. We produce synthetic observations of protostellar multiple systems undergoing realistic, non-continuous accretion. These systems consist of multiple protostars with episodic luminosities, embedded self-consistently in discs and envelopes. We model the gas dynamics of these systems using smoothed particle hydrodynamics and we generate synthetic observations by post-processing the snapshots using the SPAMCART Monte Carlo radiative transfer code. We present simulation results of three model protostellar multiple systems. For each of these, we generate 4 × 104 synthetic spectra at different points in time and from different viewing angles. We propose a Bayesian method, using similar calculations to those presented here, but in greater numbers, to infer the physical properties of protostellar multiple systems from observations.

Coupling of a distributed stakeholder-built system dynamics socio-economic model with SAHYSMOD for sustainable soil salinity management. Part 2: Model coupling and application

NASA Astrophysics Data System (ADS)

Inam, Azhar; Adamowski, Jan; Prasher, Shiv; Halbe, Johannes; Malard, Julien; Albano, Raffaele

2017-08-01

Many simulation models focus on simulating a single physical process and do not constitute balanced representations of the physical, social and economic components of a system. The present study addresses this challenge by integrating a physical (P) model (SAHYSMOD) with a group (stakeholder) built system dynamics model (GBSDM) through a component modeling approach based on widely applied tools such as MS Excel, Python and Visual Basic for Applications (VBA). The coupled model (P-GBSDM) was applied to test soil salinity management scenarios (proposed by stakeholders) for the Haveli region of the Rechna Doab Basin in Pakistan. Scenarios such as water banking, vertical drainage, canal lining, and irrigation water reallocation were simulated with the integrated model. Spatiotemporal maps and economic and environmental trade-off criteria were used to examine the effectiveness of the selected management scenarios. After 20 years of simulation, canal lining reduced soil salinity by 22% but caused an initial reduction of 18% in farm income, which requires an initial investment from the government. The government-sponsored Salinity Control and Reclamation Project (SCARP) is a short-term policy that resulted in a 37% increase in water availability with a 12% increase in farmer income. However, it showed detrimental effects on soil salinity in the long term, with a 21% increase in soil salinity due to secondary salinization. The new P-GBSDM was shown to be an effective platform for engaging stakeholders and simulating their proposed management policies while taking into account socioeconomic considerations. This was not possible using the physically based SAHYSMOD model alone.

Launch Vehicle Debris Models and Crew Vehicle Ascent Abort Risk

NASA Technical Reports Server (NTRS)

Gee, Ken; Lawrence, Scott

2013-01-01

For manned space launch systems, a reliable abort system is required to reduce the risks associated with a launch vehicle failure during ascent. Understanding the risks associated with failure environments can be achieved through the use of physics-based models of these environments. Debris fields due to destruction of the launch vehicle is one such environment. To better analyze the risk posed by debris, a physics-based model for generating launch vehicle debris catalogs has been developed. The model predicts the mass distribution of the debris field based on formulae developed from analysis of explosions. Imparted velocity distributions are computed using a shock-physics code to model the explosions within the launch vehicle. A comparison of the debris catalog with an existing catalog for the Shuttle external tank show good comparison in the debris characteristics and the predicted debris strike probability. The model is used to analyze the effects of number of debris pieces and velocity distributions on the strike probability and risk.

Advancing Physically-Based Flow Simulations of Alluvial Systems Through Atmospheric Noble Gases and the Novel 37Ar Tracer Method

NASA Astrophysics Data System (ADS)

Schilling, Oliver S.; Gerber, Christoph; Partington, Daniel J.; Purtschert, Roland; Brennwald, Matthias S.; Kipfer, Rolf; Hunkeler, Daniel; Brunner, Philip

2017-12-01

To provide a sound understanding of the sources, pathways, and residence times of groundwater water in alluvial river-aquifer systems, a combined multitracer and modeling experiment was carried out in an important alluvial drinking water wellfield in Switzerland. 222Rn, 3H/3He, atmospheric noble gases, and the novel 37Ar-method were used to quantify residence times and mixing ratios of water from different sources. With a half-life of 35.1 days, 37Ar allowed to successfully close a critical observational time gap between 222Rn and 3H/3He for residence times of weeks to months. Covering the entire range of residence times of groundwater in alluvial systems revealed that, to quantify the fractions of water from different sources in such systems, atmospheric noble gases and helium isotopes are tracers suited for end-member mixing analysis. A comparison between the tracer-based mixing ratios and mixing ratios simulated with a fully-integrated, physically-based flow model showed that models, which are only calibrated against hydraulic heads, cannot reliably reproduce mixing ratios or residence times of alluvial river-aquifer systems. However, the tracer-based mixing ratios allowed the identification of an appropriate flow model parametrization. Consequently, for alluvial systems, we recommend the combination of multitracer studies that cover all relevant residence times with fully-coupled, physically-based flow modeling to better characterize the complex interactions of river-aquifer systems.

Physical modelling of the rainfall infiltration processes and related landslide behaviour.

NASA Astrophysics Data System (ADS)

Capparelli, Giovanna; Damiano, Emilia; Olivares, Lucio; Spolverino, Gennaro; Versace, Pasquale

2016-04-01

The prediction of natural processes, such as weather-induced landslide, an issue that is of great importance. Were held numerous research to understand the processes underlying the triggering of a landslide, and to improve the forecasting systems. A valid prediction model can allow the implementation of an equally valid announcement and warning system, thus reducing the risk caused by such phenomena. The hydraulic and hydrologic modeling of the process that takes place in an unstable slope subjected to rainfall, can be performed using two approaches: through mathematical models or physical models. Our research uses an integrated approach, making system data of experimental sites, with both the results and interpretations of physical models, both with simulations of mathematical models. The intent is to observe and interpret laboratory experiments to reproduce and simulate the phenomenon with mathematical models. The research aims to obtain interpretations of hydrological and hydraulic processes, which occur in the slopes as a result of rain, more and more accurate. For our research we use a scaled-down physical model and a mathematical model FEM. The physical model is a channel with transparent walls composed of two floors at a variable angle (ignition and propagation) 1 meter wide and 3 meters long each. The model is instrumented with sensors that control the hydraulic and geotechnical parameters within the slopes and devices that simulate natural events. The model is equipped with a monitoring system able to keep under observation the physical quantities of interest. In particular, the apparatus is equipped with tensiometers miniaturized, that can be installed in different positions and at different depths, for the measurement of suction within the slope, miniaturized pressure transducers on the bottom of the channel for the measurement of any pressure neutral positive , TDR system for the measurement of the volumetric water content, and displacement transducers to laser technology for the measurement of surface movements in the direction orthogonal to the plane of sliding. The monitoring system is completed with an apparatus of scanning type PIV consists of high-definition cameras, used for the reconstruction of the flow fields on the surface of the sample. It has performed a first test, reconstructing within the channel a homogeneous deposit of volcanic ash, which committed the entire width of the channel for a length of 1,50 m and a thickness of 0.20 m. We proceeded to tilt the slope up to an angle of about 38 ° and has imposed an artificial rain of considerable intensity (about 220 mm / h), aimed at achieving the conditions trigger a landslide along the artificial slope. The second test was made with the same characteristics as the first, but reconstructing a layered deposit, using the same stratigraphy found in a test site. Comparing the values recorded in the two tests can assess the different responses of the two deposits.

PREFACE: 3rd International Conference on Mathematical Modeling in Physical Sciences (IC-MSQUARE 2014)

NASA Astrophysics Data System (ADS)

2015-01-01

The third International Conference on Mathematical Modeling in Physical Sciences (IC-MSQUARE) took place at Madrid, Spain, from Thursday 28 to Sunday 31 August 2014. The Conference was attended by more than 200 participants and hosted about 350 oral, poster, and virtual presentations. More than 600 pre-registered authors were also counted. The third IC-MSQUARE consisted of different and diverging workshops and thus covered various research fields where Mathematical Modeling is used, such as Theoretical/Mathematical Physics, Neutrino Physics, Non-Integrable Systems, Dynamical Systems, Computational Nanoscience, Biological Physics, Computational Biomechanics, Complex Networks, Stochastic Modeling, Fractional Statistics, DNA Dynamics, Macroeconomics etc. The scientific program was rather heavy since after the Keynote and Invited Talks in the morning, three parallel oral sessions and one poster session were running every day. However, according to all attendees, the program was excellent with high level of talks and the scientific environment was fruitful, thus all attendees had a creative time. We would like to thank the Keynote Speaker and the Invited Speakers for their significant contribution to IC-MSQUARE. We also would like to thank the Members of the International Advisory and Scientific Committees as well as the Members of the Organizing Committee.

PREFACE: 4th International Conference on Mathematical Modeling in Physical Sciences (IC-MSquare2015)

NASA Astrophysics Data System (ADS)

Vlachos, Dimitrios; Vagenas, Elias C.

2015-09-01

The 4th International Conference on Mathematical Modeling in Physical Sciences (IC-MSQUARE) took place in Mykonos, Greece, from Friday 5th June to Monday 8th June 2015. The Conference was attended by more than 150 participants and hosted about 200 oral, poster, and virtual presentations. There were more than 600 pre-registered authors. The 4th IC-MSQUARE consisted of different and diverging workshops and thus covered various research fields where Mathematical Modeling is used, such as Theoretical/Mathematical Physics, Neutrino Physics, Non-Integrable Systems, Dynamical Systems, Computational Nanoscience, Biological Physics, Computational Biomechanics, Complex Networks, Stochastic Modeling, Fractional Statistics, DNA Dynamics, Macroeconomics etc. The scientific program was rather intense as after the Keynote and Invited Talks in the morning, three parallel oral and one poster session were running every day. However, according to all attendees, the program was excellent with a high quality of talks creating an innovative and productive scientific environment for all attendees. We would like to thank the Keynote Speaker and the Invited Speakers for their significant contribution to IC-MSQUARE. We also would like to thank the Members of the International Advisory and Scientific Committees as well as the Members of the Organizing Committee.

Every Child a Winner with Improvised Physical Education Equipment.

ERIC Educational Resources Information Center

Irwin County Schools, Ocilla, GA.

This booklet describes physical education equipment constructed at the site of Project HOPE (Health and Optimum Physical Education) in the Irwin County School System, Ocilla, Georgia, to provide rural schools a model for elementary physical education and health services. The booklet is divided into three sections: "What To Do with No…

A Cause and A Solution for the Underprediction of Extreme Wave Events in the Northeast Pacific

NASA Astrophysics Data System (ADS)

Ellenson, A. N.; Ozkan-Haller, H. T.; Thomson, J.; Brown, A. C.; Haller, M. C.

2016-12-01

Along the coastlines of Washington and Oregon, at least one 10 m wave height event occurs every year, and the strongest storms produce wave heights of 14-15 m. Extremely high wave heights can cause severe damage to coastal infrastructure and pose hazards to stakeholders along the coast. A system which can accurately predict such sea states is important for quantifying risk and aiding in preparation for extreme wave events. This study explores how to optimize forecast model performance for extreme wave events by utilizing different physics packages or wind input in four model configurations. The different wind input products consist of a reanalyzed Global Forecasting System (GFS) wind input and a Climate Forecast System Reanalysis (CFSR) from the National Center of Environmental Prediction (NCEP). The physics packages are the Tolman-Chalikov (1996) ST2 physics package and the Ardhuin et al (2009) ST4 physics package associated with version 4.18 of WaveWatch III. A hindcast was previously performed to assess the wave character along the Pacific Northwest Coastline for wave energy applications. Inspection of hindcast model results showed that the operational model, which consisted of ST2 physics and GFS wind, underpredicted events where wave height exceeded six meters.The under-prediction is most severe for cases with the combined conditions of a distant cyclone and a strong coastal jet. Three such cases were re-analyzed with the four model configurations. Model output is compared with observations at NDBC buoy 46050, offshore of Newport, OR. The model configuration consisting of ST4 physics package and CFSR wind input performs best as compared with the original model, reducing significant wave height underprediction from 1.25 m to approximately 0.67 m and mean wave direction error from 30 degrees to 17 degrees for wave heights greater than 6 m. Spectral analysis shows that the ST4-CFSR model configuration best resolves southerly wave energy, and all model configurations tend to overestimate northerly wave energy. This directional distinction is important when attempting to identify which atmospheric feature has induced the extreme wave energy.

Rethinking Technology-Enhanced Physics Teacher Education: From Theory to Practice

ERIC Educational Resources Information Center

Milner-Bolotin, Marina

2016-01-01

This article discusses how modern technology, such as electronic response systems, PeerWise system, data collection and analysis tools, computer simulations, and modeling software can be used in physics methods courses to promote teacher-candidates' professional competencies and their positive attitudes about mathematics and science education. We…

PlayPhysics: An Emotional Games Learning Environment for Teaching Physics

NASA Astrophysics Data System (ADS)

Muñoz, Karla; Kevitt, Paul Mc; Lunney, Tom; Noguez, Julieta; Neri, Luis

To ensure learning, game-based learning environments must incorporate assessment mechanisms, e.g. Intelligent Tutoring Systems (ITSs). ITSs are focused on recognising and influencing the learner's emotional or motivational states. This research focuses on designing and implementing an affective student model for intelligent gaming, which reasons about the learner's emotional state from cognitive and motivational variables using observable behaviour. A Probabilistic Relational Models (PRMs) approach is employed to derive Dynamic Bayesian Networks (DBNs). The model uses the Control-Value theory of 'achievement emotions' as a basis. A preliminary test was conducted to recognise the students' prospective-outcome emotions with results presented and discussed. PlayPhysics is an emotional games learning environment for teaching Physics. Once the affective student model proves effective it will be incorporated into PlayPhysics' architecture. The design, evaluation and postevaluation of PlayPhysics are also discussed. Future work will focus on evaluating the affective student model with a larger population of students, and on providing affective feedback.

Applications of flow-networks to opinion-dynamics

NASA Astrophysics Data System (ADS)

Tupikina, Liubov; Kurths, Jürgen

2015-04-01

Networks were successfully applied to describe complex systems, such as brain, climate, processes in society. Recently a socio-physical problem of opinion-dynamics was studied using network techniques. We present the toy-model of opinion-formation based on the physical model of advection-diffusion. We consider spreading of the opinion on the fixed subject, assuming that opinion on society is binary: if person has opinion then the state of the node in the society-network equals 1, if the person doesn't have opinion state of the node equals 0. Opinion can be spread from one person to another if they know each other, or in the network-terminology, if the nodes are connected. We include into the system governed by advection-diffusion equation the external field to model such effects as for instance influence from media. The assumptions for our model can be formulated as the following: 1.the node-states are influenced by the network structure in such a way, that opinion can be spread only between adjacent nodes (the advective term of the opinion-dynamics), 2.the network evolution can have two scenarios: -network topology is not changing with time; -additional links can appear or disappear each time-step with fixed probability which requires adaptive networks properties. Considering these assumptions for our system we obtain the system of equations describing our model-dynamics which corresponds well to other socio-physics models, for instance, the model of the social cohesion and the famous voter-model. We investigate the behavior of the suggested model studying "waiting time" of the system, time to get to the stable state, stability of the model regimes for different values of model parameters and network topology.

PARTICULATE EMISSIONS AND CONTROL IN FLUIDIZED-BED COMBUSTION: MODELING AND PARAMETRIC PERFORMANCE

EPA Science Inventory

The report discusses a model, developed to describe the physical characteristics of the particulates emitted from fluidized-bed combustion (FBC) systems and to evaluate data on FBC particulate control systems. The model, which describes the particulate emissions profile from FBC,...

Advanced instrumentation for aeronautical propulsion research

NASA Technical Reports Server (NTRS)

Hartmann, M. J.

1986-01-01

The development and use of advanced instrumentation and measurement systems are key to extending the understanding of the physical phenomena that limit the advancement of aeropropulsion systems. The data collected by using these systems are necessary to verify numerical models and to increase the technologists' intuition into the physical phenomena. The systems must be versatile enough to allow their use with older technology measurement systems, with computer-based data reduction systems, and with existing test facilities. Researchers in all aeropropulsion fields contribute to the development of these systems.

Planetary geology: Impact processes on asteroids

NASA Technical Reports Server (NTRS)

Chapman, C. R.; Davis, D. R.; Greenberg, R.; Weidenschilling, S. J.

1982-01-01

The fundamental geological and geophysical properties of asteroids were studied by theoretical and simulation studies of their collisional evolution. Numerical simulations incorporating realistic physical models were developed to study the collisional evolution of hypothetical asteroid populations over the age of the solar system. Ideas and models are constrained by the observed distributions of sizes, shapes, and spin rates in the asteroid belt, by properties of Hirayama families, and by experimental studies of cratering and collisional phenomena. It is suggested that many asteroids are gravitationally-bound "rubble piles.' Those that rotate rapidly may have nonspherical quasi-equilibrium shapes, such as ellipsoids or binaries. Through comparison of models with astronomical data, physical properties of these asteroids (including bulk density) are determined, and physical processes that have operated in the solar system in primordial and subsequent epochs are studied.

Biology meets physics: Reductionism and multi-scale modeling of morphogenesis.

PubMed

Green, Sara; Batterman, Robert

2017-02-01

A common reductionist assumption is that macro-scale behaviors can be described "bottom-up" if only sufficient details about lower-scale processes are available. The view that an "ideal" or "fundamental" physics would be sufficient to explain all macro-scale phenomena has been met with criticism from philosophers of biology. Specifically, scholars have pointed to the impossibility of deducing biological explanations from physical ones, and to the irreducible nature of distinctively biological processes such as gene regulation and evolution. This paper takes a step back in asking whether bottom-up modeling is feasible even when modeling simple physical systems across scales. By comparing examples of multi-scale modeling in physics and biology, we argue that the "tyranny of scales" problem presents a challenge to reductive explanations in both physics and biology. The problem refers to the scale-dependency of physical and biological behaviors that forces researchers to combine different models relying on different scale-specific mathematical strategies and boundary conditions. Analyzing the ways in which different models are combined in multi-scale modeling also has implications for the relation between physics and biology. Contrary to the assumption that physical science approaches provide reductive explanations in biology, we exemplify how inputs from physics often reveal the importance of macro-scale models and explanations. We illustrate this through an examination of the role of biomechanical modeling in developmental biology. In such contexts, the relation between models at different scales and from different disciplines is neither reductive nor completely autonomous, but interdependent. Copyright © 2016 Elsevier Ltd. All rights reserved.

Student use of model-based reasoning when troubleshooting an electronic circuit

NASA Astrophysics Data System (ADS)

Lewandowski, Heather; Stetzer, Mackenzie; van de Bogart, Kevin; Dounas-Frazer, Dimitri

2016-03-01

Troubleshooting systems is an integral part of experimental physics in both research and educational settings. Accordingly, ability to troubleshoot is an important learning goal for undergraduate physics lab courses. We investigate students' model-based reasoning on a troubleshooting task using data collected in think-aloud interviews during which pairs of students from two institutions attempted to diagnose and repair a malfunctioning circuit. Our analysis scheme was informed by the Experimental Modeling Framework, which describes physicists' use of mathematical and conceptual models when reasoning about experimental systems. We show that system and subsystem models were crucial for the evaluation of repairs to the circuit and played an important role in some troubleshooting strategies. Finally, drawing on data from interviews with electronics instructors from a broad range of institution types, we outline recommendations for model-based approaches to teaching and learning troubleshooting skills.

Student use of model-based reasoning when troubleshooting an electric circuit

NASA Astrophysics Data System (ADS)

Dounas-Frazer, Dimitri

2016-05-01

Troubleshooting systems is an integral part of experimental physics in both research and educational settings. Accordingly, ability to troubleshoot is an important learning goal for undergraduate physics lab courses. We investigate students' model-based reasoning on a troubleshooting task using data collected in think-aloud interviews during which pairs of students from two institutions attempted to diagnose and repair a malfunctioning circuit. Our analysis scheme was informed by the Experimental Modeling Framework, which describes physicists' use of mathematical and conceptual models when reasoning about experimental systems. We show that system and subsystem models were crucial for the evaluation of repairs to the circuit and played an important role in some troubleshooting strategies. Finally, drawing on data from interviews with electronics instructors from a broad range of institution types, we outline recommendations for model-based approaches to teaching and learning troubleshooting skills.

Computer-implemented security evaluation methods, security evaluation systems, and articles of manufacture

DOEpatents

Muller, George; Perkins, Casey J.; Lancaster, Mary J.; MacDonald, Douglas G.; Clements, Samuel L.; Hutton, William J.; Patrick, Scott W.; Key, Bradley Robert

2015-07-28

Computer-implemented security evaluation methods, security evaluation systems, and articles of manufacture are described. According to one aspect, a computer-implemented security evaluation method includes accessing information regarding a physical architecture and a cyber architecture of a facility, building a model of the facility comprising a plurality of physical areas of the physical architecture, a plurality of cyber areas of the cyber architecture, and a plurality of pathways between the physical areas and the cyber areas, identifying a target within the facility, executing the model a plurality of times to simulate a plurality of attacks against the target by an adversary traversing at least one of the areas in the physical domain and at least one of the areas in the cyber domain, and using results of the executing, providing information regarding a security risk of the facility with respect to the target.

Adjustment of automatic control systems of production facilities at coal processing plants using multivariant physico- mathematical models

NASA Astrophysics Data System (ADS)

Evtushenko, V. F.; Myshlyaev, L. P.; Makarov, G. V.; Ivushkin, K. A.; Burkova, E. V.

2016-10-01

The structure of multi-variant physical and mathematical models of control system is offered as well as its application for adjustment of automatic control system (ACS) of production facilities on the example of coal processing plant.

Implementation of interactive virtual simulation of physical systems

NASA Astrophysics Data System (ADS)

Sanchez, H.; Escobar, J. J.; Gonzalez, J. D.; Beltran, J.

2014-03-01

Considering the limited availability of laboratories for physics teaching and the difficulties this causes in the learning of school students in Santa Marta Colombia, we have developed software in order to generate greater student interaction with the phenomena physical and improve their understanding. Thereby, this system has been proposed in an architecture Model/View- View- Model (MVVM), sharing the benefits of MVC. Basically, this pattern consists of 3 parts: The Model, that is responsible for business logic related. The View, which is the part with which we are most familiar and the user sees. Its role is to display data to the user and allowing manipulation of the data of the application. The ViewModel, which is the middle part of the Model and the View (analogous to the Controller in the MVC pattern), as well as being responsible for implementing the behavior of the view to respond to user actions and expose data model in a way that is easy to use links to data in the view. .NET Framework 4.0 and editing package Silverlight 4 and 5 are the main requirements needed for the deployment of physical simulations that are hosted in the web application and a web browser (Internet Explorer, Mozilla Firefox or Chrome). The implementation of this innovative application in educational institutions has shown that students improved their contextualization of physical phenomena.

Physical Controls on Oxygen Distribution and Denitrification Potential in the North West Arabian Sea

NASA Astrophysics Data System (ADS)

Queste, Bastien Y.; Vic, Clément; Heywood, Karen J.; Piontkovski, Sergey A.

2018-05-01

At suboxic oxygen concentrations, key biogeochemical cycles change and denitrification becomes the dominant remineralization pathway. Earth system models predict oxygen loss across most ocean basins in the next century; oxygen minimum zones near suboxia may become suboxic and therefore denitrifying. Using an ocean glider survey and historical data, we show oxygen loss in the Gulf of Oman (from 6-12 to <2 μmol kg-1) not represented in climatologies. Because of the nonlinearity between denitrification and oxygen concentration, resolutions of current Earth system models are too coarse to accurately estimate denitrification. We develop a novel physical proxy for oxygen from the glider data and use a high-resolution physical model to show eddy stirring of oxygen across the Gulf of Oman. We use the model to investigate spatial and seasonal differences in the ratio of oxic and suboxic water across the Gulf of Oman and waters exported to the wider Arabian Sea.

Dataflow models for fault-tolerant control systems

NASA Technical Reports Server (NTRS)

Papadopoulos, G. M.

1984-01-01

Dataflow concepts are used to generate a unified hardware/software model of redundant physical systems which are prone to faults. Basic results in input congruence and synchronization are shown to reduce to a simple model of data exchanges between processing sites. Procedures are given for the construction of congruence schemata, the distinguishing features of any correctly designed redundant system.

A moist Boussinesq shallow water equations set for testing atmospheric models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zerroukat, M., E-mail: mohamed.zerroukat@metoffice.gov.uk; Allen, T.

The shallow water equations have long been used as an initial test for numerical methods applied to atmospheric models with the test suite of Williamson et al. being used extensively for validating new schemes and assessing their accuracy. However the lack of physics forcing within this simplified framework often requires numerical techniques to be reworked when applied to fully three dimensional models. In this paper a novel two-dimensional shallow water equations system that retains moist processes is derived. This system is derived from three-dimensional Boussinesq approximation of the hydrostatic Euler equations where, unlike the classical shallow water set, we allowmore » the density to vary slightly with temperature. This results in extra (or buoyancy) terms for the momentum equations, through which a two-way moist-physics dynamics feedback is achieved. The temperature and moisture variables are advected as separate tracers with sources that interact with the mean-flow through a simplified yet realistic bulk moist-thermodynamic phase-change model. This moist shallow water system provides a unique tool to assess the usually complex and highly non-linear dynamics–physics interactions in atmospheric models in a simple yet realistic way. The full non-linear shallow water equations are solved numerically on several case studies and the results suggest quite realistic interaction between the dynamics and physics and in particular the generation of cloud and rain. - Highlights: • Novel shallow water equations which retains moist processes are derived from the three-dimensional hydrostatic Boussinesq equations. • The new shallow water set can be seen as a more general one, where the classical equations are a special case of these equations. • This moist shallow water system naturally allows a feedback mechanism from the moist physics increments to the momentum via buoyancy. • Like full models, temperature and moistures are advected as tracers that interact through a simplified yet realistic phase-change model. • This model is a unique tool to test numerical methods for atmospheric models, and physics–dynamics coupling, in a very realistic and simple way.« less

[Changes of soil physical properties during the conversion of cropland to agroforestry system].

PubMed

Wang, Lai; Gao, Peng Xiang; Liu, Bin; Zhong, Chong Gao; Hou, Lin; Zhang, Shuo Xin

2017-01-01

To provide theoretical basis for modeling and managing agroforestry systems, the influence of conversion of cropland to agroforestry system on soil physical properties was investigated via a walnut (Juglans regia)-wheat (Triticum aestivum) intercropping system, a wide spreading local agroforestry model in northern Weihe River of loess area, with the walnut and wheat monoculture systems as the control. The results showed that the improvement of the intercropping system on soil physical properties mainly appeared in the 0-40 cm soil layer. The intercropping system could prevent soil bulk density rising in the surface soil (0-20 cm), and the plow pan in the 20-40 cm soil layer could be significantly alleviated. The intercropping system had conti-nuous improvement on soil field capacity in each soil layer with the planting age increase, and the soil field capacity was higher than that of each monoculture system in each soil layer (except 20-40 cm soil layer) since the 5th year after planting. The intercropping system had continuous improvement on soil porosity in each soil layer, but mainly in the 0-20 and 20-40 cm soil layer, and the ratio of capillary porosity was also improved. The soil bulk density, field capacity and soil porosity obtained continuous improvement during the conversion of cropland to agroforestry system, and the improvement on soil physical properties was stronger in shallow soil layer than in deep soil.

Hierarchical Multi-Scale Approach To Validation and Uncertainty Quantification of Hyper-Spectral Image Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Engel, David W.; Reichardt, Thomas A.; Kulp, Thomas J.

Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensormore » level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.« less

Efficient evaluation of wireless real-time control networks.

PubMed

Horvath, Peter; Yampolskiy, Mark; Koutsoukos, Xenofon

2015-02-11

In this paper, we present a system simulation framework for the design and performance evaluation of complex wireless cyber-physical systems. We describe the simulator architecture and the specific developments that are required to simulate cyber-physical systems relying on multi-channel, multihop mesh networks. We introduce realistic and efficient physical layer models and a system simulation methodology, which provides statistically significant performance evaluation results with low computational complexity. The capabilities of the proposed framework are illustrated in the example of WirelessHART, a centralized, real-time, multi-hop mesh network designed for industrial control and monitor applications.

Analytical Formulation for Sizing and Estimating the Dimensions and Weight of Wind Turbine Hub and Drivetrain Components

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, Y.; Parsons, T.; King, R.

This report summarizes the theory, verification, and validation of a new sizing tool for wind turbine drivetrain components, the Drivetrain Systems Engineering (DriveSE) tool. DriveSE calculates the dimensions and mass properties of the hub, main shaft, main bearing(s), gearbox, bedplate, transformer if up-tower, and yaw system. The level of fi¬ delity for each component varies depending on whether semiempirical parametric or physics-based models are used. The physics-based models have internal iteration schemes based on system constraints and design criteria. Every model is validated against available industry data or finite-element analysis. The verification and validation results show that the models reasonablymore » capture primary drivers for the sizing and design of major drivetrain components.« less

Laboratory Modelling of Volcano Plumbing Systems: a review

NASA Astrophysics Data System (ADS)

Galland, Olivier; Holohan, Eoghan P.; van Wyk de Vries, Benjamin; Burchardt, Steffi

2015-04-01

Earth scientists have, since the XIX century, tried to replicate or model geological processes in controlled laboratory experiments. In particular, laboratory modelling has been used study the development of volcanic plumbing systems, which sets the stage for volcanic eruptions. Volcanic plumbing systems involve complex processes that act at length scales of microns to thousands of kilometres and at time scales from milliseconds to billions of years, and laboratory models appear very suitable to address them. This contribution reviews laboratory models dedicated to study the dynamics of volcano plumbing systems (Galland et al., Accepted). The foundation of laboratory models is the choice of relevant model materials, both for rock and magma. We outline a broad range of suitable model materials used in the literature. These materials exhibit very diverse rheological behaviours, so their careful choice is a crucial first step for the proper experiment design. The second step is model scaling, which successively calls upon: (1) the principle of dimensional analysis, and (2) the principle of similarity. The dimensional analysis aims to identify the dimensionless physical parameters that govern the underlying processes. The principle of similarity states that "a laboratory model is equivalent to his geological analogue if the dimensionless parameters identified in the dimensional analysis are identical, even if the values of the governing dimensional parameters differ greatly" (Barenblatt, 2003). The application of these two steps ensures a solid understanding and geological relevance of the laboratory models. In addition, this procedure shows that laboratory models are not designed to exactly mimic a given geological system, but to understand underlying generic processes, either individually or in combination, and to identify or demonstrate physical laws that govern these processes. From this perspective, we review the numerous applications of laboratory models to understand the distinct key features of volcanic plumbing systems: dykes, cone sheets, sills, laccoliths, caldera-related structures, ground deformation, magma/fault interactions, and explosive vents. Barenblatt, G.I., 2003. Scaling. Cambridge University Press, Cambridge. Galland, O., Holohan, E.P., van Wyk de Vries, B., Burchardt, S., Accepted. Laboratory modelling of volcanic plumbing systems: A review, in: Breitkreuz, C., Rocchi, S. (Eds.), Laccoliths, sills and dykes: Physical geology of shallow level magmatic systems. Springer.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Platania, P., E-mail: platania@ifp.cnr.it; Figini, L.; Farina, D.

The purpose of this work is the optical modeling and physical performances evaluations of the JT-60SA ECRF launcher system. The beams have been simulated with the electromagnetic code GRASP® and used as input for ECCD calculations performed with the beam tracing code GRAY, capable of modeling propagation, absorption and current drive of an EC Gaussion beam with general astigmatism. Full details of the optical analysis has been taken into account to model the launched beams. Inductive and advanced reference scenarios has been analysed for physical evaluations in the full poloidal and toroidal steering ranges for two slightly different layouts ofmore » the launcher system.« less

Improvements to Fidelity, Generation and Implementation of Physics-Based Lithium-Ion Reduced-Order Models

NASA Astrophysics Data System (ADS)

Rodriguez Marco, Albert

Battery management systems (BMS) require computationally simple but highly accurate models of the battery cells they are monitoring and controlling. Historically, empirical equivalent-circuit models have been used, but increasingly researchers are focusing their attention on physics-based models due to their greater predictive capabilities. These models are of high intrinsic computational complexity and so must undergo some kind of order-reduction process to make their use by a BMS feasible: we favor methods based on a transfer-function approach of battery cell dynamics. In prior works, transfer functions have been found from full-order PDE models via two simplifying assumptions: (1) a linearization assumption--which is a fundamental necessity in order to make transfer functions--and (2) an assumption made out of expedience that decouples the electrolyte-potential and electrolyte-concentration PDEs in order to render an approach to solve for the transfer functions from the PDEs. This dissertation improves the fidelity of physics-based models by eliminating the need for the second assumption and, by linearizing nonlinear dynamics around different constant currents. Electrochemical transfer functions are infinite-order and cannot be expressed as a ratio of polynomials in the Laplace variable s. Thus, for practical use, these systems need to be approximated using reduced-order models that capture the most significant dynamics. This dissertation improves the generation of physics-based reduced-order models by introducing different realization algorithms, which produce a low-order model from the infinite-order electrochemical transfer functions. Physics-based reduced-order models are linear and describe cell dynamics if operated near the setpoint at which they have been generated. Hence, multiple physics-based reduced-order models need to be generated at different setpoints (i.e., state-of-charge, temperature and C-rate) in order to extend the cell operating range. This dissertation improves the implementation of physics-based reduced-order models by introducing different blending approaches that combine the pre-computed models generated (offline) at different setpoints in order to produce good electrochemical estimates (online) along the cell state-of-charge, temperature and C-rate range.

Basic research on design analysis methods for rotorcraft vibrations

NASA Technical Reports Server (NTRS)

Hanagud, S.

1991-01-01

The objective of the present work was to develop a method for identifying physically plausible finite element system models of airframe structures from test data. The assumed models were based on linear elastic behavior with general (nonproportional) damping. Physical plausibility of the identified system matrices was insured by restricting the identification process to designated physical parameters only and not simply to the elements of the system matrices themselves. For example, in a large finite element model the identified parameters might be restricted to the moduli for each of the different materials used in the structure. In the case of damping, a restricted set of damping values might be assigned to finite elements based on the material type and on the fabrication processes used. In this case, different damping values might be associated with riveted, bolted and bonded elements. The method itself is developed first, and several approaches are outlined for computing the identified parameter values. The method is applied first to a simple structure for which the 'measured' response is actually synthesized from an assumed model. Both stiffness and damping parameter values are accurately identified. The true test, however, is the application to a full-scale airframe structure. In this case, a NASTRAN model and actual measured modal parameters formed the basis for the identification of a restricted set of physically plausible stiffness and damping parameters.

CPMIP: measurements of real computational performance of Earth system models in CMIP6

NASA Astrophysics Data System (ADS)

Balaji, Venkatramani; Maisonnave, Eric; Zadeh, Niki; Lawrence, Bryan N.; Biercamp, Joachim; Fladrich, Uwe; Aloisio, Giovanni; Benson, Rusty; Caubel, Arnaud; Durachta, Jeffrey; Foujols, Marie-Alice; Lister, Grenville; Mocavero, Silvia; Underwood, Seth; Wright, Garrett

2017-01-01

A climate model represents a multitude of processes on a variety of timescales and space scales: a canonical example of multi-physics multi-scale modeling. The underlying climate system is physically characterized by sensitive dependence on initial conditions, and natural stochastic variability, so very long integrations are needed to extract signals of climate change. Algorithms generally possess weak scaling and can be I/O and/or memory-bound. Such weak-scaling, I/O, and memory-bound multi-physics codes present particular challenges to computational performance. Traditional metrics of computational efficiency such as performance counters and scaling curves do not tell us enough about real sustained performance from climate models on different machines. They also do not provide a satisfactory basis for comparative information across models. codes present particular challenges to computational performance. We introduce a set of metrics that can be used for the study of computational performance of climate (and Earth system) models. These measures do not require specialized software or specific hardware counters, and should be accessible to anyone. They are independent of platform and underlying parallel programming models. We show how these metrics can be used to measure actually attained performance of Earth system models on different machines, and identify the most fruitful areas of research and development for performance engineering. codes present particular challenges to computational performance. We present results for these measures for a diverse suite of models from several modeling centers, and propose to use these measures as a basis for a CPMIP, a computational performance model intercomparison project (MIP).

Linking market interaction intensity of 3D Ising type financial model with market volatility

NASA Astrophysics Data System (ADS)

Fang, Wen; Ke, Jinchuan; Wang, Jun; Feng, Ling

2016-11-01

Microscopic interaction models in physics have been used to investigate the complex phenomena of economic systems. The simple interactions involved can lead to complex behaviors and help the understanding of mechanisms in the financial market at a systemic level. This article aims to develop a financial time series model through 3D (three-dimensional) Ising dynamic system which is widely used as an interacting spins model to explain the ferromagnetism in physics. Through Monte Carlo simulations of the financial model and numerical analysis for both the simulation return time series and historical return data of Hushen 300 (HS300) index in Chinese stock market, we show that despite its simplicity, this model displays stylized facts similar to that seen in real financial market. We demonstrate a possible underlying link between volatility fluctuations of real stock market and the change in interaction strengths of market participants in the financial model. In particular, our stochastic interaction strength in our model demonstrates that the real market may be consistently operating near the critical point of the system.

Evaluating performances of simplified physically based landslide susceptibility models.

NASA Astrophysics Data System (ADS)

Capparelli, Giovanna; Formetta, Giuseppe; Versace, Pasquale

2015-04-01

Rainfall induced shallow landslides cause significant damages involving loss of life and properties. Prediction of shallow landslides susceptible locations is a complex task that involves many disciplines: hydrology, geotechnical science, geomorphology, and statistics. Usually to accomplish this task two main approaches are used: statistical or physically based model. This paper presents a package of GIS based models for landslide susceptibility analysis. It was integrated in the NewAge-JGrass hydrological model using the Object Modeling System (OMS) modeling framework. The package includes three simplified physically based models for landslides susceptibility analysis (M1, M2, and M3) and a component for models verifications. It computes eight goodness of fit indices (GOF) by comparing pixel-by-pixel model results and measurements data. Moreover, the package integration in NewAge-JGrass allows the use of other components such as geographic information system tools to manage inputs-output processes, and automatic calibration algorithms to estimate model parameters. The system offers the possibility to investigate and fairly compare the quality and the robustness of models and models parameters, according a procedure that includes: i) model parameters estimation by optimizing each of the GOF index separately, ii) models evaluation in the ROC plane by using each of the optimal parameter set, and iii) GOF robustness evaluation by assessing their sensitivity to the input parameter variation. This procedure was repeated for all three models. The system was applied for a case study in Calabria (Italy) along the Salerno-Reggio Calabria highway, between Cosenza and Altilia municipality. The analysis provided that among all the optimized indices and all the three models, Average Index (AI) optimization coupled with model M3 is the best modeling solution for our test case. This research was funded by PON Project No. 01_01503 "Integrated Systems for Hydrogeological Risk Monitoring, Early Warning and Mitigation Along the Main Lifelines", CUP B31H11000370005, in the framework of the National Operational Program for "Research and Competitiveness" 2007-2013.

Boussinesq equations and other systems for small-amplitude long waves in nonlinear dispersive media: II. The nonlinear theory

NASA Astrophysics Data System (ADS)

Bona, J. L.; Chen, M.; Saut, J.-C.

2004-05-01

In part I of this work (Bona J L, Chen M and Saut J-C 2002 Boussinesq equations and other systems for small-amplitude long waves in nonlinear dispersive media I: Derivation and the linear theory J. Nonlinear Sci. 12 283-318), a four-parameter family of Boussinesq systems was derived to describe the propagation of surface water waves. Similar systems are expected to arise in other physical settings where the dominant aspects of propagation are a balance between the nonlinear effects of convection and the linear effects of frequency dispersion. In addition to deriving these systems, we determined in part I exactly which of them are linearly well posed in various natural function classes. It was argued that linear well-posedness is a natural necessary requirement for the possible physical relevance of the model in question. In this paper, it is shown that the first-order correct models that are linearly well posed are in fact locally nonlinearly well posed. Moreover, in certain specific cases, global well-posedness is established for physically relevant initial data. In part I, higher-order correct models were also derived. A preliminary analysis of a promising subclass of these models shows them to be well posed.

Black Hole on a Chip: Proposal for a Physical Realization of the Sachdev-Ye-Kitaev model in a Solid-State System

NASA Astrophysics Data System (ADS)

Pikulin, D. I.; Franz, M.

2017-07-01

A system of Majorana zero modes with random infinite-range interactions—the Sachdev-Ye-Kitaev (SYK) model—is thought to exhibit an intriguing relation to the horizons of extremal black holes in two-dimensional anti-de Sitter space. This connection provides a rare example of holographic duality between a solvable quantum-mechanical model and dilaton gravity. Here, we propose a physical realization of the SYK model in a solid-state system. The proposed setup employs the Fu-Kane superconductor realized at the interface between a three-dimensional topological insulator and an ordinary superconductor. The requisite N Majorana zero modes are bound to a nanoscale hole fabricated in the superconductor that is threaded by N quanta of magnetic flux. We show that when the system is tuned to the surface neutrality point (i.e., chemical potential coincident with the Dirac point of the topological insulator surface state) and the hole has sufficiently irregular shape, the Majorana zero modes are described by the SYK Hamiltonian. We perform extensive numerical simulations to demonstrate that the system indeed exhibits physical properties expected of the SYK model, including thermodynamic quantities and two-point as well as four-point correlators, and discuss ways in which these can be observed experimentally.

A prototype computer-aided modelling tool for life-support system models

NASA Technical Reports Server (NTRS)

Preisig, H. A.; Lee, Tae-Yeong; Little, Frank

1990-01-01

Based on the canonical decomposition of physical-chemical-biological systems, a prototype kernel has been developed to efficiently model alternative life-support systems. It supports (1) the work in an interdisciplinary group through an easy-to-use mostly graphical interface, (2) modularized object-oriented model representation, (3) reuse of models, (4) inheritance of structures from model object to model object, and (5) model data base. The kernel is implemented in Modula-II and presently operates on an IBM PC.

Computer graphics testbed to simulate and test vision systems for space applications

NASA Technical Reports Server (NTRS)

Cheatham, John B.; Wu, Chris K.; Lin, Y. H.

1991-01-01

A system was developed for displaying computer graphics images of space objects and the use of the system was demonstrated as a testbed for evaluating vision systems for space applications. In order to evaluate vision systems, it is desirable to be able to control all factors involved in creating the images used for processing by the vision system. Considerable time and expense is involved in building accurate physical models of space objects. Also, precise location of the model relative to the viewer and accurate location of the light source require additional effort. As part of this project, graphics models of space objects such as the Solarmax satellite are created that the user can control the light direction and the relative position of the object and the viewer. The work is also aimed at providing control of hue, shading, noise and shadows for use in demonstrating and testing imaging processing techniques. The simulated camera data can provide XYZ coordinates, pitch, yaw, and roll for the models. A physical model is also being used to provide comparison of camera images with the graphics images.

Quantum simulation of disordered systems with cold atoms

NASA Astrophysics Data System (ADS)

Garreau, Jean-Claude

2017-01-01

This paper reviews the physics of quantum disorder in relation with a series of experiments using laser-cooled atoms exposed to "kicks" of a standing wave, realizing a paradigmatic model of quantum chaos, the kicked rotor. This dynamical system can be mapped onto a tight-binding Hamiltonian with pseudo-disorder, formally equivalent to the Anderson model of quantum disorder, with quantum chaos playing the role of disorder. This provides a very good quantum simulator for the Anderson physics. xml:lang="fr"

Spatial resolution recovery utilizing multi-ray tracing and graphic processing unit in PET image reconstruction.

PubMed

Liang, Yicheng; Peng, Hao

2015-02-07

Depth-of-interaction (DOI) poses a major challenge for a PET system to achieve uniform spatial resolution across the field-of-view, particularly for small animal and organ-dedicated PET systems. In this work, we implemented an analytical method to model system matrix for resolution recovery, which was then incorporated in PET image reconstruction on a graphical processing unit platform, due to its parallel processing capacity. The method utilizes the concepts of virtual DOI layers and multi-ray tracing to calculate the coincidence detection response function for a given line-of-response. The accuracy of the proposed method was validated for a small-bore PET insert to be used for simultaneous PET/MR breast imaging. In addition, the performance comparisons were studied among the following three cases: 1) no physical DOI and no resolution modeling; 2) two physical DOI layers and no resolution modeling; and 3) no physical DOI design but with a different number of virtual DOI layers. The image quality was quantitatively evaluated in terms of spatial resolution (full-width-half-maximum and position offset), contrast recovery coefficient and noise. The results indicate that the proposed method has the potential to be used as an alternative to other physical DOI designs and achieve comparable imaging performances, while reducing detector/system design cost and complexity.

Initial Results from an Energy-Aware Airborne Dynamic, Data-Driven Application System Performing Sampling in Coherent Boundary-Layer Structures

NASA Astrophysics Data System (ADS)

Frew, E.; Argrow, B. M.; Houston, A. L.; Weiss, C.

2014-12-01

The energy-aware airborne dynamic, data-driven application system (EA-DDDAS) performs persistent sampling in complex atmospheric conditions by exploiting wind energy using the dynamic data-driven application system paradigm. The main challenge for future airborne sampling missions is operation with tight integration of physical and computational resources over wireless communication networks, in complex atmospheric conditions. The physical resources considered here include sensor platforms, particularly mobile Doppler radar and unmanned aircraft, the complex conditions in which they operate, and the region of interest. Autonomous operation requires distributed computational effort connected by layered wireless communication. Onboard decision-making and coordination algorithms can be enhanced by atmospheric models that assimilate input from physics-based models and wind fields derived from multiple sources. These models are generally too complex to be run onboard the aircraft, so they need to be executed in ground vehicles in the field, and connected over broadband or other wireless links back to the field. Finally, the wind field environment drives strong interaction between the computational and physical systems, both as a challenge to autonomous path planning algorithms and as a novel energy source that can be exploited to improve system range and endurance. Implementation details of a complete EA-DDDAS will be provided, along with preliminary flight test results targeting coherent boundary-layer structures.

Representing Operational Modes for Situation Awareness

NASA Astrophysics Data System (ADS)

Kirchhübel, Denis; Lind, Morten; Ravn, Ole

2017-01-01

Operating complex plants is an increasingly demanding task for human operators. Diagnosis of and reaction to on-line events requires the interpretation of real time data. Vast amounts of sensor data as well as operational knowledge about the state and design of the plant are necessary to deduct reasonable reactions to abnormal situations. Intelligent computational support tools can make the operator’s task easier, but they require knowledge about the overall system in form of some model. While tools used for fault-tolerant control design based on physical principles and relations are valuable tools for designing robust systems, the models become too complex when considering the interactions on a plant-wide level. The alarm systems meant to support human operators in the diagnosis of the plant-wide situation on the other hand fail regularly in situations where these interactions of systems lead to many related alarms overloading the operator with alarm floods. Functional modelling can provide a middle way to reduce the complexity of plant-wide models by abstracting from physical details to more general functions and behaviours. Based on functional models the propagation of failures through the interconnected systems can be inferred and alarm floods can potentially be reduced to their root-cause. However, the desired behaviour of a complex system changes due to operating procedures that require more than one physical and functional configuration. In this paper a consistent representation of possible configurations is deduced from the analysis of an exemplary start-up procedure by functional models. The proposed interpretation of the modelling concepts simplifies the functional modelling of distinct modes. The analysis further reveals relevant links between the quantitative sensor data and the qualitative perspective of the diagnostics tool based on functional models. This will form the basis for the ongoing development of a novel real-time diagnostics system based on the on-line adaptation of the underlying MFM model.

Understanding Complex Natural Systems by Articulating Structure-Behavior-Function Models

ERIC Educational Resources Information Center

Vattam, Swaroop S.; Goel, Ashok K.; Rugaber, Spencer; Hmelo-Silver, Cindy E.; Jordan, Rebecca; Gray, Steven; Sinha, Suparna

2011-01-01

Artificial intelligence research on creative design has led to Structure-Behavior-Function (SBF) models that emphasize functions as abstractions for organizing understanding of physical systems. Empirical studies on understanding complex systems suggest that novice understanding is shallow, typically focusing on their visible structures and…

Uncertainty Analysis of Coupled Socioeconomic-Cropping Models: Building Confidence in Climate Change Decision-Support Tools for Local Stakeholders

NASA Astrophysics Data System (ADS)

Malard, J. J.; Rojas, M.; Adamowski, J. F.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

2015-12-01

While cropping models represent the biophysical aspects of agricultural systems, system dynamics modelling offers the possibility of representing the socioeconomic (including social and cultural) aspects of these systems. The two types of models can then be coupled in order to include the socioeconomic dimensions of climate change adaptation in the predictions of cropping models.We develop a dynamically coupled socioeconomic-biophysical model of agricultural production and its repercussions on food security in two case studies from Guatemala (a market-based, intensive agricultural system and a low-input, subsistence crop-based system). Through the specification of the climate inputs to the cropping model, the impacts of climate change on the entire system can be analysed, and the participatory nature of the system dynamics model-building process, in which stakeholders from NGOs to local governmental extension workers were included, helps ensure local trust in and use of the model.However, the analysis of climate variability's impacts on agroecosystems includes uncertainty, especially in the case of joint physical-socioeconomic modelling, and the explicit representation of this uncertainty in the participatory development of the models is important to ensure appropriate use of the models by the end users. In addition, standard model calibration, validation, and uncertainty interval estimation techniques used for physically-based models are impractical in the case of socioeconomic modelling. We present a methodology for the calibration and uncertainty analysis of coupled biophysical (cropping) and system dynamics (socioeconomic) agricultural models, using survey data and expert input to calibrate and evaluate the uncertainty of the system dynamics as well as of the overall coupled model. This approach offers an important tool for local decision makers to evaluate the potential impacts of climate change and their feedbacks through the associated socioeconomic system.

Joint Vision 2010: Developing the System of Systems

DTIC Science & Technology

1998-04-01

The system engineering model, as described in Defense Acquisition University Coursebook , consists of five main parts and three feedback loops.4 The... physical architecture is defined and each subsystem developed. In the case of JV2010’s “system of systems” the subsystems would be the items...verify that each requirement can be traced to a system function. The purpose of the design loop is to ensure all the functions can be traced to physical

Quantum physics with non-Hermitian operators Quantum physics with non-Hermitian operators

NASA Astrophysics Data System (ADS)

Bender, Carl; Fring, Andreas; Günther, Uwe; Jones, Hugh

2012-11-01

The main motivation behind the call for this special issue was to gather recent results, developments and open problems in quantum physics with non-Hermitian operators. There have been previous special issues in this journal [1, 2] and elsewhere on this subject. The intention of this issue is to reflect the current state of this rapidly-developing field. It has therefore been open to all contributions containing new results on non-Hermitian theories that are explicitly PT-symmetric and/or pseudo-Hermitian or quasi-Hermitian. In the last decade these types of systems have proved to be viable self-consistent physical theories with well defined unitary time-evolution and real spectra. As the large number of responses demonstrates, this is a rapidly evolving field of research. A consensus has been reached regarding most of the fundamental problems, and the general ideas and techniques are now readily being employed in many areas of physics. Nonetheless, this issue still contains some treatments of a more general nature regarding the spectral analysis of these models, in particular, the physics of the exceptional points, the breaking of the PT-symmetry, an interpretation of negative energies and the consistent implementation of the WKB analysis. This issue also contains a treatment of a scattering theory associated with these types of systems, weak measurements, coherent states, decoherence, unbounded metric operators and the inclusion of domain issues to obtain well defined self-adjoint theories. Contributions in the form of applications of the general ideas include: studies of classical shock-waves and tunnelling, supersymmetric models, spin chain models, models with ring structure, random matrix models, the Pauli equation, the nonlinear Schrödinger equation, quasi-exactly solvable models, integrable models such as the Calogero model, Bose-Einstein condensates, thermodynamics, nonlinear oligomers, quantum catastrophes, the Landau-Zener problem and pseudo-Fermions. Applications close to experimental realization are proposed in optics, including short light pulse models, waveguides and laser systems, and also in electronics. We hope that this issue will become a valuable reference and inspiration for the broader scientific community working in mathematical and theoretical physics. References [1] Fring A, Jones H F and Znojil M (ed) 2008 J. Phys. A: Math. Theor. 41 240301 [2] Geyer H, Heiss D and Znojil M (ed) 2006 J. Phys. A: Math. Gen. 39 9963

Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier–Stokes simulations: A data-driven, physics-informed Bayesian approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiao, H., E-mail: hengxiao@vt.edu; Wu, J.-L.; Wang, J.-X.

Despite their well-known limitations, Reynolds-Averaged Navier–Stokes (RANS) models are still the workhorse tools for turbulent flow simulations in today's engineering analysis, design and optimization. While the predictive capability of RANS models depends on many factors, for many practical flows the turbulence models are by far the largest source of uncertainty. As RANS models are used in the design and safety evaluation of many mission-critical systems such as airplanes and nuclear power plants, quantifying their model-form uncertainties has significant implications in enabling risk-informed decision-making. In this work we develop a data-driven, physics-informed Bayesian framework for quantifying model-form uncertainties in RANS simulations.more » Uncertainties are introduced directly to the Reynolds stresses and are represented with compact parameterization accounting for empirical prior knowledge and physical constraints (e.g., realizability, smoothness, and symmetry). An iterative ensemble Kalman method is used to assimilate the prior knowledge and observation data in a Bayesian framework, and to propagate them to posterior distributions of velocities and other Quantities of Interest (QoIs). We use two representative cases, the flow over periodic hills and the flow in a square duct, to evaluate the performance of the proposed framework. Both cases are challenging for standard RANS turbulence models. Simulation results suggest that, even with very sparse observations, the obtained posterior mean velocities and other QoIs have significantly better agreement with the benchmark data compared to the baseline results. At most locations the posterior distribution adequately captures the true model error within the developed model form uncertainty bounds. The framework is a major improvement over existing black-box, physics-neutral methods for model-form uncertainty quantification, where prior knowledge and details of the models are not exploited. This approach has potential implications in many fields in which the governing equations are well understood but the model uncertainty comes from unresolved physical processes. - Highlights: • Proposed a physics–informed framework to quantify uncertainty in RANS simulations. • Framework incorporates physical prior knowledge and observation data. • Based on a rigorous Bayesian framework yet fully utilizes physical model. • Applicable for many complex physical systems beyond turbulent flows.« less

Challenges of Representing Sub-Grid Physics in an Adaptive Mesh Refinement Atmospheric Model

NASA Astrophysics Data System (ADS)

O'Brien, T. A.; Johansen, H.; Johnson, J. N.; Rosa, D.; Benedict, J. J.; Keen, N. D.; Collins, W.; Goodfriend, E.

2015-12-01

Some of the greatest potential impacts from future climate change are tied to extreme atmospheric phenomena that are inherently multiscale, including tropical cyclones and atmospheric rivers. Extremes are challenging to simulate in conventional climate models due to existing models' coarse resolutions relative to the native length-scales of these phenomena. Studying the weather systems of interest requires an atmospheric model with sufficient local resolution, and sufficient performance for long-duration climate-change simulations. To this end, we have developed a new global climate code with adaptive spatial and temporal resolution. The dynamics are formulated using a block-structured conservative finite volume approach suitable for moist non-hydrostatic atmospheric dynamics. By using both space- and time-adaptive mesh refinement, the solver focuses computational resources only where greater accuracy is needed to resolve critical phenomena. We explore different methods for parameterizing sub-grid physics, such as microphysics, macrophysics, turbulence, and radiative transfer. In particular, we contrast the simplified physics representation of Reed and Jablonowski (2012) with the more complex physics representation used in the System for Atmospheric Modeling of Khairoutdinov and Randall (2003). We also explore the use of a novel macrophysics parameterization that is designed to be explicitly scale-aware.

Learning physical biology via modeling and simulation: A new course and textbook for science and engineering undergraduates

NASA Astrophysics Data System (ADS)

Nelson, Philip

To a large extent, undergraduate physical-science curricula remain firmly rooted in pencil-and-paper calculation, despite the fact that most research is done with computers. To a large extent, undergraduate life-science curricula remain firmly rooted in descriptive approaches, despite the fact that much current research involves quantitative modeling. Not only does our pedagogy not reflect current reality; it also creates a spurious barrier between the fields, reinforcing the narrow silos that prevent students from connecting them. I'll describe an intermediate-level course on ``Physical Models of Living Systems.'' The prerequisite is first-year university physics and calculus. The course is a response to rapidly growing interest among undergraduates in a broad range of science and engineering majors. Students acquire several research skills that are often not addressed in traditional undergraduate courses: •Basic modeling skills; •Probabilistic modeling skills; •Data analysis methods; •Computer programming using a general-purpose platform like MATLAB or Python; •Pulling datasets from the Web for analysis; •Data visualization; •Dynamical systems, particularly feedback control. Partially supported by the NSF under Grants EF-0928048 and DMR-0832802.

Quantum energy teleportation in a quantum Hall system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yusa, Go; Izumida, Wataru; Hotta, Masahiro

2011-09-15

We propose an experimental method for a quantum protocol termed quantum energy teleportation (QET), which allows energy transportation to a remote location without physical carriers. Using a quantum Hall system as a realistic model, we discuss the physical significance of QET and estimate the order of energy gain using reasonable experimental parameters.

Exercise and Diet in Obesity Treatment: An Integrative System Dynamics Perspective.

ERIC Educational Resources Information Center

Abdel-Hamid, Tarek K.

2003-01-01

Examined the utility of System Dynamics modeling as a vehicle for controlled experimentation to study and gain insight into the impacts of physical activity and diet on body weight and composition. Results underscored the significant interaction effects between physical activity, diet, and body composition and demonstrated the utility of…

Key issues and technical route of cyber physical distribution system

NASA Astrophysics Data System (ADS)

Zheng, P. X.; Chen, B.; Zheng, L. J.; Zhang, G. L.; Fan, Y. L.; Pei, T.

2017-01-01

Relying on the National High Technology Research and Development Program, this paper introduced the key issues in Cyber Physical Distribution System (CPDS), mainly includes: composite modelling method and interaction mechanism, system planning method, security defence technology, distributed control theory. Then on this basis, the corresponding technical route is proposed, and a more detailed research framework along with main schemes to be adopted is also presented.

Predictive Simulation of Gas Adsorption in Fixed-Beds and Limitations due to the Ill-Posed Danckwerts Boundary Condition

NASA Technical Reports Server (NTRS)

Knox, James Clinton

2016-01-01

The 1-D axially dispersed plug flow model is a mathematical model widely used for the simulation of adsorption processes. Lumped mass transfer coefficients such as the Glueckauf linear driving force (LDF) term and the axial dispersion coefficient are generally obtained by fitting simulation results to the experimental breakthrough test data. An approach is introduced where these parameters, along with the only free parameter in the energy balance equations, are individually fit to specific test data that isolates the appropriate physics. It is shown that with this approach this model provides excellent simulation results for the C02 on zeolite SA sorbent/sorbate system; however, for the H20 on zeolite SA system, non-physical deviations from constant pattern behavior occur when fitting dispersive experimental results with a large axial dispersion coefficient. A method has also been developed that determines a priori what values of the LDF and axial dispersion terms will result in non-physical simulation results for a specific sorbent/sorbate system when using the one-dimensional axially dispersed plug flow model. A relationship between the steepness of the adsorption equilibrium isotherm as indicated by the distribution factor, the magnitude of the axial dispersion and mass transfer coefficient, and the resulting non-physical behavior is derived. This relationship is intended to provide a guide for avoiding non-physical behavior by limiting the magnitude of the axial dispersion term on the basis of the mass transfer coefficient and distribution factor.

2016 KIVA-hpFE Development: A Robust and Accurate Engine Modeling Software

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carrington, David Bradley; Waters, Jiajia

Los Alamos National Laboratory and its collaborators are facilitating engine modeling by improving accuracy and robustness of the modeling, and improving the robustness of software. We also continue to improve the physical modeling methods. We are developing and implementing new mathematical algorithms, those that represent the physics within an engine. We provide software that others may use directly or that they may alter with various models e.g., sophisticated chemical kinetics, different turbulent closure methods or other fuel injection and spray systems.

A crystal plasticity model for slip in hexagonal close packed metals based on discrete dislocation simulations

NASA Astrophysics Data System (ADS)

Messner, Mark C.; Rhee, Moono; Arsenlis, Athanasios; Barton, Nathan R.

2017-06-01

This work develops a method for calibrating a crystal plasticity model to the results of discrete dislocation (DD) simulations. The crystal model explicitly represents junction formation and annihilation mechanisms and applies these mechanisms to describe hardening in hexagonal close packed metals. The model treats these dislocation mechanisms separately from elastic interactions among populations of dislocations, which the model represents through a conventional strength-interaction matrix. This split between elastic interactions and junction formation mechanisms more accurately reproduces the DD data and results in a multi-scale model that better represents the lower scale physics. The fitting procedure employs concepts of machine learning—feature selection by regularized regression and cross-validation—to develop a robust, physically accurate crystal model. The work also presents a method for ensuring the final, calibrated crystal model respects the physical symmetries of the crystal system. Calibrating the crystal model requires fitting two linear operators: one describing elastic dislocation interactions and another describing junction formation and annihilation dislocation reactions. The structure of these operators in the final, calibrated model reflect the crystal symmetry and slip system geometry of the DD simulations.

Simplified Physics Based Models Research Topical Report on Task #2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishra, Srikanta; Ganesh, Priya

We present a simplified-physics based approach, where only the most important physical processes are modeled, to develop and validate simplified predictive models of CO2 sequestration in deep saline formation. The system of interest is a single vertical well injecting supercritical CO2 into a 2-D layered reservoir-caprock system with variable layer permeabilities. We use a set of well-designed full-physics compositional simulations to understand key processes and parameters affecting pressure propagation and buoyant plume migration. Based on these simulations, we have developed correlations for dimensionless injectivity as a function of the slope of fractional-flow curve, variance of layer permeability values, and themore » nature of vertical permeability arrangement. The same variables, along with a modified gravity number, can be used to develop a correlation for the total storage efficiency within the CO2 plume footprint. Similar correlations are also developed to predict the average pressure within the injection reservoir, and the pressure buildup within the caprock.« less

Investigating the Effect of Damage Progression Model Choice on Prognostics Performance

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil; Narasimhan, Sriram; Saha, Sankalita; Saha, Bhaskar; Goebel, Kai

2011-01-01

The success of model-based approaches to systems health management depends largely on the quality of the underlying models. In model-based prognostics, it is especially the quality of the damage progression models, i.e., the models describing how damage evolves as the system operates, that determines the accuracy and precision of remaining useful life predictions. Several common forms of these models are generally assumed in the literature, but are often not supported by physical evidence or physics-based analysis. In this paper, using a centrifugal pump as a case study, we develop different damage progression models. In simulation, we investigate how model changes influence prognostics performance. Results demonstrate that, in some cases, simple damage progression models are sufficient. But, in general, the results show a clear need for damage progression models that are accurate over long time horizons under varied loading conditions.

A multiphysical ensemble system of numerical snow modelling

NASA Astrophysics Data System (ADS)

Lafaysse, Matthieu; Cluzet, Bertrand; Dumont, Marie; Lejeune, Yves; Vionnet, Vincent; Morin, Samuel

2017-05-01

Physically based multilayer snowpack models suffer from various modelling errors. To represent these errors, we built the new multiphysical ensemble system ESCROC (Ensemble System Crocus) by implementing new representations of different physical processes in the deterministic coupled multilayer ground/snowpack model SURFEX/ISBA/Crocus. This ensemble was driven and evaluated at Col de Porte (1325 m a.s.l., French alps) over 18 years with a high-quality meteorological and snow data set. A total number of 7776 simulations were evaluated separately, accounting for the uncertainties of evaluation data. The ability of the ensemble to capture the uncertainty associated to modelling errors is assessed for snow depth, snow water equivalent, bulk density, albedo and surface temperature. Different sub-ensembles of the ESCROC system were studied with probabilistic tools to compare their performance. Results show that optimal members of the ESCROC system are able to explain more than half of the total simulation errors. Integrating members with biases exceeding the range corresponding to observational uncertainty is necessary to obtain an optimal dispersion, but this issue can also be a consequence of the fact that meteorological forcing uncertainties were not accounted for. The ESCROC system promises the integration of numerical snow-modelling errors in ensemble forecasting and ensemble assimilation systems in support of avalanche hazard forecasting and other snowpack-modelling applications.

Kinetic Theory and Simulation of Single-Channel Water Transport

NASA Astrophysics Data System (ADS)

Tajkhorshid, Emad; Zhu, Fangqiang; Schulten, Klaus

Water translocation between various compartments of a system is a fundamental process in biology of all living cells and in a wide variety of technological problems. The process is of interest in different fields of physiology, physical chemistry, and physics, and many scientists have tried to describe the process through physical models. Owing to advances in computer simulation of molecular processes at an atomic level, water transport has been studied in a variety of molecular systems ranging from biological water channels to artificial nanotubes. While simulations have successfully described various kinetic aspects of water transport, offering a simple, unified model to describe trans-channel translocation of water turned out to be a nontrivial task.

Phase Transition of a Dynamical System with a Bi-Directional, Instantaneous Coupling to a Virtual System

NASA Astrophysics Data System (ADS)

Gintautas, Vadas; Hubler, Alfred

2006-03-01

As worldwide computer resources increase in power and decrease in cost, real-time simulations of physical systems are becoming increasingly prevalent, from laboratory models to stock market projections and entire ``virtual worlds'' in computer games. Often, these systems are meticulously designed to match real-world systems as closely as possible. We study the limiting behavior of a virtual horizontally driven pendulum coupled to its real-world counterpart, where the interaction occurs on a time scale that is much shorter than the time scale of the dynamical system. We find that if the physical parameters of the virtual system match those of the real system within a certain tolerance, there is a qualitative change in the behavior of the two-pendulum system as the strength of the coupling is increased. Applications include a new method to measure the physical parameters of a real system and the use of resonance spectroscopy to refine a computer model. As virtual systems better approximate real ones, even very weak interactions may produce unexpected and dramatic behavior. The research is supported by the National Science Foundation Grant No. NSF PHY 01-40179, NSF DMS 03-25939 ITR, and NSF DGE 03-38215.

Jochem Weber | NREL

Science.gov Websites

mechanical engineering (design) and physical engineering (fluid and system dynamics), and a Ph.D. in modeling Ph.D. in Engineering, University College Cork (Ireland); M.S. and B.S. in Physical Engineering

Model Information Exchange System (MIXS).

DOT National Transportation Integrated Search

2013-08-01

Many travel demand forecast models operate at state, regional, and local levels. While they share the same physical network in overlapping geographic areas, they use different and uncoordinated modeling networks. This creates difficulties for models ...

Constructive Models of Discrete and Continuous Physical Phenomena

DTIC Science & Technology

2014-02-08

BOURKE , T., CAILLAUD, B., AND POUZET, M. The fundamentals of hybrid systems modelers. Journal of Computer and System Sciences 78, 3 (2012), 877–910...8. BENVENISTE, A., BOURKE , T., CAILLAUD, B., AND POUZET, M. Index theory for hy- brid DAE systems (abstract and slides). In Synchronous Programming

A Hypermedia Model for Teaching Technology.

ERIC Educational Resources Information Center

Savage, Ernest N.

Ohio's Model Industrial Technology Systems (MITS) project was initiated in 1987 to achieve the following: identify good activities in the areas of physical, communication, and bio-related technology; standardize the activities' format; and provide a coding system for their eventual use in a hypermedia system. To date, 220 activities have been…

Systems Engineering of Education I: The Evolution of Systems Thinking in Education, 2nd Edition.

ERIC Educational Resources Information Center

Silvern, Leonard C.

This document methodically traces the development of the fundamental concepts of systems thinking in education from Harbert to contemporary innovators. The discussion explains narrative models, concentrating on educational flowcharting techniques and mathematical models related to developments in engineering and physical science. The presentation…

A Goddard Multi-Scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2010-01-01

A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. In this talk, I will present: (1) A brief review on GCE model and its applications on the impact of the aerosol on deep precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications). We are also performing the inline tracer calculation to comprehend the ph ysical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems.

Applications of EVA guidelines and design criteria. Volume 3: EVA systems cost model formating

NASA Technical Reports Server (NTRS)

Brown, N. E.

1973-01-01

The development of a model for estimating the impact of manned EVA costs on future payloads is discussed. Basic information on the EV crewman requirements, equipment, physical and operational characteristics, and vehicle interfaces is provided. The cost model is being designed to allow system designers to quantify the impact of EVA on vehicle and payload systems.

Independent Living & Disability Policy in the Netherlands: Three Models of Residential Care & Independent Living. Monograph Number Twenty-Seven.

ERIC Educational Resources Information Center

DeJong, Gerben

The monograph examines the way in which the Netherlands' three-part system of residential care and independent living (IL) for people with physical disabilities interacts with the country's health and social welfare systems. The three-part system comprises: the residential center model, the clustered housing model, and the independent housing…

Master-slave system with force feedback based on dynamics of virtual model

NASA Technical Reports Server (NTRS)

Nojima, Shuji; Hashimoto, Hideki

1994-01-01

A master-slave system can extend manipulating and sensing capabilities of a human operator to a remote environment. But the master-slave system has two serious problems: one is the mechanically large impedance of the system; the other is the mechanical complexity of the slave for complex remote tasks. These two problems reduce the efficiency of the system. If the slave has local intelligence, it can help the human operator by using its good points like fast calculation and large memory. The authors suggest that the slave is a dextrous hand with many degrees of freedom able to manipulate an object of known shape. It is further suggested that the dimensions of the remote work space be shared by the human operator and the slave. The effect of the large impedance of the system can be reduced in a virtual model, a physical model constructed in a computer with physical parameters as if it were in the real world. A method to determine the damping parameter dynamically for the virtual model is proposed. Experimental results show that this virtual model is better than the virtual model with fixed damping.

Recent theoretical advances on superradiant phase transitions

NASA Astrophysics Data System (ADS)

Baksic, Alexandre; Nataf, Pierre; Ciuti, Cristiano

2013-03-01

The Dicke model describing a single-mode boson field coupled to two-level systems is an important paradigm in quantum optics. In particular, the physics of ``superradiant phase transitions'' in the ultrastrong coupling regime is the subject of a vigorous research activity in both cavity and circuit QED. Recently, we explored the rich physics of two interesting generalizations of the Dicke model: (i) A model describing the coupling of a boson mode to two independent chains A and B of two-level systems, where chain A is coupled to one quadrature of the boson field and chain B to the orthogonal quadrature. This original model leads to a quantum phase transition with a double symmetry breaking and a fourfold ground state degeneracy. (ii) A generalized Dicke model with three-level systems including the diamagnetic term. In contrast to the case of two-level atoms for which no-go theorems exist, in the case of three-level system we prove that the Thomas-Reich-Kuhn sum rule does not always prevent a superradiant phase transition.

The Environment-Power System Analysis Tool development program. [for spacecraft power supplies

NASA Technical Reports Server (NTRS)

Jongeward, Gary A.; Kuharski, Robert A.; Kennedy, Eric M.; Wilcox, Katherine G.; Stevens, N. John; Putnam, Rand M.; Roche, James C.

1989-01-01

The Environment Power System Analysis Tool (EPSAT) is being developed to provide engineers with the ability to assess the effects of a broad range of environmental interactions on space power systems. A unique user-interface-data-dictionary code architecture oversees a collection of existing and future environmental modeling codes (e.g., neutral density) and physical interaction models (e.g., sheath ionization). The user-interface presents the engineer with tables, graphs, and plots which, under supervision of the data dictionary, are automatically updated in response to parameter change. EPSAT thus provides the engineer with a comprehensive and responsive environmental assessment tool and the scientist with a framework into which new environmental or physical models can be easily incorporated.

Mixed finite element - discontinuous finite volume element discretization of a general class of multicontinuum models

NASA Astrophysics Data System (ADS)

Ruiz-Baier, Ricardo; Lunati, Ivan

2016-10-01

We present a novel discretization scheme tailored to a class of multiphase models that regard the physical system as consisting of multiple interacting continua. In the framework of mixture theory, we consider a general mathematical model that entails solving a system of mass and momentum equations for both the mixture and one of the phases. The model results in a strongly coupled and nonlinear system of partial differential equations that are written in terms of phase and mixture (barycentric) velocities, phase pressure, and saturation. We construct an accurate, robust and reliable hybrid method that combines a mixed finite element discretization of the momentum equations with a primal discontinuous finite volume-element discretization of the mass (or transport) equations. The scheme is devised for unstructured meshes and relies on mixed Brezzi-Douglas-Marini approximations of phase and total velocities, on piecewise constant elements for the approximation of phase or total pressures, as well as on a primal formulation that employs discontinuous finite volume elements defined on a dual diamond mesh to approximate scalar fields of interest (such as volume fraction, total density, saturation, etc.). As the discretization scheme is derived for a general formulation of multicontinuum physical systems, it can be readily applied to a large class of simplified multiphase models; on the other, the approach can be seen as a generalization of these models that are commonly encountered in the literature and employed when the latter are not sufficiently accurate. An extensive set of numerical test cases involving two- and three-dimensional porous media are presented to demonstrate the accuracy of the method (displaying an optimal convergence rate), the physics-preserving properties of the mixed-primal scheme, as well as the robustness of the method (which is successfully used to simulate diverse physical phenomena such as density fingering, Terzaghi's consolidation, deformation of a cantilever bracket, and Boycott effects). The applicability of the method is not limited to flow in porous media, but can also be employed to describe many other physical systems governed by a similar set of equations, including e.g. multi-component materials.

Science-Grade Observing Systems as Process Observatories: Mapping and Understanding Nonlinearity and Multiscale Memory with Models and Observations

NASA Astrophysics Data System (ADS)

Barros, A. P.; Wilson, A. M.; Miller, D. K.; Tao, J.; Genereux, D. P.; Prat, O.; Petersen, W. A.; Brunsell, N. A.; Petters, M. D.; Duan, Y.

2015-12-01

Using the planet as a study domain and collecting observations over unprecedented ranges of spatial and temporal scales, NASA's EOS (Earth Observing System) program was an agent of transformational change in Earth Sciences over the last thirty years. The remarkable space-time organization and variability of atmospheric and terrestrial moist processes that emerged from the analysis of comprehensive satellite observations provided much impetus to expand the scope of land-atmosphere interaction studies in Hydrology and Hydrometeorology. Consequently, input and output terms in the mass and energy balance equations evolved from being treated as fluxes that can be used as boundary conditions, or forcing, to being viewed as dynamic processes of a coupled system interacting at multiple scales. Measurements of states or fluxes are most useful if together they map, reveal and/or constrain the underlying physical processes and their interactions. This can only be accomplished through an integrated observing system designed to capture the coupled physics, including nonlinear feedbacks and tipping points. Here, we first review and synthesize lessons learned from hydrometeorology studies in the Southern Appalachians and in the Southern Great Plains using both ground-based and satellite observations, physical models and data-assimilation systems. We will specifically focus on mapping and understanding nonlinearity and multiscale memory of rainfall-runoff processes in mountainous regions. It will be shown that beyond technical rigor, variety, quantity and duration of measurements, the utility of observing systems is determined by their interpretive value in the context of physical models to describe the linkages among different observations. Second, we propose a framework for designing science-grade and science-minded process-oriented integrated observing and modeling platforms for hydrometeorological studies.

Event-based aquifer-to-atmosphere modeling over the European CORDEX domain

NASA Astrophysics Data System (ADS)

Keune, J.; Goergen, K.; Sulis, M.; Shrestha, P.; Springer, A.; Kusche, J.; Ohlwein, C.; Kollet, S. J.

2014-12-01

Despite the fact that recent studies focus on the impact of soil moisture on climate and especially land-energy feedbacks, groundwater dynamics are often neglected or conceptual groundwater flow models are used. In particular, in the context of climate change and the occurrence of droughts and floods, a better understanding and an improved simulation of the physical processes involving groundwater on continental scales is necessary. This requires the implementation of a physically consistent terrestrial modeling system, which explicitly incorporates groundwater dynamics and the connection with shallow soil moisture. Such a physics-based system enables simulations and monitoring of groundwater storage and enhanced representations of the terrestrial energy and hydrologic cycles over long time periods. On shorter timescales, the prediction of groundwater-related extremes, such as floods and droughts, are expected to improve, because of the improved simulation of components of the hydrological cycle. In this study, we present a fully coupled aquifer-to-atmosphere modeling system over the European CORDEX domain. The integrated Terrestrial Systems Modeling Platform, TerrSysMP, consisting of the three-dimensional subsurface model ParFlow, the Community Land Model CLM3.5 and the numerical weather prediction model COSMO of the German Weather Service, is used. The system is set up with a spatial resolution of 0.11° (12.5km) and closes the terrestrial water and energy cycles from aquifers into the atmosphere. Here, simulations of the fully coupled system are performed over events, such as the 2013 flood in Central Europe and the 2003 European heat wave, and over extended time periods on the order of 10 years. State and flux variables of the terrestrial hydrologic and energy cycle are analyzed and compared to both in situ (e.g. stream and water level gauge networks, FLUXNET) and remotely sensed observations (e.g. GRACE, ESA ICC ECV soil moisture and SMOS). Additionally, the presented modeling system may be useful in the assessment of groundwater-related uncertainties in virtual reality and scenario simulations.

Comparison of social and physical free energies on a toy model.

PubMed

Kasac, Josip; Stefancic, Hrvoje; Stepanic, Josip

2004-01-01

Social free energy has been recently introduced as a measure of social action obtainable in a given social system, without changes in its structure. The authors of this paper argue that social free energy surpasses the gap between the verbally formulated value sets of social systems and the quantitatively based predictions. This point is further developed by analyzing the relation between the social and the physical free energy. Generically, this is done for a particular type of social dynamics. The extracted type of social dynamics is one of many realistic types of the differing proportion of social and economic elements. Numerically, this has been done for a toy model of interacting agents. The values of the social and physical free energies are, within the numerical accuracy, equivalent in the class of nontrivial, quasistationary model states.

The use of quizStar application for online examination in basic physics course

NASA Astrophysics Data System (ADS)

Kustijono, R.; Budiningarti, H.

2018-03-01

The purpose of the study is to produce an online Basic Physics exam system using the QuizStar application. This is a research and development with ADDIE model. The steps are: 1) analysis; 2) design; 3) development; 4) implementation; 5) evaluation. System feasibility is reviewed for its validity, practicality, and effectiveness. The subjects of research are 60 Physics Department students of Universitas Negeri Surabaya. The data analysis used is a descriptive statistic. The validity, practicality, and effectiveness scores are measured using a Likert scale. Criteria feasible if the total score of all aspects obtained is ≥ 61%. The results obtained from the online test system by using QuizStar developed are 1) conceptually feasible to use; 2) the system can be implemented in the Basic Physics assessment process, and the existing constraints can be overcome; 3) student's response to system usage is in a good category. The results conclude that QuizStar application is eligible to be used for online Basic Physics exam system.

The Livingstone Model of a Main Propulsion System

NASA Technical Reports Server (NTRS)

Bajwa, Anupa; Sweet, Adam; Korsmeyer, David (Technical Monitor)

2003-01-01

Livingstone is a discrete, propositional logic-based inference engine that has been used for diagnosis of physical systems. We present a component-based model of a Main Propulsion System (MPS) and say how it is used with Livingstone (L2) in order to implement a diagnostic system for integrated vehicle health management (IVHM) for the Propulsion IVHM Technology Experiment (PITEX). We start by discussing the process of conceptualizing such a model. We describe graphical tools that facilitated the generation of the model. The model is composed of components (which map onto physical components), connections between components and constraints. A component is specified by variables, with a set of discrete, qualitative values for each variable in its local nominal and failure modes. For each mode, the model specifies the component's behavior and transitions. We describe the MPS components' nominal and fault modes and associated Livingstone variables and data structures. Given this model, and observed external commands and observations from the system, Livingstone tracks the state of the MPS over discrete time-steps by choosing trajectories that are consistent with observations. We briefly discuss how the compiled model fits into the overall PITEX architecture. Finally we summarize our modeling experience, discuss advantages and disadvantages of our approach, and suggest enhancements to the modeling process.

Choices Matter, but How Do We Model Them?

NASA Astrophysics Data System (ADS)

Brelsford, C.; Dumas, M.

2017-12-01

Quantifying interactions between social systems and the physical environment we live within has long been a major scientific challenge. Humans have had such a large influence on our environment that it is no longer reasonable to consider the behavior of an ecological or hydrological system from a purely `physical' perspective: imagining a system that excludes the influence of human choices and behavior. Understanding the role that human social choices play in the energy water nexus is crucial for developing accurate models in that space. The relatively new field of socio-hydrology is making progress towards understanding the role humans play in hydrological systems. While this fact is now widely recognized across the many academic fields that study water systems, we have yet to develop a coherent set of theories for how to model the behavior of these complex and highly interdependent socio-hydrological systems. How should we conceptualize hydrological systems as socio-ecological systems (i.e. system with variables, states, parameters, actors who can control certain variables and a sense of the desirability of states) within which the rigorous study of feedbacks becomes possible? This talk reviews the state of knowledge of how social decisions around water consumption, allocation, and transport influence and are influenced by the physical hydrology that water also moves within. We cover recent papers in socio-hydrology, engineering, water law, and institutional analysis. There have been several calls within socio-hydrology to model human social behavior endogenously along with the hydrology. These improvements are needed across a range of spatial and temporal scales. We suggest two potential strategies for coupled models that allow endogenous water consumption behavior: a social first model which looks for empirical relationships between water consumption and allocation choices and the hydrological state, and a hydrology first model in which we look for regularities in how water regimes influence behavior, regional economies, or allocation institutions.

Physically based modeling in catchment hydrology at 50: Survey and outlook

NASA Astrophysics Data System (ADS)

Paniconi, Claudio; Putti, Mario

2015-09-01

Integrated, process-based numerical models in hydrology are rapidly evolving, spurred by novel theories in mathematical physics, advances in computational methods, insights from laboratory and field experiments, and the need to better understand and predict the potential impacts of population, land use, and climate change on our water resources. At the catchment scale, these simulation models are commonly based on conservation principles for surface and subsurface water flow and solute transport (e.g., the Richards, shallow water, and advection-dispersion equations), and they require robust numerical techniques for their resolution. Traditional (and still open) challenges in developing reliable and efficient models are associated with heterogeneity and variability in parameters and state variables; nonlinearities and scale effects in process dynamics; and complex or poorly known boundary conditions and initial system states. As catchment modeling enters a highly interdisciplinary era, new challenges arise from the need to maintain physical and numerical consistency in the description of multiple processes that interact over a range of scales and across different compartments of an overall system. This paper first gives an historical overview (past 50 years) of some of the key developments in physically based hydrological modeling, emphasizing how the interplay between theory, experiments, and modeling has contributed to advancing the state of the art. The second part of the paper examines some outstanding problems in integrated catchment modeling from the perspective of recent developments in mathematical and computational science.

Recent Improvements of Particle and Heavy Ion Transport code System: PHITS

NASA Astrophysics Data System (ADS)

Sato, Tatsuhiko; Niita, Koji; Iwamoto, Yosuke; Hashimoto, Shintaro; Ogawa, Tatsuhiko; Furuta, Takuya; Abe, Shin-ichiro; Kai, Takeshi; Matsuda, Norihiro; Okumura, Keisuke; Kai, Tetsuya; Iwase, Hiroshi; Sihver, Lembit

2017-09-01

The Particle and Heavy Ion Transport code System, PHITS, has been developed under the collaboration of several research institutes in Japan and Europe. This system can simulate the transport of most particles with energy levels up to 1 TeV (per nucleon for ion) using different nuclear reaction models and data libraries. More than 2,500 registered researchers and technicians have used this system for various applications such as accelerator design, radiation shielding and protection, medical physics, and space- and geo-sciences. This paper summarizes the physics models and functions recently implemented in PHITS, between versions 2.52 and 2.88, especially those related to source generation useful for simulating brachytherapy and internal exposures of radioisotopes.

Moment-Based Physical Models of Broadband Clutter due to Aggregations of Fish

DTIC Science & Technology

2013-09-30

statistical models for signal-processing algorithm development. These in turn will help to develop a capability to statistically forecast the impact of...aggregations of fish based on higher-order statistical measures describable in terms of physical and system parameters. Environmentally , these models...processing. In this experiment, we had good ground truth on (1) and (2), and had control over (3) and (4) except for environmentally -imposed restrictions

Mid-Frequency Sonar Interactions With Beaked Whales

DTIC Science & Technology

2009-09-30

to acquire new high-resolution morphometric and physical-property data on beaked whales for use in the model. It is hoped that the availability of such... morphometric and physical-property data on beaked whales for use in the model. It is hoped that the availability of such a system, together with high-quality... morphometric data through computerized tomography (CT) scans on marine mammal carcasses, and constructing finite-element models of the anatomy

Stochastic modelling of temperatures affecting the in situ performance of a solar-assisted heat pump: The multivariate approach and physical interpretation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loveday, D.L.; Craggs, C.

Box-Jenkins-based multivariate stochastic modeling is carried out using data recorded from a domestic heating system. The system comprises an air-source heat pump sited in the roof space of a house, solar assistance being provided by the conventional tile roof acting as a radiation absorber. Multivariate models are presented which illustrate the time-dependent relationships between three air temperatures - at external ambient, at entry to, and at exit from, the heat pump evaporator. Using a deterministic modeling approach, physical interpretations are placed on the results of the multivariate technique. It is concluded that the multivariate Box-Jenkins approach is a suitable techniquemore » for building thermal analysis. Application to multivariate Box-Jenkins approach is a suitable technique for building thermal analysis. Application to multivariate model-based control is discussed, with particular reference to building energy management systems. It is further concluded that stochastic modeling of data drawn from a short monitoring period offers a means of retrofitting an advanced model-based control system in existing buildings, which could be used to optimize energy savings. An approach to system simulation is suggested.« less

Computer Simulations for Lab Experiences in Secondary Physics

ERIC Educational Resources Information Center

Murphy, David Shannon

2012-01-01

Physical science instruction often involves modeling natural systems, such as electricity that possess particles which are invisible to the unaided eye. The effect of these particles' motion is observable, but the particles are not directly observable to humans. Simulations have been developed in physics, chemistry and biology that, under certain…

Model Error Budgets

NASA Technical Reports Server (NTRS)

Briggs, Hugh C.

2008-01-01

An error budget is a commonly used tool in design of complex aerospace systems. It represents system performance requirements in terms of allowable errors and flows these down through a hierarchical structure to lower assemblies and components. The requirements may simply be 'allocated' based upon heuristics or experience, or they may be designed through use of physics-based models. This paper presents a basis for developing an error budget for models of the system, as opposed to the system itself. The need for model error budgets arises when system models are a principle design agent as is increasingly more common for poorly testable high performance space systems.

Managing Analysis Models in the Design Process

NASA Technical Reports Server (NTRS)

Briggs, Clark

2006-01-01

Design of large, complex space systems depends on significant model-based support for exploration of the design space. Integrated models predict system performance in mission-relevant terms given design descriptions and multiple physics-based numerical models. Both the design activities and the modeling activities warrant explicit process definitions and active process management to protect the project from excessive risk. Software and systems engineering processes have been formalized and similar formal process activities are under development for design engineering and integrated modeling. JPL is establishing a modeling process to define development and application of such system-level models.

Incorporating a Full-Physics Meteorological Model into an Applied Atmospheric Dispersion Modeling System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berg, Larry K.; Allwine, K Jerry; Rutz, Frederick C.

2004-08-23

A new modeling system has been developed to provide a non-meteorologist with tools to predict air pollution transport in regions of complex terrain. This system couples the Penn State/NCAR Mesoscale Model 5 (MM5) with Earth Tech’s CALMET-CALPUFF system using a unique Graphical User Interface (GUI) developed at Pacific Northwest National Laboratory. This system is most useful in data-sparse regions, where there are limited observations to initialize the CALMET model. The user is able to define the domain of interest, provide details about the source term, and enter a surface weather observation through the GUI. The system then generates initial conditionsmore » and time constant boundary conditions for use by MM5. MM5 is run and the results are piped to CALPUFF for the dispersion calculations. Contour plots of pollutant concentration are prepared for the user. The primary advantages of the system are the streamlined application of MM5 and CALMET, limited data requirements, and the ability to run the coupled system on a desktop or laptop computer. In comparison with data collected as part of a field campaign, the new modeling system shows promise that a full-physics mesoscale model can be used in an applied modeling system to effectively simulate locally thermally-driven winds with minimal observations as input. An unexpected outcome of this research was how well CALMET represented the locally thermally-driven flows.« less

Evaluation of Cirrus Cloud Simulations using ARM Data-Development of Case Study Data Set

NASA Technical Reports Server (NTRS)

Starr, David OC.; Demoz, Belay; Wang, Yansen; Lin, Ruei-Fong; Lare, Andrew; Mace, Jay; Poellot, Michael; Sassen, Kenneth; Brown, Philip

2002-01-01

Cloud-resolving models (CRMs) are being increasingly used to develop parametric treatments of clouds and related processes for use in global climate models (GCMs). CRMs represent the integrated knowledge of the physical processes acting to determine cloud system lifecycle and are well matched to typical observational data in terms of physical parameters/measurables and scale-resolved physical processes. Thus, they are suitable for direct comparison to field observations for model validation and improvement. The goal of this project is to improve state-of-the-art CRMs used for studies of cirrus clouds and to establish a relative calibration with GCMs through comparisons among CRMs, single column model (SCM) versions of the GCMs, and observations. The objective is to compare and evaluate a variety of CRMs and SCMs, under the auspices of the GEWEX Cloud Systems Study (GCSS) Working Group on Cirrus Cloud Systems (WG2), using ARM data acquired at the Southern Great Plains (SGP) site. This poster will report on progress in developing a suitable WG2 case study data set based on the September 26, 1996 ARM IOP case - the Hurricane Nora outflow case. Progress is assessing cloud and other environmental conditions will be described. Results of preliminary simulations using a regional cloud system model (MM5) and a CRM will be discussed. Focal science questions for the model comparison are strongly based on results of the idealized GCSS WG2 cirrus cloud model comparison projects (Idealized Cirrus Cloud Model Comparison Project and Cirrus Parcel Model Comparison Project), which will also be briefly summarized.

Predicting marine physical-biogeochemical variabilities in the Gulf of Mexico and southeastern U.S. shelf sea

NASA Astrophysics Data System (ADS)

He, R.; Zong, H.; Xue, Z. G.; Fennel, K.; Tian, H.; Cai, W. J.; Lohrenz, S. E.

2017-12-01

An integrated terrestrial-ocean ecosystem modeling system is developed and used to investigate marine physical-biogeochemical variabilities in the Gulf of Mexico and southeastern US shelf sea. Such variabilities stem from variations in the shelf circulation, boundary current dynamics, impacts of climate variability, as well as growing population and associated land use practices on transport of carbon and nutrients within terrestrial systems and their delivery to the coastal ocean. We will report our efforts in evaluating the performance of the coupled modeling system via extensive model and data comparisons, as well as findings from a suite of case studies and scenario simulations. Long-term model simulation results are used to quantify regional ocean circulation dynamics, nitrogen budget and carbon fluxes. Their corresponding sub-regional differences are also characterized and contrasted.

Verification of Functional Fault Models and the Use of Resource Efficient Verification Tools

NASA Technical Reports Server (NTRS)

Bis, Rachael; Maul, William A.

2015-01-01

Functional fault models (FFMs) are a directed graph representation of the failure effect propagation paths within a system's physical architecture and are used to support development and real-time diagnostics of complex systems. Verification of these models is required to confirm that the FFMs are correctly built and accurately represent the underlying physical system. However, a manual, comprehensive verification process applied to the FFMs was found to be error prone due to the intensive and customized process necessary to verify each individual component model and to require a burdensome level of resources. To address this problem, automated verification tools have been developed and utilized to mitigate these key pitfalls. This paper discusses the verification of the FFMs and presents the tools that were developed to make the verification process more efficient and effective.

Bell's Inequality: Revolution in Quantum Physics or Just AN Inadequate Mathematical Model?

NASA Astrophysics Data System (ADS)

Khrennikov, Andrei

The main aim of this review is to stress the role of mathematical models in physics. The Bell inequality (BI) is often called the "most famous inequality of the 20th century." It is commonly accepted that its violation in corresponding experiments induced a revolution in quantum physics. Unlike "old quantum mechanics" (of Einstein, Schrodinger Bohr, Heisenberg, Pauli, Landau, Fock), "modern quantum mechanics" (of Bell, Aspect, Zeilinger, Shimony, Green-berger, Gisin, Mermin) takes seriously so called quantum non-locality. We will show that the conclusion that one has to give up the realism (i.e., a possibility to assign results of measurements to physical systems) or the locality (i.e., to assume action at a distance) is heavily based on one special mathematical model. This model was invented by A. N. Kolmogorov in 1933. One should pay serious attention to the role of mathematical models in physics. The problems of the realism and locality induced by Bell's argument can be solved by using non-Kolmogorovian probabilistic models. We compare this situation with non-Euclidean geometric models in relativity theory.

Accumulation of Domain-Specific Physical Inactivity and Presence of Hypertension in Brazilian Public Healthcare System.

PubMed

Turi, Bruna Camilo; Codogno, Jamile S; Fernandes, Romulo A; Sui, Xuemei; Lavie, Carl J; Blair, Steven N; Monteiro, Henrique Luiz

2015-11-01

Hypertension is one of the most common noncommunicable diseases worldwide, and physical inactivity is a risk factor predisposing to its occurrence and complications. However, it is still unclear the association between physical inactivity domains and hypertension, especially in public healthcare systems. Thus, this study aimed to investigate the association between physical inactivity aggregation in different domains and prevalence of hypertension among users of Brazilian public health system. 963 participants composed the sample. Subjects were divided into quartiles groups according to 3 different domains of physical activity (occupational; physical exercises; and leisure-time and transportation). Hypertension was based on physician diagnosis. Physical inactivity in occupational domain was significantly associated with higher prevalence of hypertension (OR = 1.52 [1.05 to 2.21]). The same pattern occurred for physical inactivity in leisure-time (OR = 1.63 [1.11 to 2.39]) and aggregation of physical inactivity in 3 domains (OR = 2.46 [1.14 to 5.32]). However, the multivariate-adjusted model showed significant association between hypertension and physical inactivity in 3 domains (OR = 2.57 [1.14 to 5.79]). The results suggest an unequal prevalence of hypertension according to physical inactivity across different domains and increasing the promotion of physical activity in the healthcare system is needed.

PREFACE: 2nd International Conference on Mathematical Modeling in Physical Sciences 2013 (IC-MSQUARE 2013)

NASA Astrophysics Data System (ADS)

2014-03-01

The second International Conference on Mathematical Modeling in Physical Sciences (IC-MSQUARE) took place at Prague, Czech Republic, from Sunday 1 September to Thursday 5 September 2013. The Conference was attended by more than 280 participants and hosted about 400 oral, poster, and virtual presentations while counted more than 600 pre-registered authors. The second IC-MSQUARE consisted of different and diverging workshops and thus covered various research fields where Mathematical Modeling is used, such as Theoretical/Mathematical Physics, Neutrino Physics, Non-Integrable Systems, Dynamical Systems, Computational Nanoscience, Biological Physics, Computational Biomechanics, Complex Networks, Stochastic Modeling, Fractional Statistics, DNA Dynamics, Macroeconomics. The scientific program was rather heavy since after the Keynote and Invited Talks in the morning, three parallel sessions were running every day. However, according to all attendees, the program was excellent with high level of talks and the scientific environment was fruitful, thus all attendees had a creative time. We would like to thank the Keynote Speaker and the Invited Speakers for their significant contribution to IC-MSQUARE. We also would like to thank the Members of the International Advisory and Scientific Committees as well as the Members of the Organizing Committee. Further information on the editors, speakers and committees is available in the attached pdf.

An Eight-Parameter Function for Simulating Model Rocket Engine Thrust Curves

ERIC Educational Resources Information Center

Dooling, Thomas A.

2007-01-01

The toy model rocket is used extensively as an example of a realistic physical system. Teachers from grade school to the university level use them. Many teachers and students write computer programs to investigate rocket physics since the problem involves nonlinear functions related to air resistance and mass loss. This paper describes a nonlinear…

Workshop on Computational Turbulence Modeling

NASA Technical Reports Server (NTRS)

1993-01-01

This document contains presentations given at Workshop on Computational Turbulence Modeling held 15-16 Sep. 1993. The purpose of the meeting was to discuss the current status and future development of turbulence modeling in computational fluid dynamics for aerospace propulsion systems. Papers cover the following topics: turbulence modeling activities at the Center for Modeling of Turbulence and Transition (CMOTT); heat transfer and turbomachinery flow physics; aerothermochemistry and computational methods for space systems; computational fluid dynamics and the k-epsilon turbulence model; propulsion systems; and inlet, duct, and nozzle flow.

Physics-based model for predicting the performance of a miniature wind turbine

NASA Astrophysics Data System (ADS)

Xu, F. J.; Hu, J. Z.; Qiu, Y. P.; Yuan, F. G.

2011-04-01

A comprehensive physics-based model for predicting the performance of the miniature wind turbine (MWT) for power wireless sensor systems was proposed in this paper. An approximation of the power coefficient of the turbine rotor was made after the turbine rotor performance was measured. Incorporation of the approximation with the equivalent circuit model which was proposed according to the principles of the MWT, the overall system performance of the MWT was predicted. To demonstrate the prediction, the MWT system comprised of a 7.6 cm thorgren plastic propeller as turbine rotor and a DC motor as generator was designed and its performance was tested experimentally. The predicted output voltage, power and system efficiency are matched well with the tested results, which imply that this study holds promise in estimating and optimizing the performance of the MWT.

From Process Models to Decision Making: The Use of Data Mining Techniques for Developing Effect Decision Support Systems

NASA Astrophysics Data System (ADS)

Conrads, P. A.; Roehl, E. A.

2010-12-01

Natural-resource managers face the difficult problem of controlling the interactions between hydrologic and man-made systems in ways that preserve resources while optimally meeting the needs of disparate stakeholders. Finding success depends on obtaining and employing detailed scientific knowledge about the cause-effect relations that govern the physics of these hydrologic systems. This knowledge is most credible when derived from large field-based datasets that encompass the wide range of variability in the parameters of interest. The means of converting data into knowledge of the hydrologic system often involves developing computer models that predict the consequences of alternative management practices to guide resource managers towards the best path forward. Complex hydrologic systems are typically modeled using computer programs that implement traditional, generalized, physical equations, which are calibrated to match the field data as closely as possible. This type of model commonly is limited in terms of demonstrable predictive accuracy, development time, and cost. The science of data mining presents a powerful complement to physics-based models. Data mining is a relatively new science that assists in converting large databases into knowledge and is uniquely able to leverage the real-time, multivariate data now being collected for hydrologic systems. In side-by-side comparisons with state-of-the-art physics-based hydrologic models, the authors have found data-mining solutions have been substantially more accurate, less time consuming to develop, and embeddable into spreadsheets and sophisticated decision support systems (DSS), making them easy to use by regulators and stakeholders. Three data-mining applications will be presented that demonstrate how data-mining techniques can be applied to existing environmental databases to address regional concerns of long-term consequences. In each case, data were transformed into information, and ultimately, into knowledge. In each case, DSSs were developed that facilitated the use of simulation models and analysis of model output to a broad range of end users with various technical abilities. When compared to other modeling projects of comparable scope and complexity, these DSSs were able to pass through needed technical reviews much more quickly. Unlike programs such as finite-element flow models, DSSs are by design open systems that are easy to use and readily disseminated directly to decision makers. The DSSs provide direct coupling of predictive models with the real-time databases that drive them, graphical user interfaces for point-and-click program control, and streaming displays of numerical and graphical results so that users can monitor the progress of long-term simulations. Customizations for specific problems include numerical optimization loops that invert predictive models; integrations with a three-dimensional finite-element flow model, GIS packages, and a plant ecology model; and color contouring of simulation output data.

Channelling information flows from observation to decision; or how to increase certainty

NASA Astrophysics Data System (ADS)

Weijs, S. V.

2015-12-01

To make adequate decisions in an uncertain world, information needs to reach the decision problem, to enable overseeing the full consequences of each possible decision.On its way from the physical world to a decision problem, information is transferred through the physical processes that influence the sensor, then through processes that happen in the sensor, through wires or electromagnetic waves. For the last decade, most information becomes digitized at some point. From moment of digitization, information can in principle be transferred losslessly. Information about the physical world is often also stored, sometimes in compressed form, such as physical laws, concepts, or models of specific hydrological systems. It is important to note, however, that all information about a physical system eventually has to originate from observation (although inevitably coloured by some prior assumptions). This colouring makes the compression lossy, but is effectively the only way to make use of similarities in time and space that enable predictions while measuring only a a few macro-states of a complex hydrological system.Adding physical process knowledge to a hydrological model can thus be seen as a convenient way to transfer information from observations from a different time or place, to make predictions about another situation, assuming the same dynamics are at work.The key challenge to achieve more certainty in hydrological prediction can therefore be formulated as a challenge to tap and channel information flows from the environment. For tapping more information flows, new measurement techniques, large scale campaigns, historical data sets, and large sample hydrology and regionalization efforts can bring progress. For channelling the information flows with minimum loss, model calibration, and model formulation techniques should be critically investigated. Some experience from research in a Swiss high alpine catchment are used as an illustration.

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Dali; Yuan, Fengming; Hernandez, Benjamin

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

DOE PAGES

Wang, Dali; Yuan, Fengming; Hernandez, Benjamin; ...

2017-01-01

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less

Event-driven simulation in SELMON: An overview of EDSE

NASA Technical Reports Server (NTRS)

Rouquette, Nicolas F.; Chien, Steve A.; Charest, Leonard, Jr.

1992-01-01

EDSE (event-driven simulation engine), a model-based event-driven simulator implemented for SELMON, a tool for sensor selection and anomaly detection in real-time monitoring is described. The simulator is used in conjunction with a causal model to predict future behavior of the model from observed data. The behavior of the causal model is interpreted as equivalent to the behavior of the physical system being modeled. An overview of the functionality of the simulator and the model-based event-driven simulation paradigm on which it is based is provided. Included are high-level descriptions of the following key properties: event consumption and event creation, iterative simulation, synchronization and filtering of monitoring data from the physical system. Finally, how EDSE stands with respect to the relevant open issues of discrete-event and model-based simulation is discussed.

Charge frustration in complex fluids and in electronic systems

NASA Astrophysics Data System (ADS)

Carraro, Carlo

1997-02-01

The idea of charge frustration is applied to describe the properties of such diverse physical systems as oil-water-surfactant mixtures and metal-ammonia solutions. The minimalist charge-frustrated model possesses one energy scale and two length scales. For oil-water-surfactant mixtures, these parameters have been determined starting from the microscopic properties of the physical systems under study. Thus, microscopic properties are successfully related to the observed mesoscopic structure.

Model-Based Prognostics of Hybrid Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil; Bregon, Anibal

2015-01-01

Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

Development of a Hands-On Survey Course in the Physics of Living Systems

NASA Astrophysics Data System (ADS)

Matthews, Megan; Goldman, Daniel I.

Due to the widespread availability and technological capabilities of modern smartphones, many biophysical systems can be investigated using easily accessible, low-cost, and/or ``homemade'' equipment. Our survey course is structured to provide students with an overview of research in the physics of living systems, emphasizing the interplay between measurement, mechanism, and modeling required to understand principles at the intersection of physics and biology. The course proceeds through seven modules each consisting of one week of lectures and one week of hands-on experiments, called ``microlabs''. Using smartphones, Arduinos, and 3D printed materials students create their own laboratory equipment, including a 150X van Leeuwenhoek microscope, a shaking incubator, and an oscilloscope, and then use them to study biological systems ranging in length scales from nanometers to meters. These systems include population dynamics of rotifer/algae cultures, experimental evolution of multicellularity in budding yeast, and the bio- & neuromechanics involved in animal locomotion, among others. In each module, students are introduced to fundamental biological and physical concepts as well as theoretical and computational tools (nonlinear dynamics, molecular dynamics simulation, and statistical mechanics). At the end of the course, students apply these concepts and tools to the creation of their own microlab that integrates hands-on experimentation and modeling in the study of their chosen biophysical system.

Integrating machine learning to achieve an automatic parameter prediction for practical continuous-variable quantum key distribution

NASA Astrophysics Data System (ADS)

Liu, Weiqi; Huang, Peng; Peng, Jinye; Fan, Jianping; Zeng, Guihua

2018-02-01

For supporting practical quantum key distribution (QKD), it is critical to stabilize the physical parameters of signals, e.g., the intensity, phase, and polarization of the laser signals, so that such QKD systems can achieve better performance and practical security. In this paper, an approach is developed by integrating a support vector regression (SVR) model to optimize the performance and practical security of the QKD system. First, a SVR model is learned to precisely predict the time-along evolutions of the physical parameters of signals. Second, such predicted time-along evolutions are employed as feedback to control the QKD system for achieving the optimal performance and practical security. Finally, our proposed approach is exemplified by using the intensity evolution of laser light and a local oscillator pulse in the Gaussian modulated coherent state QKD system. Our experimental results have demonstrated three significant benefits of our SVR-based approach: (1) it can allow the QKD system to achieve optimal performance and practical security, (2) it does not require any additional resources and any real-time monitoring module to support automatic prediction of the time-along evolutions of the physical parameters of signals, and (3) it is applicable to any measurable physical parameter of signals in the practical QKD system.

Space weather forecasting with a Multimodel Ensemble Prediction System (MEPS)

NASA Astrophysics Data System (ADS)

Schunk, R. W.; Scherliess, L.; Eccles, V.; Gardner, L. C.; Sojka, J. J.; Zhu, L.; Pi, X.; Mannucci, A. J.; Butala, M.; Wilson, B. D.; Komjathy, A.; Wang, C.; Rosen, G.

2016-07-01

The goal of the Multimodel Ensemble Prediction System (MEPS) program is to improve space weather specification and forecasting with ensemble modeling. Space weather can have detrimental effects on a variety of civilian and military systems and operations, and many of the applications pertain to the ionosphere and upper atmosphere. Space weather can affect over-the-horizon radars, HF communications, surveying and navigation systems, surveillance, spacecraft charging, power grids, pipelines, and the Federal Aviation Administration (FAA's) Wide Area Augmentation System (WAAS). Because of its importance, numerous space weather forecasting approaches are being pursued, including those involving empirical, physics-based, and data assimilation models. Clearly, if there are sufficient data, the data assimilation modeling approach is expected to be the most reliable, but different data assimilation models can produce different results. Therefore, like the meteorology community, we created a Multimodel Ensemble Prediction System (MEPS) for the Ionosphere-Thermosphere-Electrodynamics (ITE) system that is based on different data assimilation models. The MEPS ensemble is composed of seven physics-based data assimilation models for the ionosphere, ionosphere-plasmasphere, thermosphere, high-latitude ionosphere-electrodynamics, and middle to low latitude ionosphere-electrodynamics. Hence, multiple data assimilation models can be used to describe each region. A selected storm event that was reconstructed with four different data assimilation models covering the middle and low latitude ionosphere is presented and discussed. In addition, the effect of different data types on the reconstructions is shown.

Three tenets for secure cyber-physical system design and assessment

NASA Astrophysics Data System (ADS)

Hughes, Jeff; Cybenko, George

2014-06-01

This paper presents a threat-driven quantitative mathematical framework for secure cyber-physical system design and assessment. Called The Three Tenets, this originally empirical approach has been used by the US Air Force Research Laboratory (AFRL) for secure system research and development. The Tenets were first documented in 2005 as a teachable methodology. The Tenets are motivated by a system threat model that itself consists of three elements which must exist for successful attacks to occur: - system susceptibility; - threat accessibility and; - threat capability. The Three Tenets arise naturally by countering each threat element individually. Specifically, the tenets are: Tenet 1: Focus on What's Critical - systems should include only essential functions (to reduce susceptibility); Tenet 2: Move Key Assets Out-of-Band - make mission essential elements and security controls difficult for attackers to reach logically and physically (to reduce accessibility); Tenet 3: Detect, React, Adapt - confound the attacker by implementing sensing system elements with dynamic response technologies (to counteract the attackers' capabilities). As a design methodology, the Tenets mitigate reverse engineering and subsequent attacks on complex systems. Quantified by a Bayesian analysis and further justified by analytic properties of attack graph models, the Tenets suggest concrete cyber security metrics for system assessment.

Strategic preparedness for recovery from catastrophic risks to communities and infrastructure systems of systems.

PubMed

Haimes, Yacov Y

2012-11-01

Natural and human-induced disasters affect organizations in myriad ways because of the inherent interconnectedness and interdependencies among human, cyber, and physical infrastructures, but more importantly, because organizations depend on the effectiveness of people and on the leadership they provide to the organizations they serve and represent. These human-organizational-cyber-physical infrastructure entities are termed systems of systems. Given the multiple perspectives that characterize them, they cannot be modeled effectively with a single model. The focus of this article is: (i) the centrality of the states of a system in modeling; (ii) the efficacious role of shared states in modeling systems of systems, in identification, and in the meta-modeling of systems of systems; and (iii) the contributions of the above to strategic preparedness, response to, and recovery from catastrophic risk to such systems. Strategic preparedness connotes a decision-making process and its associated actions. These must be: implemented in advance of a natural or human-induced disaster, aimed at reducing consequences (e.g., recovery time, community suffering, and cost), and/or controlling their likelihood to a level considered acceptable (through the decisionmakers' implicit and explicit acceptance of various risks and tradeoffs). The inoperability input-output model (IIM), which is grounded on Leontief's input/output model, has enabled the modeling of interdependent subsystems. Two separate modeling structures are introduced. These are: phantom system models (PSM), where shared states constitute the essence of modeling coupled systems; and the IIM, where interdependencies among sectors of the economy are manifested by the Leontief matrix of technological coefficients. This article demonstrates the potential contributions of these two models to each other, and thus to more informative modeling of systems of systems schema. The contributions of shared states to this modeling and to systems identification are presented with case studies. © 2012 Society for Risk Analysis.

An Age of Change

ERIC Educational Resources Information Center

Koch, H. William

1970-01-01

Suggests that physics is undergoing important social changes. Its definition, education, information transfer, and research and development are all being modified. A systems model is proposed that applies to education, research, and information activities in physics. Bibliography. (LC)

Report of the theory panel. [space physics

NASA Technical Reports Server (NTRS)

Ashourabdalla, Maha; Rosner, Robert; Antiochos, Spiro; Curtis, Steven; Fejer, B.; Goertz, Christoph K.; Goldstein, Melvyn L.; Holzer, Thomas E.; Jokipii, J. R.; Lee, Lou-Chuang

1991-01-01

The ultimate goal of this research is to develop an understanding which is sufficiently comprehensive to allow realistic predictions of the behavior of the physical systems. Theory has a central role to play in the quest for this understanding. The level of theoretical description is dependent on three constraints: (1) the available computer hardware may limit both the number and the size of physical processes the model system can describe; (2) the fact that some natural systems may only be described in a statistical manner; and (3) the fact that some natural systems may be observable only through remote sensing which is intrinsically limited by spatial resolution and line of sight integration. From this the report discusses present accomplishments and future goals of theoretical space physics. Finally, the development and use of new supercomputer is examined.

Understanding of Relation Structures of Graphical Models by Lower Secondary Students

ERIC Educational Resources Information Center

van Buuren, Onne; Heck, André; Ellermeijer, Ton

2016-01-01

A learning path has been developed on system dynamical graphical modelling, integrated into the Dutch lower secondary physics curriculum. As part of the developmental research for this learning path, students' understanding of the relation structures shown in the diagrams of graphical system dynamics based models has been investigated. One of our…

Establishing the Common Community Physics Package by Transitioning the GFS Physics to a Collaborative Software Framework

NASA Astrophysics Data System (ADS)

Xue, L.; Firl, G.; Zhang, M.; Jimenez, P. A.; Gill, D.; Carson, L.; Bernardet, L.; Brown, T.; Dudhia, J.; Nance, L. B.; Stark, D. R.

2017-12-01

The Global Model Test Bed (GMTB) has been established to support the evolution of atmospheric physical parameterizations in NCEP global modeling applications. To accelerate the transition to the Next Generation Global Prediction System (NGGPS), a collaborative model development framework known as the Common Community Physics Package (CCPP) is created within the GMTB to facilitate engagement from the broad community on physics experimentation and development. A key component to this Research to Operation (R2O) software framework is the Interoperable Physics Driver (IPD) that hooks the physics parameterizations from one end to the dynamical cores on the other end with minimum implementation effort. To initiate the CCPP, scientists and engineers from the GMTB separated and refactored the GFS physics. This exercise demonstrated the process of creating IPD-compliant code and can serve as an example for other physics schemes to do the same and be considered for inclusion into the CCPP. Further benefits to this process include run-time physics suite configuration and considerably reduced effort for testing modifications to physics suites through GMTB's physics test harness. The implementation will be described and the preliminary results will be presented at the conference.

Upper Rio Grande water operations model: A tool for enhanced system management

Treesearch

Gail Stockton; D. Michael Roark

1999-01-01

The Upper Rio Grande Water Operations Model (URGWOM) under development through a multi-agency effort has demonstrated capability to represent the physical river/reservoir system, to track and account for Rio Grande flows and imported San Juan flows, and to forecast flows at various points in the system. Testing of the Rio Chama portion of the water operations model was...

Modeling the Evolution of the System IV Period of the Io Torus

NASA Astrophysics Data System (ADS)

Coffin, D. A.; Delamere, P. A.

2017-12-01

The response of the Io plasma torus to superthermal electron modulation and volcanic eruptions is studied using a physical chemistry and radial/azimuthal transport model (Copper et al., 2016). The model includes radial and azimuthal transport, latitudinally-averaged physical chemistry, and prescribed System III superthermal electron modulation following Steffl et al., [2008]. Volcanic eruptions are modelled as a temporal Gaussian enhancement (e.g., 2x) of the neutral source rate and hot electron fraction (e.g., <1%). However, we adopt an alternative approach for the Steffl et al., [2008] System IV electron modulation. Radially-dependent subcorotation is prescribed, consistent with observations [Brown, 1994; Thomas et al., 2001], as well as a hot electron modulation proportional to the radial flux tube content gradient. Coupling hot electron modulation to radial transport and subcorotation, we seek to analyze magnetosphere-ionosphere coupling. We find that the model produces a radially-independent periodicity and that eruptions can alter the modeled period, consistent with multi-epoch observations of a variable System IV. This periodicity remains consistent with the prescribed subcorotation period at L = 6.3.

Modeling an integrative physical examination program for the Departments of Defense and Veterans Affairs.

PubMed

Goodrich, Scott G

2006-10-01

Current policies governing the Departments of Defense and Veterans Affairs physical examination programs are out of step with current evidence-based medical practice. Replacing periodic and other routine physical examination types with annual preventive health assessments would afford our service members additional health benefit at reduced cost. Additionally, the Departments of Defense and Veterans Affairs repeat the physical examination process at separation and have been unable to reconcile their respective disability evaluation systems to reduce duplication and waste. A clear, coherent, and coordinated strategy to improve the relevance and utility of our physical examination programs is long overdue. This article discusses existing physical examination programs and proposes a model for a new integrative physical examination program based on need, science, and common sense.

How to Make Our Models More Physically-based

NASA Astrophysics Data System (ADS)

Savenije, H. H. G.

2016-12-01

Models that are generally called "physically-based" unfortunately only have a partial view of the physical processes at play in hydrology. Although the coupled partial differential equations in these models reflect the water balance equations and the flow descriptors at laboratory scale, they miss essential characteristics of what determines the functioning of catchments. The most important active agent in catchments is the ecosystem (and sometimes people). What these agents do is manipulate the substrate in a way that it supports the essential functions of survival and productivity: infiltration of water, retention of moisture, mobilization and retention of nutrients, and drainage. Ecosystems do this in the most efficient way, in agreement with the landscape, and in response to climatic drivers. In brief, our hydrological system is alive and has a strong capacity to adjust to prevailing and changing circumstances. Although most physically based models take Newtonian theory at heart, as best they can, what they generally miss is Darwinian thinking on how an ecosystem evolves and adjusts its environment to maintain crucial hydrological functions. If this active agent is not reflected in our models, then they miss essential physics. Through a Darwinian approach, we can determine the root zone storage capacity of ecosystems, as a crucial component of hydrological models, determining the partitioning of fluxes and the conservation of moisture to bridge periods of drought. Another crucial element of physical systems is the evolution of drainage patterns, both on and below the surface. On the surface, such patterns facilitate infiltration or surface drainage with minimal erosion; in the unsaturated zone, patterns facilitate efficient replenishment of moisture deficits and preferential drainage when there is excess moisture; in the groundwater, patterns facilitate the efficient and gradual drainage of groundwater, resulting in linear reservoir recession. Models that do not incorporate these patterns are not physical. The parameters in the equations may be adjusted to compensate for the lake of patterns, but this involves scale-dependent calibration. In contrast to what is widely believed, relatively simple conceptual models can accommodate these physical processes accurately and very efficiently.

Linking Physical Climate Research and Economic Assessments of Mitigation Policies

NASA Astrophysics Data System (ADS)

Stainforth, David; Calel, Raphael

2017-04-01

Evaluating climate change policies requires economic assessments which balance the costs and benefits of climate action. A certain class of Integrated Assessment Models (IAMS) are widely used for this type of analysis; DICE, PAGE and FUND are three of the most influential. In the economics community there has been much discussion and debate about the economic assumptions implemented within these models. Two aspects in particular have gained much attention: i) the costs of damages resulting from climate change - the so-called damage function, and ii) the choice of discount rate applied to future costs and benefits. There has, however, been rather little attention given to the consequences of the choices made in the physical climate models within these IAMS. Here we discuss the practical aspects of the implementation of the physical models in these IAMS, as well as the implications of choices made in these physical science components for economic assessments[1]. We present a simple breakdown of how these IAMS differently represent the climate system as a consequence of differing underlying physical models, different parametric assumptions (for parameters representing, for instance, feedbacks and ocean heat uptake) and different numerical approaches to solving the models. We present the physical and economic consequences of these differences and reflect on how we might better incorporate the latest physical science understanding in economic models of this type. [1] Calel, R. and Stainforth D.A., "On the Physics of Three Integrated Assessment Models", Bulletin of the American Meteorological Society, in press.

Simulating Fire Disturbance and Plant Mortality Using Antecedent Eco-hydrological Conditions to Inform a Physically Based Combustion Model

NASA Astrophysics Data System (ADS)

Atchley, A. L.; Linn, R.; Middleton, R. S.; Runde, I.; Coon, E.; Michaletz, S. T.

2016-12-01

Wildfire is a complex agent of change that both affects and depends on eco-hydrological systems, thereby constituting a tightly linked system of disturbances and eco-hydrological conditions. For example, structure, build-up, and moisture content of fuel are dependent on eco-hydrological regimes, which impacts fire spread and intensity. Fire behavior, on the other hand, determines the severity and extent of eco-hydrological disturbance, often resulting in a mosaic of untouched, stressed, damaged, or completely destroyed vegetation within the fire perimeter. This in turn drives new eco-hydrological system behavior. The cycles of disturbance and recovery present a complex evolving system with many unknowns especially in the face of climate change that has implications for fire risk, water supply, and forest composition. Physically-based numerical experiments that attempt to capture the complex linkages between eco-hydrological regimes that affect fire behavior and the echo-hydrological response from those fire disturbances help build the understanding required to project how fire disturbance and eco-hydrological conditions coevolve over time. Here we explore the use of FIRETEC—a physically-based 3D combustion model that solves conservation of mass, momentum, energy, and chemical species—to resolve fire spread over complex terrain and fuel structures. Uniquely, we couple a physically-based plant mortality model with FIRETEC and examine the resultant hydrologic impact. In this proof of concept demonstration we spatially distribute fuel structure and moisture content based on the eco-hydrological condition to use as input for FIRETEC. The fire behavior simulation then produces localized burn severity and heat injures which are used as input to a spatially-informed plant mortality model. Ultimately we demonstrate the applicability of physically-based models to explore integrated disturbance and eco-hydrologic response to wildfire behavior and specifically map how fire spread and intensity is affect by the antecedent eco-hydrological condition, which then affects the resulting tree mortality patterns.

A Hierarchical Security Architecture for Cyber-Physical Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quanyan Zhu; Tamer Basar

2011-08-01

Security of control systems is becoming a pivotal concern in critical national infrastructures such as the power grid and nuclear plants. In this paper, we adopt a hierarchical viewpoint to these security issues, addressing security concerns at each level and emphasizing a holistic cross-layer philosophy for developing security solutions. We propose a bottom-up framework that establishes a model from the physical and control levels to the supervisory level, incorporating concerns from network and communication levels. We show that the game-theoretical approach can yield cross-layer security strategy solutions to the cyber-physical systems.

Integrated Multimedia Modeling System Response to Regional Land Management Change

EPA Science Inventory

A multi-media system of nitrogen and co-pollutant models describing critical physical and chemical processes that cascade synergistically and competitively through the environment, the economy and society has been developed at the USEPA Office of research and development. It is ...

DEVELOPMENT OF A RATIONALLY BASED DESIGN PROTOCOL FOR THE ULTRAVIOLET LIGHT DISINFECTION PROCESS

EPA Science Inventory

A protocol is demonstrated for the design and evaluation of ultraviolet (UV) disinfection systems based on a mathematical model. The disinfection model incorporates the system's physical dimensions, the residence time distribution of the reactor and dispersion characteristics, th...

Cyber threat impact assessment and analysis for space vehicle architectures

NASA Astrophysics Data System (ADS)

McGraw, Robert M.; Fowler, Mark J.; Umphress, David; MacDonald, Richard A.

2014-06-01

This paper covers research into an assessment of potential impacts and techniques to detect and mitigate cyber attacks that affect the networks and control systems of space vehicles. Such systems, if subverted by malicious insiders, external hackers and/or supply chain threats, can be controlled in a manner to cause physical damage to the space platforms. Similar attacks on Earth-borne cyber physical systems include the Shamoon, Duqu, Flame and Stuxnet exploits. These have been used to bring down foreign power generation and refining systems. This paper discusses the potential impacts of similar cyber attacks on space-based platforms through the use of simulation models, including custom models developed in Python using SimPy and commercial SATCOM analysis tools, as an example STK/SOLIS. The paper discusses the architecture and fidelity of the simulation model that has been developed for performing the impact assessment. The paper walks through the application of an attack vector at the subsystem level and how it affects the control and orientation of the space vehicle. SimPy is used to model and extract raw impact data at the bus level, while STK/SOLIS is used to extract raw impact data at the subsystem level and to visually display the effect on the physical plant of the space vehicle.

Psychosocial work environment and health in U.S. metropolitan areas: a test of the demand-control and demand-control-support models.

PubMed

Muntaner, C; Schoenbach, C

1994-01-01

The authors use confirmatory factor analysis to investigate the psychosocial dimensions of work environments relevant to health outcomes, in a representative sample of five U.S. metropolitan areas. Through an aggregated inference system, scales from Schwartz and associates' job scoring system and from the Dictionary of Occupational Titles (DOT) were employed to examine two alternative models: the demand-control model of Karasek and Theorell and Johnson's demand-control-support model. Confirmatory factor analysis was used to test the two models. The two multidimensional models yielded better fits than an unstructured model. After allowing for the measurement error variance due to the method of assessment (Schwartz and associates' system or DOT), both models yielded acceptable goodness-of-fit indices, but the fit of the demand-control-support model was significantly better. Overall these results indicate that the dimensions of Control (substantive complexity of work, skill discretion, decision authority), Demands (physical exertion, physical demands and hazards), and Social Support (coworker and supervisor social supports) provide an acceptable account of the psychosocial dimensions of work associated with health outcomes.

Multi-Physics Modelling of Fault Mechanics Using REDBACK: A Parallel Open-Source Simulator for Tightly Coupled Problems

NASA Astrophysics Data System (ADS)

Poulet, Thomas; Paesold, Martin; Veveakis, Manolis

2017-03-01

Faults play a major role in many economically and environmentally important geological systems, ranging from impermeable seals in petroleum reservoirs to fluid pathways in ore-forming hydrothermal systems. Their behavior is therefore widely studied and fault mechanics is particularly focused on the mechanisms explaining their transient evolution. Single faults can change in time from seals to open channels as they become seismically active and various models have recently been presented to explain the driving forces responsible for such transitions. A model of particular interest is the multi-physics oscillator of Alevizos et al. (J Geophys Res Solid Earth 119(6), 4558-4582, 2014) which extends the traditional rate and state friction approach to rate and temperature-dependent ductile rocks, and has been successfully applied to explain spatial features of exposed thrusts as well as temporal evolutions of current subduction zones. In this contribution we implement that model in REDBACK, a parallel open-source multi-physics simulator developed to solve such geological instabilities in three dimensions. The resolution of the underlying system of equations in a tightly coupled manner allows REDBACK to capture appropriately the various theoretical regimes of the system, including the periodic and non-periodic instabilities. REDBACK can then be used to simulate the drastic permeability evolution in time of such systems, where nominally impermeable faults can sporadically become fluid pathways, with permeability increases of several orders of magnitude.

A closed-loop hybrid physiological model relating to subjects under physical stress.

PubMed

El-Samahy, Emad; Mahfouf, Mahdi; Linkens, Derek A

2006-11-01

The objective of this research study is to derive a comprehensive physiological model relating to subjects under physical stress conditions. The model should describe the behaviour of the cardiovascular system, respiratory system, thermoregulation and brain activity in response to physical workload. An experimental testing rig was built which consists of recumbent high performance bicycle for inducing the physical load and a data acquisition system comprising monitors and PCs. The signals acquired and used within this study are the blood pressure, heart rate, respiration, body temperature, and EEG signals. The proposed model is based on a grey-box based modelling approach which was used because of the sufficient level of details it provides. Cardiovascular and EEG Data relating to 16 healthy subject volunteers (data from 12 subjects were used for training/validation and the data from 4 subjects were used for model testing) were collected using the Finapres and the ProComp+ monitors. For model validation, residual analysis via the computing of the confidence intervals as well as related histograms was performed. Closed-loop simulations for different subjects showed that the model can provide reliable predictions for heart rate, blood pressure, body temperature, respiration, and the EEG signals. These findings were also reinforced by the residual analyses data obtained, which suggested that the residuals were within the 90% confidence bands and that the corresponding histograms were of a normal distribution. A higher intelligent level was added to the model, based on neural networks, to extend the capabilities of the model to predict over a wide range of subjects dynamics. The elicited physiological model describing the effect of physiological stress on several physiological variables can be used to predict performance breakdown of operators in critical environments. Such a model architecture lends itself naturally to exploitation via feedback control in a 'reverse-engineering' fashion to control stress via the specification of a safe operating range for the psycho-physiological variables.

Modeling socio-cultural processes in network-centric environments

NASA Astrophysics Data System (ADS)

Santos, Eunice E.; Santos, Eugene, Jr.; Korah, John; George, Riya; Gu, Qi; Kim, Keumjoo; Li, Deqing; Russell, Jacob; Subramanian, Suresh

2012-05-01

The major focus in the field of modeling & simulation for network centric environments has been on the physical layer while making simplifications for the human-in-the-loop. However, the human element has a big impact on the capabilities of network centric systems. Taking into account the socio-behavioral aspects of processes such as team building, group decision-making, etc. are critical to realistically modeling and analyzing system performance. Modeling socio-cultural processes is a challenge because of the complexity of the networks, dynamism in the physical and social layers, feedback loops and uncertainty in the modeling data. We propose an overarching framework to represent, model and analyze various socio-cultural processes within network centric environments. The key innovation in our methodology is to simultaneously model the dynamism in both the physical and social layers while providing functional mappings between them. We represent socio-cultural information such as friendships, professional relationships and temperament by leveraging the Culturally Infused Social Network (CISN) framework. The notion of intent is used to relate the underlying socio-cultural factors to observed behavior. We will model intent using Bayesian Knowledge Bases (BKBs), a probabilistic reasoning network, which can represent incomplete and uncertain socio-cultural information. We will leverage previous work on a network performance modeling framework called Network-Centric Operations Performance and Prediction (N-COPP) to incorporate dynamism in various aspects of the physical layer such as node mobility, transmission parameters, etc. We validate our framework by simulating a suitable scenario, incorporating relevant factors and providing analyses of the results.

Probability of the Physical Association of 104 Blended Companions to Kepler Objects of Interest Using Visible and Near-infrared Adaptive Optics Photometry

NASA Astrophysics Data System (ADS)

Atkinson, Dani; Baranec, Christoph; Ziegler, Carl; Law, Nicholas; Riddle, Reed; Morton, Tim

2017-01-01

We determine probabilities of physical association for stars in blended Kepler Objects of Interest (KOIs), and find that 14.5{ % }-3.4 % +3.8 % of companions within ˜4″ are consistent with being physically unassociated with their primary. This produces a better understanding of potential false positives in the Kepler catalog and will guide models of planet formation in binary systems. Physical association is determined through two methods of calculating multi-band photometric parallax using visible and near-infrared adaptive optics observations of 84 KOI systems with 104 contaminating companions within ˜4″. We find no evidence that KOI companions with separations of less than 1″ are more likely to be physically associated than KOI companions generally. We also reinterpret transit depths for 94 planet candidates, and calculate that 2.6% ± 0.4% of transits have R> 15{R}\\oplus , which is consistent with prior modeling work.

Hydrological modelling in forested systems | Science ...

EPA Pesticide Factsheets

This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological processes. The focus of this chapter is on process-based models and approaches, specifically 'forest hydrology models'; that is, physically based simulation tools that quantify compartments of the forest hydrological cycle. Physically based models can be considered those that describe the conservation of mass, momentum and/or energy. The purpose of this chapter is to provide a brief overview of forest hydrology modeling approaches for answering important global research and management questions. The focus of this chapter is on process-based models and approaches, specifically “forest hydrology models”, i.e., physically-based simulation tools that quantify compartments of the forest hydrological cycle.

GFDL's ESM2 global coupled climate-carbon Earth System Models. Part I: physical formulation and baseline simulation characteristics

USGS Publications Warehouse

Dunne, John P.; John, Jasmin G.; Adcroft, Alistair J.; Griffies, Stephen M.; Hallberg, Robert W.; Shevalikova, Elena; Stouffer, Ronald J.; Cooke, William; Dunne, Krista A.; Harrison, Matthew J.; Krasting, John P.; Malyshev, Sergey L.; Milly, P.C.D.; Phillipps, Peter J.; Sentman, Lori A.; Samuels, Bonita L.; Spelman, Michael J.; Winton, Michael; Wittenberg, Andrew T.; Zadeh, Niki

2012-01-01

We describe the physical climate formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory's previous CM2.1 climate model while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in the El Niño-Southern Oscillation being overly strong in ESM2M and overly weak ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to: total heat content variability given its lack of long term drift, gyre circulation and ventilation in the North Pacific, tropical Atlantic and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to: surface circulation given its superior surface temperature, salinity and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. Our overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords us the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon-climate models.

Design and Impacts of Land-Biogenic-Atmosphere Coupling in the NASA-Unified WRF (NU-WRF) Modeling System

NASA Technical Reports Server (NTRS)

Tan, Qian; Santanello, Joseph A., Jr.; Zhou, Shujia; Tao, Zhining; Peters-Lidard, Christa d.; Chn, Mian

2011-01-01

Land-Atmosphere coupling is typically designed and implemented independently for physical (e.g. water and energy) and chemical (e.g. biogenic emissions and surface depositions)-based models and applications. Differences in scale, data requirements, and physics thus limit the ability of Earth System models to be fully coupled in a consistent manner. In order for the physical-chemical-biological coupling to be complete, treatment of the land in terms of surface classification, condition, fluxes, and emissions must be considered simultaneously and coherently across all components. In this study, we investigate a coupling strategy for the NASA-Unified Weather Research and Forecasting (NU-WRF) model that incorporates the traditionally disparate fluxes of water and energy through NASA's LIS (Land Information System) and biogenic emissions through BEIS (Biogenic Emissions Inventory System) and MEGAN (Model of Emissions of Gases and Aerosols from Nature) into the atmosphere. In doing so, inconsistencies across model inputs and parameter data are resolved such that the emissions from a particular plant species are consistent with the heat and moisture fluxes calculated for that land cover type. In turn, the response of the atmospheric turbulence and mixing in the planetary boundary layer (PBL) acts on the identical surface type, fluxes, and emissions for each. In addition, the coupling of dust emission within the NU-WRF system is performed in order to ensure consistency and to maximize the benefit of high-resolution land representation in LIS. The impacts of those self-consistent components on' the simulation of atmospheric aerosols are then evaluated through the WRF-Chem-GOCART (Goddard Chemistry Aerosol Radiation and Transport) model. Overall, this ambitious project highlights the current difficulties and future potential of fully coupled. components. in Earth System models, and underscores the importance of the iLEAPS community in supporting improved knowledge of processes and innovative approaches for models and observations.

ENGINEERED BARRIER SYSTEM: PHYSICAL AND CHEMICAL ENVIRONMENT

DOE Office of Scientific and Technical Information (OSTI.GOV)

R. Jarek

2005-08-29

The purpose of this model report is to describe the evolution of the physical and chemical environmental conditions within the waste emplacement drifts of the repository, including the drip shield and waste package surfaces. The resulting seepage evaporation and gas abstraction models are used in the total system performance assessment for the license application (TSPA-LA) to assess the performance of the engineered barrier system and the waste form. This report develops and documents a set of abstraction-level models that describe the engineered barrier system physical and chemical environment. Where possible, these models use information directly from other reports as input,more » which promotes integration among process models used for TSPA-LA. Specific tasks and activities of modeling the physical and chemical environment are included in ''Technical Work Plan for: Near-Field Environment and Transport In-Drift Geochemistry Model Report Integration'' (BSC 2005 [DIRS 173782], Section 1.2.2). As described in the technical work plan, the development of this report is coordinated with the development of other engineered barrier system reports. To be consistent with other project documents that address features, events, and processes (FEPs), Table 6.14.1 of the current report includes updates to FEP numbers and FEP subjects for two FEPs identified in the technical work plan (TWP) governing this report (BSC 2005 [DIRS 173782]). FEP 2.1.09.06.0A (Reduction-oxidation potential in EBS), as listed in Table 2 of the TWP (BSC 2005 [DIRS 173782]), has been updated in the current report to FEP 2.1.09.06.0B (Reduction-oxidation potential in Drifts; see Table 6.14-1). FEP 2.1.09.07.0A (Reaction kinetics in EBS), as listed in Table 2 of the TWP (BSC 2005 [DIRS 173782]), has been updated in the current report to FEP 2.1.09.07.0B (Reaction kinetics in Drifts; see Table 6.14-1). These deviations from the TWP are justified because they improve integration with FEPs documents. The updates have no impact on the model developed in this report.« less

Tidal Simulations of an Incised-Valley Fluvial System with a Physics-Based Geologic Model

NASA Astrophysics Data System (ADS)

Ghayour, K.; Sun, T.

2012-12-01

Physics-based geologic modeling approaches use fluid flow in conjunction with sediment transport and deposition models to devise evolutionary geologic models that focus on underlying physical processes and attempt to resolve them at pertinent spatial and temporal scales. Physics-based models are particularly useful when the evolution of a depositional system is driven by the interplay of autogenic processes and their response to allogenic controls. This interplay can potentially create complex reservoir architectures with high permeability sedimentary bodies bounded by a hierarchy of shales that can effectively impede flow in the subsurface. The complex stratigraphy of tide-influenced fluvial systems is an example of such co-existing and interacting environments of deposition. The focus of this talk is a novel formulation of boundary conditions for hydrodynamics-driven models of sedimentary systems. In tidal simulations, a time-accurate boundary treatment is essential for proper imposition of tidal forcing and fluvial inlet conditions where the flow may be reversed at times within a tidal cycle. As such, the boundary treatment at the inlet has to accommodate for a smooth transition from inflow to outflow and vice-versa without creating numerical artifacts. Our numerical experimentations showed that boundary condition treatments based on a local (frozen) one-dimensional approach along the boundary normal which does not account for the variation of flow quantities in the tangential direction often lead to unsatisfactory results corrupted by numerical artifacts. In this talk, we propose a new boundary treatment that retains all spatial and temporal terms in the model and as such is capable to account for nonlinearities and sharp variations of model variables near boundaries. The proposed approach borrows heavily from the idea set forth by J. Sesterhenn1 for compressible Navier-Stokes equations. The methodology is successfully applied to a tide-influenced incised valley fluvial system and the resulting stratigraphy is shown and discussed for different tide amplitudes. 1 Sesterhenn, J.: "A characteristic-type formulation of the Navier-Stokes equations for high-order upwind schemes", Computers & Fluids 30 (1) 37-67, 2001.;

Special Issue on Uncertainty Quantification in Multiscale System Design and Simulation

DOE PAGES

Wang, Yan; Swiler, Laura

2017-09-07

The importance of uncertainty has been recognized in various modeling, simulation, and analysis applications, where inherent assumptions and simplifications affect the accuracy of model predictions for physical phenomena. As model predictions are now heavily relied upon for simulation-based system design, which includes new materials, vehicles, mechanical and civil structures, and even new drugs, wrong model predictions could potentially cause catastrophic consequences. Therefore, uncertainty and associated risks due to model errors should be quantified to support robust systems engineering.

Special Issue on Uncertainty Quantification in Multiscale System Design and Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Yan; Swiler, Laura

The importance of uncertainty has been recognized in various modeling, simulation, and analysis applications, where inherent assumptions and simplifications affect the accuracy of model predictions for physical phenomena. As model predictions are now heavily relied upon for simulation-based system design, which includes new materials, vehicles, mechanical and civil structures, and even new drugs, wrong model predictions could potentially cause catastrophic consequences. Therefore, uncertainty and associated risks due to model errors should be quantified to support robust systems engineering.

Surfing on Protein Waves: Proteophoresis as a Mechanism for Bacterial Genome Partitioning

NASA Astrophysics Data System (ADS)

Walter, J.-C.; Dorignac, J.; Lorman, V.; Rech, J.; Bouet, J.-Y.; Nollmann, M.; Palmeri, J.; Parmeggiani, A.; Geniet, F.

2017-07-01

Efficient bacterial chromosome segregation typically requires the coordinated action of a three-component machinery, fueled by adenosine triphosphate, called the partition complex. We present a phenomenological model accounting for the dynamic activity of this system that is also relevant for the physics of catalytic particles in active environments. The model is obtained by coupling simple linear reaction-diffusion equations with a proteophoresis, or "volumetric" chemophoresis, force field that arises from protein-protein interactions and provides a physically viable mechanism for complex translocation. This minimal description captures most known experimental observations: dynamic oscillations of complex components, complex separation, and subsequent symmetrical positioning. The predictions of our model are in phenomenological agreement with and provide substantial insight into recent experiments. From a nonlinear physics view point, this system explores the active separation of matter at micrometric scales with a dynamical instability between static positioning and traveling wave regimes triggered by the dynamical spontaneous breaking of rotational symmetry.

A model for foreign exchange markets based on glassy Brownian systems

PubMed Central

Trinidad-Segovia, J. E.; Clara-Rahola, J.; Puertas, A. M.; De las Nieves, F. J.

2017-01-01

In this work we extend a well-known model from arrested physical systems, and employ it in order to efficiently depict different currency pairs of foreign exchange market price fluctuation distributions. We consider the exchange rate price in the time range between 2010 and 2016 at yearly time intervals and resolved at one minute frequency. We then fit the experimental datasets with this model, and find significant qualitative symmetry between price fluctuation distributions from the currency market, and the ones belonging to colloidal particles position in arrested states. The main contribution of this paper is a well-known physical model that does not necessarily assume the independent and identically distributed (i.i.d.) restrictive condition. PMID:29206868

Modelling Complex Fenestration Systems using physical and virtual models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thanachareonkit, Anothai; Scartezzini, Jean-Louis

2010-04-15

Physical or virtual models are commonly used to visualize the conceptual ideas of architects, lighting designers and researchers; they are also employed to assess the daylighting performance of buildings, particularly in cases where Complex Fenestration Systems (CFS) are considered. Recent studies have however revealed a general tendency of physical models to over-estimate this performance, compared to those of real buildings; these discrepancies can be attributed to several reasons. In order to identify the main error sources, a series of comparisons in-between a real building (a single office room within a test module) and the corresponding physical and virtual models wasmore » undertaken. The physical model was placed in outdoor conditions, which were strictly identical to those of the real building, as well as underneath a scanning sky simulator. The virtual model simulations were carried out by way of the Radiance program using the GenSky function; an alternative evaluation method, named Partial Daylight Factor method (PDF method), was also employed with the physical model together with sky luminance distributions acquired by a digital sky scanner during the monitoring of the real building. The overall daylighting performance of physical and virtual models were assessed and compared. The causes of discrepancies between the daylighting performance of the real building and the models were analysed. The main identified sources of errors are the reproduction of building details, the CFS modelling and the mocking-up of the geometrical and photometrical properties. To study the impact of these errors on daylighting performance assessment, computer simulation models created using the Radiance program were also used to carry out a sensitivity analysis of modelling errors. The study of the models showed that large discrepancies can occur in daylighting performance assessment. In case of improper mocking-up of the glazing for instance, relative divergences of 25-40% can be found in different room locations, suggesting that more light is entering than actually monitored in the real building. All these discrepancies can however be reduced by making an effort to carefully mock up the geometry and photometry of the real building. A synthesis is presented in this article which can be used as guidelines for daylighting designers to avoid or estimate errors during CFS daylighting performance assessment. (author)« less

On the nature of dissipative Timoshenko systems at light of the second spectrum of frequency

NASA Astrophysics Data System (ADS)

Almeida Júnior, D. S.; Ramos, A. J. A.

2017-12-01

In the present work, we prove that there exists a relation between a physical inconsistence known as second spectrum of frequency or non-physical spectrum and the exponential decay of a dissipative Timoshenko system where the damping mechanism acts on angle rotation. The so-called second spectrum is addressed into stabilization scenario and, in particular, we show that the second spectrum of the classical Timoshenko model can be truncated by taking a damping mechanism. Also, we show that dissipative Timoshenko type systems which are free of the second spectrum [based on important physical and historical observations made by Elishakoff (Advances mathematical modeling and experimental methods for materials and structures, solid mechanics and its applications, Springer, Berlin, pp 249-254, 2010), Elishakoff et al. (ASME Am Soc Mech Eng Appl Mech Rev 67(6):1-11 2015) and Elishakoff et al. (Int J Solids Struct 109:143-151, 2017)] are exponential stable for any values of the coefficients of system. In this direction, we provide physical explanations why weakly dissipative Timoshenko systems decay exponentially according to equality between velocity of wave propagation as proved in pioneering works by Soufyane (C R Acad Sci 328(8):731-734, 1999) and also by Muñoz Rivera and Racke (Discrete Contin Dyn Syst B 9:1625-1639, 2003). Therefore, the second spectrum of the classical Timoshenko beam model plays an important role in explaining some results on exponential decay and our investigations suggest to pay attention to the eventual consequences of this spectrum on stabilization setting for dissipative Timoshenko type systems.

Anisotropic Rabi model

NASA Astrophysics Data System (ADS)

Xie, Qiong-Tao; Cui, Shuai; Cao, Jun-Peng; Amico, Luigi; Fan, Heng

2014-04-01

We define the anisotropic Rabi model as the generalization of the spin-boson Rabi model: The Hamiltonian system breaks the parity symmetry; the rotating and counterrotating interactions are governed by two different coupling constants; a further parameter introduces a phase factor in the counterrotating terms. The exact energy spectrum and eigenstates of the generalized model are worked out. The solution is obtained as an elaboration of a recently proposed method for the isotropic limit of the model. In this way, we provide a long-sought solution of a cascade of models with immediate relevance in different physical fields, including (i) quantum optics, a two-level atom in single-mode cross-electric and magnetic fields; (ii) solid-state physics, electrons in semiconductors with Rashba and Dresselhaus spin-orbit coupling; and (iii) mesoscopic physics, Josephson-junction flux-qubit quantum circuits.

The dynamic radiation environment assimilation model (DREAM)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reeves, Geoffrey D; Koller, Josef; Tokar, Robert L

2010-01-01

The Dynamic Radiation Environment Assimilation Model (DREAM) is a 3-year effort sponsored by the US Department of Energy to provide global, retrospective, or real-time specification of the natural and potential nuclear radiation environments. The DREAM model uses Kalman filtering techniques that combine the strengths of new physical models of the radiation belts with electron observations from long-term satellite systems such as GPS and geosynchronous systems. DREAM includes a physics model for the production and long-term evolution of artificial radiation belts from high altitude nuclear explosions. DREAM has been validated against satellites in arbitrary orbits and consistently produces more accurate resultsmore » than existing models. Tools for user-specific applications and graphical displays are in beta testing and a real-time version of DREAM has been in continuous operation since November 2009.« less

New agrophysics divisions: application of ANFIS, fuzzy indicator modeling, physic-technical bases of plant breeding, and materials based on humic acids (review)

USDA-ARS?s Scientific Manuscript database

This work is devoted to review the new scientific divisions that emerged in agrophysics in the last 10-15 years. Among them are the following: 1) application of Adaptive Neuro-Fuzzy Inference System (ANFIS), 2) development and application of fuzzy indicator modeling, 3) agrophysical and physic-tech...

Control-based continuation: Bifurcation and stability analysis for physical experiments

NASA Astrophysics Data System (ADS)

Barton, David A. W.

2017-02-01

Control-based continuation is technique for tracking the solutions and bifurcations of nonlinear experiments. The idea is to apply the method of numerical continuation to a feedback-controlled physical experiment such that the control becomes non-invasive. Since in an experiment it is not (generally) possible to set the state of the system directly, the control target becomes a proxy for the state. Control-based continuation enables the systematic investigation of the bifurcation structure of a physical system, much like if it was numerical model. However, stability information (and hence bifurcation detection and classification) is not readily available due to the presence of stabilising feedback control. This paper uses a periodic auto-regressive model with exogenous inputs (ARX) to approximate the time-varying linearisation of the experiment around a particular periodic orbit, thus providing the missing stability information. This method is demonstrated using a physical nonlinear tuned mass damper.

Mutual information, neural networks and the renormalization group

NASA Astrophysics Data System (ADS)

Koch-Janusz, Maciej; Ringel, Zohar

2018-06-01

Physical systems differing in their microscopic details often display strikingly similar behaviour when probed at macroscopic scales. Those universal properties, largely determining their physical characteristics, are revealed by the powerful renormalization group (RG) procedure, which systematically retains `slow' degrees of freedom and integrates out the rest. However, the important degrees of freedom may be difficult to identify. Here we demonstrate a machine-learning algorithm capable of identifying the relevant degrees of freedom and executing RG steps iteratively without any prior knowledge about the system. We introduce an artificial neural network based on a model-independent, information-theoretic characterization of a real-space RG procedure, which performs this task. We apply the algorithm to classical statistical physics problems in one and two dimensions. We demonstrate RG flow and extract the Ising critical exponent. Our results demonstrate that machine-learning techniques can extract abstract physical concepts and consequently become an integral part of theory- and model-building.

3Mo: A Model for Music-Based Biofeedback

PubMed Central

Maes, Pieter-Jan; Buhmann, Jeska; Leman, Marc

2016-01-01

In the domain of sports and motor rehabilitation, it is of major importance to regulate and control physiological processes and physical motion in most optimal ways. For that purpose, real-time auditory feedback of physiological and physical information based on sound signals, often termed “sonification,” has been proven particularly useful. However, the use of music in biofeedback systems has been much less explored. In the current article, we assert that the use of music, and musical principles, can have a major added value, on top of mere sound signals, to the benefit of psychological and physical optimization of sports and motor rehabilitation tasks. In this article, we present the 3Mo model to describe three main functions of music that contribute to these benefits. These functions relate the power of music to Motivate, and to Monitor and Modify physiological and physical processes. The model brings together concepts and theories related to human sensorimotor interaction with music, and specifies the underlying psychological and physiological principles. This 3Mo model is intended to provide a conceptual framework that guides future research on musical biofeedback systems in the domain of sports and motor rehabilitation. PMID:27994535

Software For Design Of Life-Support Systems

NASA Technical Reports Server (NTRS)

Rudokas, Mary R.; Cantwell, Elizabeth R.; Robinson, Peter I.; Shenk, Timothy W.

1991-01-01

Design Assistant Workstation (DAWN) computer program is prototype of expert software system for analysis and design of regenerative, physical/chemical life-support systems that revitalize air, reclaim water, produce food, and treat waste. Incorporates both conventional software for quantitative mathematical modeling of physical, chemical, and biological processes and expert system offering user stored knowledge about materials and processes. Constructs task tree as it leads user through simulated process, offers alternatives, and indicates where alternative not feasible. Also enables user to jump from one design level to another.

Using Physical Models for Anomaly Detection in Control Systems

NASA Astrophysics Data System (ADS)

Svendsen, Nils; Wolthusen, Stephen

Supervisory control and data acquisition (SCADA) systems are increasingly used to operate critical infrastructure assets. However, the inclusion of advanced information technology and communications components and elaborate control strategies in SCADA systems increase the threat surface for external and subversion-type attacks. The problems are exacerbated by site-specific properties of SCADA environments that make subversion detection impractical; and by sensor noise and feedback characteristics that degrade conventional anomaly detection systems. Moreover, potential attack mechanisms are ill-defined and may include both physical and logical aspects.

Advanced instrumentation for Solar System gravitational physics

NASA Astrophysics Data System (ADS)

Peron, Roberto; Bellettini, G.; Berardi, S.; Boni, A.; Cantone, C.; Coradini, A.; Currie, D. G.; Dell'Agnello, S.; Delle Monache, G. O.; Fiorenza, E.; Garattini, M.; Iafolla, V.; Intaglietta, N.; Lefevre, C.; Lops, C.; March, R.; Martini, M.; Nozzoli, S.; Patrizi, G.; Porcelli, L.; Reale, A.; Santoli, F.; Tauraso, R.; Vittori, R.

2010-05-01

The Solar System is a complex laboratory for testing gravitational physics. Indeed, its scale and hierarchical structure make possible a wide range of tests for gravitational theories, studying the motion of both natural and artificial objects. The usual methodology makes use of tracking information related to the bodies, fitted by a suitable dynamical model. Different equations of motion are provided by different theories, which can be therefore tested and compared. Future exploration scenarios show the possibility of placing deep-space probes near the Sun or in outer Solar System, thereby extending the available experimental data sets. In particular, the Earth-Moon is the most accurately known gravitational three-body laboratory, which is undergoing a new, strong wave of research and exploration (both robotic and manned). In addition, the benefits of a synergetic study of planetary science and gravitational physics are of the greatest importance (as shown by the success of the Apollo program), especially in the Earth-Moon, Mars-Phobos, Jovian and Saturnian sub-suystems. This scenarios open critical issues regarding the quality of the available dynamical models, i.e. their capability of fitting data without an excessive number of empirical hypotheses. A typical case is represented by the non-gravitational phenomena, which in general are difficult to model. More generally, gravitation tests with Lunar Laser Ranging, inner or outer Solar System probes and the appearance of the so-called 'anomalies'(like the one indicated by the Pioneers), whatever their real origin (either instrumental effects or due to new physics), show the necessity of a coordinated improvement of tracking and modelization techniques. A common research path will be discussed, employing the development and use of advanced instrumentation to cope with current limitations of Solar System gravitational tests. In particular, the use of high-sensitivity accelerometers, combined with microwave and laser tracking, will be discussed.

Composing Models of Geographic Physical Processes

NASA Astrophysics Data System (ADS)

Hofer, Barbara; Frank, Andrew U.

Processes are central for geographic information science; yet geographic information systems (GIS) lack capabilities to represent process related information. A prerequisite to including processes in GIS software is a general method to describe geographic processes independently of application disciplines. This paper presents such a method, namely a process description language. The vocabulary of the process description language is derived formally from mathematical models. Physical processes in geography can be described in two equivalent languages: partial differential equations or partial difference equations, where the latter can be shown graphically and used as a method for application specialists to enter their process models. The vocabulary of the process description language comprises components for describing the general behavior of prototypical geographic physical processes. These process components can be composed by basic models of geographic physical processes, which is shown by means of an example.

Reading Time as Evidence for Mental Models in Understanding Physics

NASA Astrophysics Data System (ADS)

Brookes, David T.; Mestre, José; Stine-Morrow, Elizabeth A. L.

2007-11-01

We present results of a reading study that show the usefulness of probing physics students' cognitive processing by measuring reading time. According to contemporary discourse theory, when people read a text, a network of associated inferences is activated to create a mental model. If the reader encounters an idea in the text that conflicts with existing knowledge, the construction of a coherent mental model is disrupted and reading times are prolonged, as measured using a simple self-paced reading paradigm. We used this effect to study how "non-Newtonian" and "Newtonian" students create mental models of conceptual systems in physics as they read texts related to the ideas of Newton's third law, energy, and momentum. We found significant effects of prior knowledge state on patterns of reading time, suggesting that students attempt to actively integrate physics texts with their existing knowledge.

Monitoring a Complex Physical System using a Hybrid Dynamic Bayes Net

NASA Technical Reports Server (NTRS)

Lerner, Uri; Moses, Brooks; Scott, Maricia; McIlraith, Sheila; Keller, Daphne

2005-01-01

The Reverse Water Gas Shift system (RWGS) is a complex physical system designed to produce oxygen from the carbon dioxide atmosphere on Mars. If sent to Mars, it would operate without human supervision, thus requiring a reliable automated system for monitoring and control. The RWGS presents many challenges typical of real-world systems, including: noisy and biased sensors, nonlinear behavior, effects that are manifested over different time granularities, and unobservability of many important quantities. In this paper we model the RWGS using a hybrid (discrete/continuous) Dynamic Bayesian Network (DBN), where the state at each time slice contains 33 discrete and 184 continuous variables. We show how the system state can be tracked using probabilistic inference over the model. We discuss how to deal with the various challenges presented by the RWGS, providing a suite of techniques that are likely to be useful in a wide range of applications. In particular, we describe a general framework for dealing with nonlinear behavior using numerical integration techniques, extending the successful Unscented Filter. We also show how to use a fixed-point computation to deal with effects that develop at different time scales, specifically rapid changes occuring during slowly changing processes. We test our model using real data collected from the RWGS, demonstrating the feasibility of hybrid DBNs for monitoring complex real-world physical systems.

A physical data model for fields and agents

NASA Astrophysics Data System (ADS)

de Jong, Kor; de Bakker, Merijn; Karssenberg, Derek

2016-04-01

Two approaches exist in simulation modeling: agent-based and field-based modeling. In agent-based (or individual-based) simulation modeling, the entities representing the system's state are represented by objects, which are bounded in space and time. Individual objects, like an animal, a house, or a more abstract entity like a country's economy, have properties representing their state. In an agent-based model this state is manipulated. In field-based modeling, the entities representing the system's state are represented by fields. Fields capture the state of a continuous property within a spatial extent, examples of which are elevation, atmospheric pressure, and water flow velocity. With respect to the technology used to create these models, the domains of agent-based and field-based modeling have often been separate worlds. In environmental modeling, widely used logical data models include feature data models for point, line and polygon objects, and the raster data model for fields. Simulation models are often either agent-based or field-based, even though the modeled system might contain both entities that are better represented by individuals and entities that are better represented by fields. We think that the reason for this dichotomy in kinds of models might be that the traditional object and field data models underlying those models are relatively low level. We have developed a higher level conceptual data model for representing both non-spatial and spatial objects, and spatial fields (De Bakker et al. 2016). Based on this conceptual data model we designed a logical and physical data model for representing many kinds of data, including the kinds used in earth system modeling (e.g. hydrological and ecological models). The goal of this work is to be able to create high level code and tools for the creation of models in which entities are representable by both objects and fields. Our conceptual data model is capable of representing the traditional feature data models and the raster data model, among many other data models. Our physical data model is capable of storing a first set of kinds of data, like omnipresent scalars, mobile spatio-temporal points and property values, and spatio-temporal rasters. With our poster we will provide an overview of the physical data model expressed in HDF5 and show examples of how it can be used to capture both object- and field-based information. References De Bakker, M, K. de Jong, D. Karssenberg. 2016. A conceptual data model and language for fields and agents. European Geosciences Union, EGU General Assembly, 2016, Vienna.

Machine Learning and Deep Learning Models to Predict Runoff Water Quantity and Quality

NASA Astrophysics Data System (ADS)

Bradford, S. A.; Liang, J.; Li, W.; Murata, T.; Simunek, J.

2017-12-01

Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models, which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with physically-based models, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. In this presentation we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport (the HYDRUS-1D overland flow module). A large number of numerical simulations were carried out to develop a database containing information about the impact of various input parameters (weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices) on runoff water quantity and quality outputs. This database was used to train data-driven models. Three different methods (Neural Networks, Support Vector Machines, and Recurrence Neural Networks) were explored to prepare input- output functional relations. Results demonstrate the ability and limitations of machine learning and deep learning models to predict runoff water quantity and quality.

Recent improvements of reactor physics codes in MHI

NASA Astrophysics Data System (ADS)

Kosaka, Shinya; Yamaji, Kazuya; Kirimura, Kazuki; Kamiyama, Yohei; Matsumoto, Hideki

2015-12-01

This paper introduces recent improvements for reactor physics codes in Mitsubishi Heavy Industries, Ltd(MHI). MHI has developed a new neutronics design code system Galaxy/Cosmo-S(GCS) for PWR core analysis. After TEPCO's Fukushima Daiichi accident, it is required to consider design extended condition which has not been covered explicitly by the former safety licensing analyses. Under these circumstances, MHI made some improvements for GCS code system. A new resonance calculation model of lattice physics code and homogeneous cross section representative model for core simulator have been developed to apply more wide range core conditions corresponding to severe accident status such like anticipated transient without scram (ATWS) analysis and criticality evaluation of dried-up spent fuel pit. As a result of these improvements, GCS code system has very wide calculation applicability with good accuracy for any core conditions as far as fuel is not damaged. In this paper, the outline of GCS code system is described briefly and recent relevant development activities are presented.

Resolution and Orbit Reconstruction of Spectroscopic Binary Stars with the Palomar Testbed Interferometer

NASA Astrophysics Data System (ADS)

Boden, A. F.; Lane, B. F.; Creech-Eakman, M. J.; Queloz, D.; Koresko, C. D.

2000-05-01

The Palomar Testbed Interferometer (PTI) is a long-baseline near-infrared interferometer located at Palomar Observatory. For the past several years we have had an ongoing program of resolving and reconstructing the visual and physical orbits of spectroscopic binary stars with PTI, with the goal of obtaining precise dynamical mass estimates and other physical parameters. We will present a number of new visual and physical orbit determinations derived from integrated reductions of PTI visibility and archival and new spectroscopic radial velocity data. The systems for which we will discuss our orbit models are: iota Pegasi (HD 210027), 64 Psc (HD 4676), 12 Boo (HD 123999), 75 Cnc (HD 78418), 47 And (HD 8374), HD 205539, BY Draconis (HDE 234677), and 3 Boo (HD 120064), and 3 Boo (HD 120064). All of these systems are double-lined binary systems (SB2), and integrated astrometric/radial velocity orbit modeling provides precise fundamental parameters (mass, luminosity) and system distance determinations comparable with Hipparcos precisions.

HELIOGate, a Portal for the Heliophysics Community

NASA Astrophysics Data System (ADS)

Pierantoni; Gabriele; Carley, Eoin

2014-10-01

Heliophysics is the branch of physics that investigates the interactions between the Sun and the other bodies of the solar system. Heliophysicists rely on data collected from numerous sources scattered across the Solar System. The data collected from these sources is processed to extract metadata and the metadata extracted in this fashion is then used to build indexes of features and events called catalogues. Heliophysicists also develop conceptual and mathematical models of the phenomena and the environment of the Solar System. More specifically, they investigate the physical characteristics of the phenomena and they simulate how they propagate throughout the Solar System with mathematical and physical abstractions called propagation models. HELIOGate aims at addressing the need to combine and orchestrate existing web services in a flexible and easily configurable fashion to tackle different scientific questions. HELIOGate also offers a tool capable of connecting to size! able computation and storage infrastructures to execute data processing codes that are needed to calibrate raw data and to extract metadata.

BESIU Physical Analysis on Hadoop Platform

NASA Astrophysics Data System (ADS)

Huo, Jing; Zang, Dongsong; Lei, Xiaofeng; Li, Qiang; Sun, Gongxing

2014-06-01

In the past 20 years, computing cluster has been widely used for High Energy Physics data processing. The jobs running on the traditional cluster with a Data-to-Computing structure, have to read large volumes of data via the network to the computing nodes for analysis, thereby making the I/O latency become a bottleneck of the whole system. The new distributed computing technology based on the MapReduce programming model has many advantages, such as high concurrency, high scalability and high fault tolerance, and it can benefit us in dealing with Big Data. This paper brings the idea of using MapReduce model to do BESIII physical analysis, and presents a new data analysis system structure based on Hadoop platform, which not only greatly improve the efficiency of data analysis, but also reduces the cost of system building. Moreover, this paper establishes an event pre-selection system based on the event level metadata(TAGs) database to optimize the data analyzing procedure.

Recent improvements of reactor physics codes in MHI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kosaka, Shinya, E-mail: shinya-kosaka@mhi.co.jp; Yamaji, Kazuya; Kirimura, Kazuki

2015-12-31

This paper introduces recent improvements for reactor physics codes in Mitsubishi Heavy Industries, Ltd(MHI). MHI has developed a new neutronics design code system Galaxy/Cosmo-S(GCS) for PWR core analysis. After TEPCO’s Fukushima Daiichi accident, it is required to consider design extended condition which has not been covered explicitly by the former safety licensing analyses. Under these circumstances, MHI made some improvements for GCS code system. A new resonance calculation model of lattice physics code and homogeneous cross section representative model for core simulator have been developed to apply more wide range core conditions corresponding to severe accident status such like anticipatedmore » transient without scram (ATWS) analysis and criticality evaluation of dried-up spent fuel pit. As a result of these improvements, GCS code system has very wide calculation applicability with good accuracy for any core conditions as far as fuel is not damaged. In this paper, the outline of GCS code system is described briefly and recent relevant development activities are presented.« less

DEVELOPMENT AND APPLICATION OF A NEW AIR POLLUTION MODELING SYSTEM--II. AEROSOL MODULE STRUCTURE AND DESIGN (R823186)

EPA Science Inventory

The methods used for simulating aerosol physical and chemical processes in a new air pollution modeling system are discussed and analyzed. Such processes include emissions, nucleation, coagulation, reversible chemistry, condensation, dissolution, evaporation, irreversible chem...

A PetriNet-Based Approach for Supporting Traceability in Cyber-Physical Manufacturing Systems

PubMed Central

Huang, Jiwei; Zhu, Yeping; Cheng, Bo; Lin, Chuang; Chen, Junliang

2016-01-01

With the growing popularity of complex dynamic activities in manufacturing processes, traceability of the entire life of every product has drawn significant attention especially for food, clinical materials, and similar items. This paper studies the traceability issue in cyber-physical manufacturing systems from a theoretical viewpoint. Petri net models are generalized for formulating dynamic manufacturing processes, based on which a detailed approach for enabling traceability analysis is presented. Models as well as algorithms are carefully designed, which can trace back the lifecycle of a possibly contaminated item. A practical prototype system for supporting traceability is designed, and a real-life case study of a quality control system for bee products is presented to validate the effectiveness of the approach. PMID:26999141

Interacting Winds in Eclipsing Symbiotic Systems - The Case Study of EG Andromedae

NASA Astrophysics Data System (ADS)

Calabrò, Emanuele

2014-03-01

We report the mathematical representation of the so called eccentric eclipse model, whose numerical solutions can be used to obtain the physical parameters of a quiescent eclipsing symbiotic system. Indeed the nebular region produced by the collision of the stellar winds should be shifted to the orbital axis because of the orbital motion of the system. This mechanism is not negligible, and it led us to modify the classical concept of an eclipse. The orbital elements obtained from spectroscopy and photometry of the symbiotic EG Andromedae were used to test the eccentric eclipse model. Consistent values for the unknown orbital elements of this symbiotic were obtained. The physical parameters are in agreement with those obtained by means of other simulations for this system.

A PetriNet-Based Approach for Supporting Traceability in Cyber-Physical Manufacturing Systems.

PubMed

Huang, Jiwei; Zhu, Yeping; Cheng, Bo; Lin, Chuang; Chen, Junliang

2016-03-17

With the growing popularity of complex dynamic activities in manufacturing processes, traceability of the entire life of every product has drawn significant attention especially for food, clinical materials, and similar items. This paper studies the traceability issue in cyber-physical manufacturing systems from a theoretical viewpoint. Petri net models are generalized for formulating dynamic manufacturing processes, based on which a detailed approach for enabling traceability analysis is presented. Models as well as algorithms are carefully designed, which can trace back the lifecycle of a possibly contaminated item. A practical prototype system for supporting traceability is designed, and a real-life case study of a quality control system for bee products is presented to validate the effectiveness of the approach.

Current algebra, statistical mechanics and quantum models

NASA Astrophysics Data System (ADS)

Vilela Mendes, R.

2017-11-01

Results obtained in the past for free boson systems at zero and nonzero temperatures are revisited to clarify the physical meaning of current algebra reducible functionals which are associated to systems with density fluctuations, leading to observable effects on phase transitions. To use current algebra as a tool for the formulation of quantum statistical mechanics amounts to the construction of unitary representations of diffeomorphism groups. Two mathematical equivalent procedures exist for this purpose. One searches for quasi-invariant measures on configuration spaces, the other for a cyclic vector in Hilbert space. Here, one argues that the second approach is closer to the physical intuition when modelling complex systems. An example of application of the current algebra methodology to the pairing phenomenon in two-dimensional fermion systems is discussed.

Hardware-in-the-Loop Modeling and Simulation Methods for Daylight Systems in Buildings

NASA Astrophysics Data System (ADS)

Mead, Alex Robert

This dissertation introduces hardware-in-the-loop modeling and simulation techniques to the daylighting community, with specific application to complex fenestration systems. No such application of this class of techniques, optimally combining mathematical-modeling and physical-modeling experimentation, is known to the author previously in the literature. Daylighting systems in buildings have a large impact on both the energy usage of a building as well as the occupant experience within a space. As such, a renewed interest has been placed on designing and constructing buildings with an emphasis on daylighting in recent times as part of the "green movement.''. Within daylighting systems, a specific subclass of building envelope is receiving much attention: complex fenestration systems (CFSs). CFSs are unique as compared to regular fenestration systems (e.g. glazing) in the regard that they allow for non-specular transmission of daylight into a space. This non-specular nature can be leveraged by designers to "optimize'' the times of the day and the days of the year that daylight enters a space. Examples of CFSs include: Venetian blinds, woven fabric shades, and prismatic window coatings. In order to leverage the non-specular transmission properties of CFSs, however, engineering analysis techniques capable of faithfully representing the physics of these systems are needed. Traditionally, the analysis techniques available to the daylighting community fall broadly into three classes: simplified techniques, mathematical-modeling and simulation, and physical-modeling and experimentation. Simplified techniques use "rules-of-thumb'' heuristics to provide insights for simple daylighting systems. Mathematical-modeling and simulation use complex numerical models to provide more detailed insights into system performance. Finally, physical-models can be instrumented and excited using artificial and natural light sources to provide performance insight into a daylighting system. Each class of techniques, broadly speaking however, has advantages and disadvantages with respect to the cost of execution (e.g. money, time, expertise) and the fidelity of the provided insight into the performance of the daylighting system. This varying tradeoff of cost and insight between the techniques determines which techniques are employed for which projects. Daylighting systems with CFS components, however, when considered for simulation with respect to these traditional technique classes, defy high fidelity analysis. Simplified techniques are clearly not applicable. Mathematical-models must have great complexity in order to capture the non-specular transmission accurately, which greatly limit their applicability. This leaves physical modeling, the most costly, as the preferred method for CFS. While mathematical-modeling and simulation methods do exist, they are in general costly and and still approximations of the underlying CFS behavior. Meaning in fact, measurements of CFSs are currently the only practical method to capture the behavior of CFSs. Traditional measurements of CFSs transmission and reflection properties are conducted using an instrument called a goniophotometer and produce a measurement in the form of a Bidirectional Scatter Distribution Function (BSDF) based on the Klems Basis. This measurement must be executed for each possible state of the CFS, hence only a subset of the possible behaviors can be captured for CFSs with continuously varying configurations. In the current era of rapid prototyping (e.g. 3D printing) and automated control of buildings including daylighting systems, a new analysis technique is needed which can faithfully represent these CFSs which are being designed and constructed at an increasing rate. Hardware-in-the-loop modeling and simulation is a perfect fit to the current need of analyzing daylighting systems with CFSs. In the proposed hardware-in-the-loop modeling and simulation approach of this dissertation, physical-models of real CFSs are excited using either natural or artificial light. The exiting luminance distribution from these CFSs is measured and used as inputs to a Radiance mathematical-model of the interior of the space, which is proposed to be lit by the CFS containing daylighting system. Hence, the components of the total daylighting and building system which are not mathematically-modeled well, the CFS, are physically excited and measured, while the components which are modeled properly, namely the interior building space, are mathematically-modeled. In order to excite and measure CFSs behavior, a novel parallel goniophotometer, referred to as the CUBE 2.0, is developed in this dissertation. The CUBE 2.0 measures the input illuminance distribution and the output luminance distribution with respect to a CFS under test. Further, the process is fully automated allowing for deployable experiments on proposed building sites, as well as in laboratory based experiments. In this dissertation, three CFSs, two commercially available and one novel--Twitchell's Textilene 80 Black, Twitchell's Shade View Ebony, and Translucent Concrete Panels (TCP)--are simulated on the CUBE 2.0 system for daylong deployments at one minute time steps. These CFSs are assumed to be placed in the glazing space within the Reference Office Radiance model, for which horizontal illuminance on a work plane of 0.8 m height is calculated for each time step. While Shade View Ebony and TCPs are unmeasured CFSs with respect to BSDF, Textilene 80 Black has been previously measured. As such a validation of the CUBE 2.0 using the goniophotometer measured BSDF is presented, with measurement errors of the horizontal illuminance between +3% and -10%. These error levels are considered to be valid within experimental daylighting investigations. Non-validated results are also presented in full for both Shade View Ebony as well as TCP. Concluding remarks and future directions for HWiL simulation close the dissertation.

A physical model of sensorimotor interactions during locomotion

NASA Astrophysics Data System (ADS)

Klein, Theresa J.; Lewis, M. Anthony

2012-08-01

In this paper, we describe the development of a bipedal robot that models the neuromuscular architecture of human walking. The body is based on principles derived from human muscular architecture, using muscles on straps to mimic agonist/antagonist muscle action as well as bifunctional muscles. Load sensors in the straps model Golgi tendon organs. The neural architecture is a central pattern generator (CPG) composed of a half-center oscillator combined with phase-modulated reflexes that is simulated using a spiking neural network. We show that the interaction between the reflex system, body dynamics and CPG results in a walking cycle that is entrained to the dynamics of the system. We also show that the CPG helped stabilize the gait against perturbations relative to a purely reflexive system, and compared the joint trajectories to human walking data. This robot represents a complete physical, or ‘neurorobotic’, model of the system, demonstrating the usefulness of this type of robotics research for investigating the neurophysiological processes underlying walking in humans and animals.

Random diffusivity from stochastic equations: comparison of two models for Brownian yet non-Gaussian diffusion

NASA Astrophysics Data System (ADS)

Sposini, Vittoria; Chechkin, Aleksei V.; Seno, Flavio; Pagnini, Gianni; Metzler, Ralf

2018-04-01

A considerable number of systems have recently been reported in which Brownian yet non-Gaussian dynamics was observed. These are processes characterised by a linear growth in time of the mean squared displacement, yet the probability density function of the particle displacement is distinctly non-Gaussian, and often of exponential (Laplace) shape. This apparently ubiquitous behaviour observed in very different physical systems has been interpreted as resulting from diffusion in inhomogeneous environments and mathematically represented through a variable, stochastic diffusion coefficient. Indeed different models describing a fluctuating diffusivity have been studied. Here we present a new view of the stochastic basis describing time-dependent random diffusivities within a broad spectrum of distributions. Concretely, our study is based on the very generic class of the generalised Gamma distribution. Two models for the particle spreading in such random diffusivity settings are studied. The first belongs to the class of generalised grey Brownian motion while the second follows from the idea of diffusing diffusivities. The two processes exhibit significant characteristics which reproduce experimental results from different biological and physical systems. We promote these two physical models for the description of stochastic particle motion in complex environments.

Physical and JIT Model Based Hybrid Modeling Approach for Building Thermal Load Prediction

NASA Astrophysics Data System (ADS)

Iino, Yutaka; Murai, Masahiko; Murayama, Dai; Motoyama, Ichiro

Energy conservation in building fields is one of the key issues in environmental point of view as well as that of industrial, transportation and residential fields. The half of the total energy consumption in a building is occupied by HVAC (Heating, Ventilating and Air Conditioning) systems. In order to realize energy conservation of HVAC system, a thermal load prediction model for building is required. This paper propose a hybrid modeling approach with physical and Just-in-Time (JIT) model for building thermal load prediction. The proposed method has features and benefits such as, (1) it is applicable to the case in which past operation data for load prediction model learning is poor, (2) it has a self checking function, which always supervises if the data driven load prediction and the physical based one are consistent or not, so it can find if something is wrong in load prediction procedure, (3) it has ability to adjust load prediction in real-time against sudden change of model parameters and environmental conditions. The proposed method is evaluated with real operation data of an existing building, and the improvement of load prediction performance is illustrated.

A Multi-Scale Integrated Approach to Representing Watershed Systems: Significance and Challenges

NASA Astrophysics Data System (ADS)

Kim, J.; Ivanov, V. Y.; Katopodes, N.

2013-12-01

A range of processes associated with supplying services and goods to human society originate at the watershed level. Predicting watershed response to forcing conditions has been of high interest to many practical societal problems, however, remains challenging due to two significant properties of the watershed systems, i.e., connectivity and non-linearity. Connectivity implies that disturbances arising at any larger scale will necessarily propagate and affect local-scale processes; their local effects consequently influence other processes, and often convey nonlinear relationships. Physically-based, process-scale modeling is needed to approach the understanding and proper assessment of non-linear effects between the watershed processes. We have developed an integrated model simulating hydrological processes, flow dynamics, erosion and sediment transport, tRIBS-OFM-HRM (Triangulated irregular network - based Real time Integrated Basin Simulator-Overland Flow Model-Hairsine and Rose Model). This coupled model offers the advantage of exploring the hydrological effects of watershed physical factors such as topography, vegetation, and soil, as well as their feedback mechanisms. Several examples investigating the effects of vegetation on flow movement, the role of soil's substrate on sediment dynamics, and the driving role of topography on morphological processes are illustrated. We show how this comprehensive modeling tool can help understand interconnections and nonlinearities of the physical system, e.g., how vegetation affects hydraulic resistance depending on slope, vegetation cover fraction, discharge, and bed roughness condition; how the soil's substrate condition impacts erosion processes with an non-unique characteristic at the scale of a zero-order catchment; and how topographic changes affect spatial variations of morphologic variables. Due to feedback and compensatory nature of mechanisms operating in different watershed compartments, our conclusion is that a key to representing watershed systems lies in an integrated, interdisciplinary approach, whereby a physically-based model is used for assessments/evaluations associated with future changes in landuse, climate, and ecosystems.

Lithium-ion battery models: a comparative study and a model-based powerline communication

NASA Astrophysics Data System (ADS)

Saidani, Fida; Hutter, Franz X.; Scurtu, Rares-George; Braunwarth, Wolfgang; Burghartz, Joachim N.

2017-09-01

In this work, various Lithium-ion (Li-ion) battery models are evaluated according to their accuracy, complexity and physical interpretability. An initial classification into physical, empirical and abstract models is introduced. Also known as white, black and grey boxes, respectively, the nature and characteristics of these model types are compared. Since the Li-ion battery cell is a thermo-electro-chemical system, the models are either in the thermal or in the electrochemical state-space. Physical models attempt to capture key features of the physical process inside the cell. Empirical models describe the system with empirical parameters offering poor analytical, whereas abstract models provide an alternative representation. In addition, a model selection guideline is proposed based on applications and design requirements. A complex model with a detailed analytical insight is of use for battery designers but impractical for real-time applications and in situ diagnosis. In automotive applications, an abstract model reproducing the battery behavior in an equivalent but more practical form, mainly as an equivalent circuit diagram, is recommended for the purpose of battery management. As a general rule, a trade-off should be reached between the high fidelity and the computational feasibility. Especially if the model is embedded in a real-time monitoring unit such as a microprocessor or a FPGA, the calculation time and memory requirements rise dramatically with a higher number of parameters. Moreover, examples of equivalent circuit models of Lithium-ion batteries are covered. Equivalent circuit topologies are introduced and compared according to the previously introduced criteria. An experimental sequence to model a 20 Ah cell is presented and the results are used for the purposes of powerline communication.

Environmental Modeling

EPA Pesticide Factsheets

EPA's modeling community is working to gain insights into certain parts of a physical, biological, economic, or social system by conducting environmental assessments for Agency decision making to complex environmental issues.

Modeling Feedbacks Between Individual Human Decisions and Hydrology Using Interconnected Physical and Social Models

NASA Astrophysics Data System (ADS)

Murphy, J.; Lammers, R. B.; Proussevitch, A. A.; Ozik, J.; Altaweel, M.; Collier, N. T.; Alessa, L.; Kliskey, A. D.

2014-12-01

The global hydrological cycle intersects with human decision making at multiple scales, from dams and irrigation works to the taps in individuals' homes. Residential water consumers are commonly encouraged to conserve; these messages are heard against a background of individual values and conceptions about water quality, uses, and availability. The degree to which these values impact the larger-hydrological dynamics, the way that changes in those values have impacts on the hydrological cycle through time, and the feedbacks by which water availability and quality in turn shape those values, are not well explored. To investigate this domain we employ a global-scale water balance model (WBM) coupled with a social-science-grounded agent-based model (ABM). The integration of a hydrological model with an agent-based model allows us to explore driving factors in the dynamics in coupled human-natural systems. From the perspective of the physical hydrologist, the ABM offers a richer means of incorporating the human decisions that drive the hydrological system; from the view of the social scientist, a physically-based hydrological model allows the decisions of the agents to play out against constraints faithful to the real world. We apply the interconnected models to a study of Tucson, Arizona, USA, and its role in the larger Colorado River system. Our core concept is Technology-Induced Environmental Distancing (TIED), which posits that layers of technology can insulate consumers from direct knowledge of a resource. In Tucson, multiple infrastructure and institutional layers have arguably increased the conceptual distance between individuals and their water supply, offering a test case of the TIED framework. Our coupled simulation allows us to show how the larger system transforms a resource with high temporal and spatial variability into a consumer constant, and the effects of this transformation on the regional system. We use this to explore how pricing, messaging, and social dynamics impact demand, how changes in demand affect the regional water system, and under what system challenges the values of the individuals are likely to change. This study is a preamble to modeling multiple regionally connected cities and larger systems with impacts on hydrology at the continental and global scales.

Representing functions/procedures and processes/structures for analysis of effects of failures on functions and operations

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Leifker, Daniel B.

1991-01-01

Current qualitative device and process models represent only the structure and behavior of physical systems. However, systems in the real world include goal-oriented activities that generally cannot be easily represented using current modeling techniques. An extension of a qualitative modeling system, known as functional modeling, which captures goal-oriented activities explicitly is proposed and how they may be used to support intelligent automation and fault management is shown.

A system dynamics optimization framework to achieve population desired of average weight target

NASA Astrophysics Data System (ADS)

Abidin, Norhaslinda Zainal; Zulkepli, Jafri Haji; Zaibidi, Nerda Zura

2017-11-01

Obesity is becoming a serious problem in Malaysia as it has been rated as the highest among Asian countries. The aim of the paper is to propose a system dynamics (SD) optimization framework to achieve population desired weight target based on the changes in physical activity behavior and its association to weight and obesity. The system dynamics approach of stocks and flows diagram was used to quantitatively model the impact of both behavior on the population's weight and obesity trends. This work seems to bring this idea together and highlighting the interdependence of the various aspects of eating and physical activity behavior on the complex of human weight regulation system. The model was used as an experimentation vehicle to investigate the impacts of changes in physical activity on weight and prevalence of obesity implications. This framework paper provides evidence on the usefulness of SD optimization as a strategic decision making approach to assist in decision making related to obesity prevention. SD applied in this research is relatively new in Malaysia and has a high potential to apply to any feedback models that address the behavior cause to obesity.

Physical model of the immune response of bacteria against bacteriophage through the adaptive CRISPR-Cas immune system

NASA Astrophysics Data System (ADS)

Han, Pu; Niestemski, Liang Ren; Barrick, Jeffrey E.; Deem, Michael W.

2013-04-01

Bacteria and archaea have evolved an adaptive, heritable immune system that recognizes and protects against viruses or plasmids. This system, known as the CRISPR-Cas system, allows the host to recognize and incorporate short foreign DNA or RNA sequences, called ‘spacers’ into its CRISPR system. Spacers in the CRISPR system provide a record of the history of bacteria and phage coevolution. We use a physical model to study the dynamics of this coevolution as it evolves stochastically over time. We focus on the impact of mutation and recombination on bacteria and phage evolution and evasion. We discuss the effect of different spacer deletion mechanisms on the coevolutionary dynamics. We make predictions about bacteria and phage population growth, spacer diversity within the CRISPR locus, and spacer protection against the phage population.

Revealing physical interaction networks from statistics of collective dynamics

PubMed Central

Nitzan, Mor; Casadiego, Jose; Timme, Marc

2017-01-01

Revealing physical interactions in complex systems from observed collective dynamics constitutes a fundamental inverse problem in science. Current reconstruction methods require access to a system’s model or dynamical data at a level of detail often not available. We exploit changes in invariant measures, in particular distributions of sampled states of the system in response to driving signals, and use compressed sensing to reveal physical interaction networks. Dynamical observations following driving suffice to infer physical connectivity even if they are temporally disordered, are acquired at large sampling intervals, and stem from different experiments. Testing various nonlinear dynamic processes emerging on artificial and real network topologies indicates high reconstruction quality for existence as well as type of interactions. These results advance our ability to reveal physical interaction networks in complex synthetic and natural systems. PMID:28246630

Predicting the performance uncertainty of a 1-MW pilot-scale carbon capture system after hierarchical laboratory-scale calibration and validation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Zhijie; Lai, Canhai; Marcy, Peter William

2017-05-01

A challenging problem in designing pilot-scale carbon capture systems is to predict, with uncertainty, the adsorber performance and capture efficiency under various operating conditions where no direct experimental data exist. Motivated by this challenge, we previously proposed a hierarchical framework in which relevant parameters of physical models were sequentially calibrated from different laboratory-scale carbon capture unit (C2U) experiments. Specifically, three models of increasing complexity were identified based on the fundamental physical and chemical processes of the sorbent-based carbon capture technology. Results from the corresponding laboratory experiments were used to statistically calibrate the physical model parameters while quantifying some of theirmore » inherent uncertainty. The parameter distributions obtained from laboratory-scale C2U calibration runs are used in this study to facilitate prediction at a larger scale where no corresponding experimental results are available. In this paper, we first describe the multiphase reactive flow model for a sorbent-based 1-MW carbon capture system then analyze results from an ensemble of simulations with the upscaled model. The simulation results are used to quantify uncertainty regarding the design’s predicted efficiency in carbon capture. In particular, we determine the minimum gas flow rate necessary to achieve 90% capture efficiency with 95% confidence.« less

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2011-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to use of the multi-satellite simulator tqimproy precipitation processes will be discussed.

Modeling of luminance distribution in CAVE-type virtual reality systems

NASA Astrophysics Data System (ADS)

Meironke, Michał; Mazikowski, Adam

2017-08-01

At present, one of the most advanced virtual reality systems are CAVE-type (Cave Automatic Virtual Environment) installations. Such systems are usually consisted of four, five or six projection screens and in case of six screens arranged in form of a cube. Providing the user with a high level of immersion feeling in such systems is largely dependent of optical properties of the system. The modeling of physical phenomena plays nowadays a huge role in the most fields of science and technology. It allows to simulate work of device without a need to make any changes in the physical constructions. In this paper distribution of luminance in CAVE-type virtual reality systems were modelled. Calculations were performed for the model of 6-walled CAVE-type installation, based on Immersive 3D Visualization Laboratory, situated at the Faculty of Electronics, Telecommunications and Informatics at the Gdańsk University of Technology. Tests have been carried out for two different scattering distribution of the screen material in order to check how these characteristicinfluence on the luminance distribution of the whole CAVE. The basis assumption and simplification of modeled CAVE-type installation and results were presented. The brief discussion about the results and usefulness of developed model were also carried out.

Cell Patterns Emerge from Coupled Chemical and Physical Fields with Cell Proliferation Dynamics: The Arabidopsis thaliana Root as a Study System

PubMed Central

Barrio, Rafael A.; Romero-Arias, José Roberto; Noguez, Marco A.; Azpeitia, Eugenio; Ortiz-Gutiérrez, Elizabeth; Hernández-Hernández, Valeria; Cortes-Poza, Yuriria; Álvarez-Buylla, Elena R.

2013-01-01

A central issue in developmental biology is to uncover the mechanisms by which stem cells maintain their capacity to regenerate, yet at the same time produce daughter cells that differentiate and attain their ultimate fate as a functional part of a tissue or an organ. In this paper we propose that, during development, cells within growing organs obtain positional information from a macroscopic physical field that is produced in space while cells are proliferating. This dynamical interaction triggers and responds to chemical and genetic processes that are specific to each biological system. We chose the root apical meristem of Arabidopsis thaliana to develop our dynamical model because this system is well studied at the molecular, genetic and cellular levels and has the key traits of multicellular stem-cell niches. We built a dynamical model that couples fundamental molecular mechanisms of the cell cycle to a tension physical field and to auxin dynamics, both of which are known to play a role in root development. We perform extensive numerical calculations that allow for quantitative comparison with experimental measurements that consider the cellular patterns at the root tip. Our model recovers, as an emergent pattern, the transition from proliferative to transition and elongation domains, characteristic of stem-cell niches in multicellular organisms. In addition, we successfully predict altered cellular patterns that are expected under various applied auxin treatments or modified physical growth conditions. Our modeling platform may be extended to explicitly consider gene regulatory networks or to treat other developmental systems. PMID:23658505

ADHydro: A Parallel Implementation of a Large-scale High-Resolution Multi-Physics Distributed Water Resources Model Using the Charm++ Run Time System

NASA Astrophysics Data System (ADS)

Steinke, R. C.; Ogden, F. L.; Lai, W.; Moreno, H. A.; Pureza, L. G.

2014-12-01

Physics-based watershed models are useful tools for hydrologic studies, water resources management and economic analyses in the contexts of climate, land-use, and water-use changes. This poster presents a parallel implementation of a quasi 3-dimensional, physics-based, high-resolution, distributed water resources model suitable for simulating large watersheds in a massively parallel computing environment. Developing this model is one of the objectives of the NSF EPSCoR RII Track II CI-WATER project, which is joint between Wyoming and Utah EPSCoR jurisdictions. The model, which we call ADHydro, is aimed at simulating important processes in the Rocky Mountain west, including: rainfall and infiltration, snowfall and snowmelt in complex terrain, vegetation and evapotranspiration, soil heat flux and freezing, overland flow, channel flow, groundwater flow, water management and irrigation. Model forcing is provided by the Weather Research and Forecasting (WRF) model, and ADHydro is coupled with the NOAH-MP land-surface scheme for calculating fluxes between the land and atmosphere. The ADHydro implementation uses the Charm++ parallel run time system. Charm++ is based on location transparent message passing between migrateable C++ objects. Each object represents an entity in the model such as a mesh element. These objects can be migrated between processors or serialized to disk allowing the Charm++ system to automatically provide capabilities such as load balancing and checkpointing. Objects interact with each other by passing messages that the Charm++ system routes to the correct destination object regardless of its current location. This poster discusses the algorithms, communication patterns, and caching strategies used to implement ADHydro with Charm++. The ADHydro model code will be released to the hydrologic community in late 2014.

Meteorological Processes Affecting Air Quality – Research and Model Development Needs

EPA Science Inventory

Meteorology modeling is an important component of air quality modeling systems that defines the physical and dynamical environment for atmospheric chemistry. The meteorology models used for air quality applications are based on numerical weather prediction models that were devel...

Watershed models for decision support in the Yakima River basin, Washington

USGS Publications Warehouse

Mastin, M.C.; Vaccaro, J.J.

2002-01-01

A Decision Support System (DSS) is being developed by the U.S. Geological Survey and the Bureau of Reclamation as part of a long-term project, the Watershed and River Systems Management Program. The goal of the program is to apply the DSS to U.S. Bureau of Reclamation projects in the western United States. The DSS was applied to the Reclamation's Yakima Project in the Yakima River Basin in eastern Washington. An important component of the DSS is the physical hydrology modeling. For the application to the Yakima River Basin, the physical hydrology component consisted of constructing four watershed models using the U.S. Geological Survey's Precipitation-Runoff Modeling System within the Modular Modeling System. The implementation of these models is described. To facilitate calibration of the models, mean annual streamflow also was estimated for ungaged subbasins. The models were calibrated for water years 1950-94 and tested for water years 1995-98. The integration of the models in the DSS for real-time water-management operations using an interface termed the Object User Interface is also described. The models were incorporated in the DSS for use in long-term to short-term planning and have been used in a real-time operational mode since water year 1999.

Student Modeling in Orthopedic Surgery Training: Exploiting Symbiosis between Temporal Bayesian Networks and Fine-Grained Didactic Analysis

ERIC Educational Resources Information Center

Chieu, Vu Minh; Luengo, Vanda; Vadcard, Lucile; Tonetti, Jerome

2010-01-01

Cognitive approaches have been used for student modeling in intelligent tutoring systems (ITSs). Many of those systems have tackled fundamental subjects such as mathematics, physics, and computer programming. The change of the student's cognitive behavior over time, however, has not been considered and modeled systematically. Furthermore, the…

Towards an integrated forecasting system for fisheries on habitat-bound stocks

NASA Astrophysics Data System (ADS)

Christensen, A.; Butenschön, M.; Gürkan, Z.; Allen, I. J.

2013-03-01

First results of a coupled modelling and forecasting system for fisheries on habitat-bound stocks are being presented. The system consists currently of three mathematically, fundamentally different model subsystems coupled offline: POLCOMS providing the physical environment implemented in the domain of the north-west European shelf, the SPAM model which describes sandeel stocks in the North Sea, and the third component, the SLAM model, which connects POLCOMS and SPAM by computing the physical-biological interaction. Our major experience by the coupling model subsystems is that well-defined and generic model interfaces are very important for a successful and extendable coupled model framework. The integrated approach, simulating ecosystem dynamics from physics to fish, allows for analysis of the pathways in the ecosystem to investigate the propagation of changes in the ocean climate and to quantify the impacts on the higher trophic level, in this case the sandeel population, demonstrated here on the basis of hindcast data. The coupled forecasting system is tested for some typical scientific questions appearing in spatial fish stock management and marine spatial planning, including determination of local and basin-scale maximum sustainable yield, stock connectivity and source/sink structure. Our presented simulations indicate that sandeel stocks are currently exploited close to the maximum sustainable yield, even though periodic overfishing seems to have occurred, but large uncertainty is associated with determining stock maximum sustainable yield due to stock inherent dynamics and climatic variability. Our statistical ensemble simulations indicates that the predictive horizon set by climate interannual variability is 2-6 yr, after which only an asymptotic probability distribution of stock properties, like biomass, are predictable.

Mirror neuron system and observational learning: behavioral and neurophysiological evidence.

PubMed

Lago-Rodriguez, Angel; Lopez-Alonso, Virginia; Fernández-del-Olmo, Miguel

2013-07-01

Three experiments were performed to study observational learning using behavioral, perceptual, and neurophysiological data. Experiment 1 investigated whether observing an execution model, during physical practice of a transitive task that only presented one execution strategy, led to performance improvements compared with physical practice alone. Experiment 2 investigated whether performing an observational learning protocol improves subjects' action perception. In experiment 3 we evaluated whether the type of practice performed determined the activation of the Mirror Neuron System during action observation. Results showed that, compared with physical practice, observing an execution model during a task that only showed one execution strategy does not provide behavioral benefits. However, an observational learning protocol allows subjects to predict more precisely the outcome of the learned task. Finally, intersperse observation of an execution model with physical practice results in changes of primary motor cortex activity during the observation of the motor pattern previously practiced, whereas modulations in the connectivity between primary and non primary motor areas (PMv-M1; PPC-M1) were not affected by the practice protocol performed by the observer. Copyright © 2013 Elsevier B.V. All rights reserved.

Collaborative Project: Improving the Representation of Coastal and Estuarine Processes in Earth System Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bryan, Frank; Dennis, John; MacCready, Parker

This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation.

Final Report Collaborative Project: Improving the Representation of Coastal and Estuarine Processes in Earth System Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bryan, Frank; Dennis, John; MacCready, Parker

This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation.

The Impact of STTP on the GEFS Forecast of Week-2 and Beyond in the Presence of Stochastic Physics

NASA Astrophysics Data System (ADS)

Hou, D.

2015-12-01

The Stochastic Total Tendency Perturbation (STTP) scheme was designed to represent the model related uncertainties not considered in the numerical model itself and the physics based stochastic schemes. It has been applied in NCEP's Global Ensemble Forecast System (GEFS) since 2010, showing significant positive impacts on the forecast with improved spread-error ratio and probabilistic forecast skills. The scheme is robust and it went well with the resolution increases and model improvements in 2012 and 2015 with minimum changes. Recently, a set of stochastic physics schemes are coded in the Global Forecast System model and tested in the GEFS package. With these schemes turned on and STTP off, the forecast performance is comparable or even superior to the operational GEFS, in which STTP is the only contributor to the model related uncertainties. This is true especially in week one. However, over the second week and beyond, both the experimental and the operational GEFS has insufficient spread, especially over the warmer seasons. This is a major challenge when the GEFS is extended to sub-seasonal (week 4-6) time scales. The impact of STTP on the GEFS forecast in the presence of stochastic physics is investigated by turning both the stochastic physics schemes and STTP on and carefully tuning their amplitudes. Analysis will be focused on the forecast of extended range, especially week 2. Its impacts on week 3-4 will also be addressed.

Statistical and engineering methods for model enhancement

NASA Astrophysics Data System (ADS)

Chang, Chia-Jung

Models which describe the performance of physical process are essential for quality prediction, experimental planning, process control and optimization. Engineering models developed based on the underlying physics/mechanics of the process such as analytic models or finite element models are widely used to capture the deterministic trend of the process. However, there usually exists stochastic randomness in the system which may introduce the discrepancy between physics-based model predictions and observations in reality. Alternatively, statistical models can be used to develop models to obtain predictions purely based on the data generated from the process. However, such models tend to perform poorly when predictions are made away from the observed data points. This dissertation contributes to model enhancement research by integrating physics-based model and statistical model to mitigate the individual drawbacks and provide models with better accuracy by combining the strengths of both models. The proposed model enhancement methodologies including the following two streams: (1) data-driven enhancement approach and (2) engineering-driven enhancement approach. Through these efforts, more adequate models are obtained, which leads to better performance in system forecasting, process monitoring and decision optimization. Among different data-driven enhancement approaches, Gaussian Process (GP) model provides a powerful methodology for calibrating a physical model in the presence of model uncertainties. However, if the data contain systematic experimental errors, the GP model can lead to an unnecessarily complex adjustment of the physical model. In Chapter 2, we proposed a novel enhancement procedure, named as “Minimal Adjustment”, which brings the physical model closer to the data by making minimal changes to it. This is achieved by approximating the GP model by a linear regression model and then applying a simultaneous variable selection of the model and experimental bias terms. Two real examples and simulations are presented to demonstrate the advantages of the proposed approach. Different from enhancing the model based on data-driven perspective, an alternative approach is to focus on adjusting the model by incorporating the additional domain or engineering knowledge when available. This often leads to models that are very simple and easy to interpret. The concepts of engineering-driven enhancement are carried out through two applications to demonstrate the proposed methodologies. In the first application where polymer composite quality is focused, nanoparticle dispersion has been identified as a crucial factor affecting the mechanical properties. Transmission Electron Microscopy (TEM) images are commonly used to represent nanoparticle dispersion without further quantifications on its characteristics. In Chapter 3, we developed the engineering-driven nonhomogeneous Poisson random field modeling strategy to characterize nanoparticle dispersion status of nanocomposite polymer, which quantitatively represents the nanomaterial quality presented through image data. The model parameters are estimated through the Bayesian MCMC technique to overcome the challenge of limited amount of accessible data due to the time consuming sampling schemes. The second application is to calibrate the engineering-driven force models of laser-assisted micro milling (LAMM) process statistically, which facilitates a systematic understanding and optimization of targeted processes. In Chapter 4, the force prediction interval has been derived by incorporating the variability in the runout parameters as well as the variability in the measured cutting forces. The experimental results indicate that the model predicts the cutting force profile with good accuracy using a 95% confidence interval. To conclude, this dissertation is the research drawing attention to model enhancement, which has considerable impacts on modeling, design, and optimization of various processes and systems. The fundamental methodologies of model enhancement are developed and further applied to various applications. These research activities developed engineering compliant models for adequate system predictions based on observational data with complex variable relationships and uncertainty, which facilitate process planning, monitoring, and real-time control.

Weak Galilean invariance as a selection principle for coarse-grained diffusive models.

PubMed

Cairoli, Andrea; Klages, Rainer; Baule, Adrian

2018-05-29

How does the mathematical description of a system change in different reference frames? Galilei first addressed this fundamental question by formulating the famous principle of Galilean invariance. It prescribes that the equations of motion of closed systems remain the same in different inertial frames related by Galilean transformations, thus imposing strong constraints on the dynamical rules. However, real world systems are often described by coarse-grained models integrating complex internal and external interactions indistinguishably as friction and stochastic forces. Since Galilean invariance is then violated, there is seemingly no alternative principle to assess a priori the physical consistency of a given stochastic model in different inertial frames. Here, starting from the Kac-Zwanzig Hamiltonian model generating Brownian motion, we show how Galilean invariance is broken during the coarse-graining procedure when deriving stochastic equations. Our analysis leads to a set of rules characterizing systems in different inertial frames that have to be satisfied by general stochastic models, which we call "weak Galilean invariance." Several well-known stochastic processes are invariant in these terms, except the continuous-time random walk for which we derive the correct invariant description. Our results are particularly relevant for the modeling of biological systems, as they provide a theoretical principle to select physically consistent stochastic models before a validation against experimental data.

Accelerator System Model (ASM) user manual with physics and engineering model documentation. ASM version 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1993-07-01

The Accelerator System Model (ASM) is a computer program developed to model proton radiofrequency accelerators and to carry out system level trade studies. The ASM FORTRAN subroutines are incorporated into an intuitive graphical user interface which provides for the {open_quotes}construction{close_quotes} of the accelerator in a window on the computer screen. The interface is based on the Shell for Particle Accelerator Related Codes (SPARC) software technology written for the Macintosh operating system in the C programming language. This User Manual describes the operation and use of the ASM application within the SPARC interface. The Appendix provides a detailed description of themore » physics and engineering models used in ASM. ASM Version 1.0 is joint project of G. H. Gillespie Associates, Inc. and the Accelerator Technology (AT) Division of the Los Alamos National Laboratory. Neither the ASM Version 1.0 software nor this ASM Documentation may be reproduced without the expressed written consent of both the Los Alamos National Laboratory and G. H. Gillespie Associates, Inc.« less

An Artificially Intelligent Physical Model-Checking Approach to Detect Switching-Related Attacks on Power Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

El Hariri, Mohamad; Faddel, Samy; Mohammed, Osama

Decentralized and hierarchical microgrid control strategies have lain the groundwork for shaping the future smart grid. Such control approaches require the cooperation between microgrid operators in control centers, intelligent microcontrollers, and remote terminal units via secure and reliable communication networks. In order to enhance the security and complement the work of network intrusion detection systems, this paper presents an artificially intelligent physical model-checking that detects tampered-with circuit breaker switching control commands whether, due to a cyber-attack or human error. In this technique, distributed agents, which are monitoring sectionalized areas of a given microgrid, will be trained and continuously adapted tomore » verify that incoming control commands do not violate the physical system operational standards and do not put the microgrid in an insecure state. The potential of this approach has been tested by deploying agents that monitor circuit breakers status commands on a 14-bus IEEE benchmark system. The results showed the accuracy of the proposed framework in characterizing the power system and successfully detecting malicious and/or erroneous control commands.« less

Characterizing the Physics of Plant Root Gravitropism: A Systems Modeling Approach

DTIC Science & Technology

1999-01-01

with its root directly downward, the root and stem undergo a gravitropic response. Statoliths (gravity-sensing organelles) within the root cap respond...this study is to model the plant root gravitropic response using classical controls and system identification principles. Specific objectives of this

Modeling meniscus rise in capillary tubes using fluid in rigid-body motion approach

NASA Astrophysics Data System (ADS)

Hamdan, Mohammad O.; Abu-Nabah, Bassam A.

2018-04-01

In this study, a new term representing net flux rate of linear momentum is introduced to Lucas-Washburn equation. Following a fluid in rigid-body motion in modeling the meniscus rise in vertical capillary tubes transforms the nonlinear Lucas-Washburn equation to a linear mass-spring-damper system. The linear nature of mass-spring-damper system with constant coefficients offers a nondimensional analytical solution where meniscus dynamics are dictated by two parameters, namely the system damping ratio and its natural frequency. This connects the numerous fluid-surface interaction physical and geometrical properties to rather two nondimensional parameters, which capture the underlying physics of meniscus dynamics in three distinct cases, namely overdamped, critically damped, and underdamped systems. Based on experimental data available in the literature and the understanding meniscus dynamics, the proposed model brings a new approach of understanding the system initial conditions. Accordingly, a closed form relation is produced for the imbibition velocity, which equals half of the Bosanquet velocity divided by the damping ratio. The proposed general analytical model is ideal for overdamped and critically damped systems. While for underdamped systems, the solution shows fair agreement with experimental measurements once the effective viscosity is determined. Moreover, the presented model shows meniscus oscillations around equilibrium height occur if the damping ratio is less than one.

Functional and Physical Outcomes following Use of a Flexible CO2 Laser Fiber and Bipolar Electrocautery in Close Proximity to the Rat Sciatic Nerve with Correlation to an In Vitro Thermal Profile Model

PubMed Central

Robinson, A. M.; Fishman, A. J.; Bendok, B. R.; Richter, C.-P.

2015-01-01

This study compared functional and physical collateral damage to a nerve when operating a Codman MALIS Bipolar Electrosurgical System CMC-III or a CO2 laser coupled to a laser, with correlation to an in vitro model of heating profiles created by the devices in thermochromic ink agarose. Functional damage of the rat sciatic nerve after operating the MALIS or CO2 laser at various power settings and proximities to the nerve was measured by electrically evoked nerve action potentials, and histology of the nerve was used to assess physical damage. Thermochromic ink dissolved in agarose was used to model the spatial and temporal profile of the collateral heating zone of the electrosurgical system and the laser ablation cone. We found that this laser can be operated at 2 W directly above the nerve with minimal damage, while power settings of 5 W and 10 W resulted in acute functional and physical nerve damage, correlating with the maximal heating cone in the thermochromic ink model. MALIS settings up to 40 (11 W) did not result in major functional or physical nerve damage until the nerve was between the forceps tips, correlating with the hottest zone, localized discretely between the tips. PMID:25699266

General Pressurization Model in Simscape

NASA Technical Reports Server (NTRS)

Servin, Mario; Garcia, Vicky

2010-01-01

System integration is an essential part of the engineering design process. The Ares I Upper Stage (US) is a complex system which is made up of thousands of components assembled into subsystems including a J2-X engine, liquid hydrogen (LH2) and liquid oxygen (LO2) tanks, avionics, thrust vector control, motors, etc. System integration is the task of connecting together all of the subsystems into one large system. To ensure that all the components will "fit together" as well as safety and, quality, integration analysis is required. Integration analysis verifies that, as an integrated system, the system will behave as designed. Models that represent the actual subsystems are built for more comprehensive analysis. Matlab has been an instrument widely use by engineers to construct mathematical models of systems. Simulink, one of the tools offered by Matlab, provides multi-domain graphical environment to simulate and design time-varying systems. Simulink is a powerful tool to analyze the dynamic behavior of systems over time. Furthermore, Simscape, a tool provided by Simulink, allows users to model physical (such as mechanical, thermal and hydraulic) systems using physical networks. Using Simscape, a model representing an inflow of gas to a pressurized tank was created where the temperature and pressure of the tank are measured over time to show the behavior of the gas. By further incorporation of Simscape into model building, the full potential of this software can be discovered and it hopefully can become a more utilized tool.

Entrainment in the master equation.

PubMed

Margaliot, Michael; Grüne, Lars; Kriecherbauer, Thomas

2018-04-01

The master equation plays an important role in many scientific fields including physics, chemistry, systems biology, physical finance and sociodynamics. We consider the master equation with periodic transition rates. This may represent an external periodic excitation like the 24 h solar day in biological systems or periodic traffic lights in a model of vehicular traffic. Using tools from systems and control theory, we prove that under mild technical conditions every solution of the master equation converges to a periodic solution with the same period as the rates. In other words, the master equation entrains (or phase locks) to periodic excitations. We describe two applications of our theoretical results to important models from statistical mechanics and epidemiology.

Entrainment in the master equation

PubMed Central

Grüne, Lars; Kriecherbauer, Thomas

2018-01-01

The master equation plays an important role in many scientific fields including physics, chemistry, systems biology, physical finance and sociodynamics. We consider the master equation with periodic transition rates. This may represent an external periodic excitation like the 24 h solar day in biological systems or periodic traffic lights in a model of vehicular traffic. Using tools from systems and control theory, we prove that under mild technical conditions every solution of the master equation converges to a periodic solution with the same period as the rates. In other words, the master equation entrains (or phase locks) to periodic excitations. We describe two applications of our theoretical results to important models from statistical mechanics and epidemiology. PMID:29765669

Metallic Rotor Sizing and Performance Model for Flywheel Systems

NASA Technical Reports Server (NTRS)

Moore, Camille J.; Kraft, Thomas G.

2012-01-01

The NASA Glenn Research Center (GRC) is developing flywheel system requirements and designs for terrestrial and spacecraft applications. Several generations of flywheels have been designed and tested at GRC using in-house expertise in motors, magnetic bearings, controls, materials and power electronics. The maturation of a flywheel system from the concept phase to the preliminary design phase is accompanied by maturation of the Integrated Systems Performance model, where estimating relationships are replaced by physics based analytical techniques. The modeling can incorporate results from engineering model testing and emerging detail from the design process.

Execution Of Systems Integration Principles During Systems Engineering Design

DTIC Science & Technology

2016-09-01

This thesis discusses integration failures observed by DOD and non - DOD systems as, inadequate stakeholder analysis, incomplete problem space and design ... design , development, test and deployment of a system. A lifecycle structure consists of phases within a methodology or process model. There are many...investigate design decisions without the need to commit to physical forms; “ experimental investigation using a model yields design or operational

Let's Get Physical: Teaching Physics through Gymnastics

ERIC Educational Resources Information Center

Sojourner, Elena J.; Burgasser, Adam J.; Weise, Eric D.

2018-01-01

The concept of embodied learning--that we can learn with our bodies and with our minds--is a well-established concept in physics and math education research, and includes symbolic understanding (e.g., gestures that track how students think or facilitate learning to model complex systems of energy flow) as well as the literal experience of…

Astrophysics today

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cameron, A.G.W.

1984-01-01

Examining recent history, current trends, and future possibilities, the author reports the frontiers of research on the solar system, stars, galactic physics, and cosmological physics. The book discusses the great discoveries in astronomy and astrophysics and examines the circumstances in which they occurred. It discusses the physics of white dwarfs, the inflationary universe, the extinction of dinosaurs, black hole, cosmological models, and much more.

A Call To Action for Physics Departments: Findings and Recommendations of the National Task Force on Teacher Education in Physics

NASA Astrophysics Data System (ADS)

Vokos, Stamatis

2010-10-01

The National Task Force on Teacher Education in Physics (T-TEP) concluded its two-year investigation of the professional preparation of teachers of physics in the U.S. T-TEP, formed by APS, AAPT, and AIP, was charged with (a) identifying generalizable, yet flexible, strategies that institutions, and in particular physics departments and schools or colleges of education, can employ to increase the number of qualified physics teachers, (b) identifying effective strategies in recruitment, models of professional preparation, and higher education systems of support during the first three years of teaching, and (c) articulating research, policy, and funding implications. In this talk, the major findings and recommendations of the T-TEP report will be discussed and ways to leverage the report to transform the physics teacher education system will be outlined.

Toward an Integrated Design, Inspection and Redundancy Research Program.

DTIC Science & Technology

1984-01-01

William Creelman William H. Silcox National Marine Service Standard Oil Company of California St. Louis, Missouri San Francisco, California .-- N...develop physical models and generic tools for analyzing the effects of redundancy, reserve strength, and residual strength on the system behavior of marine...probabilistic analyses to be applicable to real-world problems, this program needs to provide - the deterministic physical models and generic tools upon

Scientific Data Services -- A High-Performance I/O System with Array Semantics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Kesheng; Byna, Surendra; Rotem, Doron

2011-09-21

As high-performance computing approaches exascale, the existing I/O system design is having trouble keeping pace in both performance and scalability. We propose to address this challenge by adopting database principles and techniques in parallel I/O systems. First, we propose to adopt an array data model because many scientific applications represent their data in arrays. This strategy follows a cardinal principle from database research, which separates the logical view from the physical layout of data. This high-level data model gives the underlying implementation more freedom to optimize the physical layout and to choose the most effective way of accessing the data.more » For example, knowing that a set of write operations is working on a single multi-dimensional array makes it possible to keep the subarrays in a log structure during the write operations and reassemble them later into another physical layout as resources permit. While maintaining the high-level view, the storage system could compress the user data to reduce the physical storage requirement, collocate data records that are frequently used together, or replicate data to increase availability and fault-tolerance. Additionally, the system could generate secondary data structures such as database indexes and summary statistics. We expect the proposed Scientific Data Services approach to create a “live” storage system that dynamically adjusts to user demands and evolves with the massively parallel storage hardware.« less

Implementing a modeling software for animated protein-complex interactions using a physics simulation library.

PubMed

Ueno, Yutaka; Ito, Shuntaro; Konagaya, Akihiko

2014-12-01

To better understand the behaviors and structural dynamics of proteins within a cell, novel software tools are being developed that can create molecular animations based on the findings of structural biology. This study proposes our method developed based on our prototypes to detect collisions and examine the soft-body dynamics of molecular models. The code was implemented with a software development toolkit for rigid-body dynamics simulation and a three-dimensional graphics library. The essential functions of the target software system included the basic molecular modeling environment, collision detection in the molecular models, and physical simulations of the movement of the model. Taking advantage of recent software technologies such as physics simulation modules and interpreted scripting language, the functions required for accurate and meaningful molecular animation were implemented efficiently.

Causal tapestries for psychology and physics.

PubMed

Sulis, William H

2012-04-01

Archetypal dynamics is a formal approach to the modeling of information flow in complex systems used to study emergence. It is grounded in the Fundamental Triad of realisation (system), interpretation (archetype) and representation (formal model). Tapestries play a fundamental role in the framework of archetypal dynamics as a formal representational system. They represent information flow by means of multi layered, recursive, interlinked graphical structures that express both geometry (form or sign) and logic (semantics). This paper presents a detailed mathematical description of a specific tapestry model, the causal tapestry, selected for use in describing behaving systems such as appear in psychology and physics from the standpoint of Process Theory. Causal tapestries express an explicit Lorentz invariant transient now generated by means of a reality game. Observables are represented by tapestry informons while subjective or hidden components (for example intellectual and emotional processes) are incorporated into the reality game that determines the tapestry dynamics. As a specific example, we formulate a random graphical dynamical system using causal tapestries.

Predicting remaining life by fusing the physics of failure modeling with diagnostics

NASA Astrophysics Data System (ADS)

Kacprzynski, G. J.; Sarlashkar, A.; Roemer, M. J.; Hess, A.; Hardman, B.

2004-03-01

Technology that enables failure prediction of critical machine components (prognostics) has the potential to significantly reduce maintenance costs and increase availability and safety. This article summarizes a research effort funded through the U.S. Defense Advanced Research Projects Agency and Naval Air System Command aimed at enhancing prognostic accuracy through more advanced physics-of-failure modeling and intelligent utilization of relevant diagnostic information. H-60 helicopter gear is used as a case study to introduce both stochastic sub-zone crack initiation and three-dimensional fracture mechanics lifing models along with adaptive model updating techniques for tuning key failure mode variables at a local material/damage site based on fused vibration features. The overall prognostic scheme is aimed at minimizing inherent modeling and operational uncertainties via sensed system measurements that evolve as damage progresses.

Development of a Three-Dimensional Spectral Element Model for NWP: Idealized Simulations on the Sphere

NASA Astrophysics Data System (ADS)

Viner, K.; Reinecke, P. A.; Gabersek, S.; Flagg, D. D.; Doyle, J. D.; Martini, M.; Ryglicki, D.; Michalakes, J.; Giraldo, F.

2016-12-01

NEPTUNE: the Navy Environmental Prediction sysTem Using the NUMA*corE, is a 3D spectral element atmospheric model composed of a full suite of physics parameterizations and pre- and post-processing infrastructure with plans for data assimilation and coupling components to a variety of Earth-system models. This talk will focus on the initial struggles and solutions in adapting NUMA for stable and accurate integration on the sphere using both the deep atmosphere equations and a newly developed shallow-atmosphere approximation, as demonstrated through idealized test cases. In addition, details of the physics-dynamics coupling methodology will be discussed. NEPTUNE results for test cases from the 2016 Dynamical Core Model Intercomparison Project (DCMIP-2016) will be shown and discussed. *NUMA: Nonhydrostatic Unified Model of the Atmosphere; Kelly and Giraldo 2012, JCP

Will electrical cyber-physical interdependent networks undergo first-order transition under random attacks?

NASA Astrophysics Data System (ADS)

Ji, Xingpei; Wang, Bo; Liu, Dichen; Dong, Zhaoyang; Chen, Guo; Zhu, Zhenshan; Zhu, Xuedong; Wang, Xunting

2016-10-01

Whether the realistic electrical cyber-physical interdependent networks will undergo first-order transition under random failures still remains a question. To reflect the reality of Chinese electrical cyber-physical system, the "partial one-to-one correspondence" interdependent networks model is proposed and the connectivity vulnerabilities of three realistic electrical cyber-physical interdependent networks are analyzed. The simulation results show that due to the service demands of power system the topologies of power grid and its cyber network are highly inter-similar which can effectively avoid the first-order transition. By comparing the vulnerability curves between electrical cyber-physical interdependent networks and its single-layer network, we find that complex network theory is still useful in the vulnerability analysis of electrical cyber-physical interdependent networks.

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei--Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2010-01-01

In recent years, exponentially increasing computer power extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale models can be run in grid size similar to cloud resolving models through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model). (2) a regional scale model (a NASA unified weather research and forecast, W8F). (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling systems to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use the multi-satellite simulator to improve precipitation processes will be discussed.

Using Multi-Scale Modeling Systems to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2010-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

Model-Based Detection of Radioactive Contraband for Harbor Defense Incorporating Compton Scattering Physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Candy, J V; Chambers, D H; Breitfeller, E F

2010-03-02

The detection of radioactive contraband is a critical problem is maintaining national security for any country. Photon emissions from threat materials challenge both detection and measurement technologies especially when concealed by various types of shielding complicating the transport physics significantly. This problem becomes especially important when ships are intercepted by U.S. Coast Guard harbor patrols searching for contraband. The development of a sequential model-based processor that captures both the underlying transport physics of gamma-ray emissions including Compton scattering and the measurement of photon energies offers a physics-based approach to attack this challenging problem. The inclusion of a basic radionuclide representationmore » of absorbed/scattered photons at a given energy along with interarrival times is used to extract the physics information available from the noisy measurements portable radiation detection systems used to interdict contraband. It is shown that this physics representation can incorporated scattering physics leading to an 'extended' model-based structure that can be used to develop an effective sequential detection technique. The resulting model-based processor is shown to perform quite well based on data obtained from a controlled experiment.« less

Computer-based creativity enhanced conceptual design model for non-routine design of mechanical systems

NASA Astrophysics Data System (ADS)

Li, Yutong; Wang, Yuxin; Duffy, Alex H. B.

2014-11-01

Computer-based conceptual design for routine design has made great strides, yet non-routine design has not been given due attention, and it is still poorly automated. Considering that the function-behavior-structure(FBS) model is widely used for modeling the conceptual design process, a computer-based creativity enhanced conceptual design model(CECD) for non-routine design of mechanical systems is presented. In the model, the leaf functions in the FBS model are decomposed into and represented with fine-grain basic operation actions(BOA), and the corresponding BOA set in the function domain is then constructed. Choosing building blocks from the database, and expressing their multiple functions with BOAs, the BOA set in the structure domain is formed. Through rule-based dynamic partition of the BOA set in the function domain, many variants of regenerated functional schemes are generated. For enhancing the capability to introduce new design variables into the conceptual design process, and dig out more innovative physical structure schemes, the indirect function-structure matching strategy based on reconstructing the combined structure schemes is adopted. By adjusting the tightness of the partition rules and the granularity of the divided BOA subsets, and making full use of the main function and secondary functions of each basic structure in the process of reconstructing of the physical structures, new design variables and variants are introduced into the physical structure scheme reconstructing process, and a great number of simpler physical structure schemes to accomplish the overall function organically are figured out. The creativity enhanced conceptual design model presented has a dominant capability in introducing new deign variables in function domain and digging out simpler physical structures to accomplish the overall function, therefore it can be utilized to solve non-routine conceptual design problem.

Condensed-Matter Physics.

ERIC Educational Resources Information Center

Hirsch, Jorge E.; Scalapino, Douglas J.

1983-01-01

Discusses ways computers are being used in condensed-matter physics by experimenters and theorists. Experimenters use them to control experiments and to gather and analyze data. Theorists use them for detailed predictions based on realistic models and for studies on systems not realizable in practice. (JN)

Longitudinal trajectories of self-system processes and depressive symptoms among maltreated and nonmaltreated children

PubMed Central

Kim, Jungmeen; Cicchetti, Dante

2006-01-01

This study used latent growth modeling to investigate longitudinal relationships between self-system processes and depressive symptoms among maltreated (n=142) and nonmaltreated children (n=109) aged 6–11 years. On average, self-esteem and self-agency increased and depressive symptoms decreased over time. Multivariate growth modeling indicated that, regardless of gender, physical abuse was negatively related to initial levels of self-esteem, and physical abuse and physical neglect were positively associated with initial levels of depressive symptoms. Emotional maltreatment was predictive of changes in self-esteem and changes in depressive symptoms. Initial levels of self-esteem were negatively associated with initial levels of depressive symptoms. The findings contribute to enhancing our understanding of the developmental processes whereby early maltreatment experiences are linked to later maladjustment. PMID:16686792

Physical parameters in long-decay coronal enhancements. [from Skylab X ray observations

NASA Technical Reports Server (NTRS)

Maccombie, W. J.; Rust, D. M.

1979-01-01

Four well-observed long-decay X-ray enhancements (LDEs) are examined which were associated with filament eruptions, white-light transients, and loop prominence systems. In each case the physical parameters of the X-ray-emitting plasma are determined, including the spatial distribution and temporal evolution of temperature and density. The results and recent analyses of other aspects of the four LDEs are compared with current models of loop prominence systems. It is concluded that only a magnetic-reconnection model, such as that proposed by Kopp and Pneuman (1976) is consistent with the observations.

Physics and Process Modeling (PPM) and Other Propulsion R and T. Volume 1; Materials Processing, Characterization, and Modeling; Lifting Models

NASA Technical Reports Server (NTRS)

1997-01-01

This CP contains the extended abstracts and presentation figures of 36 papers presented at the PPM and Other Propulsion R&T Conference. The focus of the research described in these presentations is on materials and structures technologies that are parts of the various projects within the NASA Aeronautics Propulsion Systems Research and Technology Base Program. These projects include Physics and Process Modeling; Smart, Green Engine; Fast, Quiet Engine; High Temperature Engine Materials Program; and Hybrid Hyperspeed Propulsion. Also presented were research results from the Rotorcraft Systems Program and work supported by the NASA Lewis Director's Discretionary Fund. Authors from NASA Lewis Research Center, industry, and universities conducted research in the following areas: material processing, material characterization, modeling, life, applied life models, design techniques, vibration control, mechanical components, and tribology. Key issues, research accomplishments, and future directions are summarized in this publication.

Automated Analysis of Stateflow Models

NASA Technical Reports Server (NTRS)

Bourbouh, Hamza; Garoche, Pierre-Loic; Garion, Christophe; Gurfinkel, Arie; Kahsaia, Temesghen; Thirioux, Xavier

2017-01-01

Stateflow is a widely used modeling framework for embedded and cyber physical systems where control software interacts with physical processes. In this work, we present a framework a fully automated safety verification technique for Stateflow models. Our approach is two-folded: (i) we faithfully compile Stateflow models into hierarchical state machines, and (ii) we use automated logic-based verification engine to decide the validity of safety properties. The starting point of our approach is a denotational semantics of State flow. We propose a compilation process using continuation-passing style (CPS) denotational semantics. Our compilation technique preserves the structural and modal behavior of the system. The overall approach is implemented as an open source toolbox that can be integrated into the existing Mathworks Simulink Stateflow modeling framework. We present preliminary experimental evaluations that illustrate the effectiveness of our approach in code generation and safety verification of industrial scale Stateflow models.

SimCheck: An Expressive Type System for Simulink

NASA Technical Reports Server (NTRS)

Roy, Pritam; Shankar, Natarajan

2010-01-01

MATLAB Simulink is a member of a class of visual languages that are used for modeling and simulating physical and cyber-physical systems. A Simulink model consists of blocks with input and output ports connected using links that carry signals. We extend the type system of Simulink with annotations and dimensions/units associated with ports and links. These types can capture invariants on signals as well as relations between signals. We define a type-checker that checks the wellformedness of Simulink blocks with respect to these type annotations. The type checker generates proof obligations that are solved by SRI's Yices solver for satisfiability modulo theories (SMT). This translation can be used to detect type errors, demonstrate counterexamples, generate test cases, or prove the absence of type errors. Our work is an initial step toward the symbolic analysis of MATLAB Simulink models.

Examining protein-lipid interactions in model systems with a new squarylium fluorescent dye.

PubMed

Ioffe, Valeriya M; Gorbenko, Galyna P; Tatarets, Anatoliy L; Patsenker, Leonid D; Terpechnig, Ewald A

2006-07-01

The applicability of newly synthesized squarylium dye Sq to probing the changes in physical characteristics of lipid bilayer on the formation of protein-lipid complexes has been evaluated. Lipid vesicles composed of zwitterionic phospholipid phosphatidylcholine (PC) and its mixtures with positively charged detergent cetyltrimethylammonium bromide (CTAB), anionic phospholipid cardiolipin (CL), and cholesterol (Chol) were employed as lipid component of model membrane systems while protein constituent was represented by lysozyme (Lz). Fluorescence intensity of Sq was found to decrease on Lz association with lipid bilayer. This effect was observed in all kinds of model systems suggesting that Sq is sensitive to modification of lipid bilayer physical properties on hydrophobic protein-lipid interactions. It was found that Sq spectral response to variations in Chol content depends on relative contributions of electrostatic and hydrophobic components of Lz-membrane binding.

A review of physically based models for soil erosion by water

NASA Astrophysics Data System (ADS)

Le, Minh-Hoang; Cerdan, Olivier; Sochala, Pierre; Cheviron, Bruno; Brivois, Olivier; Cordier, Stéphane

2010-05-01

Physically-based models rely on fundamental physical equations describing stream flow and sediment and associated nutrient generation in a catchment. This paper reviews several existing erosion and sediment transport approaches. The process of erosion include soil detachment, transport and deposition, we present various forms of equations and empirical formulas used when modelling and quantifying each of these processes. In particular, we detail models describing rainfall and infiltration effects and the system of equations to describe the overland flow and the evolution of the topography. We also present the formulas for the flow transport capacity and the erodibility functions. Finally, we present some recent numerical schemes to approach the shallow water equations and it's coupling with infiltration and erosion source terms.

Oxygen cycling in the northern Benguela Upwelling System: Modelling oxygen sources and sinks

NASA Astrophysics Data System (ADS)

Schmidt, Martin; Eggert, Anja

2016-12-01

This paper elucidates the oxygen dynamics in the northern Benguela Upwelling System by means of process oriented, numerical modelling. Owing to the complex physical-biological interaction in this system, a coupled hydrodynamic-biogeochemical model is required to grasp the various aspects of the oxygen dynamics. We used high-resolution atmospheric fields derived from observations to force our model, available since 1999. The model results represent a 15 years, consistent data set of realistic hydrographic and ecosystem variables, including oxygen distribution patterns. After a concise description of the main aspects of the model, we use the model data to analyse the components contributing to the oxygen dynamics, namely, the ocean circulation, the exchange between ocean and atmosphere as well as the local biogeochemical oxygen cycling in the system. We thoroughly validate the model with available field observations and remote sensing data. The strengths of coastal upwelling, which controls the nutrient supply to the euphotic zone, as well as the poleward undercurrent that carries oxygen and nutrients to the shelf in the northern Benguela Upwelling System are well reproduced in the model. Among the biological oxygen sinks, mineralisation in the sediment, respiration of zooplankton and nitrification in the water column are important. We also found that vertical migration of zooplankton in response to the oxygen conditions provides a regulating feedback, which may prevent a complete deoxygenation of suboxic waters. As long as oxygen or nitrate are available in the bottom waters, the activities of chemolithoautotrophic sulphur bacteria on the sediment surface keep the redoxcline within the sediment and prevent the release of hydrogen sulphide into the water column. By horizontal integration of the simulated ocean-atmosphere oxygen flux, it can be shown that the Kunene upwelling cell between 16 ° S and 18 ° S is a boundary between the equatorial ocean, characterise by weak oxygen release to the atmosphere, and the subtropical Benguela Upwelling System governed by an enhanced and seasonal varying flux. Furthermore, a comparison of oxygen fluxes controlled by physical transport versus biogeochemical processes shows that the physical processes dominate in the northern Benguela Upwelling System.

Environmental Characterization of Mine Countermeasure Test Ranges: Hydrography and Water Column Optics

DTIC Science & Technology

2015-09-30

changes in near-shore water columns and support companion laser imaging system tests. The physical, biological and optical oceanographic data...developed under this project will be used as input to optical and environmental models to assess the performance characteristics of laser imaging systems...OBJECTIVES We proposed to characterize the physical, biological and optical fields present during deployments of the Streak Tube Imaging Lidar

Emerging concepts for management of river ecosystems and challenges to applied integration of physical and biological sciences in the Pacific Northwest, USA

Treesearch

Bruce E. Rieman; Jason B. Dunham; James L. Clayton

2006-01-01

Integration of biological and physical concepts is necessary to understand and conserve the ecological integrity of river systems. Past attempts at integration have often focused at relatively small scales and on mechanistic models that may not capture the complexity of natural systems leaving substantial uncertainty about ecological responses to management actions....

Development and Exploration of the Core-Corona Model of Imploding Plasma Loads.

DTIC Science & Technology

1980-07-01

cal relaxation processes can maintain an isothermal system . The final constraint in the original core-corona model equations was that of quasi-static...on the energy balance. The detailed physics of these upgrades and their improvement of the quantitative modeling of the system are discussed in the...participate in lengthening the radiaton pulse. 18 If such motion is favored in these systems , the impact on the radiation pulse length could be

Modeling and Simulation for a Surf Zone Robot

DTIC Science & Technology

2012-12-14

of-freedom surf zone robot is developed and tested with a physical test platform and with a simulated robot in Robot Operating System . Derived from...terrain. The application of the model to future platforms is analyzed and a broad examination of the current state of surf zone robotic systems is...public release; distribution is unlimited MODELING AND SIMULATION FOR A SURF ZONE ROBOT Eric Shuey Lieutenant, United States Navy B.S., Systems

Response of a One-Biosphere Nutrient Modeling System to Regional Land Use and Management Change

EPA Science Inventory

A multi-media system of nitrogen and co-pollutant models describing critical physical and chemical processes that cascade synergistically and competitively through the environment, the economy and society has been developed at the USEPA Office of Research and Development (see fig...

Variable thickness transient ground-water flow model. Volume 1. Formulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reisenauer, A.E.

1979-12-01

Mathematical formulation for the variable thickness transient (VTT) model of an aquifer system is presented. The basic assumptions are described. Specific data requirements for the physical parameters are discussed. The boundary definitions and solution techniques of the numerical formulation of the system of equations are presented.

Building Dynamic Conceptual Physics Understanding

ERIC Educational Resources Information Center

Trout, Charlotte; Sinex, Scott A.; Ragan, Susan

2011-01-01

Models are essential to the learning and doing of science, and systems thinking is key to appreciating many environmental issues. The National Science Education Standards include models and systems in their unifying concepts and processes standard, while the AAAS Benchmarks include them in their common themes chapter. Hyerle and Marzano argue for…

What can formal methods offer to digital flight control systems design

NASA Technical Reports Server (NTRS)

Good, Donald I.

1990-01-01

Formal methods research begins to produce methods which will enable mathematic modeling of the physical behavior of digital hardware and software systems. The development of these methods directly supports the NASA mission of increasing the scope and effectiveness of flight system modeling capabilities. The conventional, continuous mathematics that is used extensively in modeling flight systems is not adequate for accurate modeling of digital systems. Therefore, the current practice of digital flight control system design has not had the benefits of extensive mathematical modeling which are common in other parts of flight system engineering. Formal methods research shows that by using discrete mathematics, very accurate modeling of digital systems is possible. These discrete modeling methods will bring the traditional benefits of modeling to digital hardware and hardware design. Sound reasoning about accurate mathematical models of flight control systems can be an important part of reducing risk of unsafe flight control.

Discrete-time modelling of musical instruments

NASA Astrophysics Data System (ADS)

Välimäki, Vesa; Pakarinen, Jyri; Erkut, Cumhur; Karjalainen, Matti

2006-01-01

This article describes physical modelling techniques that can be used for simulating musical instruments. The methods are closely related to digital signal processing. They discretize the system with respect to time, because the aim is to run the simulation using a computer. The physics-based modelling methods can be classified as mass-spring, modal, wave digital, finite difference, digital waveguide and source-filter models. We present the basic theory and a discussion on possible extensions for each modelling technique. For some methods, a simple model example is chosen from the existing literature demonstrating a typical use of the method. For instance, in the case of the digital waveguide modelling technique a vibrating string model is discussed, and in the case of the wave digital filter technique we present a classical piano hammer model. We tackle some nonlinear and time-varying models and include new results on the digital waveguide modelling of a nonlinear string. Current trends and future directions in physical modelling of musical instruments are discussed.

The Hydra model - a model for what?

PubMed

Gierer, Alfred

2012-01-01

The introductory personal remarks refer to my motivations for choosing research projects, and for moving from physics to molecular biology and then to development, with Hydra as a model system. Historically, Trembley's discovery of Hydra regeneration in 1744 was the beginning of developmental biology as we understand it, with passionate debates about preformation versus de novo generation, mechanisms versus organisms. In fact, seemingly conflicting bottom-up and top-down concepts are both required in combination to understand development. In modern terms, this means analysing the molecules involved, as well as searching for physical principles underlying development within systems of molecules, cells and tissues. During the last decade, molecular biology has provided surprising and impressive evidence that the same types of molecules and molecular systems are involved in pattern formation in a wide range of organisms, including coelenterates like Hydra, and thus appear to have been "invented" early in evolution. Likewise, the features of certain systems, especially those of developmental regulation, are found in many different organisms. This includes the generation of spatial structures by the interplay of self-enhancing activation and "lateral" inhibitory effects of wider range, which is a main topic of my essay. Hydra regeneration is a particularly clear model for the formation of defined patterns within initially near-uniform tissues. In conclusion, this essay emphasizes the analysis of development in terms of physical laws, including the application of mathematics, and insists that Hydra was, and will continue to be, a rewarding model for understanding general features of embryogenesis and regeneration.

A new method for teaching physical examination to junior medical students.

PubMed

Sayma, Meelad; Williams, Hywel Rhys

2016-01-01

Teaching effective physical examination is a key component in the education of medical students. Preclinical medical students often have insufficient clinical knowledge to apply to physical examination recall, which may hinder their learning when taught through certain understanding-based models. This pilot project aimed to develop a method to teach physical examination to preclinical medical students using "core clinical cases", overcoming the need for "rote" learning. This project was developed utilizing three cycles of planning, action, and reflection. Thematic analysis of feedback was used to improve this model, and ensure it met student expectations. A model core clinical case developed in this project is described, with gout as the basis for a "foot and ankle" examination. Key limitations and difficulties encountered on implementation of this pilot are discussed for future users, including the difficulty encountered in "content overload". This approach aims to teach junior medical students physical examination through understanding, using a simulated patient environment. Robust research is now required to demonstrate efficacy and repeatability in the physical examination of other systems.

A Global Data Assimilation System for Atmospheric Aerosol

NASA Technical Reports Server (NTRS)

daSilva, Arlindo

1999-01-01

We will give an overview of an aerosol data assimilation system which combines advances in remote sensing of atmospheric aerosols, aerosol modeling and data assimilation methodology to produce high spatial and temporal resolution 3D aerosol fields. Initially, the Goddard Aerosol Assimilation System (GAAS) will assimilate TOMS, AVHRR and AERONET observations; later we will include MODIS and MISR. This data assimilation capability will allows us to integrate complementing aerosol observations from these platforms, enabling the development of an assimilated aerosol climatology as well as a global aerosol forecasting system in support of field campaigns. Furthermore, this system provides an interactive retrieval framework for each aerosol observing satellites, in particular TOMS and AVHRR. The Goddard Aerosol Assimilation System (GAAS) takes advantage of recent advances in constituent data assimilation at DAO, including flow dependent parameterizations of error covariances and the proper consideration of model bias. For its prognostic transport model, GAAS will utilize the Goddard Ozone, Chemistry, Aerosol, Radiation and Transport (GOCART) model developed at NASA/GSFC Codes 916 and 910.3. GOCART includes the Lin-Rood flux-form, semi-Langrangian transport model with parameterized aerosol chemistry and physical processes for absorbing (dust and black carbon) and non-absorbing aerosols (sulfate and organic carbon). Observations and model fields are combined using a constituent version of DAO's Physical-space Statistical Analysis System (PSAS), including its adaptive quality control system. In this talk we describe the main components of this assimilation system and present preliminary results obtained by assimilating TOMS data.

Can there be a physics of financial markets? Methodological reflections on econophysics

NASA Astrophysics Data System (ADS)

Huber, Tobias A.; Sornette, Didier

2016-12-01

We address the question whether there can be a physical science of financial markets. In particular, we examine the argument that, given the reflexivity of financial markets (i.e., the feedback mechanism between expectations and prices), there is a fundamental difference between social and physical systems, which demands a new scientific method. By providing a selective history of the mutual cross-fertilization between physics and economics, we reflect on the methodological differences of how models and theories get constructed in these fields. We argue that the novel conception of financial markets as complex adaptive systems is one of the most important contributions of econophysics and show that this field of research provides the methods, concepts, and tools to scientifically account for reflexivity. We conclude by arguing that a new science of economic and financial systems should not only be physics-based, but needs to integrate findings from other scientific fields, so that a truly multi-disciplinary complex systems science of financial markets can be built.

Data Assimilation Into Physics-Based Models Via Kalman Filters

NASA Astrophysics Data System (ADS)

Schunk, R. W.; Scherliess, L.; Sojka, J. J.

2002-12-01

The magnetosphere-ionosphere-thermosphere (M-I-T) system is a highly dynamic, coupled, and nonlinear system that can vary significantly from hour to hour at any location. The coupling is particularly strong during geomagnetic storms and substorms, but there are appreciable time delays associated with the transfer of mass, momentum, and energy between the domains. Therefore, both global physics-based models and vast observational data sets are needed to elucidate the dynamics, energetics, and coupling in the M-I-T system. Fortunately, during the coming decade, tens of millions of measurements of the global M-I-T system could become available from a variety of in situ and remote sensing instruments. Some of the measurements will provide direct information about the state variables (densities, drift velocities, and temperatures), while others will provide indirect information, such as optical emissions and magnetic perturbations. The data sources available could include: thousands of ground-based GPS Total Electron Content (TEC) receivers; a world-wide network of ionosondes; hundreds of magnetometers both on the ground and in space; occultations from the COSMIC Satellites, numerous ground-based tomography chains; auroral images from the POLAR Satellite; images of the magnetosphere and plasmasphere from the IMAGE Satellite; SuperDARN radar measurements in the polar regions; the Living With a Star (LWS) Solar Dynamics Observatory and the LWS Radiation Belt and Ionosphere-Thermosphere Storm Probes; and the world-wide network of incoherent scatter radars. To optimize the scientific return and to provide specifications and forecasts for societal applications, the global models and data must be combined in an optimum way. A powerful way of assimilating multiple data types into a time-dependent, physics-based, numerical model is via a Kalman filter. The basic principle of this approach is to combine measurements from multiple instrument types with the information obtained from a physics-based model, taking into account the uncertainties in both the model and measurements. The advantages of this technique and the data sources that might be available will be discussed.

Variable cycle control model for intersection based on multi-source information

NASA Astrophysics Data System (ADS)

Sun, Zhi-Yuan; Li, Yue; Qu, Wen-Cong; Chen, Yan-Yan

2018-05-01

In order to improve the efficiency of traffic control system in the era of big data, a new variable cycle control model based on multi-source information is presented for intersection in this paper. Firstly, with consideration of multi-source information, a unified framework based on cyber-physical system is proposed. Secondly, taking into account the variable length of cell, hysteresis phenomenon of traffic flow and the characteristics of lane group, a Lane group-based Cell Transmission Model is established to describe the physical properties of traffic flow under different traffic signal control schemes. Thirdly, the variable cycle control problem is abstracted into a bi-level programming model. The upper level model is put forward for cycle length optimization considering traffic capacity and delay. The lower level model is a dynamic signal control decision model based on fairness analysis. Then, a Hybrid Intelligent Optimization Algorithm is raised to solve the proposed model. Finally, a case study shows the efficiency and applicability of the proposed model and algorithm.

The use of molten salts as physical models for the study of solidification in metals and semiconductors

NASA Technical Reports Server (NTRS)

Koziol, Jurek K.; Sadoway, Donald R.

1987-01-01

It is presently noted that molten salts possess attributes rendering them attractive as physical models of cast metals in solidification studies. Molten alkali halides have an approximately correct Prandtl number for this modeling of metallic melts, and are transparent to visible light. Attention is given to solidification in the LiCl-KCl system, in order to determine whether such phenomena as solute rejection can be observed and characterized through the application of laser schlieren imaging.

Component-Based Modelling for Scalable Smart City Systems Interoperability: A Case Study on Integrating Energy Demand Response Systems.

PubMed

Palomar, Esther; Chen, Xiaohong; Liu, Zhiming; Maharjan, Sabita; Bowen, Jonathan

2016-10-28

Smart city systems embrace major challenges associated with climate change, energy efficiency, mobility and future services by embedding the virtual space into a complex cyber-physical system. Those systems are constantly evolving and scaling up, involving a wide range of integration among users, devices, utilities, public services and also policies. Modelling such complex dynamic systems' architectures has always been essential for the development and application of techniques/tools to support design and deployment of integration of new components, as well as for the analysis, verification, simulation and testing to ensure trustworthiness. This article reports on the definition and implementation of a scalable component-based architecture that supports a cooperative energy demand response (DR) system coordinating energy usage between neighbouring households. The proposed architecture, called refinement of Cyber-Physical Component Systems (rCPCS), which extends the refinement calculus for component and object system (rCOS) modelling method, is implemented using Eclipse Extensible Coordination Tools (ECT), i.e., Reo coordination language. With rCPCS implementation in Reo, we specify the communication, synchronisation and co-operation amongst the heterogeneous components of the system assuring, by design scalability and the interoperability, correctness of component cooperation.

Workload Model Based Dynamic Adaptation of Social Internet of Vehicles

PubMed Central

Alam, Kazi Masudul; Saini, Mukesh; El Saddik, Abdulmotaleb

2015-01-01

Social Internet of Things (SIoT) has gained much interest among different research groups in recent times. As a key member of a smart city, the vehicular domain of SIoT (SIoV) is also undergoing steep development. In the SIoV, vehicles work as sensor-hub to capture surrounding information using the in-vehicle and Smartphone sensors and later publish them for the consumers. A cloud centric cyber-physical system better describes the SIoV model where physical sensing-actuation process affects the cloud based service sharing or computation in a feedback loop or vice versa. The cyber based social relationship abstraction enables distributed, easily navigable and scalable peer-to-peer communication among the SIoV subsystems. These cyber-physical interactions involve a huge amount of data and it is difficult to form a real instance of the system to test the feasibility of SIoV applications. In this paper, we propose an analytical model to measure the workloads of various subsystems involved in the SIoV process. We present the basic model which is further extended to incorporate complex scenarios. We provide extensive simulation results for different parameter settings of the SIoV system. The findings of the analyses are further used to design example adaptation strategies for the SIoV subsystems which would foster deployment of intelligent transport systems. PMID:26389905

Workload Model Based Dynamic Adaptation of Social Internet of Vehicles.

PubMed

Alam, Kazi Masudul; Saini, Mukesh; El Saddik, Abdulmotaleb

2015-09-15

Social Internet of Things (SIoT) has gained much interest among different research groups in recent times. As a key member of a smart city, the vehicular domain of SIoT (SIoV) is also undergoing steep development. In the SIoV, vehicles work as sensor-hub to capture surrounding information using the in-vehicle and Smartphone sensors and later publish them for the consumers. A cloud centric cyber-physical system better describes the SIoV model where physical sensing-actuation process affects the cloud based service sharing or computation in a feedback loop or vice versa. The cyber based social relationship abstraction enables distributed, easily navigable and scalable peer-to-peer communication among the SIoV subsystems. These cyber-physical interactions involve a huge amount of data and it is difficult to form a real instance of the system to test the feasibility of SIoV applications. In this paper, we propose an analytical model to measure the workloads of various subsystems involved in the SIoV process. We present the basic model which is further extended to incorporate complex scenarios. We provide extensive simulation results for different parameter settings of the SIoV system. The findings of the analyses are further used to design example adaptation strategies for the SIoV subsystems which would foster deployment of intelligent transport systems.

Winnowing and Flocculation in Bio-physical Cohesive Substrate: A Flume Experimental and Estuarine Study

NASA Astrophysics Data System (ADS)

Ye, L.; Parsons, D. R.; Manning, A. J.

2016-12-01

Cohesive sediment, or mud, is ubiquitously found in most aqueous environments, such as coasts and estuaries. The study of cohesive sediment behaviors requires the synchronous description of mutual interactions of grains (e.g., winnowing and flocculation), their physical properties (e.g., grain size) and also the ambient water. Herein, a series of flume experiments (14 runs) with different substrate mixtures of sand-clay-EPS (Extracellular Polymeric Substrates: secreted by aquatic microorganisms) are combined with an estuarine field survey (Dee estuary, NW England) to investigate the behavior of suspensions over bio-physical cohesive substrates. The experimental results indicate that winnowing and flocculation occur pervasively in bio-physical cohesive flow systems. Importantly however, the evolution of the bed and bedform dynamics and hence turbulence production can be lower when cohesivity is high. The estuarine survey also revealed that the bio-physical cohesion provided by both the clay and microorganism fractions in the bed, that pervasively exists in many natural estuarine systems, plays a significant role in controlling the interactions between bed substrate and sediment suspension and deposition, including controlling processes such as sediment winnowing, flocculation and re-deposition. Full understanding of these processes are essential in advancing sediment transport modelling and prediction studies across natural estuarine systems and the work will report on an improved conceptual model for sediment sorting deposition in bio-physical cohesive substrates.

Admissible perturbations and false instabilities in PT -symmetric quantum systems

NASA Astrophysics Data System (ADS)

Znojil, Miloslav

2018-03-01

One of the most characteristic mathematical features of the PT -symmetric quantum mechanics is the explicit Hamiltonian dependence of its physical Hilbert space of states H =H (H ) . Some of the most important physical consequences are discussed, with emphasis on the dynamical regime in which the system is close to phase transition. Consistent perturbation treatment of such a regime is proposed. An illustrative application of the innovated perturbation theory to a non-Hermitian but PT -symmetric user-friendly family of J -parametric "discrete anharmonic" quantum Hamiltonians H =H (λ ⃗) is provided. The models are shown to admit the standard probabilistic interpretation if and only if the parameters remain compatible with the reality of the spectrum, λ ⃗∈D(physical ) . In contradiction to conventional wisdom, the systems are then shown to be stable with respect to admissible perturbations, inside the domain D(physical ), even in the immediate vicinity of the phase-transition boundaries ∂ D(physical ) .

Physics-driven Spatiotemporal Regularization for High-dimensional Predictive Modeling: A Novel Approach to Solve the Inverse ECG Problem

NASA Astrophysics Data System (ADS)

Yao, Bing; Yang, Hui

2016-12-01

This paper presents a novel physics-driven spatiotemporal regularization (STRE) method for high-dimensional predictive modeling in complex healthcare systems. This model not only captures the physics-based interrelationship between time-varying explanatory and response variables that are distributed in the space, but also addresses the spatial and temporal regularizations to improve the prediction performance. The STRE model is implemented to predict the time-varying distribution of electric potentials on the heart surface based on the electrocardiogram (ECG) data from the distributed sensor network placed on the body surface. The model performance is evaluated and validated in both a simulated two-sphere geometry and a realistic torso-heart geometry. Experimental results show that the STRE model significantly outperforms other regularization models that are widely used in current practice such as Tikhonov zero-order, Tikhonov first-order and L1 first-order regularization methods.

The UK Earth System Model project

NASA Astrophysics Data System (ADS)

Tang, Yongming

2016-04-01

In this talk we will describe the development and current status of the UK Earth System Model (UKESM). This project is a NERC/Met Office collaboration and has two objectives; to develop and apply a world-leading Earth System Model, and to grow a community of UK Earth System Model scientists. We are building numerical models that include all the key components of the global climate system, and contain the important process interactions between global biogeochemistry, atmospheric chemistry and the physical climate system. UKESM will be used to make key CMIP6 simulations as well as long-time (e.g. millennium) simulations, large ensemble experiments and investigating a range of future carbon emission scenarios.

Integrated Modelling and Performance Analysis of Green Roof Technologies in Urban Environments

NASA Astrophysics Data System (ADS)

Liu, Xi; Mijic, Ana; Maksimovic, Cedo

2014-05-01

As a result of the changing global climate and increase in urbanisation, the behaviour of the urban environment has been significantly altered, causing an increase in both the frequency of extreme weather events, such as flooding and drought, and also the associated costs. Moreover, uncontrolled or inadequately planned urbanisation can exacerbate the damage. The Blue-Green Dream (BGD) project therefore develops a series of components for urban areas that link urban vegetated areas (green infrastructure) with existing urban water (blue) systems, which will enhance the synergy of urban blue and green systems and provide effective, multifunctional BGD solutions to support urban adaptation to future climatic changes. Coupled with new urban water management technologies and engineering, multifunctional benefits can be gained. Some of the technologies associated with BGD solutions include green roofs, swales that might deal with runoff more effectively and urban river restoration that can produce benefits similar to those produced from sustainable urban drainage systems (SUDS). For effective implementation of these technologies, however, appropriate tools and methodologies for designing and modelling BGD solutions are required to be embedded within urban drainage models. Although several software packages are available for modelling urban drainage, the way in which green roofs and other BGD solutions are integrated into these models is not yet fully developed and documented. This study develops a physically based mass and energy balance model to monitor, test and quantitatively evaluate green roof technology for integrated BGD solutions. The assessment of environmental benefits will be limited to three aspects: (1) reduction of the total runoff volume, (2) delay in the initiation of runoff, and (3) reduction of building energy consumption, rather than water quality, visual, social or economic impacts. This physically based model represents water and heat dynamics in a layered soil profile covered with vegetation which can be used to simulate the physical behaviour of different green roof systems in response to rainfall under various climatic conditions. Because it is a physically based model, this model could be generalised to other atmosphere-plant-soil systems. The validity of this mass and energy balance approach will be demonstrated by comparing its outcomes with observations from a green roof experimental site in London, UK.

Applications of nonlinear systems theory to control design

NASA Technical Reports Server (NTRS)

Hunt, L. R.; Villarreal, Ramiro

1988-01-01

For most applications in the control area, the standard practice is to approximate a nonlinear mathematical model by a linear system. Since the feedback linearizable systems contain linear systems as a subclass, the procedure of approximating a nonlinear system by a feedback linearizable one is examined. Because many physical plants (e.g., aircraft at the NASA Ames Research Center) have mathematical models which are close to feedback linearizable systems, such approximations are certainly justified. Results and techniques are introduced for measuring the gap between the model and its truncated linearizable part. The topic of pure feedback systems is important to the study.

EXPECTED EFFECTS OF RESIDUAL CHLORINE AND NITROGEN IN SEWAGE EFFLUENT ON THE ESTUARINE ECOSYSTEM OF GREENWICH COVE, RI: AN ENERGY SYSTEMS AND RISK ASSESSMENT OF EFFECTS

EPA Science Inventory

Physical, toxicological, and energy systems modeling were combined to make estimates of likely ecosystem-level effects due to residual chlorine in sewage effluent. The energy systems model also allowed us to make estimates of the effects of nutrient loading on the estuary both se...

Modeling of Quantum Transport in Semiconductor Devices (The Physics and Operation of Ultra-Submicron Length Semiconductor Devices).

DTIC Science & Technology

1994-05-01

Open Systems and Contacts ...................... 16 A Ballistic Transport .......................... 17 B Role of the Boundaries and Contacts...15 Other Devices ................................ 90 V Modeling with the Green’s Functions 91 16 Homogeneous, Low-Field Systems .................. 93 A...The Retarded Function ..................... 95 B The "Less-Than" Function ................... 99 17 Homogeneous, High-Field Systems

Models for the modern power grid

NASA Astrophysics Data System (ADS)

Nardelli, Pedro H. J.; Rubido, Nicolas; Wang, Chengwei; Baptista, Murilo S.; Pomalaza-Raez, Carlos; Cardieri, Paulo; Latva-aho, Matti

2014-10-01

This article reviews different kinds of models for the electric power grid that can be used to understand the modern power system, the smart grid. From the physical network to abstract energy markets, we identify in the literature different aspects that co-determine the spatio-temporal multilayer dynamics of power system. We start our review by showing how the generation, transmission and distribution characteristics of the traditional power grids are already subject to complex behaviour appearing as a result of the the interplay between dynamics of the nodes and topology, namely synchronisation and cascade effects. When dealing with smart grids, the system complexity increases even more: on top of the physical network of power lines and controllable sources of electricity, the modernisation brings information networks, renewable intermittent generation, market liberalisation, prosumers, among other aspects. In this case, we forecast a dynamical co-evolution of the smart grid and other kind of networked systems that cannot be understood isolated. This review compiles recent results that model electric power grids as complex systems, going beyond pure technological aspects. From this perspective, we then indicate possible ways to incorporate the diverse co-evolving systems into the smart grid model using, for example, network theory and multi-agent simulation.