A unified dislocation density-dependent physical-based constitutive model for cold metal forming

NASA Astrophysics Data System (ADS)

Schacht, K.; Motaman, A. H.; Prahl, U.; Bleck, W.

2017-10-01

Dislocation-density-dependent physical-based constitutive models of metal plasticity while are computationally efficient and history-dependent, can accurately account for varying process parameters such as strain, strain rate and temperature; different loading modes such as continuous deformation, creep and relaxation; microscopic metallurgical processes; and varying chemical composition within an alloy family. Since these models are founded on essential phenomena dominating the deformation, they have a larger range of usability and validity. Also, they are suitable for manufacturing chain simulations since they can efficiently compute the cumulative effect of the various manufacturing processes by following the material state through the entire manufacturing chain and also interpass periods and give a realistic prediction of the material behavior and final product properties. In the physical-based constitutive model of cold metal plasticity introduced in this study, physical processes influencing cold and warm plastic deformation in polycrystalline metals are described using physical/metallurgical internal variables such as dislocation density and effective grain size. The evolution of these internal variables are calculated using adequate equations that describe the physical processes dominating the material behavior during cold plastic deformation. For validation, the model is numerically implemented in general implicit isotropic elasto-viscoplasticity algorithm as a user-defined material subroutine (UMAT) in ABAQUS/Standard and used for finite element simulation of upsetting tests and a complete cold forging cycle of case hardenable MnCr steel family.

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-10-20

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

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

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Physical Fitness and the Stress Process

ERIC Educational Resources Information Center

Ensel, Walter M.; Lin, Nan

2004-01-01

In the current paper we focus on the role of physical fitness in the life stress process for both psychological and physical well-being. The major research question posed in the current study is: Does physical fitness deter distress in a model containing the major components of the life stress process? That is, do individuals who exercise show…

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.

Physics-based signal processing algorithms for micromachined cantilever arrays

DOEpatents

Candy, James V; Clague, David S; Lee, Christopher L; Rudd, Robert E; Burnham, Alan K; Tringe, Joseph W

2013-11-19

A method of using physics-based signal processing algorithms for micromachined cantilever arrays. The methods utilize deflection of a micromachined cantilever that represents the chemical, biological, or physical element being detected. One embodiment of the method comprises the steps of modeling the deflection of the micromachined cantilever producing a deflection model, sensing the deflection of the micromachined cantilever and producing a signal representing the deflection, and comparing the signal representing the deflection with the deflection model.

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.

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.

A model for undergraduate physics major outcomes objectives

NASA Astrophysics Data System (ADS)

Taylor, G. R.; Erwin, T. Dary

1989-06-01

Concern with assessment of student outcomes of undergraduate physics major programs is rapidly rising. The Southern Association of Colleges and Schools and many other regional and state organizations are requiring explicit outcomes assessment in the accrediting process. The first step in this assessment process for major programs is the establishment of student outcomes objectives. A model and set of physics outcomes (educational) objectives that were developed by the faculty in the Physics Department at James Madison University are presented.

Structural Stability Monitoring of a Physical Model Test on an Underground Cavern Group during Deep Excavations Using FBG Sensors.

PubMed

Li, Yong; Wang, Hanpeng; Zhu, Weishen; Li, Shucai; Liu, Jian

2015-08-31

Fiber Bragg Grating (FBG) sensors are comprehensively recognized as a structural stability monitoring device for all kinds of geo-materials by either embedding into or bonding onto the structural entities. The physical model in geotechnical engineering, which could accurately simulate the construction processes and the effects on the stability of underground caverns on the basis of satisfying the similarity principles, is an actual physical entity. Using a physical model test of underground caverns in Shuangjiangkou Hydropower Station, FBG sensors were used to determine how to model the small displacements of some key monitoring points in the large-scale physical model during excavation. In the process of building the test specimen, it is most successful to embed FBG sensors in the physical model through making an opening and adding some quick-set silicon. The experimental results show that the FBG sensor has higher measuring accuracy than other conventional sensors like electrical resistance strain gages and extensometers. The experimental results are also in good agreement with the numerical simulation results. In conclusion, FBG sensors could effectively measure small displacements of monitoring points in the whole process of the physical model test. The experimental results reveal the deformation and failure characteristics of the surrounding rock mass and make some guidance for the in situ engineering construction.

Structural Stability Monitoring of a Physical Model Test on an Underground Cavern Group during Deep Excavations Using FBG Sensors

PubMed Central

Li, Yong; Wang, Hanpeng; Zhu, Weishen; Li, Shucai; Liu, Jian

2015-01-01

Fiber Bragg Grating (FBG) sensors are comprehensively recognized as a structural stability monitoring device for all kinds of geo-materials by either embedding into or bonding onto the structural entities. The physical model in geotechnical engineering, which could accurately simulate the construction processes and the effects on the stability of underground caverns on the basis of satisfying the similarity principles, is an actual physical entity. Using a physical model test of underground caverns in Shuangjiangkou Hydropower Station, FBG sensors were used to determine how to model the small displacements of some key monitoring points in the large-scale physical model during excavation. In the process of building the test specimen, it is most successful to embed FBG sensors in the physical model through making an opening and adding some quick-set silicon. The experimental results show that the FBG sensor has higher measuring accuracy than other conventional sensors like electrical resistance strain gages and extensometers. The experimental results are also in good agreement with the numerical simulation results. In conclusion, FBG sensors could effectively measure small displacements of monitoring points in the whole process of the physical model test. The experimental results reveal the deformation and failure characteristics of the surrounding rock mass and make some guidance for the in situ engineering construction. PMID:26404287

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

CMS Physics Technical Design Report, Volume II: Physics Performance

NASA Astrophysics Data System (ADS)

CMS Collaboration

2007-06-01

CMS is a general purpose experiment, designed to study the physics of pp collisions at 14 TeV at the Large Hadron Collider (LHC). It currently involves more than 2000 physicists from more than 150 institutes and 37 countries. The LHC will provide extraordinary opportunities for particle physics based on its unprecedented collision energy and luminosity when it begins operation in 2007. The principal aim of this report is to present the strategy of CMS to explore the rich physics programme offered by the LHC. This volume demonstrates the physics capability of the CMS experiment. The prime goals of CMS are to explore physics at the TeV scale and to study the mechanism of electroweak symmetry breaking—through the discovery of the Higgs particle or otherwise. To carry out this task, CMS must be prepared to search for new particles, such as the Higgs boson or supersymmetric partners of the Standard Model particles, from the start-up of the LHC since new physics at the TeV scale may manifest itself with modest data samples of the order of a few fb -1 or less. The analysis tools that have been developed are applied to study in great detail and with all the methodology of performing an analysis on CMS data specific benchmark processes upon which to gauge the performance of CMS. These processes cover several Higgs boson decay channels, the production and decay of new particles such as Z' and supersymmetric particles, B s production and processes in heavy ion collisions. The simulation of these benchmark processes includes subtle effects such as possible detector miscalibration and misalignment. Besides these benchmark processes, the physics reach of CMS is studied for a large number of signatures arising in the Standard Model and also in theories beyond the Standard Model for integrated luminosities ranging from 1 fb -1 to 30 fb -1 . The Standard Model processes include QCD, B -physics, diffraction, detailed studies of the top quark properties, and electroweak physics topics such as the W and Z 0 boson properties. The production and decay of the Higgs particle is studied for many observable decays, and the precision with which the Higgs boson properties can be derived is determined. About ten different supersymmetry benchmark points are analysed using full simulation. The CMS discovery reach is evaluated in the SUSY parameter space covering a large variety of decay signatures. Furthermore, the discovery reach for a plethora of alternative models for new physics is explored, notably extra dimensions, new vector boson high mass states, little Higgs models, technicolour and others. Methods to discriminate between models have been investigated. This report is organized as follows. Chapter 1, the Introduction, describes the context of this document. Chapters 2 6 describe examples of full analyses, with photons, electrons, muons, jets, missing E T , B-mesons and τ's, and for quarkonia in heavy ion collisions. Chapters 7 15 describe the physics reach for Standard Model processes, Higgs discovery and searches for new physics beyond the Standard Model.

Evaluating crown fire rate of spread predictions from physics-based models

Treesearch

C. M. Hoffman; J. Ziegler; J. Canfield; R. R. Linn; W. Mell; C. H. Sieg; F. Pimont

2015-01-01

Modeling the behavior of crown fires is challenging due to the complex set of coupled processes that drive the characteristics of a spreading wildfire and the large range of spatial and temporal scales over which these processes occur. Detailed physics-based modeling approaches such as FIRETEC and the Wildland Urban Interface Fire Dynamics Simulator (WFDS) simulate...

Computational Modeling of Hydrodynamics and Scour around Underwater Munitions

NASA Astrophysics Data System (ADS)

Liu, X.; Xu, Y.

2017-12-01

Munitions deposited in water bodies are a big threat to human health, safety, and environment. It is thus imperative to predict the motion and the resting status of the underwater munitions. A multitude of physical processes are involved, which include turbulent flows, sediment transport, granular material mechanics, 6 degree-of-freedom motion of the munition, and potential liquefaction. A clear understanding of this unique physical setting is currently lacking. Consequently, it is extremely hard to make reliable predictions. In this work, we present the computational modeling of two importance processes, i.e., hydrodynamics and scour, around munition objects. Other physical processes are also considered in our comprehensive model. However, they are not shown in this talk. To properly model the dynamics of the deforming bed and the motion of the object, an immersed boundary method is implemented in the open source CFD package OpenFOAM. Fixed bed and scour cases are simulated and compared with laboratory experiments. The future work of this project will implement the coupling between all the physical processes.

Data-driven multi-scale multi-physics models to derive process-structure-property relationships for additive manufacturing

NASA Astrophysics Data System (ADS)

Yan, Wentao; Lin, Stephen; Kafka, Orion L.; Lian, Yanping; Yu, Cheng; Liu, Zeliang; Yan, Jinhui; Wolff, Sarah; Wu, Hao; Ndip-Agbor, Ebot; Mozaffar, Mojtaba; Ehmann, Kornel; Cao, Jian; Wagner, Gregory J.; Liu, Wing Kam

2018-05-01

Additive manufacturing (AM) possesses appealing potential for manipulating material compositions, structures and properties in end-use products with arbitrary shapes without the need for specialized tooling. Since the physical process is difficult to experimentally measure, numerical modeling is a powerful tool to understand the underlying physical mechanisms. This paper presents our latest work in this regard based on comprehensive material modeling of process-structure-property relationships for AM materials. The numerous influencing factors that emerge from the AM process motivate the need for novel rapid design and optimization approaches. For this, we propose data-mining as an effective solution. Such methods—used in the process-structure, structure-properties and the design phase that connects them—would allow for a design loop for AM processing and materials. We hope this article will provide a road map to enable AM fundamental understanding for the monitoring and advanced diagnostics of AM processing.

Data-driven multi-scale multi-physics models to derive process-structure-property relationships for additive manufacturing

NASA Astrophysics Data System (ADS)

Yan, Wentao; Lin, Stephen; Kafka, Orion L.; Lian, Yanping; Yu, Cheng; Liu, Zeliang; Yan, Jinhui; Wolff, Sarah; Wu, Hao; Ndip-Agbor, Ebot; Mozaffar, Mojtaba; Ehmann, Kornel; Cao, Jian; Wagner, Gregory J.; Liu, Wing Kam

2018-01-01

Additive manufacturing (AM) possesses appealing potential for manipulating material compositions, structures and properties in end-use products with arbitrary shapes without the need for specialized tooling. Since the physical process is difficult to experimentally measure, numerical modeling is a powerful tool to understand the underlying physical mechanisms. This paper presents our latest work in this regard based on comprehensive material modeling of process-structure-property relationships for AM materials. The numerous influencing factors that emerge from the AM process motivate the need for novel rapid design and optimization approaches. For this, we propose data-mining as an effective solution. Such methods—used in the process-structure, structure-properties and the design phase that connects them—would allow for a design loop for AM processing and materials. We hope this article will provide a road map to enable AM fundamental understanding for the monitoring and advanced diagnostics of AM processing.

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.

Investigation of model-based physical design restrictions (Invited Paper)

NASA Astrophysics Data System (ADS)

Lucas, Kevin; Baron, Stanislas; Belledent, Jerome; Boone, Robert; Borjon, Amandine; Couderc, Christophe; Patterson, Kyle; Riviere-Cazaux, Lionel; Rody, Yves; Sundermann, Frank; Toublan, Olivier; Trouiller, Yorick; Urbani, Jean-Christophe; Wimmer, Karl

2005-05-01

As lithography and other patterning processes become more complex and more non-linear with each generation, the task of physical design rules necessarily increases in complexity also. The goal of the physical design rules is to define the boundary between the physical layout structures which will yield well from those which will not. This is essentially a rule-based pre-silicon guarantee of layout correctness. However the rapid increase in design rule requirement complexity has created logistical problems for both the design and process functions. Therefore, similar to the semiconductor industry's transition from rule-based to model-based optical proximity correction (OPC) due to increased patterning complexity, opportunities for improving physical design restrictions by implementing model-based physical design methods are evident. In this paper we analyze the possible need and applications for model-based physical design restrictions (MBPDR). We first analyze the traditional design rule evolution, development and usage methodologies for semiconductor manufacturers. Next we discuss examples of specific design rule challenges requiring new solution methods in the patterning regime of low K1 lithography and highly complex RET. We then evaluate possible working strategies for MBPDR in the process development and product design flows, including examples of recent model-based pre-silicon verification techniques. Finally we summarize with a proposed flow and key considerations for MBPDR implementation.

Femur Model Reconstruction Based on Reverse Engineering and Rapid Prototyping

NASA Astrophysics Data System (ADS)

Tang, Tongming; Zhang, Zheng; Ni, Hongjun; Deng, Jiawen; Huang, Mingyu

Precise reconstruction of 3D models is fundamental and crucial to the researches of human femur. In this paper we present our approach towards tackling this problem. The surface of a human femur was scanned using a hand-held 3D laser scanner. The data obtained, in the form of point cloud, was then processed using the reverse engineering software Geomagic and the CAD/CAM software CimatronE to reconstruct a digital 3D model. The digital model was then used by the rapid prototyping machine to build a physical model of human femur using 3D printing. The geometric characteristics of the obtained physical model matched that of the original femur. The process of "physical object - 3D data - digital 3D model - physical model" presented in this paper provides a foundation of precise modeling for the digital manufacturing, virtual assembly, stress analysis, and simulated surgery of artificial bionic femurs.

Using the EZ-Diffusion Model to Score a Single-Category Implicit Association Test of Physical Activity

PubMed Central

Rebar, Amanda L.; Ram, Nilam; Conroy, David E.

2014-01-01

Objective The Single-Category Implicit Association Test (SC-IAT) has been used as a method for assessing automatic evaluations of physical activity, but measurement artifact or consciously-held attitudes could be confounding the outcome scores of these measures. The objective of these two studies was to address these measurement concerns by testing the validity of a novel SC-IAT scoring technique. Design Study 1 was a cross-sectional study, and study 2 was a prospective study. Method In study 1, undergraduate students (N = 104) completed SC-IATs for physical activity, flowers, and sedentary behavior. In study 2, undergraduate students (N = 91) completed a SC-IAT for physical activity, self-reported affective and instrumental attitudes toward physical activity, physical activity intentions, and wore an accelerometer for two weeks. The EZ-diffusion model was used to decompose the SC-IAT into three process component scores including the information processing efficiency score. Results In study 1, a series of structural equation model comparisons revealed that the information processing score did not share variability across distinct SC-IATs, suggesting it does not represent systematic measurement artifact. In study 2, the information processing efficiency score was shown to be unrelated to self-reported affective and instrumental attitudes toward physical activity, and positively related to physical activity behavior, above and beyond the traditional D-score of the SC-IAT. Conclusions The information processing efficiency score is a valid measure of automatic evaluations of physical activity. PMID:25484621

Accounting for the influence of salt water in the physics required for processing underwater UXO EMI signals

NASA Astrophysics Data System (ADS)

Shubitidze, Fridon; Barrowes, Benjamin E.; Shamatava, Irma; Sigman, John; O'Neill, Kevin A.

2018-05-01

Processing electromagnetic induction signals from subsurface targets, for purposes of discrimination, requires accurate physical models. To date, successful approaches for on-land cases have entailed advanced modeling of responses by the targets themselves, with quite adequate treatment of instruments as well. Responses from the environment were typically slight and/or were treated very simply. When objects are immersed in saline solutions, however, more sophisticated modeling of the diffusive EMI physics in the environment is required. One needs to account for the response of the environment itself as well as the environment's frequency and time-dependent effects on both primary and secondary fields, from sensors and targets, respectively. Here we explicate the requisite physics and identify its effects quantitatively via analytical, numerical, and experimental investigations. Results provide a path for addressing the quandaries posed by previous underwater measurements and indicate how the environmental physics may be included in more successful processing.

Does physics instruction foster university students' cognitive processes?: A descriptive study of teacher activities

NASA Astrophysics Data System (ADS)

Ferguson-Hessler, Monica G. M.; de Jong, Ton

This study aims at giving a systematic description of the cognitive activities involved in teaching physics. Such a description of instruction in physics requires a basis in two models, that is, the cognitive activities involved in learning physics and the knowledge base that is the foundation of expertise in that subject. These models have been provided by earlier research. The model of instruction distinguishes three main categories of instruction process: presenting new information, integrating (i.e., bringing structure into) new knowledge, and connecting elements of new knowledge to prior knowledge. Each of the main categories has been divided into a number of specific instruction processes. Hereby any limited and specific cognitive teacher activity can be described along the two dimensions of process and type of knowledge. The model was validated by application to lectures and problem-solving classes of first year university courses. These were recorded and analyzed as to instruction process and type of knowledge. Results indicate that teachers are indeed involved in the various types of instruction processes defined. The importance of this study lies in the creation of a terminology that makes it possible to discuss instruction in an explicit and specific way.

Semantic modeling of the structural and process entities during plastic deformation of crystals and rocks

NASA Astrophysics Data System (ADS)

Babaie, Hassan; Davarpanah, Armita

2016-04-01

We are semantically modeling the structural and dynamic process components of the plastic deformation of minerals and rocks in the Plastic Deformation Ontology (PDO). Applying the Ontology of Physics in Biology, the PDO classifies the spatial entities that participate in the diverse processes of plastic deformation into the Physical_Plastic_Deformation_Entity and Nonphysical_Plastic_Deformation_Entity classes. The Material_Physical_Plastic_Deformation_Entity class includes things such as microstructures, lattice defects, atoms, liquid, and grain boundaries, and the Immaterial_Physical_Plastic_Deformation_Entity class includes vacancies in crystals and voids along mineral grain boundaries. The objects under the many subclasses of these classes (e.g., crystal, lattice defect, layering) have spatial parts that are related to each other through taxonomic (e.g., Line_Defect isA Lattice_Defect), structural (mereological, e.g., Twin_Plane partOf Twin), spatial-topological (e.g., Vacancy adjacentTo Atom, Fluid locatedAlong Grain_Boundary), and domain specific (e.g., displaces, Fluid crystallizes Dissolved_Ion, Void existsAlong Grain_Boundary) relationships. The dynamic aspect of the plastic deformation is modeled under the dynamical Process_Entity class that subsumes classes such as Recrystallization and Pressure_Solution that define the flow of energy amongst the physical entities. The values of the dynamical state properties of the physical entities (e.g., Chemical_Potential, Temperature, Particle_Velocity) change while they take part in the deformational processes such as Diffusion and Dislocation_Glide. The process entities have temporal parts (phases) that are related to each other through temporal relations such as precedes, isSubprocessOf, and overlaps. The properties of the physical entities, defined under the Physical_Property class, change as they participate in the plastic deformational processes. The properties are categorized into dynamical, constitutive, spatial, temporal, statistical, and thermodynamical. The dynamical properties, categorized under the Dynamical_Rate_Property and Dynamical_State_Property classes, subsume different classes of properties (e.g., Fluid_Flow_Rate, Temperature, Chemical_Potential, Displacement, Electrical_Charge) based on the physical domain (e.g., fluid, heat, chemical, solid, electrical). The properties are related to the objects under the Physical_Entity class through diverse object type (e.g., physicalPropertyOf) and data type (e.g., Fluid_Pressure unit 'MPa') properties. The changes of the dynamical properties of the physical entities, described by the empirical laws (equations) modeled by experimental structural geologists, are modeled through the Physical_Property_Dependency class that subsumes the more specialized constitutive, kinetic, and thermodynamic expressions of the relationships among the dynamic properties. Annotation based on the PDO will make it possible to integrate and reuse experimental plastic deformation data, knowledge, and simulation models, and conduct semantic-based search of the source data originating from different rock testing laboratories.

Welding arc plasma physics

NASA Technical Reports Server (NTRS)

Cain, Bruce L.

1990-01-01

The problems of weld quality control and weld process dependability continue to be relevant issues in modern metal welding technology. These become especially important for NASA missions which may require the assembly or repair of larger orbiting platforms using automatic welding techniques. To extend present welding technologies for such applications, NASA/MSFC's Materials and Processes Lab is developing physical models of the arc welding process with the goal of providing both a basis for improved design of weld control systems, and a better understanding of how arc welding variables influence final weld properties. The physics of the plasma arc discharge is reasonably well established in terms of transport processes occurring in the arc column itself, although recourse to sophisticated numerical treatments is normally required to obtain quantitative results. Unfortunately the rigor of these numerical computations often obscures the physics of the underlying model due to its inherent complexity. In contrast, this work has focused on a relatively simple physical model of the arc discharge to describe the gross features observed in welding arcs. Emphasis was placed of deriving analytic expressions for the voltage along the arc axis as a function of known or measurable arc parameters. The model retains the essential physics for a straight polarity, diffusion dominated free burning arc in argon, with major simplifications of collisionless sheaths and simple energy balances at the electrodes.

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 Processes by which Perceived Autonomy Support in Physical Education Promotes Leisure-Time Physical Activity Intentions and Behavior: A Trans-Contextual Model.

ERIC Educational Resources Information Center

Hagger, Martin S.; Chatzisarantis, Nikos L. D.; Culverhouse, Trudi; Biddle, Stuart J. H.

2003-01-01

Model proposes that young people's perceived autonomy support in physical education will affect their perceived locus of causality, intentions, and physical activity behavior in leisure time. Results support the trans-contextual model indicating that perceived autonomy support in an educational context influences motivation in a leisure-time…

Physical Education Resources, Class Management, and Student Physical Activity Levels: A Structure-Process-Outcome Approach to Evaluating Physical Education Effectiveness

ERIC Educational Resources Information Center

Bevans, Katherine B.; Fitzpatrick, Leslie-Anne; Sanchez, Betty M.; Riley, Anne W.; Forrest, Christopher

2010-01-01

Background: This study was conducted to empirically evaluate specific human, curricular, and material resources that maximize student opportunities for physical activity during physical education (PE) class time. A structure-process-outcome model was proposed to identify the resources that influence the frequency of PE and intensity of physical…

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.

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

Long-term simulation of vertical transport process and its impact on bottom DO in Chesapeake Bay

NASA Astrophysics Data System (ADS)

Du, J.; Shen, J.

2016-02-01

Hypoxia in coastal waters is a widespread phenomenon that appears to have been growing globally for at least 60 years. The fact that physical transport processes and biological processes are equally important in determining the bottom DO in Chesapeake Bay is commonly agreed. However, the quantitative impact of physical transport processes is rarely documented. In this study, we use a timescale, vertical exchange time (VET), to quantify the impact of all physical processes that might have on the bottom DO. Simulation of VET from 1985 to 2012 is conducted and the monthly observed DO data along the deep channel in the Bay's main stem is collected. A conceptual bottom DO budget model is applied, using the VET to quantify the physical condition and net oxygen consumption rate to quantify biological activities. The DO budget model results show that the interannual variations of physical conditions accounts for 88.8% of the interannual variations of observed DO. The high similarity between the VET spatial pattern and the observed DO suggests that physical processes play a key role in regulating the DO condition. Model results also show that long-term VET has a slight increase in summer, but no statistically significant trend is found. Correlations among southerly wind strength, North Atlantic Oscillation index, and VET demonstrate that the physical condition in the Chesapeake Bay is highly controlled by the large-scale climate variation. The relationship is most significant during the summer, when the southerly wind dominates throughout the Chesapeake Bay.

Modelling Students' Construction of Energy Models in Physics.

ERIC Educational Resources Information Center

Devi, Roshni; And Others

1996-01-01

Examines students' construction of experimentation models for physics theories in energy storage, transformation, and transfers involving electricity and mechanics. Student problem solving dialogs and artificial intelligence modeling of these processes is analyzed. Construction of models established relations between elements with linear causal…

Transpiration and Leaf Temperature. Physical Processes in Terrestrial and Aquatic Ecosystems, Transport Processes.

ERIC Educational Resources Information Center

Gates, David M.

These materials were designed to be used by life science students for instruction in the application of physical theory to ecosystem operation. Most modules contain computer programs which are built around a particular application of a physical process. This report introduces two models of the thermal energy budget of a leaf. Typical values for…

Ontology of physics for biology: representing physical dependencies as a basis for biological processes.

PubMed

Cook, Daniel L; Neal, Maxwell L; Bookstein, Fred L; Gennari, John H

2013-12-02

In prior work, we presented the Ontology of Physics for Biology (OPB) as a computational ontology for use in the annotation and representations of biophysical knowledge encoded in repositories of physics-based biosimulation models. We introduced OPB:Physical entity and OPB:Physical property classes that extend available spatiotemporal representations of physical entities and processes to explicitly represent the thermodynamics and dynamics of physiological processes. Our utilitarian, long-term aim is to develop computational tools for creating and querying formalized physiological knowledge for use by multiscale "physiome" projects such as the EU's Virtual Physiological Human (VPH) and NIH's Virtual Physiological Rat (VPR). Here we describe the OPB:Physical dependency taxonomy of classes that represent of the laws of classical physics that are the "rules" by which physical properties of physical entities change during occurrences of physical processes. For example, the fluid analog of Ohm's law (as for electric currents) is used to describe how a blood flow rate depends on a blood pressure gradient. Hooke's law (as in elastic deformations of springs) is used to describe how an increase in vascular volume increases blood pressure. We classify such dependencies according to the flow, transformation, and storage of thermodynamic energy that occurs during processes governed by the dependencies. We have developed the OPB and annotation methods to represent the meaning-the biophysical semantics-of the mathematical statements of physiological analysis and the biophysical content of models and datasets. Here we describe and discuss our approach to an ontological representation of physical laws (as dependencies) and properties as encoded for the mathematical analysis of biophysical processes.

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.

A combustion model of vegetation burning in "Tiger" fire propagation tool

NASA Astrophysics Data System (ADS)

Giannino, F.; Ascoli, D.; Sirignano, M.; Mazzoleni, S.; Russo, L.; Rego, F.

2017-11-01

In this paper, we propose a semi-physical model for the burning of vegetation in a wildland fire. The main physical-chemical processes involved in fire spreading are modelled through a set of ordinary differential equations, which describe the combustion process as linearly related to the consumption of fuel. The water evaporation process from leaves and wood is also considered. Mass and energy balance equations are written for fuel (leaves and wood) assuming that combustion process is homogeneous in space. The model is developed with the final aim of simulating large-scale wildland fires which spread on heterogeneous landscape while keeping the computation cost very low.

Assessing Students' Deep Conceptual Understanding in Physical Sciences: An Example on Sinking and Floating

ERIC Educational Resources Information Center

Shen, Ji; Liu, Ou Lydia; Chang, Hsin-Yi

2017-01-01

This paper presents a transformative modeling framework that guides the development of assessment to measure students' deep understanding in physical sciences. The framework emphasizes 3 types of connections that students need to make when learning physical sciences: (1) linking physical states, processes, and explanatory models, (2) integrating…

State-Transition Structures in Physics and in Computation

NASA Astrophysics Data System (ADS)

Petri, C. A.

1982-12-01

In order to establish close connections between physical and computational processes, it is assumed that the concepts of “state” and of “transition” are acceptable both to physicists and to computer scientists, at least in an informal way. The aim of this paper is to propose formal definitions of state and transition elements on the basis of very low level physical concepts in such a way that (1) all physically possible computations can be described as embedded in physical processes; (2) the computational aspects of physical processes can be described on a well-defined level of abstraction; (3) the gulf between the continuous models of physics and the discrete models of computer science can be bridged by simple mathematical constructs which may be given a physical interpretation; (4) a combinatorial, nonstatistical definition of “information” can be given on low levels of abstraction which may serve as a basis to derive higher-level concepts of information, e.g., by a statistical or probabilistic approach. Conceivable practical consequences are discussed.

Dynamic Emulation Modelling (DEMo) of large physically-based environmental models

NASA Astrophysics Data System (ADS)

Galelli, S.; Castelletti, A.

2012-12-01

In environmental modelling large, spatially-distributed, physically-based models are widely adopted to describe the dynamics of physical, social and economic processes. Such an accurate process characterization comes, however, to a price: the computational requirements of these models are considerably high and prevent their use in any problem requiring hundreds or thousands of model runs to be satisfactory solved. Typical examples include optimal planning and management, data assimilation, inverse modelling and sensitivity analysis. An effective approach to overcome this limitation is to perform a top-down reduction of the physically-based model by identifying a simplified, computationally efficient emulator, constructed from and then used in place of the original model in highly resource-demanding tasks. The underlying idea is that not all the process details in the original model are equally important and relevant to the dynamics of the outputs of interest for the type of problem considered. Emulation modelling has been successfully applied in many environmental applications, however most of the literature considers non-dynamic emulators (e.g. metamodels, response surfaces and surrogate models), where the original dynamical model is reduced to a static map between input and the output of interest. In this study we focus on Dynamic Emulation Modelling (DEMo), a methodological approach that preserves the dynamic nature of the original physically-based model, with consequent advantages in a wide variety of problem areas. In particular, we propose a new data-driven DEMo approach that combines the many advantages of data-driven modelling in representing complex, non-linear relationships, but preserves the state-space representation typical of process-based models, which is both particularly effective in some applications (e.g. optimal management and data assimilation) and facilitates the ex-post physical interpretation of the emulator structure, thus enhancing the credibility of the model to stakeholders and decision-makers. Numerical results from the application of the approach to the reduction of 3D coupled hydrodynamic-ecological models in several real world case studies, including Marina Reservoir (Singapore) and Googong Reservoir (Australia), are illustrated.

Physically based modeling of bedrock incision by abrasion, plucking, and macroabrasion

NASA Astrophysics Data System (ADS)

Chatanantavet, Phairot; Parker, Gary

2009-11-01

Many important insights into the dynamic coupling among climate, erosion, and tectonics in mountain areas have derived from several numerical models of the past few decades which include descriptions of bedrock incision. However, many questions regarding incision processes and morphology of bedrock streams still remain unanswered. A more mechanistically based incision model is needed as a component to study landscape evolution. Major bedrock incision processes include (among other mechanisms) abrasion by bed load, plucking, and macroabrasion (a process of fracturing of the bedrock into pluckable sizes mediated by particle impacts). The purpose of this paper is to develop a physically based model of bedrock incision that includes all three processes mentioned above. To build the model, we start by developing a theory of abrasion, plucking, and macroabrasion mechanisms. We then incorporate hydrology, the evaluation of boundary shear stress, capacity transport, an entrainment relation for pluckable particles, a routing model linking in-stream sediment and hillslopes, a formulation for alluvial channel coverage, a channel width relation, Hack's law, and Exner equation into the model so that we can simulate the evolution of bedrock channels. The model successfully simulates various features of bed elevation profiles of natural bedrock rivers under a variety of input or boundary conditions. The results also illustrate that knickpoints found in bedrock rivers may be autogenic in addition to being driven by base level fall and lithologic changes. This supports the concept that bedrock incision by knickpoint migration may be an integral part of normal incision processes. The model is expected to improve the current understanding of the linkage among physically meaningful input parameters, the physics of incision process, and morphological changes in bedrock streams.

Advantages and Challenges of Using Physics Curricula as a Model for Reforming an Undergraduate Biology Course

ERIC Educational Resources Information Center

Donovan, D. A.; Atkins, L. J.; Salter, I. Y.; Gallagher, D. J.; Kratz, R. F.; Rousseau, J. V.; Nelson, G. D.

2013-01-01

We report on the development of a life sciences curriculum, targeted to undergraduate students, which was modeled after a commercially available physics curriculum and based on aspects of how people learn. Our paper describes the collaborative development process and necessary modifications required to apply a physics pedagogical model in a life…

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

Physical modelling in biomechanics.

PubMed Central

Koehl, M A R

2003-01-01

Physical models, like mathematical models, are useful tools in biomechanical research. Physical models enable investigators to explore parameter space in a way that is not possible using a comparative approach with living organisms: parameters can be varied one at a time to measure the performance consequences of each, while values and combinations not found in nature can be tested. Experiments using physical models in the laboratory or field can circumvent problems posed by uncooperative or endangered organisms. Physical models also permit some aspects of the biomechanical performance of extinct organisms to be measured. Use of properly scaled physical models allows detailed physical measurements to be made for organisms that are too small or fast to be easily studied directly. The process of physical modelling and the advantages and limitations of this approach are illustrated using examples from our research on hydrodynamic forces on sessile organisms, mechanics of hydraulic skeletons, food capture by zooplankton and odour interception by olfactory antennules. PMID:14561350

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.

Ontology of physics for biology: representing physical dependencies as a basis for biological processes

PubMed Central

2013-01-01

Background In prior work, we presented the Ontology of Physics for Biology (OPB) as a computational ontology for use in the annotation and representations of biophysical knowledge encoded in repositories of physics-based biosimulation models. We introduced OPB:Physical entity and OPB:Physical property classes that extend available spatiotemporal representations of physical entities and processes to explicitly represent the thermodynamics and dynamics of physiological processes. Our utilitarian, long-term aim is to develop computational tools for creating and querying formalized physiological knowledge for use by multiscale “physiome” projects such as the EU’s Virtual Physiological Human (VPH) and NIH’s Virtual Physiological Rat (VPR). Results Here we describe the OPB:Physical dependency taxonomy of classes that represent of the laws of classical physics that are the “rules” by which physical properties of physical entities change during occurrences of physical processes. For example, the fluid analog of Ohm’s law (as for electric currents) is used to describe how a blood flow rate depends on a blood pressure gradient. Hooke’s law (as in elastic deformations of springs) is used to describe how an increase in vascular volume increases blood pressure. We classify such dependencies according to the flow, transformation, and storage of thermodynamic energy that occurs during processes governed by the dependencies. Conclusions We have developed the OPB and annotation methods to represent the meaning—the biophysical semantics—of the mathematical statements of physiological analysis and the biophysical content of models and datasets. Here we describe and discuss our approach to an ontological representation of physical laws (as dependencies) and properties as encoded for the mathematical analysis of biophysical processes. PMID:24295137

Search for new physics in events with photons, jets, and missing transverse energy in pp collisions at $$ \\sqrt{s}=7 $$ TeV

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

Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.

A search for physics beyond the standard model involving events with one or more photons, jets, and missing transverse energy has been performed by the CMS experiment. The data sample corresponds to an integrated luminosity of 4.93 fb -1 of proton-proton collisions at TeV, produced at the Large Hadron Collider. No excess of events with large missing transverse energy is observed beyond expectations from standard model processes, and upper limits on the signal production cross sections for new physics processes are set at the 95% confidence level. The results of this search are interpreted in the context of three modelsmore » of new physics: a general model of gauge-mediated supersymmetry breaking, Simplified Models, and a theory involving universal extra dimensions. In the absence of evidence for new physics, exclusion regions are derived in the parameter spaces of the respective models.« less

Physical-mathematical model of condensation process of the sub-micron dust capture in sprayer scrubber

NASA Astrophysics Data System (ADS)

Shilyaev, M. I.; Khromova, E. M.; Grigoriev, A. V.; Tumashova, A. V.

2011-09-01

A physical-mathematical model of the heat and mass exchange process and condensation capture of sub-micron dust particles on the droplets of dispersed liquid in a sprayer scrubber is proposed and analysed. A satisfactory agreement of computed results and experimental data on soot capturing from the cracking gases is obtained.

3D physical modeling for patterning process development

NASA Astrophysics Data System (ADS)

Sarma, Chandra; Abdo, Amr; Bailey, Todd; Conley, Will; Dunn, Derren; Marokkey, Sajan; Talbi, Mohamed

2010-03-01

In this paper we will demonstrate how a 3D physical patterning model can act as a forensic tool for OPC and ground-rule development. We discuss examples where the 2D modeling shows no issues in printing gate lines but 3D modeling shows severe resist loss in the middle. In absence of corrective measure, there is a high likelihood of line discontinuity post etch. Such early insight into process limitations of prospective ground rules can be invaluable for early technology development. We will also demonstrate how the root cause of broken poly-line after etch could be traced to resist necking in the region of STI step with the help of 3D models. We discuss different cases of metal and contact layouts where 3D modeling gives an early insight in to technology limitations. In addition such a 3D physical model could be used for early resist evaluation and selection for required ground-rule challenges, which can substantially reduce the cycle time for process development.

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.

Graphene growth process modeling: a physical-statistical approach

NASA Astrophysics Data System (ADS)

Wu, Jian; Huang, Qiang

2014-09-01

As a zero-band semiconductor, graphene is an attractive material for a wide variety of applications such as optoelectronics. Among various techniques developed for graphene synthesis, chemical vapor deposition on copper foils shows high potential for producing few-layer and large-area graphene. Since fabrication of high-quality graphene sheets requires the understanding of growth mechanisms, and methods of characterization and control of grain size of graphene flakes, analytical modeling of graphene growth process is therefore essential for controlled fabrication. The graphene growth process starts with randomly nucleated islands that gradually develop into complex shapes, grow in size, and eventually connect together to cover the copper foil. To model this complex process, we develop a physical-statistical approach under the assumption of self-similarity during graphene growth. The growth kinetics is uncovered by separating island shapes from area growth rate. We propose to characterize the area growth velocity using a confined exponential model, which not only has clear physical explanation, but also fits the real data well. For the shape modeling, we develop a parametric shape model which can be well explained by the angular-dependent growth rate. This work can provide useful information for the control and optimization of graphene growth process on Cu foil.

Physical Modeling for Processing Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Hyperspectral Data

DTIC Science & Technology

2003-09-30

Physical Modeling for Processing Geosynchronous Imaging Fourier Transform Spectrometer ( GIFTS ) Hyperspectral Data Dr. Allen H.-L. Huang...ssec.wisc.edu Award Number: N000140110850 Grant Number: 144KE70 http://www.ssec.wisc.edu/ gifts /navy/ LONG-TERM GOALS This Office of Naval...objective of this DoD research effort is to develop and demonstrate a fully functional GIFTS hyperspectral data processing system with the potential for a

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, ...

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.

A Study of Heavy Precipitation Events in Taiwan During 10-13 August, 1994. Part 2; Mesoscale Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei Kuo; Chen, C.-S.; Jia, Y.; Baker, D.; Lang, S.; Wetzel, P.; Lau, W. K.-M.

2001-01-01

Several heavy precipitation episodes occurred over Taiwan from August 10 to 13, 1994. Precipitation patterns and characteristics are quite different between the precipitation events that occurred from August 10 and I I and from August 12 and 13. In Part I (Chen et al. 2001), the environmental situation and precipitation characteristics are analyzed using the EC/TOGA data, ground-based radar data, surface rainfall patterns, surface wind data, and upper air soundings. In this study (Part II), the Penn State/NCAR Mesoscale Model (MM5) is used to study the precipitation characteristics of these heavy precipitation events. Various physical processes (schemes) developed at NASA Goddard Space Flight Center (i.e., cloud microphysics scheme, radiative transfer model, and land-soil-vegetation surface model) have recently implemented into the MM5. These physical packages are described in the paper, Two way interactive nested grids are used with horizontal resolutions of 45, 15 and 5 km. The model results indicated that Cloud physics, land surface and radiation processes generally do not change the location (horizontal distribution) of heavy precipitation. The Goddard 3-class ice scheme produced more rainfall than the 2-class scheme. The Goddard multi-broad-band radiative transfer model reduced precipitation compared to a one-broad band (emissivity) radiation model. The Goddard land-soil-vegetation surface model also reduce the rainfall compared to a simple surface model in which the surface temperature is computed from a Surface energy budget following the "force-re store" method. However, model runs including all Goddard physical processes enhanced precipitation significantly for both cases. The results from these runs are in better agreement with observations. Despite improved simulations using different physical schemes, there are still some deficiencies in the model simulations. Some potential problems are discussed. Sensitivity tests (removing either terrain or radiative processes) are performed to identify the physical processes that determine the precipitation patterns and characteristics for heavy rainfall events. These sensitivity tests indicated that terrain can play a major role in determining the exact location for both precipitation events. The terrain can also play a major role in determining the intensity of precipitation for both events. However, it has a large impact on one event but a smaller one on the other. The radiative processes are also important for determining, the precipitation patterns for one case but. not the other. The radiative processes can also effect the total rainfall for both cases to different extents.

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.

The new car following model considering vehicle dynamics influence and numerical simulation

NASA Astrophysics Data System (ADS)

Sun, Dihua; Liu, Hui; Zhang, Geng; Zhao, Min

2015-12-01

In this paper, the car following model is investigated by considering the vehicle dynamics in a cyber physical view. In fact, that driving is a typical cyber physical process which couples the cyber aspect of the vehicles' information and driving decision tightly with the dynamics and physics of the vehicles and traffic environment. However, the influence from the physical (vehicle) view was been ignored in the previous car following models. In order to describe the car following behavior more reasonably in real traffic, a new car following model by considering vehicle dynamics (for short, D-CFM) is proposed. In this paper, we take the full velocity difference (FVD) car following model as a case. The stability condition is given on the base of the control theory. The analytical method and numerical simulation results show that the new models can describe the evolution of traffic congestion. The simulations also show vehicles with a more actual acceleration of starting process than early models.

The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

NASA Astrophysics Data System (ADS)

Clark, Martyn P.; Bierkens, Marc F. P.; Samaniego, Luis; Woods, Ross A.; Uijlenhoet, Remko; Bennett, Katrina E.; Pauwels, Valentijn R. N.; Cai, Xitian; Wood, Andrew W.; Peters-Lidard, Christa D.

2017-07-01

The diversity in hydrologic models has historically led to great controversy on the correct approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this paper, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We illustrate how modeling advances have been made by groups using models of different type and complexity, and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.

The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

NASA Astrophysics Data System (ADS)

Clark, M. P.; Nijssen, B.; Wood, A.; Mizukami, N.; Newman, A. J.

2017-12-01

The diversity in hydrologic models has historically led to great controversy on the "correct" approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this paper, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We illustrate how modeling advances have been made by groups using models of different type and complexity, and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.

Extending the Trans-Contextual Model in Physical Education and Leisure-Time Contexts: Examining the Role of Basic Psychological Need Satisfaction

ERIC Educational Resources Information Center

Barkoukis, Vassilis; Hagger, Martin S.; Lambropoulos, George; Tsorbatzoudis, Haralambos

2010-01-01

Background: The trans-contextual model (TCM) is an integrated model of motivation that aims to explain the processes by which agentic support for autonomous motivation in physical education promotes autonomous motivation and physical activity in a leisure-time context. It is proposed that perceived support for autonomous motivation in physical…

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.

Physical Modeling of Contact Processes on the Cutting Tools Surfaces of STM When Turning

NASA Astrophysics Data System (ADS)

Belozerov, V. A.; Uteshev, M. H.

2016-08-01

This article describes how to create an optimization model of the process of fine turning of superalloys and steel tools from STM on CNC machines, flexible manufacturing units (GPM), machining centers. Creation of the optimization model allows you to link (unite) contact processes simultaneously on the front and back surfaces of the tool from STM to manage contact processes and the dynamic strength of the cutting tool at the top of the STM. Established optimization model of management of the dynamic strength of the incisors of the STM in the process of fine turning is based on a previously developed thermomechanical (physical, heat) model, which allows the system thermomechanical approach to choosing brands STM (domestic and foreign) for cutting tools from STM designed for fine turning of heat resistant alloys and steels.

Chinese College Students' Physical Activity Correlates and Behavior: A Transtheoretical Model Perspective

ERIC Educational Resources Information Center

Xiong, Shanying; Li, Xianxiong; Tao, Kun; Zeng, Nan; Ayyub, Mohammad; Peng, Qingwen; Yan, Xiaoni; Wang, Junli; Wu, Yizhong; Lei, Mingzhi

2017-01-01

Guided by the Transtheoretical Model (Prochaska & DiClemente, 1982), this study investigated the differences of physical activity levels and correlates (i.e., self-efficacy, decisional balance, process of change) across different stages of change levels among Chinese college students. The relationships between students' physical activity…

Guided-Inquiry Experiments for Physical Chemistry: The POGIL-PCL Model

ERIC Educational Resources Information Center

Hunnicutt, Sally S.; Grushow, Alexander; Whitnell, Robert

2015-01-01

The POGIL-PCL project implements the principles of process-oriented, guided-inquiry learning (POGIL) in order to improve student learning in the physical chemistry laboratory (PCL) course. The inquiry-based physical chemistry experiments being developed emphasize modeling of chemical phenomena. In each experiment, students work through at least…

Development Instrument’s Learning of Physics Through Scientific Inquiry Model Based Batak Culture to Improve Science Process Skill and Student’s Curiosity

NASA Astrophysics Data System (ADS)

Nasution, Derlina; Syahreni Harahap, Putri; Harahap, Marabangun

2018-03-01

This research aims to: (1) developed a instrument’s learning (lesson plan, worksheet, student’s book, teacher’s guide book, and instrument test) of physics learning through scientific inquiry learning model based Batak culture to achieve skills improvement process of science students and the students’ curiosity; (2) describe the quality of the result of develop instrument’s learning in high school using scientific inquiry learning model based Batak culture (lesson plan, worksheet, student’s book, teacher’s guide book, and instrument test) to achieve the science process skill improvement of students and the student curiosity. This research is research development. This research developed a instrument’s learning of physics by using a development model that is adapted from the development model Thiagarajan, Semmel, and Semmel. The stages are traversed until retrieved a valid physics instrument’s learning, practical, and effective includes :(1) definition phase, (2) the planning phase, and (3) stages of development. Test performed include expert test/validation testing experts, small groups, and test classes is limited. Test classes are limited to do in SMAN 1 Padang Bolak alternating on a class X MIA. This research resulted in: 1) the learning of physics static fluid material specially for high school grade 10th consisted of (lesson plan, worksheet, student’s book, teacher’s guide book, and instrument test) and quality worthy of use in the learning process; 2) each component of the instrument’s learning meet the criteria have valid learning, practical, and effective way to reach the science process skill improvement and curiosity in students.

The calculation of theoretical chromospheric models and the interpretation of the solar spectrum

NASA Technical Reports Server (NTRS)

Avrett, Eugene H.

1994-01-01

Since the early 1970s we have been developing the extensive computer programs needed to construct models of the solar atmosphere and to calculate detailed spectra for use in the interpretation of solar observations. This research involves two major related efforts: work by Avrett and Loeser on the Pandora computer program for non-LTE modeling of the solar atmosphere including a wide range of physical processes, and work by Kurucz on the detailed synthesis of the solar spectrum based on opacity data for over 58 million atomic and molecular lines. Our goals are to determine models of the various features observed on the sun (sunspots, different components of quiet and active regions, and flares) by means of physically realistic models, and to calculate detailed spectra at all wavelengths that match observations of those features. These two goals are interrelated: discrepancies between calculated and observed spectra are used to determine improvements in the structure of the models, and in the detailed physical processes used in both the model calculations and the spectrum calculations. The atmospheric models obtained in this way provide not only the depth variation of various atmospheric parameters, but also a description of the internal physical processes that are responsible for nonradiative heating, and for solar activity in general.

The calculation of theoretical chromospheric models and the interpretation of solar spectra from rockets and spacecraft

NASA Technical Reports Server (NTRS)

Avrett, Eugene H.

1993-01-01

Since the early 1970s we have been developing the extensive computer programs needed to construct models of the solar atmosphere and to calculate detailed spectra for use in the interpretation of solar observations. This research involves two major related efforts: work by Avrett and Loeser on the Pandora computer program for non-LTE modeling of the solar atmosphere including a wide range of physical processes, and work by Kurucz on the detailed synthesis of the solar spectrum based on opacity data for over 58 million atomic and molecular lines. Our goals are to determine models of the various features observed on the Sun (sunspots, different components of quiet and active regions, and flares) by means of physically realistic models, and to calculate detailed spectra at all wavelengths that match observations of those features. These two goals are interrelated: discrepancies between calculated and observed spectra are used to determine improvements in the structure of the models, and in the detailed physical processes used in both the model calculations and the spectrum calculations. The atmospheric models obtained in this way provide not only the depth variation of various atmospheric parameters, but also a description of the internal physical processes that are responsible for non-radiative heating, and for solar activity in general.

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.

Parameter extraction with neural networks

NASA Astrophysics Data System (ADS)

Cazzanti, Luca; Khan, Mumit; Cerrina, Franco

1998-06-01

In semiconductor processing, the modeling of the process is becoming more and more important. While the ultimate goal is that of developing a set of tools for designing a complete process (Technology CAD), it is also necessary to have modules to simulate the various technologies and, in particular, to optimize specific steps. This need is particularly acute in lithography, where the continuous decrease in CD forces the technologies to operate near their limits. In the development of a 'model' for a physical process, we face several levels of challenges. First, it is necessary to develop a 'physical model,' i.e. a rational description of the process itself on the basis of know physical laws. Second, we need an 'algorithmic model' to represent in a virtual environment the behavior of the 'physical model.' After a 'complete' model has been developed and verified, it becomes possible to do performance analysis. In many cases the input parameters are poorly known or not accessible directly to experiment. It would be extremely useful to obtain the values of these 'hidden' parameters from experimental results by comparing model to data. This is particularly severe, because the complexity and costs associated with semiconductor processing make a simple 'trial-and-error' approach infeasible and cost- inefficient. Even when computer models of the process already exists, obtaining data through simulations may be time consuming. Neural networks (NN) are powerful computational tools to predict the behavior of a system from an existing data set. They are able to adaptively 'learn' input/output mappings and to act as universal function approximators. In this paper we use artificial neural networks to build a mapping from the input parameters of the process to output parameters which are indicative of the performance of the process. Once the NN has been 'trained,' it is also possible to observe the process 'in reverse,' and to extract the values of the inputs which yield outputs with desired characteristics. Using this method, we can extract optimum values for the parameters and determine the process latitude very quickly.

Hydrology or biology? Modeling simplistic physical constraints on lake carbon biogeochemistry to identify when and where biology is likely to matter

NASA Astrophysics Data System (ADS)

Jones, S.; Zwart, J. A.; Solomon, C.; Kelly, P. T.

2017-12-01

Current efforts to scale lake carbon biogeochemistry rely heavily on empirical observations and rarely consider physical or biological inter-lake heterogeneity that is likely to regulate terrestrial dissolved organic carbon (tDOC) decomposition in lakes. This may in part result from a traditional focus of lake ecologists on in-lake biological processes OR physical-chemical pattern across lake regions, rather than on process AND pattern across scales. To explore the relative importance of local biological processes and physical processes driven by lake hydrologic setting, we created a simple, analytical model of tDOC decomposition in lakes that focuses on the regulating roles of lake size and catchment hydrologic export. Our simplistic model can generally recreate patterns consistent with both local- and regional-scale patterns in tDOC concentration and decomposition. We also see that variation in lake hydrologic setting, including the importance of evaporation as a hydrologic export, generates significant, emergent variation in tDOC decomposition at a given hydrologic residence time, and creates patterns that have been historically attributed to variation in tDOC quality. Comparing predictions of this `biologically null model' to field observations and more biologically complex models could indicate when and where biology is likely to matter most.

The efficiency of driving chemical reactions by a physical non-equilibrium is kinetically controlled.

PubMed

Göppel, Tobias; Palyulin, Vladimir V; Gerland, Ulrich

2016-07-27

An out-of-equilibrium physical environment can drive chemical reactions into thermodynamically unfavorable regimes. Under prebiotic conditions such a coupling between physical and chemical non-equilibria may have enabled the spontaneous emergence of primitive evolutionary processes. Here, we study the coupling efficiency within a theoretical model that is inspired by recent laboratory experiments, but focuses on generic effects arising whenever reactant and product molecules have different transport coefficients in a flow-through system. In our model, the physical non-equilibrium is represented by a drift-diffusion process, which is a valid coarse-grained description for the interplay between thermophoresis and convection, as well as for many other molecular transport processes. As a simple chemical reaction, we consider a reversible dimerization process, which is coupled to the transport process by different drift velocities for monomers and dimers. Within this minimal model, the coupling efficiency between the non-equilibrium transport process and the chemical reaction can be analyzed in all parameter regimes. The analysis shows that the efficiency depends strongly on the Damköhler number, a parameter that measures the relative timescales associated with the transport and reaction kinetics. Our model and results will be useful for a better understanding of the conditions for which non-equilibrium environments can provide a significant driving force for chemical reactions in a prebiotic setting.

Evaluation of SCS-CN method using a fully distributed physically based coupled surface-subsurface flow model

NASA Astrophysics Data System (ADS)

Shokri, Ali

2017-04-01

The hydrological cycle contains a wide range of linked surface and subsurface flow processes. In spite of natural connections between surface water and groundwater, historically, these processes have been studied separately. The current trend in hydrological distributed physically based model development is to combine distributed surface water models with distributed subsurface flow models. This combination results in a better estimation of the temporal and spatial variability of the interaction between surface and subsurface flow. On the other hand, simple lumped models such as the Soil Conservation Service Curve Number (SCS-CN) are still quite common because of their simplicity. In spite of the popularity of the SCS-CN method, there have always been concerns about the ambiguity of the SCS-CN method in explaining physical mechanism of rainfall-runoff processes. The aim of this study is to minimize these ambiguity by establishing a method to find an equivalence of the SCS-CN solution to the DrainFlow model, which is a fully distributed physically based coupled surface-subsurface flow model. In this paper, two hypothetical v-catchment tests are designed and the direct runoff from a storm event are calculated by both SCS-CN and DrainFlow models. To find a comparable solution to runoff prediction through the SCS-CN and DrainFlow, the variance between runoff predictions by the two models are minimized by changing Curve Number (CN) and initial abstraction (Ia) values. Results of this study have led to a set of lumped model parameters (CN and Ia) for each catchment that is comparable to a set of physically based parameters including hydraulic conductivity, Manning roughness coefficient, ground surface slope, and specific storage. Considering the lack of physical interpretation in CN and Ia is often argued as a weakness of SCS-CN method, the novel method in this paper gives a physical explanation to CN and Ia.

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.

Multi-physics CFD simulations in engineering

NASA Astrophysics Data System (ADS)

Yamamoto, Makoto

2013-08-01

Nowadays Computational Fluid Dynamics (CFD) software is adopted as a design and analysis tool in a great number of engineering fields. We can say that single-physics CFD has been sufficiently matured in the practical point of view. The main target of existing CFD software is single-phase flows such as water and air. However, many multi-physics problems exist in engineering. Most of them consist of flow and other physics, and the interactions between different physics are very important. Obviously, multi-physics phenomena are critical in developing machines and processes. A multi-physics phenomenon seems to be very complex, and it is so difficult to be predicted by adding other physics to flow phenomenon. Therefore, multi-physics CFD techniques are still under research and development. This would be caused from the facts that processing speed of current computers is not fast enough for conducting a multi-physics simulation, and furthermore physical models except for flow physics have not been suitably established. Therefore, in near future, we have to develop various physical models and efficient CFD techniques, in order to success multi-physics simulations in engineering. In the present paper, I will describe the present states of multi-physics CFD simulations, and then show some numerical results such as ice accretion and electro-chemical machining process of a three-dimensional compressor blade which were obtained in my laboratory. Multi-physics CFD simulations would be a key technology in near future.

Modelling of runoff generation and soil moisture dynamics for hillslopes and micro-catchments

NASA Astrophysics Data System (ADS)

Bronstert, Axel; Plate, Erich J.

1997-11-01

The modelling of hillslope hydrology is of great importance not only for the reason that all non-plain, i.e. hilly or mountainous, landscapes can be considered as being composed of a mosaic of hillslopes. A hillslope model may also be used for both research purposes and for application-oriented, detailed, hillslope-scale hydrological studies in conjunction with related scientific disciplines such as geotechnics, geo-chemistry and environmental technology. Despite the current limited application of multi-process and multi-dimensional hydrological models (particularly at the hillslope scale), hardly any comprehensive model has been available for operational use. In this paper we introduce a model which considers most of the relevant hillslope hydrological processes. Some recent applications are described which demonstrate its ability to narrow the stated gap in hillslope hydrological modelling. The modelling system accounts for the hydrological processes of interception, evapotranspiration, infiltration, soil-moisture movement (where the flow processes can be modelled in three dimensions), surface runoff, subsurface stormflow and streamflow discharge. The relevant process interactions are also included. Special regard has been given to consideration of state-of-the-art knowledge concerning rapid soilwater flow processes during storm conditions (e.g. macropore infiltration, lateral subsurface stormflow, return flow) and to its transfer to and inclusion within an operational modelling scheme. The model is "physically based" in the sense that its parameters have a physical meaning and can be obtained or derived from field measurements. This somewhat weaker than usual definition of a physical basis implies that some of the sub-models (still) contain empirical components, that the effects of the high spatial and temporal variability found in nature cannot always be expressed within the various physical laws, i.e. that the laws are scale dependent, and that due to limitations of measurements and data processing, one can express only averaged and incomplete data conditions. Several applications demonstrate the reliable performance of the model for one-, two- and three-dimensional simulations. The described examples of application are part of a comprehensive erosion and agro-chemical transport study in a loessy agricultural catchment in southwestern Germany, and of a study on the sealing efficacy of capillary barriers in landfill covers.

Planning Model of Physics Learning In Senior High School To Develop Problem Solving Creativity Based On National Standard Of Education

NASA Astrophysics Data System (ADS)

Putra, A.; Masril, M.; Yurnetti, Y.

2018-04-01

One of the causes of low achievement of student’s competence in physics learning in high school is the process which they have not been able to develop student’s creativity in problem solving. This is shown that the teacher’s learning plan is not accordance with the National Eduction Standard. This study aims to produce a reconstruction model of physics learning that fullfil the competency standards, content standards, and assessment standards in accordance with applicable curriculum standards. The development process follows: Needs analysis, product design, product development, implementation, and product evaluation. The research process involves 2 peers judgment, 4 experts judgment and two study groups of high school students in Padang. The data obtained, in the form of qualitative and quantitative data that collected through documentation, observation, questionnaires, and tests. The result of this research up to the product development stage that obtained the physics learning plan model that meets the validity of the content and the validity of the construction in terms of the fulfillment of Basic Competence, Content Standards, Process Standards and Assessment Standards.

Initialization and assimilation of cloud and rainwater in a regional model

NASA Technical Reports Server (NTRS)

Raymond, William H.; Olson, William S.

1990-01-01

The initialization and assimilation of cloud and rainwater quantities in a mesoscale regional model was examined. Forecasts of explicit cloud and rainwater are made using conservation equations. The physical processes include condensation, evaporation, autoconversion, accretion, and the removal of rainwater by fallout. These physical processes, some of which are parameterized, represent source and sink in terms in the conservation equations. The question of how to initialize the explicit liquid water calculations in numerical models and how to retain information about precipitation processes during the 4-D assimilation cycle are important issues that are addressed.

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.

The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

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

Clark, Martyn P.; Bierkens, Marc F. P.; Samaniego, Luis

The diversity in hydrologic models has historically led to great controversy on the correct approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. Here, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We also illustrate how modeling advances have been made by groups using models of different type and complexity,more » and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.« less

The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

DOE PAGES

Clark, Martyn P.; Bierkens, Marc F. P.; Samaniego, Luis; ...

2017-07-11

The diversity in hydrologic models has historically led to great controversy on the correct approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. Here, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We also illustrate how modeling advances have been made by groups using models of different type and complexity,more » and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.« less

Toward a Model for Picture and Word Processing.

ERIC Educational Resources Information Center

Snodgrass, Joan Gay

A model was developed to account for similarities and differences between picture and word processing in a variety of semantic and episodic memory tasks. The model contains three levels of processing: low-level processing of the physical characteristics of externally presented pictures and words; an intermediate level where the low-level processor…

A Physically Based Coupled Chemical and Physical Weathering Model for Simulating Soilscape Evolution

NASA Astrophysics Data System (ADS)

Willgoose, G. R.; Welivitiya, D.; Hancock, G. R.

2015-12-01

A critical missing link in existing landscape evolution models is a dynamic soil evolution models where soils co-evolve with the landform. Work by the authors over the last decade has demonstrated a computationally manageable model for soil profile evolution (soilscape evolution) based on physical weathering. For chemical weathering it is clear that full geochemistry models such as CrunchFlow and PHREEQC are too computationally intensive to be couplable to existing soilscape and landscape evolution models. This paper presents a simplification of CrunchFlow chemistry and physics that makes the task feasible, and generalises it for hillslope geomorphology applications. Results from this simplified model will be compared with field data for soil pedogenesis. Other researchers have previously proposed a number of very simple weathering functions (e.g. exponential, humped, reverse exponential) as conceptual models of the in-profile weathering process. The paper will show that all of these functions are possible for specific combinations of in-soil environmental, geochemical and geologic conditions, and the presentation will outline the key variables controlling which of these conceptual models can be realistic models of in-profile processes and under what conditions. The presentation will finish by discussing the coupling of this model with a physical weathering model, and will show sample results from our SSSPAM soilscape evolution model to illustrate the implications of including chemical weathering in the soilscape evolution model.

Physical and mathematical modeling of antimicrobial photodynamic therapy

NASA Astrophysics Data System (ADS)

Bürgermeister, Lisa; López, Fernando Romero; Schulz, Wolfgang

2014-07-01

Antimicrobial photodynamic therapy (aPDT) is a promising method to treat local bacterial infections. The therapy is painless and does not cause bacterial resistances. However, there are gaps in understanding the dynamics of the processes, especially in periodontal treatment. This work describes the advances in fundamental physical and mathematical modeling of aPDT used for interpretation of experimental evidence. The result is a two-dimensional model of aPDT in a dental pocket phantom model. In this model, the propagation of laser light and the kinetics of the chemical reactions are described as coupled processes. The laser light induces the chemical processes depending on its intensity. As a consequence of the chemical processes, the local optical properties and distribution of laser light change as well as the reaction rates. The mathematical description of these coupled processes will help to develop treatment protocols and is the first step toward an inline feedback system for aPDT users.

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 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.

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).

An acoustic glottal source for vocal tract physical models

NASA Astrophysics Data System (ADS)

Hannukainen, Antti; Kuortti, Juha; Malinen, Jarmo; Ojalammi, Antti

2017-11-01

A sound source is proposed for the acoustic measurement of physical models of the human vocal tract. The physical models are produced by fast prototyping, based on magnetic resonance imaging during prolonged vowel production. The sound source, accompanied by custom signal processing algorithms, is used for two kinds of measurements from physical models of the vocal tract: (i) amplitude frequency response and resonant frequency measurements, and (ii) signal reconstructions at the source output according to a target pressure waveform with measurements at the mouth position. The proposed source and the software are validated by computational acoustics experiments and measurements on a physical model of the vocal tract corresponding to the vowels [] of a male speaker.

Disposal of Industrial and Domestic Wastes: Land and Sea Alternatives.

DTIC Science & Technology

1984-01-01

square kilometers. The rough classification of physical, chemical , and biological processes into near field versus far field and short term versus...contaminants by sedimentation is slowed. Chemical Precipitation and Dissolution During the few minutes of the initial dilution of a buoyant plume ...model. Time and space scales of physical, chemical , and biological processes often provide natural divisions in such modeling. Near -field and far-field

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.

A test harness for accelerating physics parameterization advancements into operations

NASA Astrophysics Data System (ADS)

Firl, G. J.; Bernardet, L.; Harrold, M.; Henderson, J.; Wolff, J.; Zhang, M.

2017-12-01

The process of transitioning advances in parameterization of sub-grid scale processes from initial idea to implementation is often much quicker than the transition from implementation to use in an operational setting. After all, considerable work must be undertaken by operational centers to fully test, evaluate, and implement new physics. The process is complicated by the scarcity of like-to-like comparisons, availability of HPC resources, and the ``tuning problem" whereby advances in physics schemes are difficult to properly evaluate without first undertaking the expensive and time-consuming process of tuning to other schemes within a suite. To address this process shortcoming, the Global Model TestBed (GMTB), supported by the NWS NGGPS project and undertaken by the Developmental Testbed Center, has developed a physics test harness. It implements the concept of hierarchical testing, where the same code can be tested in model configurations of varying complexity from single column models (SCM) to fully coupled, cycled global simulations. Developers and users may choose at which level of complexity to engage. Several components of the physics test harness have been implemented, including a SCM and an end-to-end workflow that expands upon the one used at NOAA/EMC to run the GFS operationally, although the testbed components will necessarily morph to coincide with changes to the operational configuration (FV3-GFS). A standard, relatively user-friendly interface known as the Interoperable Physics Driver (IPD) is available for physics developers to connect their codes. This prerequisite exercise allows access to the testbed tools and removes a technical hurdle for potential inclusion into the Common Community Physics Package (CCPP). The testbed offers users the opportunity to conduct like-to-like comparisons between the operational physics suite and new development as well as among multiple developments. GMTB staff have demonstrated use of the testbed through a comparison between the 2017 operational GFS suite and one containing the Grell-Freitas convective parameterization. An overview of the physics test harness and its early use will be presented.

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.

The Health Action Process Approach as a motivational model for physical activity self-management for people with multiple sclerosis: a path analysis.

PubMed

Chiu, Chung-Yi; Lynch, Ruth T; Chan, Fong; Berven, Norman L

2011-08-01

To evaluate the Health Action Process Approach (HAPA) as a motivational model for physical activity self-management for people with multiple sclerosis (MS). Quantitative descriptive research design using path analysis. One hundred ninety-five individuals with MS were recruited from the National Multiple Sclerosis Society and a neurology clinic at a university teaching hospital in the Midwest. Outcome was measured by the Physical Activity Stages of Change Instrument, along with measures for nine predictors (severity, action self-efficacy, outcome expectancy, risk perception, perceived barriers, intention, maintenance self-efficacy, action and coping planning, and recovery self-efficacy). The respecified HAPA physical activity model fit the data relatively well (goodness-of-fit index = .92, normed fit index = .91, and comparative fit index = .93) explaining 38% of the variance in physical activity. Recovery self-efficacy, action and coping planning, and perceived barriers directly contributed to the prediction of physical activity. Outcome expectancy significantly influenced intention and the relationship between intention and physical activity is mediated by action and coping planning. Action self-efficacy, maintenance self-efficacy, and recovery self-efficacy directly or indirectly affected physical activity. Severity of MS and action self-efficacy had an inverse relationship with perceived barriers and perceived barriers influenced physical activity. Empirical support was found for the proposed HAPA model of physical activity for people with MS. The HAPA model appears to provide useful information for clinical rehabilitation and health promotion interventions.

Reverse engineering physical models employing a sensor integration between 3D stereo detection and contact digitization

NASA Astrophysics Data System (ADS)

Chen, Liang-Chia; Lin, Grier C. I.

1997-12-01

A vision-drive automatic digitization process for free-form surface reconstruction has been developed, with a coordinate measurement machine (CMM) equipped with a touch-triggered probe and a CCD camera, in reverse engineering physical models. The process integrates 3D stereo detection, data filtering, Delaunay triangulation, adaptive surface digitization into a single process of surface reconstruction. By using this innovative approach, surface reconstruction can be implemented automatically and accurately. Least-squares B- spline surface models with the controlled accuracy of digitization can be generated for further application in product design and manufacturing processes. One industrial application indicates that this approach is feasible, and the processing time required in reverse engineering process can be significantly reduced up to more than 85%.

Site-level model intercomparison of high latitude and high altitude soil thermal dynamics in tundra and barren landscapes

NASA Astrophysics Data System (ADS)

Ekici, A.; Chadburn, S.; Chaudhary, N.; Hajdu, L. H.; Marmy, A.; Peng, S.; Boike, J.; Burke, E.; Friend, A. D.; Hauck, C.; Krinner, G.; Langer, M.; Miller, P. A.; Beer, C.

2015-07-01

Modeling soil thermal dynamics at high latitudes and altitudes requires representations of physical processes such as snow insulation, soil freezing and thawing and subsurface conditions like soil water/ice content and soil texture. We have compared six different land models: JSBACH, ORCHIDEE, JULES, COUP, HYBRID8 and LPJ-GUESS, at four different sites with distinct cold region landscape types, to identify the importance of physical processes in capturing observed temperature dynamics in soils. The sites include alpine, high Arctic, wet polygonal tundra and non-permafrost Arctic, thus showing how a range of models can represent distinct soil temperature regimes. For all sites, snow insulation is of major importance for estimating topsoil conditions. However, soil physics is essential for the subsoil temperature dynamics and thus the active layer thicknesses. This analysis shows that land models need more realistic surface processes, such as detailed snow dynamics and moss cover with changing thickness and wetness, along with better representations of subsoil thermal dynamics.

Validation of the TTM processes of change measure for physical activity in an adult French sample.

PubMed

Bernard, Paquito; Romain, Ahmed-Jérôme; Trouillet, Raphael; Gernigon, Christophe; Nigg, Claudio; Ninot, Gregory

2014-04-01

Processes of change (POC) are constructs from the transtheoretical model that propose to examine how people engage in a behavior. However, there is no consensus about a leading model explaining POC and there is no validated French POC scale in physical activity This study aimed to compare the different existing models to validate a French POC scale. Three studies, with 748 subjects included, were carried out to translate the items and evaluate their clarity (study 1, n = 77), to assess the factorial validity (n = 200) and invariance/equivalence (study 2, n = 471), and to analyze the concurrent validity by stage × process analyses (study 3, n = 671). Two models displayed adequate fit to the data; however, based on the Akaike information criterion, the fully correlated five-factor model appeared as the most appropriate to measure POC in physical activity. The invariance/equivalence was also confirmed across genders and student status. Four of the five existing factors discriminated pre-action and post-action stages. These data support the validation of the POC questionnaire in physical activity among a French sample. More research is needed to explore the longitudinal properties of this scale.

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.

A 2D modeling approach for fluid propagation during FE-forming simulation of continuously reinforced composites in wet compression moulding

NASA Astrophysics Data System (ADS)

Poppe, Christian; Dörr, Dominik; Henning, Frank; Kärger, Luise

2018-05-01

Wet compression moulding (WCM) provides large-scale production potential for continuously fiber reinforced components as a promising alternative to resin transfer moulding (RTM). Lower cycle times are possible due to parallelization of the process steps draping, infiltration and curing during moulding (viscous draping). Experimental and theoretical investigations indicate a strong mutual dependency between the physical mechanisms, which occur during draping and mould filling (fluid-structure-interaction). Thus, key process parameters, like fiber orientation, fiber volume fraction, cavity pressure and the amount and viscosity of the resin are physically coupled. To enable time and cost efficient product and process development throughout all design stages, accurate process simulation tools are desirable. Separated draping and mould filling simulation models, as appropriate for the sequential RTM-process, cannot be applied for the WCM process due to the above outlined physical couplings. Within this study, a two-dimensional Darcy-Propagation-Element (DPE-2D) based on a finite element formulation with additional control volumes (FE/CV) is presented, verified and applied to forming simulation of a generic geometry, as a first step towards a fluid-structure-interaction model taking into account simultaneous resin infiltration and draping. The model is implemented in the commercial FE-Solver Abaqus by means of several user subroutines considering simultaneous draping and 2D-infiltration mechanisms. Darcy's equation is solved with respect to a local fiber orientation. Furthermore, the material model can access the local fluid domain properties to update the mechanical forming material parameter, which enables further investigations on the coupled physical mechanisms.

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.

Multi-model comparison on the effects of climate change on tree species in the eastern U.S.: results from an enhanced niche model and process-based ecosystem and landscape models

Treesearch

Louis R. Iverson; Frank R. Thompson; Stephen Matthews; Matthew Peters; Anantha Prasad; William D. Dijak; Jacob Fraser; Wen J. Wang; Brice Hanberry; Hong He; Maria Janowiak; Patricia Butler; Leslie Brandt; Chris Swanston

2016-01-01

Context. Species distribution models (SDM) establish statistical relationships between the current distribution of species and key attributes whereas process-based models simulate ecosystem and tree species dynamics based on representations of physical and biological processes. TreeAtlas, which uses DISTRIB SDM, and Linkages and LANDIS PRO, process...

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

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Does job burnout mediate negative effects of job demands on mental and physical health in a group of teachers? Testing the energetic process of Job Demands-Resources model.

PubMed

Baka, Łukasz

2015-01-01

The aim of the study was to investigate the direct and indirect - mediated by job burnout - effects of job demands on mental and physical health problems. The Job Demands-Resources model was the theoretical framework of the study. Three job demands were taken into account - interpersonal conflicts at work, organizational constraints and workload. Indicators of mental and physical health problems included depression and physical symptoms, respectively. Three hundred and sixteen Polish teachers from 8 schools participated in the study. The hypotheses were tested with the use of tools measuring job demands (Interpersonal Conflicts at Work, Organizational Constraints, Quantitative Workload), job burnout (the Oldenburg Burnout Inventory), depression (the Beck Hopelessness Scale), and physical symptoms (the Physical Symptoms Inventory). The regression analysis with bootstrapping, using the PROCESS macros of Hayes was applied. The results support the hypotheses partially. The indirect effect and to some extent the direct effect of job demands turned out to be statistically important. The negative impact of 3 job demands on mental (hypothesis 1 - H1) and physical (hypothesis 2 - H2) health were mediated by the increasing job burnout. Only organizational constraints were directly associated with mental (and not physical) health. The results partially support the notion of the Job Demands-Resources model and provide further insight into processes leading to the low well-being of teachers in the workplace. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

The Canadian Assessment of Physical Literacy: Development of a Model of Children's Capacity for a Healthy, Active Lifestyle Through a Delphi Process.

PubMed

Francis, Claire E; Longmuir, Patricia E; Boyer, Charles; Andersen, Lars Bo; Barnes, Joel D; Boiarskaia, Elena; Cairney, John; Faigenbaum, Avery D; Faulkner, Guy; Hands, Beth P; Hay, John A; Janssen, Ian; Katzmarzyk, Peter T; Kemper, Han C; Knudson, Duane; Lloyd, Meghann; McKenzie, Thomas L; Olds, Tim S; Sacheck, Jennifer M; Shephard, Roy J; Zhu, Weimo; Tremblay, Mark S

2016-02-01

The Canadian Assessment of Physical Literacy (CAPL) was conceptualized as a tool to monitor children's physical literacy. The original model (fitness, activity behavior, knowledge, motor skill) required revision and relative weights for calculating/interpreting scores were required. Nineteen childhood physical activity/fitness experts completed a 3-round Delphi process. Round 1 was open-ended questions. Subsequent rounds rated statements using a 5-point Likert scale. Recommendations were sought regarding protocol inclusion, relative importance within composite scores and score interpretation. Delphi participant consensus was achieved for 64% (47/73) of statement topics, including a revised conceptual model, specific assessment protocols, the importance of longitudinal tracking, and the relative importance of individual protocols and composite scores. Divergent opinions remained regarding the inclusion of sleep time, assessment/ scoring of the obstacle course assessment of motor skill, and the need for an overall physical literacy classification. The revised CAPL model (overlapping domains of physical competence, motivation, and knowledge, encompassed by daily behavior) is appropriate for monitoring the physical literacy of children aged 8 to 12 years. Objectively measured domains (daily behavior, physical competence) have higher relative importance. The interpretation of CAPL results should be reevaluated as more data become available.

Decoupling the influence of biological and physical processes on the dissolved oxygen in the Chesapeake Bay

NASA Astrophysics Data System (ADS)

Du, Jiabi; Shen, Jian

2015-01-01

is instructive and essential to decouple the effects of biological and physical processes on the dissolved oxygen condition, in order to understand their contribution to the interannual variability of hypoxia in Chesapeake Bay since the 1980s. A conceptual bottom DO budget model is applied, using the vertical exchange time scale (VET) to quantify the physical condition and net oxygen consumption rate to quantify biological activities. By combining observed DO data and modeled VET values along the main stem of the Chesapeake Bay, the monthly net bottom DO consumption rate was estimated for 1985-2012. The DO budget model results show that the interannual variations of physical conditions accounts for 88.8% of the interannual variations of observed DO. The high similarity between the VET spatial pattern and the observed DO suggests that physical processes play a key role in regulating the DO condition. Model results also show that long-term VET has a slight increase in summer, but no statistically significant trend is found. Correlations among southerly wind strength, North Atlantic Oscillation index, and VET demonstrate that the physical condition in the Chesapeake Bay is highly controlled by the large-scale climate variation. The relationship is most significant during the summer, when the southerly wind dominates throughout the Chesapeake Bay. The seasonal pattern of the averaged net bottom DO consumption rate (B'20) along the main stem coincides with that of the chlorophyll-a concentration. A significant correlation between nutrient loading and B'20 suggests that the biological processes in April-May are most sensitive to the nutrient loading.

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.

LANDPLANER (LANDscape, Plants, LANdslide and ERosion): a model to describe the dynamic response of slopes (or basins) under different changing scenarios

NASA Astrophysics Data System (ADS)

Rossi, Mauro; Torri, Dino; Santi, Elisa; Bacaro, Giovanni; Marchesini, Ivan

2014-05-01

Landslide phenomena and erosion processes are widespread and cause every year extensive damages to the environment and sensible reduction of ecosystem services. These processes are in competition among them, and their complex interaction control the landscapes evolution. Landslide phenomena and erosion processes can be strongly influenced by land use, vegetation, soil characteristics and anthropic actions. Such type of phenomena are mainly model separately using empirical and physically based approaches. The former rely upon the identification of simple empirical laws correlating/relating the occurrence of instability processes to some of their potential causes. The latter are based on physical descriptions of the processes, and depending on the degree of complexity they can integrate different variables characterizing the process and their trigger. Those model often couple an hydrological model with an erosion or a landslide model. The spatial modeling schemas are heterogeneous, but mostly the raster (i.e. matrices of data) or the conceptual (i.e. cascading planes and channels) description of the terrain are used. The two model types are generally designed and applied at different scales. Empirical models, less demanding in terms of input data cannot consider explicitly the real process triggering mechanisms and commonly they are exploited to assess the potential occurrence of instability phenomena over large areas (small scale assessment). Physically-based models are high-demanding in term of input data, difficult to obtain over large areas if not with large uncertainty, and their applicability is often limited to small catchments or single slopes (large scale assessment). More those models, even if physically-based, are simplified description of the instability processes and can neglect significant issues of the real triggering mechanisms. For instance the influence of vegetation has been considered just partially. Although in the literature a variety of model approaches have been proposed to model separately landslide and erosion processes, only few attempts were made to model both jointly, mostly integrating pre-existing models. To overcome this limitation we develop a new model called LANDPLANER (LANDscape, Plants, LANdslide and ERosion), specifically design to describe the dynamic response of slopes (or basins) under different changing scenarios including: (i) changes of meteorological factors, (ii) changes of vegetation or land-use, (iii) and changes of slope morphology. The was applied in different study area in order to check its basic assumptions, and to test its general operability and applicability. Results show a reasonable model behaviors and confirm its easy applicability in real cases.

The Trans-Contextual Model of Autonomous Motivation in Education: Conceptual and Empirical Issues and Meta-Analysis

ERIC Educational Resources Information Center

Hagger, Martin S.; Chatzisarantis, Nikos L. D.

2016-01-01

The trans-contextual model outlines the processes by which autonomous motivation toward activities in a physical education context predicts autonomous motivation toward physical activity outside of school, and beliefs about, intentions toward, and actual engagement in, out-of-school physical activity. In the present article, we clarify the…

Physics textbooks from the viewpoint of network structures

NASA Astrophysics Data System (ADS)

Králiková, Petra; Teleki, Aba

2017-01-01

We can observe self-organized networks all around us. These networks are, in general, scale invariant networks described by the Bianconi-Barabasi model. The self-organized networks (networks formed naturally when feedback acts on the system) show certain universality. These networks, in simplified models, have scale invariant distribution (Pareto distribution type I) and parameter α has value between 2 and 5. The textbooks are extremely important in the learning process and from this reason we studied physics textbook at the level of sentences and physics terms (bipartite network). The nodes represent physics terms, sentences, and pictures, tables, connected by links (by physics terms and transitional words and transitional phrases). We suppose that learning process are more robust and goes faster and easier if the physics textbook has a structure similar to structures of self-organized networks.

Prediction of porosity of food materials during drying: Current challenges and directions.

PubMed

Joardder, Mohammad U H; Kumar, C; Karim, M A

2017-07-18

Pore formation in food samples is a common physical phenomenon observed during dehydration processes. The pore evolution during drying significantly affects the physical properties and quality of dried foods. Therefore, it should be taken into consideration when predicting transport processes in the drying sample. Characteristics of pore formation depend on the drying process parameters, product properties and processing time. Understanding the physics of pore formation and evolution during drying will assist in accurately predicting the drying kinetics and quality of food materials. Researchers have been trying to develop mathematical models to describe the pore formation and evolution during drying. In this study, existing porosity models are critically analysed and limitations are identified. Better insight into the factors affecting porosity is provided, and suggestions are proposed to overcome the limitations. These include considerations of process parameters such as glass transition temperature, sample temperature, and variable material properties in the porosity models. Several researchers have proposed models for porosity prediction of food materials during drying. However, these models are either very simplistic or empirical in nature and failed to consider relevant significant factors that influence porosity. In-depth understanding of characteristics of the pore is required for developing a generic model of porosity. A micro-level analysis of pore formation is presented for better understanding, which will help in developing an accurate and generic porosity model.

Physical Modeling for Processing Geosynchronous Imaging Fourier Transform Spectrometer-Indian Ocean METOC Imager (GIFTS-IOMI) Hyperspectral Data

DTIC Science & Technology

2002-09-30

Physical Modeling for Processing Geosynchronous Imaging Fourier Transform Spectrometer-Indian Ocean METOC Imager ( GIFTS -IOMI) Hyperspectral Data...water quality assessment. OBJECTIVES The objective of this DoD research effort is to develop and demonstrate a fully functional GIFTS - IOMI...environment once GIFTS -IOMI is stationed over the Indian Ocean. The system will provide specialized methods for the characterization of the atmospheric

The Effect of Scientific Inquiry Learning Model Based on Conceptual Change on Physics Cognitive Competence and Science Process Skill (SPS) of Students at Senior High School

ERIC Educational Resources Information Center

Sahhyar; Nst, Febriani Hastini

2017-01-01

The purpose of this research was to analyze the physics cognitive competence and science process skill of students using scientific inquiry learning model based on conceptual change better than using conventional learning. The research type was quasi experiment and two group pretest-posttest designs were used in this study. The sample were Class…

Modeling and analyses for an extended car-following model accounting for drivers' situation awareness from cyber physical perspective

NASA Astrophysics Data System (ADS)

Chen, Dong; Sun, Dihua; Zhao, Min; Zhou, Tong; Cheng, Senlin

2018-07-01

In fact, driving process is a typical cyber physical process which couples tightly the cyber factor of traffic information with the physical components of the vehicles. Meanwhile, the drivers have situation awareness in driving process, which is not only ascribed to the current traffic states, but also extrapolates the changing trend. In this paper, an extended car-following model is proposed to account for drivers' situation awareness. The stability criterion of the proposed model is derived via linear stability analysis. The results show that the stable region of proposed model will be enlarged on the phase diagram compared with previous models. By employing the reductive perturbation method, the modified Korteweg de Vries (mKdV) equation is obtained. The kink-antikink soliton of mKdV equation reveals theoretically the evolution of traffic jams. Numerical simulations are conducted to verify the analytical results. Two typical traffic Scenarios are investigated. The simulation results demonstrate that drivers' situation awareness plays a key role in traffic flow oscillations and the congestion transition.

The fiber walk: a model of tip-driven growth with lateral expansion.

PubMed

Bucksch, Alexander; Turk, Greg; Weitz, Joshua S

2014-01-01

Tip-driven growth processes underlie the development of many plants. To date, tip-driven growth processes have been modeled as an elongating path or series of segments, without taking into account lateral expansion during elongation. Instead, models of growth often introduce an explicit thickness by expanding the area around the completed elongated path. Modeling expansion in this way can lead to contradictions in the physical plausibility of the resulting surface and to uncertainty about how the object reached certain regions of space. Here, we introduce fiber walks as a self-avoiding random walk model for tip-driven growth processes that includes lateral expansion. In 2D, the fiber walk takes place on a square lattice and the space occupied by the fiber is modeled as a lateral contraction of the lattice. This contraction influences the possible subsequent steps of the fiber walk. The boundary of the area consumed by the contraction is derived as the dual of the lattice faces adjacent to the fiber. We show that fiber walks generate fibers that have well-defined curvatures, and thus enable the identification of the process underlying the occupancy of physical space. Hence, fiber walks provide a base from which to model both the extension and expansion of physical biological objects with finite thickness.

The Fiber Walk: A Model of Tip-Driven Growth with Lateral Expansion

PubMed Central

Bucksch, Alexander; Turk, Greg; Weitz, Joshua S.

2014-01-01

Tip-driven growth processes underlie the development of many plants. To date, tip-driven growth processes have been modeled as an elongating path or series of segments, without taking into account lateral expansion during elongation. Instead, models of growth often introduce an explicit thickness by expanding the area around the completed elongated path. Modeling expansion in this way can lead to contradictions in the physical plausibility of the resulting surface and to uncertainty about how the object reached certain regions of space. Here, we introduce fiber walks as a self-avoiding random walk model for tip-driven growth processes that includes lateral expansion. In 2D, the fiber walk takes place on a square lattice and the space occupied by the fiber is modeled as a lateral contraction of the lattice. This contraction influences the possible subsequent steps of the fiber walk. The boundary of the area consumed by the contraction is derived as the dual of the lattice faces adjacent to the fiber. We show that fiber walks generate fibers that have well-defined curvatures, and thus enable the identification of the process underlying the occupancy of physical space. Hence, fiber walks provide a base from which to model both the extension and expansion of physical biological objects with finite thickness. PMID:24465607

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...

Modeling Adsorption-Desorption Processes at the Intermolecular Interactions Level

NASA Astrophysics Data System (ADS)

Varfolomeeva, Vera V.; Terentev, Alexey V.

2018-01-01

Modeling of the surface adsorption and desorption processes, as well as the diffusion, are of considerable interest for the physical phenomenon under study in ground tests conditions. When imitating physical processes and phenomena, it is important to choose the correct parameters to describe the adsorption of gases and the formation of films on the structural materials surface. In the present research the adsorption-desorption processes on the gas-solid interface are modeled with allowance for diffusion. Approaches are proposed to describe the adsorbate distribution on the solid body surface at the intermolecular interactions level. The potentials of the intermolecular interaction of water-water, water-methane and methane-methane were used to adequately modeling the real physical and chemical processes. The energies calculated by the B3LYP/aug-cc-pVDZ method. Computational algorithms for determining the average molecule area in a dense monolayer, are considered here. Differences in modeling approaches are also given: that of the proposed in this work and the previously approved probabilistic cellular automaton (PCA) method. It has been shown that the main difference is due to certain limitations of the PCA method. The importance of accounting the intermolecular interactions via hydrogen bonding has been indicated. Further development of the adsorption-desorption processes modeling will allow to find the conditions for of surface processes regulation by means of quantity adsorbed molecules control. The proposed approach to representing the molecular system significantly shortens the calculation time in comparison with the use of atom-atom potentials. In the future, this will allow to modeling the multilayer adsorption at a reasonable computational cost.

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.

Different modelling approaches to evaluate nitrogen transport and turnover at the watershed scale

NASA Astrophysics Data System (ADS)

Epelde, Ane Miren; Antiguedad, Iñaki; Brito, David; Jauch, Eduardo; Neves, Ramiro; Garneau, Cyril; Sauvage, Sabine; Sánchez-Pérez, José Miguel

2016-08-01

This study presents the simulation of hydrological processes and nutrient transport and turnover processes using two integrated numerical models: Soil and Water Assessment Tool (SWAT) (Arnold et al., 1998), an empirical and semi-distributed numerical model; and Modelo Hidrodinâmico (MOHID) (Neves, 1985), a physics-based and fully distributed numerical model. This work shows that both models reproduce satisfactorily water and nitrate exportation at the watershed scale at annual and daily basis, MOHID providing slightly better results. At the watershed scale, both SWAT and MOHID simulated similarly and satisfactorily the denitrification amount. However, as MOHID numerical model was the only one able to reproduce adequately the spatial variation of the soil hydrological conditions and water table level fluctuation, it proved to be the only model able of reproducing the spatial variation of the nutrient cycling processes that are dependent to the soil hydrological conditions such as the denitrification process. This evidences the strength of the fully distributed and physics-based models to simulate the spatial variability of nutrient cycling processes that are dependent to the hydrological conditions of the soils.

Reevaluating the two-representation model of numerical magnitude processing.

PubMed

Jiang, Ting; Zhang, Wenfeng; Wen, Wen; Zhu, Haiting; Du, Han; Zhu, Xiangru; Gao, Xuefei; Zhang, Hongchuan; Dong, Qi; Chen, Chuansheng

2016-01-01

One debate in mathematical cognition centers on the single-representation model versus the two-representation model. Using an improved number Stroop paradigm (i.e., systematically manipulating physical size distance), in the present study we tested the predictions of the two models for number magnitude processing. The results supported the single-representation model and, more importantly, explained how a design problem (failure to manipulate physical size distance) and an analytical problem (failure to consider the interaction between congruity and task-irrelevant numerical distance) might have contributed to the evidence used to support the two-representation model. This study, therefore, can help settle the debate between the single-representation and two-representation models.

NASA GPM GV Science Implementation

NASA Technical Reports Server (NTRS)

Petersen, W. A.

2009-01-01

Pre-launch algorithm development & post-launch product evaluation: The GPM GV paradigm moves beyond traditional direct validation/comparison activities by incorporating improved algorithm physics & model applications (end-to-end validation) in the validation process. Three approaches: 1) National Network (surface): Operational networks to identify and resolve first order discrepancies (e.g., bias) between satellite and ground-based precipitation estimates. 2) Physical Process (vertical column): Cloud system and microphysical studies geared toward testing and refinement of physically-based retrieval algorithms. 3) Integrated (4-dimensional): Integration of satellite precipitation products into coupled prediction models to evaluate strengths/limitations of satellite precipitation producers.

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...

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.

PREDICTING SUBSURFACE CONTAMINANT TRANSPORT AND TRANSFORMATION: CONSIDERATIONS FOR MODEL SELECTION AND FIELD VALIDATION

EPA Science Inventory

Predicting subsurface contaminant transport and transformation requires mathematical models based on a variety of physical, chemical, and biological processes. The mathematical model is an attempt to quantitatively describe observed processes in order to permit systematic forecas...

Evaluation of a Theory of Instructional Sequences for Physics Instruction

NASA Astrophysics Data System (ADS)

Wackermann, Rainer; Trendel, Georg; Fischer, Hans E.

2010-05-01

The background of the study is the theory of basis models of teaching and learning, a comprehensive set of models of learning processes which includes, for example, learning through experience and problem-solving. The combined use of different models of learning processes has not been fully investigated and it is frequently not clear under what circumstances a particular model should be used by teachers. In contrast, the theory under investigation here gives guidelines for choosing a particular model and provides instructional sequences for each model. The aim is to investigate the implementation of the theory applied to physics instruction and to show if possible effects for the students may be attributed to the use of the theory. Therefore, a theory-oriented education programme for 18 physics teachers was developed and implemented in the 2005/06 school year. The main features of the intervention consisted of coaching physics lessons and video analysis according to the theory. The study follows a pre-treatment-post design with non-equivalent control group. Findings of repeated-measures ANOVAs show large effects for teachers' subjective beliefs, large effects for classroom actions, and small to medium effects for student outcomes such as perceived instructional quality and student emotions. The teachers/classes that applied the theory especially well according to video analysis showed the larger effects. The results showed that differentiating between different models of learning processes improves physics instruction. Effects can be followed through to student outcomes. The education programme effect was clearer for classroom actions and students' outcomes than for teachers' beliefs.

A Toolkit to Study Sensitivity of the Geant4 Predictions to the Variations of the Physics Model Parameters

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

Fields, Laura; Genser, Krzysztof; Hatcher, Robert

Geant4 is the leading detector simulation toolkit used in high energy physics to design detectors and to optimize calibration and reconstruction software. It employs a set of carefully validated physics models to simulate interactions of particles with matter across a wide range of interaction energies. These models, especially the hadronic ones, rely largely on directly measured cross-sections and phenomenological predictions with physically motivated parameters estimated by theoretical calculation or measurement. Because these models are tuned to cover a very wide range of possible simulation tasks, they may not always be optimized for a given process or a given material. Thismore » raises several critical questions, e.g. how sensitive Geant4 predictions are to the variations of the model parameters, or what uncertainties are associated with a particular tune of a Geant4 physics model, or a group of models, or how to consistently derive guidance for Geant4 model development and improvement from a wide range of available experimental data. We have designed and implemented a comprehensive, modular, user-friendly software toolkit to study and address such questions. It allows one to easily modify parameters of one or several Geant4 physics models involved in the simulation, and to perform collective analysis of multiple variants of the resulting physics observables of interest and comparison against a variety of corresponding experimental data. Based on modern event-processing infrastructure software, the toolkit offers a variety of attractive features, e.g. flexible run-time configurable workflow, comprehensive bookkeeping, easy to expand collection of analytical components. Design, implementation technology, and key functionalities of the toolkit are presented and illustrated with results obtained with Geant4 key hadronic models.« less

Visual search for conjunctions of physical and numerical size shows that they are processed independently.

PubMed

Sobel, Kenith V; Puri, Amrita M; Faulkenberry, Thomas J; Dague, Taylor D

2017-03-01

The size congruity effect refers to the interaction between numerical magnitude and physical digit size in a symbolic comparison task. Though this effect is well established in the typical 2-item scenario, the mechanisms at the root of the interference remain unclear. Two competing explanations have emerged in the literature: an early interaction model and a late interaction model. In the present study, we used visual conjunction search to test competing predictions from these 2 models. Participants searched for targets that were defined by a conjunction of physical and numerical size. Some distractors shared the target's physical size, and the remaining distractors shared the target's numerical size. We held the total number of search items fixed and manipulated the ratio of the 2 distractor set sizes. The results from 3 experiments converge on the conclusion that numerical magnitude is not a guiding feature for visual search, and that physical and numerical magnitude are processed independently, which supports a late interaction model of the size congruity effect. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

[Advance in researches on the effect of forest on hydrological process].

PubMed

Zhang, Zhiqiang; Yu, Xinxiao; Zhao, Yutao; Qin, Yongsheng

2003-01-01

According to the effects of forest on hydrological process, forest hydrology can be divided into three related aspects: experimental research on the effects of forest changing on hydrological process quantity and water quality; mechanism study on the effects of forest changing on hydrological cycle, and establishing and exploitating physical-based distributed forest hydrological model for resource management and engineering construction. Orientation experiment research can not only support the first-hand data for forest hydrological model, but also make clear the precipitation-runoff mechanisms. Research on runoff mechanisms can be valuable for the exploitation and improvement of physical based hydrological models. Moreover, the model can also improve the experimental and runoff mechanism researches. A review of above three aspects are summarized in this paper.

Comparison of effects of cold-region soil/snow processes and the uncertainties from model forcing data on permafrost physical characteristics

DOE PAGES

Barman, Rahul; Jain, Atul K.

2016-03-28

Here, we used a land surface model to (1) evaluate the influence of recent improvements in modeling cold-region soil/snow physics on near-surface permafrost physical characteristics (within 0–3 m soil column) in the northern high latitudes (NHL) and (2) compare them with uncertainties from climate and land-cover data sets. Specifically, four soil/snow processes are investigated: deep soil energetics, soil organic carbon (SOC) effects on soil properties, wind compaction of snow, and depth hoar formation. In the model, together they increased the contemporary NHL permafrost area by 9.2 × 10 6 km 2 (from 2.9 to 12.3—without and with these processes, respectively)more » and reduced historical degradation rates. In comparison, permafrost area using different climate data sets (with annual air temperature difference of ~0.5°C) differed by up to 2.3 × 10 6 km 2, with minimal contribution of up to 0.7 × 10 6 km 2 from substantial land-cover differences. Individually, the strongest role in permafrost increase was from deep soil energetics, followed by contributions from SOC and wind compaction, while depth hoar decreased permafrost. The respective contribution on 0–3 m permafrost stability also followed a similar pattern. However, soil temperature and moisture within vegetation root zone (~0–1 m), which strongly influence soil biogeochemistry, were only affected by the latter three processes. The ecosystem energy and water fluxes were impacted the least due to these soil/snow processes. While it is evident that simulated permafrost physical characteristics benefit from detailed treatment of cold-region biogeophysical processes, we argue that these should also lead to integrated improvements in modeling of biogeochemistry.« less

Are Atmospheric Updrafts a Key to Unlocking Climate Forcing and Sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-06-08

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

75 FR 77475 - Endangered and Threatened Species; Proposed Threatened Status for Subspecies of the Ringed Seal

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-10

... ice area are linked in the IPCC climate models to GHG emissions by the physics of radiation processes... scenario), a model that is known for incorporating advanced sea ice physics, and for which snow data were...

Solar Physics

NASA Technical Reports Server (NTRS)

Wu, S. T.

2000-01-01

The areas of emphasis are: (1) develop theoretical models of the transient release of magnetic energy in the solar atmosphere, e.g., in solar flares, eruptive prominences, coronal mass ejections, etc.; (2) investigate the role of the Sun's magnetic field in the structuring of solar corona by the development of three-dimensional numerical models that describe the field configuration at various heights in the solar atmosphere by extrapolating the field at the photospheric level; (3) develop numerical models to investigate the physical parameters obtained by the ULYSSES mission; (4) develop numerical and theoretical models to investigate solar activity effects on the solar wind characteristics for the establishment of the solar-interplanetary transmission line; and (5) develop new instruments to measure solar magnetic fields and other features in the photosphere, chromosphere transition region and corona. We focused our investigation on the fundamental physical processes in solar atmosphere which directly effect our Planet Earth. The overall goal is to establish the physical process for the Sun-Earth connections.

Defining event reconstruction of digital crime scenes.

PubMed

Carrier, Brian D; Spafford, Eugene H

2004-11-01

Event reconstruction plays a critical role in solving physical crimes by explaining why a piece of physical evidence has certain characteristics. With digital crimes, the current focus has been on the recognition and identification of digital evidence using an object's characteristics, but not on the identification of the events that caused the characteristics. This paper examines digital event reconstruction and proposes a process model and procedure that can be used for a digital crime scene. The model has been designed so that it can apply to physical crime scenes, can support the unique aspects of a digital crime scene, and can be implemented in software to automate part of the process. We also examine the differences between physical event reconstruction and digital event reconstruction.

The Problem-Solving Process in Physics as Observed When Engineering Students at University Level Work in Groups

ERIC Educational Resources Information Center

Gustafsson, Peter; Jonsson, Gunnar; Enghag, Margareta

2015-01-01

The problem-solving process is investigated for five groups of students when solving context-rich problems in an introductory physics course included in an engineering programme. Through transcripts of their conversation, the paths in the problem-solving process have been traced and related to a general problem-solving model. All groups exhibit…

A quantitative model for transforming reflectance spectra into the Munsell color space using cone sensitivity functions and opponent process weights.

PubMed

D'Andrade, Roy G; Romney, A Kimball

2003-05-13

This article presents a computational model of the process through which the human visual system transforms reflectance spectra into perceptions of color. Using physical reflectance spectra data and standard human cone sensitivity functions we describe the transformations necessary for predicting the location of colors in the Munsell color space. These transformations include quantitative estimates of the opponent process weights needed to transform cone activations into Munsell color space coordinates. Using these opponent process weights, the Munsell position of specific colors can be predicted from their physical spectra with a mean correlation of 0.989.

Physically-Based Models for the Reflection, Transmission and Subsurface Scattering of Light by Smooth and Rough Surfaces, with Applications to Realistic Image Synthesis

NASA Astrophysics Data System (ADS)

He, Xiao Dong

This thesis studies light scattering processes off rough surfaces. Analytic models for reflection, transmission and subsurface scattering of light are developed. The results are applicable to realistic image generation in computer graphics. The investigation focuses on the basic issue of how light is scattered locally by general surfaces which are neither diffuse nor specular; Physical optics is employed to account for diffraction and interference which play a crucial role in the scattering of light for most surfaces. The thesis presents: (1) A new reflectance model; (2) A new transmittance model; (3) A new subsurface scattering model. All of these models are physically-based, depend on only physical parameters, apply to a wide range of materials and surface finishes and more importantly, provide a smooth transition from diffuse-like to specular reflection as the wavelength and incidence angle are increased or the surface roughness is decreased. The reflectance and transmittance models are based on the Kirchhoff Theory and the subsurface scattering model is based on Energy Transport Theory. They are valid only for surfaces with shallow slopes. The thesis shows that predicted reflectance distributions given by the reflectance model compare favorably with experiment. The thesis also investigates and implements fast ways of computing the reflectance and transmittance models. Furthermore, the thesis demonstrates that a high level of realistic image generation can be achieved due to the physically -correct treatment of the scattering processes by the reflectance model.

A Model for Generation of Martian Surface Dust, Soil and Rock Coatings: Physical vs. Chemical Interactions, and Palagonitic Plus Hydrothermal Alteration

NASA Technical Reports Server (NTRS)

Bishop, J. L.; Murchie, S.; Pieters, C.; Zent, A.

1999-01-01

This model is one of many possible scenarios to explain the generation of the current surface material on Mars using chemical, magnetic and spectroscopic data from Mars and geologic analogs from terrestrial sites. One basic premise is that there are physical and chemical interactions of the atmospheric dust particles and that these two processes create distinctly different results. Physical processes distribute dust particles on rocks, forming physical rock coatings, and on the surface between rocks forming soil units; these are reversible processes. Chemical reactions of the dust/soil particles create alteration rinds on rock surfaces or duricrust surface units, both of which are relatively permanent materials. According to this model the mineral components of the dust/soil particles are derived from a combination of "typical" palagonitic weathering of volcanic ash and hydrothermally altered components, primarily from steam vents or fumeroles. Both of these altered materials are composed of tiny particles, about 1 micron or smaller, that are aggregates of silicates and iron oxide/oxyhydroxide/sulfate phases. Additional information is contained in the original extended abstract.

Removing the Blinders: Toward an Integrative Model of Organizational Change in Sport and Physical Activity.

ERIC Educational Resources Information Center

Cunningham, George B.

2002-01-01

Discusses the nature of the change process in physical education and sports, presenting a model to incorporate in studies of radical organizational change. The integration of four theories (institutionalism, population ecology, strategic choice, and resource dependence) provides the basis for the model. The paper offers a hypothetical example and…

Methodology for Physics and Engineering of Reliable Products

NASA Technical Reports Server (NTRS)

Cornford, Steven L.; Gibbel, Mark

1996-01-01

Physics of failure approaches have gained wide spread acceptance within the electronic reliability community. These methodologies involve identifying root cause failure mechanisms, developing associated models, and utilizing these models to inprove time to market, lower development and build costs and higher reliability. The methodology outlined herein sets forth a process, based on integration of both physics and engineering principles, for achieving the same goals.

A Constraints-Led Perspective to Understanding Skill Acquisition and Game Play: A Basis for Integration of Motor Learning Theory and Physical Education Praxis?

ERIC Educational Resources Information Center

Renshaw, Ian; Chow, Jia Yi; Davids, Keith; Hammond, John

2010-01-01

Background: In order to design appropriate environments for performance and learning of movement skills, physical educators need a sound theoretical model of the learner and of processes of learning. In physical education, this type of modelling informs the organisation of learning environments and effective and efficient use of practice time. An…

Modeling the Water Balloon Slingshot

NASA Astrophysics Data System (ADS)

Bousquet, Benjamin D.; Figura, Charles C.

2013-01-01

In the introductory physics courses at Wartburg College, we have been working to create a lab experience focused on the scientific process itself rather than verification of physical laws presented in the classroom or textbook. To this end, we have developed a number of open-ended modeling exercises suitable for a variety of learning environments, from non-science major classes to algebra-based and calculus-based introductory physics classes.

Using Machine Learning as a fast emulator of physical processes within the Met Office's Unified Model

NASA Astrophysics Data System (ADS)

Prudden, R.; Arribas, A.; Tomlinson, J.; Robinson, N.

2017-12-01

The Unified Model is a numerical model of the atmosphere used at the UK Met Office (and numerous partner organisations including Korean Meteorological Agency, Australian Bureau of Meteorology and US Air Force) for both weather and climate applications.Especifically, dynamical models such as the Unified Model are now a central part of weather forecasting. Starting from basic physical laws, these models make it possible to predict events such as storms before they have even begun to form. The Unified Model can be simply described as having two components: one component solves the navier-stokes equations (usually referred to as the "dynamics"); the other solves relevant sub-grid physical processes (usually referred to as the "physics"). Running weather forecasts requires substantial computing resources - for example, the UK Met Office operates the largest operational High Performance Computer in Europe - and the cost of a typical simulation is spent roughly 50% in the "dynamics" and 50% in the "physics". Therefore there is a high incentive to reduce cost of weather forecasts and Machine Learning is a possible option because, once a machine learning model has been trained, it is often much faster to run than a full simulation. This is the motivation for a technique called model emulation, the idea being to build a fast statistical model which closely approximates a far more expensive simulation. In this paper we discuss the use of Machine Learning as an emulator to replace the "physics" component of the Unified Model. Various approaches and options will be presented and the implications for further model development, operational running of forecasting systems, development of data assimilation schemes, and development of ensemble prediction techniques will be discussed.

Advanced Machine Learning Emulators of Radiative Transfer Models

NASA Astrophysics Data System (ADS)

Camps-Valls, G.; Verrelst, J.; Martino, L.; Vicent, J.

2017-12-01

Physically-based model inversion methodologies are based on physical laws and established cause-effect relationships. A plethora of remote sensing applications rely on the physical inversion of a Radiative Transfer Model (RTM), which lead to physically meaningful bio-geo-physical parameter estimates. The process is however computationally expensive, needs expert knowledge for both the selection of the RTM, its parametrization and the the look-up table generation, as well as its inversion. Mimicking complex codes with statistical nonlinear machine learning algorithms has become the natural alternative very recently. Emulators are statistical constructs able to approximate the RTM, although at a fraction of the computational cost, providing an estimation of uncertainty, and estimations of the gradient or finite integral forms. We review the field and recent advances of emulation of RTMs with machine learning models. We posit Gaussian processes (GPs) as the proper framework to tackle the problem. Furthermore, we introduce an automatic methodology to construct emulators for costly RTMs. The Automatic Gaussian Process Emulator (AGAPE) methodology combines the interpolation capabilities of GPs with the accurate design of an acquisition function that favours sampling in low density regions and flatness of the interpolation function. We illustrate the good capabilities of our emulators in toy examples, leaf and canopy levels PROSPECT and PROSAIL RTMs, and for the construction of an optimal look-up-table for atmospheric correction based on MODTRAN5.

Modelling accumulation of marine plastics in the coastal zone; what are the dominant physical processes?

NASA Astrophysics Data System (ADS)

Critchell, Kay; Lambrechts, Jonathan

2016-03-01

Anthropogenic marine debris, mainly of plastic origin, is accumulating in estuarine and coastal environments around the world causing damage to fauna, flora and habitats. Plastics also have the potential to accumulate in the food web, as well as causing economic losses to tourism and sea-going industries. If we are to manage this increasing threat, we must first understand where debris is accumulating and why these locations are different to others that do not accumulate large amounts of marine debris. This paper demonstrates an advection-diffusion model that includes beaching, settling, resuspension/re-floating, degradation and topographic effects on the wind in nearshore waters to quantify the relative importance of these physical processes governing plastic debris accumulation. The aim of this paper is to prioritise research that will improve modelling outputs in the future. We have found that the physical characteristic of the source location has by far the largest effect on the fate of the debris. The diffusivity, used to parameterise the sub-grid scale movements, and the relationship between debris resuspension/re-floating from beaches and the wind shadow created by high islands also has a dramatic impact on the modelling results. The rate of degradation of macroplastics into microplastics also have a large influence in the result of the modelling. The other processes presented (settling, wind drift velocity) also help determine the fate of debris, but to a lesser degree. These findings may help prioritise research on physical processes that affect plastic accumulation, leading to more accurate modelling, and subsequently management in the future.

Mental Models in Expert Physics Reasoning.

ERIC Educational Resources Information Center

Roschelle, Jeremy; Greeno, James G.

Proposed is a relational framework for characterizing experienced physicists' representations of physics problem situations and the process of constructing these representations. A representation includes a coherent set of relations among: (1) a mental model of the objects in the situation, along with their relevant properties and relations; (2) a…

Biomorphodynamics: Physical-biological feedbacks that shape landscapes

USGS Publications Warehouse

Murray, A.B.; Knaapen, M.A.F.; Tal, M.; Kirwan, M.L.

2008-01-01

Plants and animals affect morphological evolution in many environments. The term "ecogeomorphology" describes studies that address such effects. In this opinion article we use the term "biomorphodynamics" to characterize a subset of ecogeomorphologic studies: those that investigate not only the effects of organisms on physical processes and morphology but also how the biological processes depend on morphology and physical forcing. The two-way coupling precipitates feedbacks, leading to interesting modes of behavior, much like the coupling between flow/sediment transport and morphology leads to rich morphodynamic behaviors. Select examples illustrate how even the basic aspects of some systems cannot be understood without considering biomorphodynamic coupling. Prominent examples include the dynamic interactions between vegetation and flow/sediment transport that can determine river channel patterns and the multifaceted biomorphodynamic feedbacks shaping tidal marshes and channel networks. These examples suggest that the effects of morphology and physical processes on biology tend to operate over the timescale of the evolution of the morphological pattern. Thus, in field studies, which represent a snapshot in the pattern evolution, these effects are often not as obvious as the effects of biology on physical processes. However, numerical modeling indicates that the influences on biology from physical processes can play a key role in shaping landscapes and that even local and temporary vegetation disturbances can steer large-scale, long-term landscape evolution. The prevalence of biomorphodynamic research is burgeoning in recent years, driven by societal need and a confluence of complex systems-inspired modeling approaches in ecology and geomorphology. To make fundamental progress in understanding the dynamics of many landscapes, our community needs to increasingly learn to look for two-way, biomorphodynamic feedbacks and to collect new types of data to support the modeling of such emergent interactions. Copyright 2008 by the American Geophysical Union.

Methodologies for Development of Patient Specific Bone Models from Human Body CT Scans

NASA Astrophysics Data System (ADS)

Chougule, Vikas Narayan; Mulay, Arati Vinayak; Ahuja, Bharatkumar Bhagatraj

2016-06-01

This work deals with development of algorithm for physical replication of patient specific human bone and construction of corresponding implants/inserts RP models by using Reverse Engineering approach from non-invasive medical images for surgical purpose. In medical field, the volumetric data i.e. voxel and triangular facet based models are primarily used for bio-modelling and visualization, which requires huge memory space. On the other side, recent advances in Computer Aided Design (CAD) technology provides additional facilities/functions for design, prototyping and manufacturing of any object having freeform surfaces based on boundary representation techniques. This work presents a process to physical replication of 3D rapid prototyping (RP) physical models of human bone from various CAD modeling techniques developed by using 3D point cloud data which is obtained from non-invasive CT/MRI scans in DICOM 3.0 format. This point cloud data is used for construction of 3D CAD model by fitting B-spline curves through these points and then fitting surface between these curve networks by using swept blend techniques. This process also can be achieved by generating the triangular mesh directly from 3D point cloud data without developing any surface model using any commercial CAD software. The generated STL file from 3D point cloud data is used as a basic input for RP process. The Delaunay tetrahedralization approach is used to process the 3D point cloud data to obtain STL file. CT scan data of Metacarpus (human bone) is used as the case study for the generation of the 3D RP model. A 3D physical model of the human bone is generated on rapid prototyping machine and its virtual reality model is presented for visualization. The generated CAD model by different techniques is compared for the accuracy and reliability. The results of this research work are assessed for clinical reliability in replication of human bone in medical field.

The NASA-AMES Research Center Stratospheric Aerosol Model. 1. Physical Processes and Computational Analogs

NASA Technical Reports Server (NTRS)

Turco, R. P.; Hamill, P.; Toon, O. B.; Whitten, R. C.; Kiang, C. S.

1979-01-01

A time-dependent one-dimensional model of the stratospheric sulfate aerosol layer is presented. In constructing the model, a wide range of basic physical and chemical processes are incorporated in order to avoid predetermining or biasing the model predictions. The simulation, which extends from the surface to an altitude of 58 km, includes the troposphere as a source of gases and condensation nuclei and as a sink for aerosol droplets. The size distribution of aerosol particles is resolved into 25 categories with particle radii increasing geometrically from 0.01 to 2.56 microns such that particle volume doubles between categories.

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

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.

On storm movement and its applications

NASA Astrophysics Data System (ADS)

Niemczynowicz, Janusz

Rainfall-runoff models applicable for design and analysis of sewage systems in urban areas are further developed in order to represent better different physical processes going on on an urban catchment. However, one important part of the modelling procedure, the generation of the rainfall input is still a weak point. The main problem is lack of adequate rainfall data which represent temporal and spatial variations of the natural rainfall process. Storm movement is a natural phenomenon which influences urban runoff. However, the rainfall movement and its influence on runoff generation process is not represented in presently available urban runoff simulation models. Physical description of the rainfall movement and its parameters is given based on detailed measurements performed on twelve gauges in Lund, Sweden. The paper discusses the significance of the rainfall movement on the runoff generation process and gives suggestions how the rainfall movement parameters may be used in runoff modelling.

Basic Processes and Instructional Practices in Teaching Reading. Reading Education Report No. 7.

ERIC Educational Resources Information Center

Pearson, P. David; Kamil, Michael L.

Informal reading models, although more like metaphors than truly scientific models, may be just as useful in making instructional decisions as formal models are in physical science. Models are a vital part of the instructional process even when teachers are not consciously aware of their presence. Three classes of reading models are bottom-up…

Cirrus Susceptibility to Changes in Ice Nuclei: Physical Processes, Model Uncertainties, and Measurement Needs

NASA Technical Reports Server (NTRS)

Jensen, Eric

2017-01-01

In this talk, I will begin by discussing the physical processes that govern the competition between heterogeneous and homogeneous ice nucleation in upper tropospheric cirrus clouds. Next, I will review the current knowledge of low-temperature ice nucleation from laboratory experiments and field measurements. I will then discuss the uncertainties and deficiencies in representations of cirrus processes in global models used to estimate the climate impacts of changes in cirrus clouds. Lastly, I will review the critical field measurements needed to advance our understanding of cirrus and their susceptibility to changes in aerosol properties.

A Goddard Multi-Scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, W.K.; Anderson, D.; Atlas, R.; Chern, J.; Houser, P.; Hou, A.; Lang, S.; Lau, W.; Peters-Lidard, C.; Kakar, R.;

Strategies for Large Scale Implementation of a Multiscale, Multiprocess Integrated Hydrologic Model

NASA Astrophysics Data System (ADS)

Kumar, M.; Duffy, C.

2006-05-01

Distributed models simulate hydrologic state variables in space and time while taking into account the heterogeneities in terrain, surface, subsurface properties and meteorological forcings. Computational cost and complexity associated with these model increases with its tendency to accurately simulate the large number of interacting physical processes at fine spatio-temporal resolution in a large basin. A hydrologic model run on a coarse spatial discretization of the watershed with limited number of physical processes needs lesser computational load. But this negatively affects the accuracy of model results and restricts physical realization of the problem. So it is imperative to have an integrated modeling strategy (a) which can be universally applied at various scales in order to study the tradeoffs between computational complexity (determined by spatio- temporal resolution), accuracy and predictive uncertainty in relation to various approximations of physical processes (b) which can be applied at adaptively different spatial scales in the same domain by taking into account the local heterogeneity of topography and hydrogeologic variables c) which is flexible enough to incorporate different number and approximation of process equations depending on model purpose and computational constraint. An efficient implementation of this strategy becomes all the more important for Great Salt Lake river basin which is relatively large (~89000 sq. km) and complex in terms of hydrologic and geomorphic conditions. Also the types and the time scales of hydrologic processes which are dominant in different parts of basin are different. Part of snow melt runoff generated in the Uinta Mountains infiltrates and contributes as base flow to the Great Salt Lake over a time scale of decades to centuries. The adaptive strategy helps capture the steep topographic and climatic gradient along the Wasatch front. Here we present the aforesaid modeling strategy along with an associated hydrologic modeling framework which facilitates a seamless, computationally efficient and accurate integration of the process model with the data model. The flexibility of this framework leads to implementation of multiscale, multiresolution, adaptive refinement/de-refinement and nested modeling simulations with least computational burden. However, performing these simulations and related calibration of these models over a large basin at higher spatio- temporal resolutions is computationally intensive and requires use of increasing computing power. With the advent of parallel processing architectures, high computing performance can be achieved by parallelization of existing serial integrated-hydrologic-model code. This translates to running the same model simulation on a network of large number of processors thereby reducing the time needed to obtain solution. The paper also discusses the implementation of the integrated model on parallel processors. Also will be discussed the mapping of the problem on multi-processor environment, method to incorporate coupling between hydrologic processes using interprocessor communication models, model data structure and parallel numerical algorithms to obtain high performance.

Modern meta-heuristics based on nonlinear physics processes: A review of models and design procedures

NASA Astrophysics Data System (ADS)

Salcedo-Sanz, S.

2016-10-01

Meta-heuristic algorithms are problem-solving methods which try to find good-enough solutions to very hard optimization problems, at a reasonable computation time, where classical approaches fail, or cannot even been applied. Many existing meta-heuristics approaches are nature-inspired techniques, which work by simulating or modeling different natural processes in a computer. Historically, many of the most successful meta-heuristic approaches have had a biological inspiration, such as evolutionary computation or swarm intelligence paradigms, but in the last few years new approaches based on nonlinear physics processes modeling have been proposed and applied with success. Non-linear physics processes, modeled as optimization algorithms, are able to produce completely new search procedures, with extremely effective exploration capabilities in many cases, which are able to outperform existing optimization approaches. In this paper we review the most important optimization algorithms based on nonlinear physics, how they have been constructed from specific modeling of a real phenomena, and also their novelty in terms of comparison with alternative existing algorithms for optimization. We first review important concepts on optimization problems, search spaces and problems' difficulty. Then, the usefulness of heuristics and meta-heuristics approaches to face hard optimization problems is introduced, and some of the main existing classical versions of these algorithms are reviewed. The mathematical framework of different nonlinear physics processes is then introduced as a preparatory step to review in detail the most important meta-heuristics based on them. A discussion on the novelty of these approaches, their main computational implementation and design issues, and the evaluation of a novel meta-heuristic based on Strange Attractors mutation will be carried out to complete the review of these techniques. We also describe some of the most important application areas, in broad sense, of meta-heuristics, and describe free-accessible software frameworks which can be used to make easier the implementation of these algorithms.

Aspects of the Cognitive Model of Physics Problem Solving.

ERIC Educational Resources Information Center

Brekke, Stewart E.

Various aspects of the cognitive model of physics problem solving are discussed in detail including relevant cues, encoding, memory, and input stimuli. The learning process involved in the recognition of familiar and non-familiar sensory stimuli is highlighted. Its four components include selection, acquisition, construction, and integration. The…

Numerical simulations of an advection fog event over Shanghai Pudong International Airport with the WRF model

NASA Astrophysics Data System (ADS)

Lin, Caiyan; Zhang, Zhongfeng; Pu, Zhaoxia; Wang, Fengyun

2017-10-01

A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advection fog event over Shanghai Pudong International Airport (ZSPD) with the Weather Research and Forecasting (WRF) model. Using the current operational settings at the Meteorological Center of East China Air Traffic Management Bureau, the WRF model successfully predicts the fog event at ZSPD. Additional numerical experiments are performed to examine the physical processes associated with the fog event. The results indicate that prediction of this particular fog event is sensitive to microphysical schemes for the time of fog dissipation but not for the time of fog onset. The simulated timing of the arrival and dissipation of the fog, as well as the cloud distribution, is substantially sensitive to the planetary boundary layer and radiation (both longwave and shortwave) processes. Moreover, varying forecast lead times also produces different simulation results for the fog event regarding its onset and duration, suggesting a trade-off between more accurate initial conditions and a proper forecast lead time that allows model physical processes to spin up adequately during the fog simulation. The overall outcomes from this study imply that the complexity of physical processes and their interactions within the WRF model during fog evolution and dissipation is a key area of future research.

Perspective: Sloppiness and emergent theories in physics, biology, and beyond.

PubMed

Transtrum, Mark K; Machta, Benjamin B; Brown, Kevin S; Daniels, Bryan C; Myers, Christopher R; Sethna, James P

2015-07-07

Large scale models of physical phenomena demand the development of new statistical and computational tools in order to be effective. Many such models are "sloppy," i.e., exhibit behavior controlled by a relatively small number of parameter combinations. We review an information theoretic framework for analyzing sloppy models. This formalism is based on the Fisher information matrix, which is interpreted as a Riemannian metric on a parameterized space of models. Distance in this space is a measure of how distinguishable two models are based on their predictions. Sloppy model manifolds are bounded with a hierarchy of widths and extrinsic curvatures. The manifold boundary approximation can extract the simple, hidden theory from complicated sloppy models. We attribute the success of simple effective models in physics as likewise emerging from complicated processes exhibiting a low effective dimensionality. We discuss the ramifications and consequences of sloppy models for biochemistry and science more generally. We suggest that the reason our complex world is understandable is due to the same fundamental reason: simple theories of macroscopic behavior are hidden inside complicated microscopic processes.

Vertical structure and physical processes of the Madden-Julian oscillation: Linking hindcast fidelity to simulated diabatic heating and moistening

DOE PAGES

Klingaman, Nicholas P.; Woolnough, Steven J.; Jiang, Xianan; ...

2015-04-10

Here, many theories for the Madden-Julian oscillation (MJO) focus on diabatic processes, particularly the evolution of vertical heating and moistening. Poor MJO performance in weather and climate models is often blamed on biases in these processes and their interactions with the large-scale circulation. We introduce one of the three components of a model evaluation project, which aims to connect MJO fidelity in models to their representations of several physical processes, focusing on diabatic heating and moistening. This component consists of 20 day hindcasts, initialized daily during two MJO events in winter 2009–2010. The 13 models exhibit a range of skill:more » several have accurate forecasts to 20 days lead, while others perform similarly to statistical models (8–11 days). Models that maintain the observed MJO amplitude accurately predict propagation, but not vice versa. We find no link between hindcast fidelity and the precipitation-moisture relationship, in contrast to other recent studies. There is also no relationship between models' performance and the evolution of their diabatic heating profiles with rain rate. A more robust association emerges between models' fidelity and net moistening: the highest-skill models show a clear transition from low-level moistening for light rainfall to midlevel moistening at moderate rainfall and upper level moistening for heavy rainfall. The midlevel moistening, arising from both dynamics and physics, may be most important. Accurately representing many processes may be necessary but not sufficient for capturing the MJO, which suggests that models fail to predict the MJO for a broad range of reasons and limits the possibility of finding a panacea.« less

Algodoo: A Tool for Encouraging Creativity in Physics Teaching and Learning

NASA Astrophysics Data System (ADS)

Gregorcic, Bor; Bodin, Madelen

2017-01-01

Algodoo (http://www.algodoo.com) is a digital sandbox for physics 2D simulations. It allows students and teachers to easily create simulated "scenes" and explore physics through a user-friendly and visually attractive interface. In this paper, we present different ways in which students and teachers can use Algodoo to visualize and solve physics problems, investigate phenomena and processes, and engage in out-of-school activities and projects. Algodoo, with its approachable interface, inhabits a middle ground between computer games and "serious" computer modeling. It is suitable as an entry-level modeling tool for students of all ages and can facilitate discussions about the role of computer modeling in physics.

Computational Studies for Underground Coal Gasification (UCG) Process

NASA Astrophysics Data System (ADS)

Chatterjee, Dipankar

2017-07-01

Underground coal gasification (UCG) is a well proven technology in order to access the coal lying either too deep underground, or is otherwise too costly to be extracted using the conventional mining methods. UCG product gas is commonly used as a chemical feedstock or as fuel for power generation. During the UCG process, a cavity is formed in the coal seam during its conversion to gaseous products. The cavity grows in a three-dimensional fashion as the gasification proceeds. The UCG process is indeed a result of several complex interactions of various geo-thermo-mechanical processes such as the fluid flow, heat and mass transfer, chemical reactions, water influx, thermo-mechanical failure, and other geological aspects. The rate of the growth of this cavity and its shape will have a significant impact on the gas flow patterns, chemical kinetics, temperature distributions, and finally the quality of the product gas. It has been observed that there is insufficient information available in the literature to provide clear insight into these issues. It leaves us with a great opportunity to investigate and explore the UCG process, both from the experimental as well as theoretical perspectives. In the development and exploration of new research, experiment is undoubtedly very important. However, due to the excessive cost involvement with experimentation it is not always recommended for the complicated process like UCG. Recently, with the advent of the high performance computational facilities it is quite possible to make alternative experimentation numerically of many physically involved problems using certain computational tools like CFD (computational fluid dynamics). In order to gain a comprehensive understanding of the underlying physical phenomena, modeling strategies have frequently been utilized for the UCG process. Keeping in view the above, the various modeling strategies commonly deployed for carrying out mathematical modeling of UCG process are described here in a concise manner. The available strategies are categorized in several groups and their salient features are discussed in order to have a good understanding of the underlying physical phenomena. This would likely to be a valuable documentation in order to understand the physical process of UCG and will pave to formulate new and involved modeling and simulation techniques for computationally modeling the UCG process.

The physics of interstellar shock waves

NASA Technical Reports Server (NTRS)

Shull, J. Michael; Draine, Bruce T.

1987-01-01

This review discusses the observations and theoretical models of interstellar shock waves, in both diffuse cloud and molecular cloud environments. It summarizes the relevant gas dynamics, atomic, molecular and grain processes, radiative transfer, and physics of radiative and magnetic precursors in shock models. It then describes the importance of shocks for observations, diagnostics, and global interstellar dynamics. It concludes with current research problems and data needs for atomic, molecular and grain physics.

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.

The Nature and Role of Physical Models in Enhancing Sixth Grade Students' Mental Models of Groundwater and Groundwater Processes

ERIC Educational Resources Information Center

Duffy, Debra Lynne Foster

2012-01-01

Through a non-experimental descriptive and comparative mixed-methods approach, this study investigated the experiences of sixth grade earth science students with groundwater physical models through an extended SE learning cycle format. The data collection was based on a series of quantitative and qualitative research tools intended to investigate…

Optimization of the ANFIS using a genetic algorithm for physical work rate classification.

PubMed

Habibi, Ehsanollah; Salehi, Mina; Yadegarfar, Ghasem; Taheri, Ali

2018-03-13

Recently, a new method was proposed for physical work rate classification based on an adaptive neuro-fuzzy inference system (ANFIS). This study aims to present a genetic algorithm (GA)-optimized ANFIS model for a highly accurate classification of physical work rate. Thirty healthy men participated in this study. Directly measured heart rate and oxygen consumption of the participants in the laboratory were used for training the ANFIS classifier model in MATLAB version 8.0.0 using a hybrid algorithm. A similar process was done using the GA as an optimization technique. The accuracy, sensitivity and specificity of the ANFIS classifier model were increased successfully. The mean accuracy of the model was increased from 92.95 to 97.92%. Also, the calculated root mean square error of the model was reduced from 5.4186 to 3.1882. The maximum estimation error of the optimized ANFIS during the network testing process was ± 5%. The GA can be effectively used for ANFIS optimization and leads to an accurate classification of physical work rate. In addition to high accuracy, simple implementation and inter-individual variability consideration are two other advantages of the presented model.

Computer model for economic study of unbleached kraft paperboard production

Treesearch

Peter J. Ince

1984-01-01

Unbleached kraft paperboard is produced from wood fiber in an industrial papermaking process. A highly specific and detailed model of the process is presented. The model is also presented as a working computer program. A user of the computer program will provide data on physical parameters of the process and on prices of material inputs and outputs. The program is then...

Using a Systematic Conceptual Model for a Process Evaluation of a Middle School Obesity Risk-Reduction Nutrition Curriculum Intervention: "Choice, Control & Change"

ERIC Educational Resources Information Center

Lee, Heewon; Contento, Isobel R.; Koch, Pamela

2013-01-01

Objective: To use and review a conceptual model of process evaluation and to examine the implementation of a nutrition education curriculum, "Choice, Control & Change", designed to promote dietary and physical activity behaviors that reduce obesity risk. Design: A process evaluation study based on a systematic conceptual model. Setting: Five…

A new model of physical evolution of Jupiter-family comets

NASA Astrophysics Data System (ADS)

Rickman, H.; Szutowicz, S.; Wójcikowski, K.

2014-07-01

We aim to find the statistical physical lifetimes of Jupiter Family comets. For this purpose, we try to model the processes that govern the dynamical and physical evolution of comets. We pay special attention to physical evolution; attempts at such modelling have been made before, but we propose a more accurate model, which will include more physical effects. The model is tested on a sample of fictitious comets based on real Jupiter Family comets with some orbital elements changed to a state before the capture by Jupiter. We model four different physical effects: erosion by sublimation, dust mantling, rejuvenation (mantle blow-off), and splitting. While for sublimation and splitting there already are some models, like di Sisto et. al. (2009), and we only wish to make them more accurate, dust mantling and rejuvenation have not been included in previous, statistical physical evolution models. Each of these effects depends on one or more tunable parameters, which we establish by choosing the model that best fits the observed comet sample in a way similar to di Sisto et. al. (2009). In contrast to di Sisto et. al., our comparison also involves the observed active fractions vs. nuclear radii.

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*.

Introduction to Stochastic Simulations for Chemical and Physical Processes: Principles and Applications

ERIC Educational Resources Information Center

Weiss, Charles J.

2017-01-01

An introduction to digital stochastic simulations for modeling a variety of physical and chemical processes is presented. Despite the importance of stochastic simulations in chemistry, the prevalence of turn-key software solutions can impose a layer of abstraction between the user and the underlying approach obscuring the methodology being…

Advances in understanding and parameterization of small-scale physical processes in the marine Arctic climate system: a review

NASA Astrophysics Data System (ADS)

Vihma, T.; Pirazzini, R.; Fer, I.; Renfrew, I. A.; Sedlar, J.; Tjernström, M.; Lüpkes, C.; Nygård, T.; Notz, D.; Weiss, J.; Marsan, D.; Cheng, B.; Birnbaum, G.; Gerland, S.; Chechin, D.; Gascard, J. C.

2014-09-01

The Arctic climate system includes numerous highly interactive small-scale physical processes in the atmosphere, sea ice, and ocean. During and since the International Polar Year 2007-2009, significant advances have been made in understanding these processes. Here, these recent advances are reviewed, synthesized, and discussed. In atmospheric physics, the primary advances have been in cloud physics, radiative transfer, mesoscale cyclones, coastal, and fjordic processes as well as in boundary layer processes and surface fluxes. In sea ice and its snow cover, advances have been made in understanding of the surface albedo and its relationships with snow properties, the internal structure of sea ice, the heat and salt transfer in ice, the formation of superimposed ice and snow ice, and the small-scale dynamics of sea ice. For the ocean, significant advances have been related to exchange processes at the ice-ocean interface, diapycnal mixing, double-diffusive convection, tidal currents and diurnal resonance. Despite this recent progress, some of these small-scale physical processes are still not sufficiently understood: these include wave-turbulence interactions in the atmosphere and ocean, the exchange of heat and salt at the ice-ocean interface, and the mechanical weakening of sea ice. Many other processes are reasonably well understood as stand-alone processes but the challenge is to understand their interactions with and impacts and feedbacks on other processes. Uncertainty in the parameterization of small-scale processes continues to be among the greatest challenges facing climate modelling, particularly in high latitudes. Further improvements in parameterization require new year-round field campaigns on the Arctic sea ice, closely combined with satellite remote sensing studies and numerical model experiments.

Advances in understanding and parameterization of small-scale physical processes in the marine Arctic climate system: a review

NASA Astrophysics Data System (ADS)

Vihma, T.; Pirazzini, R.; Renfrew, I. A.; Sedlar, J.; Tjernström, M.; Nygård, T.; Fer, I.; Lüpkes, C.; Notz, D.; Weiss, J.; Marsan, D.; Cheng, B.; Birnbaum, G.; Gerland, S.; Chechin, D.; Gascard, J. C.

2013-12-01

The Arctic climate system includes numerous highly interactive small-scale physical processes in the atmosphere, sea ice, and ocean. During and since the International Polar Year 2007-2008, significant advances have been made in understanding these processes. Here these advances are reviewed, synthesized and discussed. In atmospheric physics, the primary advances have been in cloud physics, radiative transfer, mesoscale cyclones, coastal and fjordic processes, as well as in boundary-layer processes and surface fluxes. In sea ice and its snow cover, advances have been made in understanding of the surface albedo and its relationships with snow properties, the internal structure of sea ice, the heat and salt transfer in ice, the formation of super-imposed ice and snow ice, and the small-scale dynamics of sea ice. In the ocean, significant advances have been related to exchange processes at the ice-ocean interface, diapycnal mixing, tidal currents and diurnal resonance. Despite this recent progress, some of these small-scale physical processes are still not sufficiently understood: these include wave-turbulence interactions in the atmosphere and ocean, the exchange of heat and salt at the ice-ocean interface, and the mechanical weakening of sea ice. Many other processes are reasonably well understood as stand-alone processes but challenge is to understand their interactions with, and impacts and feedbacks on, other processes. Uncertainty in the parameterization of small-scale processes continues to be among the largest challenges facing climate modeling, and nowhere is this more true than in the Arctic. Further improvements in parameterization require new year-round field campaigns on the Arctic sea ice, closely combined with satellite remote sensing studies and numerical model experiments.

A longitudinal investigation of older adults' physical activity: Testing an integrated dual-process model.

PubMed

Arnautovska, Urska; Fleig, Lena; O'Callaghan, Frances; Hamilton, Kyra

2017-02-01

To assess the effects of conscious and non-conscious processes for prediction of older adults' physical activity (PA), we tested a dual-process model that integrated motivational (behavioural intention) and volitional (action planning and coping planning) processes with non-conscious, automatic processes (habit). Participants (N = 215) comprised community-dwelling older adults (M = 73.8 years). A longitudinal design was adopted to investigate direct and indirect effects of intentions, habit strength (Time 1), and action planning and coping planning (Time 2) on PA behaviour (Time 3). Structural equation modelling was used to evaluate the model. The model provided a good fit to the data, accounting for 44% of the variance in PA behaviour at Time 3. PA was predicted by intentions, action planning, and habit strength, with action planning mediating the intention-behaviour relationship. An effect of sex was also found where males used fewer planning strategies and engaged in more PA than females. By investigating an integration of conscious and non-conscious processes, this study provides a novel understanding of older adults' PA. Interventions aiming to promote PA behaviour of older adults should target the combination of psychological processes.

Calculation of the Intensity of Physical Time Fluctuations Using the Standard Solar Model and its Comparison with the Results of Experimental Measurements

NASA Astrophysics Data System (ADS)

Morozov, A. N.

2017-11-01

The article reviews the possibility of describing physical time as a random Poisson process. An equation allowing the intensity of physical time fluctuations to be calculated depending on the entropy production density within irreversible natural processes has been proposed. Based on the standard solar model the work calculates the entropy production density inside the Sun and the dependence of the intensity of physical time fluctuations on the distance to the centre of the Sun. A free model parameter has been established, and the method of its evaluation has been suggested. The calculations of the entropy production density inside the Sun showed that it differs by 2-3 orders of magnitude in different parts of the Sun. The intensity of physical time fluctuations on the Earth's surface depending on the entropy production density during the sunlight-to-Earth's thermal radiation conversion has been theoretically predicted. A method of evaluation of the Kullback's measure of voltage fluctuations in small amounts of electrolyte has been proposed. Using a simple model of the Earth's surface heat transfer to the upper atmosphere, the effective Earth's thermal radiation temperature has been determined. A comparison between the theoretical values of the Kullback's measure derived from the fluctuating physical time model and the experimentally measured values of this measure for two independent electrolytic cells showed a good qualitative and quantitative concurrence of predictions of both theoretical model and experimental data.

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.

Towards physical principles of biological evolution

NASA Astrophysics Data System (ADS)

Katsnelson, Mikhail I.; Wolf, Yuri I.; Koonin, Eugene V.

2018-03-01

Biological systems reach organizational complexity that far exceeds the complexity of any known inanimate objects. Biological entities undoubtedly obey the laws of quantum physics and statistical mechanics. However, is modern physics sufficient to adequately describe, model and explain the evolution of biological complexity? Detailed parallels have been drawn between statistical thermodynamics and the population-genetic theory of biological evolution. Based on these parallels, we outline new perspectives on biological innovation and major transitions in evolution, and introduce a biological equivalent of thermodynamic potential that reflects the innovation propensity of an evolving population. Deep analogies have been suggested to also exist between the properties of biological entities and processes, and those of frustrated states in physics, such as glasses. Such systems are characterized by frustration whereby local state with minimal free energy conflict with the global minimum, resulting in ‘emergent phenomena’. We extend such analogies by examining frustration-type phenomena, such as conflicts between different levels of selection, in biological evolution. These frustration effects appear to drive the evolution of biological complexity. We further address evolution in multidimensional fitness landscapes from the point of view of percolation theory and suggest that percolation at level above the critical threshold dictates the tree-like evolution of complex organisms. Taken together, these multiple connections between fundamental processes in physics and biology imply that construction of a meaningful physical theory of biological evolution might not be a futile effort. However, it is unrealistic to expect that such a theory can be created in one scoop; if it ever comes to being, this can only happen through integration of multiple physical models of evolutionary processes. Furthermore, the existing framework of theoretical physics is unlikely to suffice for adequate modeling of the biological level of complexity, and new developments within physics itself are likely to be required.

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.

Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework.

PubMed

Zammit-Mangion, Andrew; Rougier, Jonathan; Bamber, Jonathan; Schön, Nana

2014-06-01

Determining the Antarctic contribution to sea-level rise from observational data is a complex problem. The number of physical processes involved (such as ice dynamics and surface climate) exceeds the number of observables, some of which have very poor spatial definition. This has led, in general, to solutions that utilise strong prior assumptions or physically based deterministic models to simplify the problem. Here, we present a new approach for estimating the Antarctic contribution, which only incorporates descriptive aspects of the physically based models in the analysis and in a statistical manner. By combining physical insights with modern spatial statistical modelling techniques, we are able to provide probability distributions on all processes deemed to play a role in both the observed data and the contribution to sea-level rise. Specifically, we use stochastic partial differential equations and their relation to geostatistical fields to capture our physical understanding and employ a Gaussian Markov random field approach for efficient computation. The method, an instantiation of Bayesian hierarchical modelling, naturally incorporates uncertainty in order to reveal credible intervals on all estimated quantities. The estimated sea-level rise contribution using this approach corroborates those found using a statistically independent method. © 2013 The Authors. Environmetrics Published by John Wiley & Sons, Ltd.

Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework†

PubMed Central

Zammit-Mangion, Andrew; Rougier, Jonathan; Bamber, Jonathan; Schön, Nana

2014-01-01

Determining the Antarctic contribution to sea-level rise from observational data is a complex problem. The number of physical processes involved (such as ice dynamics and surface climate) exceeds the number of observables, some of which have very poor spatial definition. This has led, in general, to solutions that utilise strong prior assumptions or physically based deterministic models to simplify the problem. Here, we present a new approach for estimating the Antarctic contribution, which only incorporates descriptive aspects of the physically based models in the analysis and in a statistical manner. By combining physical insights with modern spatial statistical modelling techniques, we are able to provide probability distributions on all processes deemed to play a role in both the observed data and the contribution to sea-level rise. Specifically, we use stochastic partial differential equations and their relation to geostatistical fields to capture our physical understanding and employ a Gaussian Markov random field approach for efficient computation. The method, an instantiation of Bayesian hierarchical modelling, naturally incorporates uncertainty in order to reveal credible intervals on all estimated quantities. The estimated sea-level rise contribution using this approach corroborates those found using a statistically independent method. © 2013 The Authors. Environmetrics Published by John Wiley & Sons, Ltd. PMID:25505370

Multiphase Reactive Transport and Platelet Ice Accretion in the Sea Ice of McMurdo Sound, Antarctica

NASA Astrophysics Data System (ADS)

Buffo, J. J.; Schmidt, B. E.; Huber, C.

2018-01-01

Sea ice seasonally to interannually forms a thermal, chemical, and physical boundary between the atmosphere and hydrosphere over tens of millions of square kilometers of ocean. Its presence affects both local and global climate and ocean dynamics, ice shelf processes, and biological communities. Accurate incorporation of sea ice growth and decay, and its associated thermal and physiochemical processes, is underrepresented in large-scale models due to the complex physics that dictate oceanic ice formation and evolution. Two phenomena complicate sea ice simulation, particularly in the Antarctic: the multiphase physics of reactive transport brought about by the inhomogeneous solidification of seawater, and the buoyancy driven accretion of platelet ice formed by supercooled ice shelf water onto the basal surface of the overlying ice. Here a one-dimensional finite difference model capable of simulating both processes is developed and tested against ice core data. Temperature, salinity, liquid fraction, fluid velocity, total salt content, and ice structure are computed during model runs. The model results agree well with empirical observations and simulations highlight the effect platelet ice accretion has on overall ice thickness and characteristics. Results from sensitivity studies emphasize the need to further constrain sea ice microstructure and the associated physics, particularly permeability-porosity relationships, if a complete model of sea ice evolution is to be obtained. Additionally, implications for terrestrial ice shelves and icy moons in the solar system are discussed.

Processes in scientific workflows for information seeking related to physical sample materials

NASA Astrophysics Data System (ADS)

Ramdeen, S.

2014-12-01

The majority of State Geological Surveys have repositories containing cores, cuttings, fossils or other physical sample material. State surveys maintain these collections to support their own research as well as the research conducted by external users from other organizations. This includes organizations such as government agencies (state and federal), academia, industry and the public. The preliminary results presented in this paper will look at the research processes of these external users. In particular: how they discover, access and use digital surrogates, which they use to evaluate and access physical items in these collections. Data such as physical samples are materials that cannot be completely replaced with digital surrogates. Digital surrogates may be represented as metadata, which enable discovery and ultimately access to these samples. These surrogates may be found in records, databases, publications, etc. But surrogates do not completely prevent the need for access to the physical item as they cannot be subjected to chemical testing and/or other similar analysis. The goal of this research is to document the various processes external users perform in order to access physical materials. Data for this study will be collected by conducting interviews with these external users. During the interviews, participants will be asked to describe the workflow that lead them to interact with state survey repositories, and what steps they took afterward. High level processes/categories of behavior will be identified. These processes will be used in the development of an information seeking behavior model. This model may be used to facilitate the development of management tools and other aspects of cyberinfrastructure related to physical samples.

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.

PERSPECTIVE: Physical aspects of cancer invasion

NASA Astrophysics Data System (ADS)

Guiot, Caterina; Pugno, Nicola; Delsanto, Pier Paolo; Deisboeck, Thomas S.

2007-12-01

Invasiveness, one of the hallmarks of tumor progression, represents the tumor's ability to expand into the host tissue by means of several complex biochemical and biomechanical processes. Since certain aspects of the problem present a striking resemblance with well-known physical mechanisms, such as the mechanical insertion of a solid inclusion in an elastic material specimen (G Eaves 1973 The invasive growth of malignant tumours as a purely mechanical process J. Pathol. 109 233; C Guiot, N Pugno and P P Delsanto 2006 Elastomechanical model of tumor invasion Appl. Phys. Lett. 89 233901) or a water drop impinging on a surface (C Guiot, P P Delsanto and T S Deisboeck 2007 Morphological instability and cancer invasion: a 'splashing water drop' analogy Theor. Biol. Med. Model 4 4), we propose here an analogy between these physical processes and a cancer system's invasive branching into the surrounding tissue. Accounting for its solid and viscous properties, we then arrive, as a unifying model, to an analogy with a granular solid. While our model has been explicitly formulated for multicellular tumor spheroids in vitro, it should also contribute to a better understanding of tumor invasion in vivo.

Modeling the Oxygen Cycle in the Equatorial Pacific: Regulation of Physical and Biogeochemical Processes

NASA Astrophysics Data System (ADS)

Wang, X.; Murtugudde, R. G.; Zhang, D.

2016-12-01

Photosynthesis and respiration are important processes in all ecosystems on the Earth, in which carbon and oxygen are the two main elements. However, the oxygen cycle has received much less attention (relative to the carbon cycle) despite its big role in the earth system. Oxygen is a sensitive indicator of physical and biogeochemical processes in the ocean thus a key parameter for understanding the ocean's ecosystem and biogeochemistry. The Oxygen-Minimum-Zone (OMZ), often seen below 200 m, is a profound feature in the world oceans. There has been evidence of OMZ expansion over the past few decades in the tropical oceans. Climate models project that there would be a continued decline in dissolved oxygen (DO) and an expansion of the tropical OMZs under future warming conditions, which is of great concern because of the implications for marine organisms. We employ a validated three-dimensional model that simulates physical transport (circulation and vertical mixing), biological processes (O2 production and consumption) and ocean-atmosphere O2 exchange to quantify various sources and sinks of DO over 1980-2015. We show how we use observational data to improve our model simulation. Then we assess the spatial and temporal variability in simulated DO in the tropical Pacific Ocean, and explore the impacts of physical and biogeochemical processes on the DO dynamics, with a focus on the MOZ. Our analyses indicate that DO in the OMZ has a positive relationship with the 13ºC isotherm depth and a negative relationship with the concentration of dissolved organic material.

A Software Toolkit to Study Systematic Uncertainties of the Physics Models of the Geant4 Simulation Package

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

Genser, Krzysztof; Hatcher, Robert; Kelsey, Michael

The Geant4 simulation toolkit is used to model interactions between particles and matter. Geant4 employs a set of validated physics models that span a wide range of interaction energies. These models rely on measured cross-sections and phenomenological models with the physically motivated parameters that are tuned to cover many application domains. To study what uncertainties are associated with the Geant4 physics models we have designed and implemented a comprehensive, modular, user-friendly software toolkit that allows the variation of one or more parameters of one or more Geant4 physics models involved in simulation studies. It also enables analysis of multiple variantsmore » of the resulting physics observables of interest in order to estimate the uncertainties associated with the simulation model choices. Based on modern event-processing infrastructure software, the toolkit offers a variety of attractive features, e.g. exible run-time con gurable work ow, comprehensive bookkeeping, easy to expand collection of analytical components. Design, implementation technology, and key functionalities of the toolkit are presented in this paper and illustrated with selected results.« less

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.

A domain-decomposed multi-model plasma simulation of collisionless magnetic reconnection

NASA Astrophysics Data System (ADS)

Datta, I. A. M.; Shumlak, U.; Ho, A.; Miller, S. T.

2017-10-01

Collisionless magnetic reconnection is a process relevant to many areas of plasma physics in which energy stored in magnetic fields within highly conductive plasmas is rapidly converted into kinetic and thermal energy. Both in natural phenomena such as solar flares and terrestrial aurora as well as in magnetic confinement fusion experiments, the reconnection process is observed on timescales much shorter than those predicted by a resistive MHD model. As a result, this topic is an active area of research in which plasma models with varying fidelity have been tested in order to understand the proper physics explaining the reconnection process. In this research, a hybrid multi-model simulation employing the Hall-MHD and two-fluid plasma models on a decomposed domain is used to study this problem. The simulation is set up using the WARPXM code developed at the University of Washington, which uses a discontinuous Galerkin Runge-Kutta finite element algorithm and implements boundary conditions between models in the domain to couple their variable sets. The goal of the current work is to determine the parameter regimes most appropriate for each model to maintain sufficient physical fidelity over the whole domain while minimizing computational expense. This work is supported by a Grant from US AFOSR.

Model of a programmable quantum processing unit based on a quantum transistor effect

NASA Astrophysics Data System (ADS)

Ablayev, Farid; Andrianov, Sergey; Fetisov, Danila; Moiseev, Sergey; Terentyev, Alexandr; Urmanchev, Andrey; Vasiliev, Alexander

2018-02-01

In this paper we propose a model of a programmable quantum processing device realizable with existing nano-photonic technologies. It can be viewed as a basis for new high performance hardware architectures. Protocols for physical implementation of device on the controlled photon transfer and atomic transitions are presented. These protocols are designed for executing basic single-qubit and multi-qubit gates forming a universal set. We analyze the possible operation of this quantum computer scheme. Then we formalize the physical architecture by a mathematical model of a Quantum Processing Unit (QPU), which we use as a basis for the Quantum Programming Framework. This framework makes it possible to perform universal quantum computations in a multitasking environment.

Bayesian Analysis of Non-Gaussian Long-Range Dependent Processes

NASA Astrophysics Data System (ADS)

Graves, T.; Franzke, C.; Gramacy, R. B.; Watkins, N. W.

2012-12-01

Recent studies have strongly suggested that surface temperatures exhibit long-range dependence (LRD). The presence of LRD would hamper the identification of deterministic trends and the quantification of their significance. It is well established that LRD processes exhibit stochastic trends over rather long periods of time. Thus, accurate methods for discriminating between physical processes that possess long memory and those that do not are an important adjunct to climate modeling. We have used Markov Chain Monte Carlo algorithms to perform a Bayesian analysis of Auto-Regressive Fractionally-Integrated Moving-Average (ARFIMA) processes, which are capable of modeling LRD. Our principal aim is to obtain inference about the long memory parameter, d,with secondary interest in the scale and location parameters. We have developed a reversible-jump method enabling us to integrate over different model forms for the short memory component. We initially assume Gaussianity, and have tested the method on both synthetic and physical time series such as the Central England Temperature. Many physical processes, for example the Faraday time series from Antarctica, are highly non-Gaussian. We have therefore extended this work by weakening the Gaussianity assumption. Specifically, we assume a symmetric α -stable distribution for the innovations. Such processes provide good, flexible, initial models for non-Gaussian processes with long memory. We will present a study of the dependence of the posterior variance σ d of the memory parameter d on the length of the time series considered. This will be compared with equivalent error diagnostics for other measures of d.

Vertical structure and physical processes of the Madden-Julian oscillation: Exploring key model physics in climate simulations

DOE PAGES

Jiang, Xianan; Waliser, Duane E.; Xavier, Prince K.; ...

2015-05-27

Aimed at reducing deficiencies in representing the Madden-Julian oscillation (MJO) in general circulation models (GCMs), a global model evaluation project on vertical structure and physical processes of the MJO was coordinated. In this paper, results from the climate simulation component of this project are reported. Here, it is shown that the MJO remains a great challenge in these latest generation GCMs. The systematic eastward propagation of the MJO is only well simulated in about one fourth of the total participating models. The observed vertical westward tilt with altitude of the MJO is well simulated in good MJO models but notmore » in the poor ones. Damped Kelvin wave responses to the east of convection in the lower troposphere could be responsible for the missing MJO preconditioning process in these poor MJO models. Several process-oriented diagnostics were conducted to discriminate key processes for realistic MJO simulations. While large-scale rainfall partition and low-level mean zonal winds over the Indo-Pacific in a model are not found to be closely associated with its MJO skill, two metrics, including the low-level relative humidity difference between high- and low-rain events and seasonal mean gross moist stability, exhibit statistically significant correlations with the MJO performance. It is further indicated that increased cloud-radiative feedback tends to be associated with reduced amplitude of intraseasonal variability, which is incompatible with the radiative instability theory previously proposed for the MJO. Finally, results in this study confirm that inclusion of air-sea interaction can lead to significant improvement in simulating the MJO.« less

Dynamic Biological Functioning Important for Simulating and Stabilizing Ocean Biogeochemistry

NASA Astrophysics Data System (ADS)

Buchanan, P. J.; Matear, R. J.; Chase, Z.; Phipps, S. J.; Bindoff, N. L.

2018-04-01

The biogeochemistry of the ocean exerts a strong influence on the climate by modulating atmospheric greenhouse gases. In turn, ocean biogeochemistry depends on numerous physical and biological processes that change over space and time. Accurately simulating these processes is fundamental for accurately simulating the ocean's role within the climate. However, our simulation of these processes is often simplistic, despite a growing understanding of underlying biological dynamics. Here we explore how new parameterizations of biological processes affect simulated biogeochemical properties in a global ocean model. We combine 6 different physical realizations with 6 different biogeochemical parameterizations (36 unique ocean states). The biogeochemical parameterizations, all previously published, aim to more accurately represent the response of ocean biology to changing physical conditions. We make three major findings. First, oxygen, carbon, alkalinity, and phosphate fields are more sensitive to changes in the ocean's physical state. Only nitrate is more sensitive to changes in biological processes, and we suggest that assessment protocols for ocean biogeochemical models formally include the marine nitrogen cycle to assess their performance. Second, we show that dynamic variations in the production, remineralization, and stoichiometry of organic matter in response to changing environmental conditions benefit the simulation of ocean biogeochemistry. Third, dynamic biological functioning reduces the sensitivity of biogeochemical properties to physical change. Carbon and nitrogen inventories were 50% and 20% less sensitive to physical changes, respectively, in simulations that incorporated dynamic biological functioning. These results highlight the importance of a dynamic biology for ocean properties and climate.

Physical Modeling of Microtubules Network

NASA Astrophysics Data System (ADS)

Allain, Pierre; Kervrann, Charles

2014-10-01

Microtubules (MT) are highly dynamic tubulin polymers that are involved in many cellular processes such as mitosis, intracellular cell organization and vesicular transport. Nevertheless, the modeling of cytoskeleton and MT dynamics based on physical properties is difficult to achieve. Using the Euler-Bernoulli beam theory, we propose to model the rigidity of microtubules on a physical basis using forces, mass and acceleration. In addition, we link microtubules growth and shrinkage to the presence of molecules (e.g. GTP-tubulin) in the cytosol. The overall model enables linking cytosol to microtubules dynamics in a constant state space thus allowing usage of data assimilation techniques.

In vitro experimental investigation of voice production

PubMed Central

Horáčcek, Jaromír; Brücker, Christoph; Becker, Stefan

2012-01-01

The process of human phonation involves a complex interaction between the physical domains of structural dynamics, fluid flow, and acoustic sound production and radiation. Given the high degree of nonlinearity of these processes, even small anatomical or physiological disturbances can significantly affect the voice signal. In the worst cases, patients can lose their voice and hence the normal mode of speech communication. To improve medical therapies and surgical techniques it is very important to understand better the physics of the human phonation process. Due to the limited experimental access to the human larynx, alternative strategies, including artificial vocal folds, have been developed. The following review gives an overview of experimental investigations of artificial vocal folds within the last 30 years. The models are sorted into three groups: static models, externally driven models, and self-oscillating models. The focus is on the different models of the human vocal folds and on the ways in which they have been applied. PMID:23181007

Incorporating signal-dependent noise for hyperspectral target detection

NASA Astrophysics Data System (ADS)

Morman, Christopher J.; Meola, Joseph

2015-05-01

The majority of hyperspectral target detection algorithms are developed from statistical data models employing stationary background statistics or white Gaussian noise models. Stationary background models are inaccurate as a result of two separate physical processes. First, varying background classes often exist in the imagery that possess different clutter statistics. Many algorithms can account for this variability through the use of subspaces or clustering techniques. The second physical process, which is often ignored, is a signal-dependent sensor noise term. For photon counting sensors that are often used in hyperspectral imaging systems, sensor noise increases as the measured signal level increases as a result of Poisson random processes. This work investigates the impact of this sensor noise on target detection performance. A linear noise model is developed describing sensor noise variance as a linear function of signal level. The linear noise model is then incorporated for detection of targets using data collected at Wright Patterson Air Force Base.

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.

Toward a Stress Process Model of Children's Exposure to Physical Family and Community Violence

ERIC Educational Resources Information Center

Foster, Holly; Brooks-Gunn, Jeanne

2009-01-01

Theoretically informed models are required to further the comprehensive understanding of children's ETV. We draw on the stress process paradigm to forward an overall conceptual model of ETV (ETV) in childhood and adolescence. Around this conceptual model, we synthesize research in four dominant areas of the literature which are detailed but often…

A process-sedimentary framework for characterizing recent and ancient sabkhas

USGS Publications Warehouse

Handford, C.R.

1981-01-01

The discovery of sabkha environments during the 1960's, marked the beginning of Recent evaporite sedimentological studies and their perception as models for facies analysis. However, variation among Recent sabkhas, though recognized by the geologic community, has not been duly addressed, which has resulted in overuse of the Trucial Coast model in comparative sedimentological studies. Knowledge of the dominant physical processes which determine sabkha morphology, and of the sedimentary response to those processes, can lead to a fundamental understanding of a sabkha's origin and of how it differs from other sabkhas. Physical processes thought to be most important (besides evaporation) include those operative under: (1) marine-; (2) fluvial-lacustrine-; and (3) eolian-dominated conditions. Dominance of one or more of these in the proper settings give rise to marine coastal sabkhas, continental playas, and interdune sabkhas. Sedimentary responses to dominant physical processes lead to the development of sabkhas consisting of a combination of either: (1) terrigenous clastics; (2) carbonate-sulfate (anhydrite-gypsum) minerals; or (3) soluble salts (halite, sylvite, polyhalite, etc.). Sediment characterization can also allow discrimination of the range or compositional variety in, for example, coastal sabkhas. Where applied to the stratigraphic record, this classification system may help unravel the sedimentary history of an ancient sabkha system, and a determination of the dominant physical processes that ruled its development. ?? 1981.

Atomistic Model of Physical Ageing in Se-rich As-Se Glasses

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

Golovchak,R.; Shpotyuk, O.; Kozdras, A.

2007-01-01

Thermal, optical, X-ray excited and magnetic methods were used to develop a microstructural model of physical ageing in Se-rich glasses. The glass composition As10Se90, possessing a typical cross-linked chain structure, was chosen as a model object for the investigations. The effect of physical ageing in this glass was revealed by differential scanning calorimetry, whereas the corresponding changes in its atomic arrangement were studied by extended X-ray absorption fine structure, Raman and solid-state 77Se nuclear magnetic resonance spectroscopy. Straightening-shrinkage processes are shown to be responsible for the physical ageing in this Se-rich As-Se glass.

Crystal Growth of ZnSe by Physical Vapor Transport: A Modeling Study

NASA Technical Reports Server (NTRS)

Ramachandran, Narayanan; Su, Ching-Hua

1998-01-01

Crystal growth from the vapor phase has various advantages over melt growth. The main advantage is from a lower processing temperature which makes the process more amenable in instances where the melting temperature of the crystal is high. Other benefits stem from the inherent purification mechanism in the process due to differences in the vapor pressures of the native elements and impurities, and the enhanced interfacial morphological stability during the growth process. Further, the implementation of Physical Vapor Transport (PVT) growth in closed ampoules affords experimental simplicity with minimal needs for complex process control which makes it an ideal candidate for space investigations in systems where gravity tends to have undesirable effects on the growth process. Bulk growth of wide band gap II-VI semiconductors by physical vapor transport has been developed and refined over the past several years at NASA MSFC. Results from a modeling study of PVT crystal growth of ZnSe arc reported in this paper. The PVI process is numerically investigated using both two-dimensional and fully three-dimensional formulation of the governing equations and associated boundary conditions. Both the incompressible Boussinesq approximation and the compressible model are tested to determine the influence of gravity on the process and to discern the differences between the two approaches. The influence of a residual gas is included in the models. The preliminary results show that both the incompressible and compressible approximations provide comparable results and the presence of a residual gas tends to measurably reduce the mass flux in the system. Detailed flow, thermal and concentration profiles will be provided in the final manuscript along with computed heat and mass transfer rates. Comparisons with the 1-D model will also be provided.

3D finite element modelling of sheet metal blanking process

NASA Astrophysics Data System (ADS)

Bohdal, Lukasz; Kukielka, Leon; Chodor, Jaroslaw; Kulakowska, Agnieszka; Patyk, Radoslaw; Kaldunski, Pawel

2018-05-01

The shearing process such as the blanking of sheet metals has been used often to prepare workpieces for subsequent forming operations. The use of FEM simulation is increasing for investigation and optimizing the blanking process. In the current literature a blanking FEM simulations for the limited capability and large computational cost of the three dimensional (3D) analysis has been largely limited to two dimensional (2D) plane axis-symmetry problems. However, a significant progress in modelling which takes into account the influence of real material (e.g. microstructure of the material), physical and technological conditions can be obtained by using 3D numerical analysis methods in this area. The objective of this paper is to present 3D finite element analysis of the ductile fracture, strain distribution and stress in blanking process with the assumption geometrical and physical nonlinearities. The physical, mathematical and computer model of the process are elaborated. Dynamic effects, mechanical coupling, constitutive damage law and contact friction are taken into account. The application in ANSYS/LS-DYNA program is elaborated. The effect of the main process parameter a blanking clearance on the deformation of 1018 steel and quality of the blank's sheared edge is analyzed. The results of computer simulations can be used to forecasting quality of the final parts optimization.

Ocean Carbon States: Data Mining in Observations and Numerical Simulations Results

NASA Astrophysics Data System (ADS)

Latto, R.; Romanou, A.

2017-12-01

Advanced data mining techniques are rapidly becoming widely used in Climate and Earth Sciences with the purpose of extracting new meaningful information from increasingly larger and more complex datasets. This is particularly important in studies of the global carbon cycle, where any lack of understanding of its combined physical and biogeochemical drivers is detrimental to our ability to accurately describe, understand, and predict CO2 concentrations and their changes in the major carbon reservoirs. The analysis presented here evaluates the use of cluster analysis as a means of identifying and comparing spatial and temporal patterns extracted from observational and model datasets. As the observational data is organized into various regimes, which we will call "ocean carbon states", we gain insight into the physical and/or biogeochemical processes controlling the ocean carbon cycle as well as how well these processes are simulated by a state-of-the-art climate model. We find that cluster analysis effectively produces realistic, dynamic regimes that can be associated with specific processes at different temporal scales for both observations and the model. In addition, we show how these regimes can be used to illustrate and characterize the model biases in the model air-sea flux of CO2. These biases are attributed to biases in salinity, sea surface temperature, wind speed, and nitrate, which are then used to identify the physical processes that are inaccurately reproduced by the model. In this presentation, we provide a proof-of-concept application using simple datasets, and we expand to more complex ones, using several physical and biogeochemical variable pairs, thus providing considerable insight into the mechanisms and phases of the ocean carbon cycle over different temporal and spatial scales.

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

Yang, Huan; Cheng, Liang; Chuah, Mooi Choo

In the generation, transmission, and distribution sectors of the smart grid, intelligence of field devices is realized by programmable logic controllers (PLCs). Many smart-grid subsystems are essentially cyber-physical energy systems (CPES): For instance, the power system process (i.e., the physical part) within a substation is monitored and controlled by a SCADA network with hosts running miscellaneous applications (i.e., the cyber part). To study the interactions between the cyber and physical components of a CPES, several co-simulation platforms have been proposed. However, the network simulators/emulators of these platforms do not include a detailed traffic model that takes into account the impactsmore » of the execution model of PLCs on traffic characteristics. As a result, network traces generated by co-simulation only reveal the impacts of the physical process on the contents of the traffic generated by SCADA hosts, whereas the distinction between PLCs and computing nodes (e.g., a hardened computer running a process visualization application) has been overlooked. To generate realistic network traces using co-simulation for the design and evaluation of applications relying on accurate traffic profiles, it is necessary to establish a traffic model for PLCs. In this work, we propose a parameterized model for PLCs that can be incorporated into existing co-simulation platforms. We focus on the DNP3 subsystem of slave PLCs, which automates the processing of packets from the DNP3 master. To validate our approach, we extract model parameters from both the configuration and network traces of real PLCs. Simulated network traces are generated and compared against those from PLCs. Our evaluation shows that our proposed model captures the essential traffic characteristics of DNP3 slave PLCs, which can be used to extend existing co-simulation platforms and gain further insights into the behaviors of CPES.« less

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...

Modeling the Water Balloon Slingshot

ERIC Educational Resources Information Center

Bousquet, Benjamin D.; Figura, Charles C.

2013-01-01

In the introductory physics courses at Wartburg College, we have been working to create a lab experience focused on the scientific process itself rather than verification of physical laws presented in the classroom or textbook. To this end, we have developed a number of open-ended modeling exercises suitable for a variety of learning environments,…

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.

Explanatory Power of Multi-scale Physical Descriptors in Modeling Benthic Indices Across Nested Ecoregions of the Pacific Northwest

NASA Astrophysics Data System (ADS)

Holburn, E. R.; Bledsoe, B. P.; Poff, N. L.; Cuhaciyan, C. O.

2005-05-01

Using over 300 R/EMAP sites in OR and WA, we examine the relative explanatory power of watershed, valley, and reach scale descriptors in modeling variation in benthic macroinvertebrate indices. Innovative metrics describing flow regime, geomorphic processes, and hydrologic-distance weighted watershed and valley characteristics are used in multiple regression and regression tree modeling to predict EPT richness, % EPT, EPT/C, and % Plecoptera. A nested design using seven ecoregions is employed to evaluate the influence of geographic scale and environmental heterogeneity on the explanatory power of individual and combined scales. Regression tree models are constructed to explain variability while identifying threshold responses and interactions. Cross-validated models demonstrate differences in the explanatory power associated with single-scale and multi-scale models as environmental heterogeneity is varied. Models explaining the greatest variability in biological indices result from multi-scale combinations of physical descriptors. Results also indicate that substantial variation in benthic macroinvertebrate response can be explained with process-based watershed and valley scale metrics derived exclusively from common geospatial data. This study outlines a general framework for identifying key processes driving macroinvertebrate assemblages across a range of scales and establishing the geographic extent at which various levels of physical description best explain biological variability. Such information can guide process-based stratification to avoid spurious comparison of dissimilar stream types in bioassessments and ensure that key environmental gradients are adequately represented in sampling designs.

Understanding the West African Monsoon from the analysis of diabatic heating distributions as simulated by climate models

NASA Astrophysics Data System (ADS)

Martin, G. M.; Peyrillé, P.; Roehrig, R.; Rio, C.; Caian, M.; Bellon, G.; Codron, F.; Lafore, J.-P.; Poan, D. E.; Idelkadi, A.

2017-03-01

Vertical and horizontal distributions of diabatic heating in the West African monsoon (WAM) region as simulated by four model families are analyzed in order to assess the physical processes that affect the WAM circulation. For each model family, atmosphere-only runs of their CMIP5 configurations are compared with more recent configurations which are on the development path toward CMIP6. The various configurations of these models exhibit significant differences in their heating/moistening profiles, related to the different representation of physical processes such as boundary layer mixing, convection, large-scale condensation and radiative heating/cooling. There are also significant differences in the models' simulation of WAM rainfall patterns and circulations. The weaker the radiative cooling in the Saharan region, the larger the ascent in the rainband and the more intense the monsoon flow, while the latitude of the rainband is related to heating in the Gulf of Guinea region and on the northern side of the Saharan heat low. Overall, this work illustrates the difficulty experienced by current climate models in representing the characteristics of monsoon systems, but also that we can still use them to understand the interactions between local subgrid physical processes and the WAM circulation. Moreover, our conclusions regarding the relationship between errors in the large-scale circulation of the WAM and the structure of the heating by small-scale processes will motivate future studies and model development.

Performance of the air2stream model that relates air and stream water temperatures depends on the calibration method

NASA Astrophysics Data System (ADS)

Piotrowski, Adam P.; Napiorkowski, Jaroslaw J.

2018-06-01

A number of physical or data-driven models have been proposed to evaluate stream water temperatures based on hydrological and meteorological observations. However, physical models require a large amount of information that is frequently unavailable, while data-based models ignore the physical processes. Recently the air2stream model has been proposed as an intermediate alternative that is based on physical heat budget processes, but it is so simplified that the model may be applied like data-driven ones. However, the price for simplicity is the need to calibrate eight parameters that, although have some physical meaning, cannot be measured or evaluated a priori. As a result, applicability and performance of the air2stream model for a particular stream relies on the efficiency of the calibration method. The original air2stream model uses an inefficient 20-year old approach called Particle Swarm Optimization with inertia weight. This study aims at finding an effective and robust calibration method for the air2stream model. Twelve different optimization algorithms are examined on six different streams from northern USA (states of Washington, Oregon and New York), Poland and Switzerland, located in both high mountains, hilly and lowland areas. It is found that the performance of the air2stream model depends significantly on the calibration method. Two algorithms lead to the best results for each considered stream. The air2stream model, calibrated with the chosen optimization methods, performs favorably against classical streamwater temperature models. The MATLAB code of the air2stream model and the chosen calibration procedure (CoBiDE) are available as Supplementary Material on the Journal of Hydrology web page.

The Influence of Hands On Physics Experiments on Scientific Process Skills According to Prospective Teachers' Experiences

ERIC Educational Resources Information Center

Hirça, Necati

2013-01-01

In this study, relationship between prospective science and technology teachers' experiences in conducting Hands on physics experiments and their physics lab I achievement was investigated. Survey model was utilized and the study was carried out in the 2012 spring semester. Seven Hands on physics experiments were conducted with 28 prospective…

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

Foundations of anticipatory logic in biology and physics.

PubMed

Bettinger, Jesse S; Eastman, Timothy E

2017-12-01

Recent advances in modern physics and biology reveal several scenarios in which top-down effects (Ellis, 2016) and anticipatory systems (Rosen, 1980) indicate processes at work enabling active modeling and inference such that anticipated effects project onto potential causes. We extrapolate a broad landscape of anticipatory systems in the natural sciences extending to computational neuroscience of perception in the capacity of Bayesian inferential models of predictive processing. This line of reasoning also comes with philosophical foundations, which we develop in terms of counterfactual reasoning and possibility space, Whitehead's process thought, and correlations with Eastern wisdom traditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Processing Motion: Using Code to Teach Newtonian Physics

NASA Astrophysics Data System (ADS)

Massey, M. Ryan

Prior to instruction, students often possess a common-sense view of motion, which is inconsistent with Newtonian physics. Effective physics lessons therefore involve conceptual change. To provide a theoretical explanation for concepts and how they change, the triangulation model brings together key attributes of prototypes, exemplars, theories, Bayesian learning, ontological categories, and the causal model theory. The triangulation model provides a theoretical rationale for why coding is a viable method for physics instruction. As an experiment, thirty-two adolescent students participated in summer coding academies to learn how to design Newtonian simulations. Conceptual and attitudinal data was collected using the Force Concept Inventory and the Colorado Learning Attitudes about Science Survey. Results suggest that coding is an effective means for teaching Newtonian physics.

Informatics and physics intersubject communications in the 7th and 8th grades of the basics level by means of computer modeling

NASA Astrophysics Data System (ADS)

Vasina, A. V.

2017-01-01

The author of the article imparts pedagogical experience of realization of intersubject communications of school basic courses of informatics, technology and physics through research activity of students with the use of specialized programs for the development and studying of computer models of physical processes. The considered technique is based on the principles of independent scholar activity of students, intersubject communications such as educational disciplines of technology, physics and informatics; it helps to develop the research activity of students and a professional and practical orientation of education. As an example the lesson of modeling of flotation with the use of the environment "1C Physical simulator" is considered.

Virtual milk for modelling and simulation of dairy processes.

PubMed

Munir, M T; Zhang, Y; Yu, W; Wilson, D I; Young, B R

2016-05-01

The modeling of dairy processing using a generic process simulator suffers from shortcomings, given that many simulators do not contain milk components in their component libraries. Recently, pseudo-milk components for a commercial process simulator were proposed for simulation and the current work extends this pseudo-milk concept by studying the effect of both total milk solids and temperature on key physical properties such as thermal conductivity, density, viscosity, and heat capacity. This paper also uses expanded fluid and power law models to predict milk viscosity over the temperature range from 4 to 75°C and develops a succinct regressed model for heat capacity as a function of temperature and fat composition. The pseudo-milk was validated by comparing the simulated and actual values of the physical properties of milk. The milk thermal conductivity, density, viscosity, and heat capacity showed differences of less than 2, 4, 3, and 1.5%, respectively, between the simulated results and actual values. This work extends the capabilities of the previously proposed pseudo-milk and of a process simulator to model dairy processes, processing different types of milk (e.g., whole milk, skim milk, and concentrated milk) with different intrinsic compositions, and to predict correct material and energy balances for dairy processes. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

PULSE: A numerical model for the simulation of snowpack solute dynamics to capture runoff ionic pulses during snowmelt

NASA Astrophysics Data System (ADS)

Costa, D.; Pomeroy, J. W.; Wheater, H. S.

2017-12-01

Early ionic pulses in spring snowmelt can cause the temporary acidification of streams and account for a significant portion of the total annual nutrient export, particularly in seasonally snow-covered areas where the frozen ground may limit runoff-soil contact and cause the rapid delivery of these ions to streams. Ionic pulses are a consequence of snow ion exclusion, a process induced by snow metamorphism where ions are segregated from the snow grains losing mass to the surface of the grains gaining mass. While numerous studies have been successful in providing quantitative evidence of this process, few mechanistic mathematical models have been proposed for diagnostic and prediction. A few early modelling attempts have been successful in capturing this process assuming transport through porous media with variable porosity, however their implementation is difficult because they require complex models of snow physics to resolve the evolution of in-snow properties and processes during snowmelt, such as heat conduction, metamorphism, melt and water flow. Furthermore, initial snowpack to snow-surface ion concentration ratios are difficult to measure but are required to initiate these models and ion exclusion processes are not represented in a physically-based transparent fashion. In this research, a standalone numerical model has been developed to capture ionic pulses in snowmelt by emulating solute leaching from snow grains during melt and its subsequent transport by the percolating meltwater. Estimating snow porosity and water content dynamics is shown to be a viable alternative to deployment of complex snow physics models for this purpose. The model was applied to four study sites located in the Arctic and in Sierra Nevada to test for different climatic and hydrological conditions. The model compares very well with observations and could capture both the timing and magnitude of early melt ionic pulses accurately. This study demonstrates how physically based approaches can provide successful simulations of the spatial and temporal fluxes of snowmelt ions, which can be used to improve the prediction of nutrient export in cold regions for the spring freshet.

PULSE: A numerical model for the simulation of snowpack solute dynamics to capture runoff ionic pulses during snowmelt

NASA Astrophysics Data System (ADS)

Clark, M. P.; Nijssen, B.; Lundquist, J. D.; Luce, C. H.; Musselman, K. N.; Wayand, N. E.; Ou, M.; Lapo, K. E.

2016-12-01

Early ionic pulses in spring snowmelt can cause the temporary acidification of streams and account for a significant portion of the total annual nutrient export, particularly in seasonally snow-covered areas where the frozen ground may limit runoff-soil contact and cause the rapid delivery of these ions to streams. Ionic pulses are a consequence of snow ion exclusion, a process induced by snow metamorphism where ions are segregated from the snow grains losing mass to the surface of the grains gaining mass. While numerous studies have been successful in providing quantitative evidence of this process, few mechanistic mathematical models have been proposed for diagnostic and prediction. A few early modelling attempts have been successful in capturing this process assuming transport through porous media with variable porosity, however their implementation is difficult because they require complex models of snow physics to resolve the evolution of in-snow properties and processes during snowmelt, such as heat conduction, metamorphism, melt and water flow. Furthermore, initial snowpack to snow-surface ion concentration ratios are difficult to measure but are required to initiate these models and ion exclusion processes are not represented in a physically-based transparent fashion. In this research, a standalone numerical model has been developed to capture ionic pulses in snowmelt by emulating solute leaching from snow grains during melt and its subsequent transport by the percolating meltwater. Estimating snow porosity and water content dynamics is shown to be a viable alternative to deployment of complex snow physics models for this purpose. The model was applied to four study sites located in the Arctic and in Sierra Nevada to test for different climatic and hydrological conditions. The model compares very well with observations and could capture both the timing and magnitude of early melt ionic pulses accurately. This study demonstrates how physically based approaches can provide successful simulations of the spatial and temporal fluxes of snowmelt ions, which can be used to improve the prediction of nutrient export in cold regions for the spring freshet.

Processes of behavior change and weight loss in a theory-based weight loss intervention program: a test of the process model for lifestyle behavior change.

PubMed

Gillison, Fiona; Stathi, Afroditi; Reddy, Prasuna; Perry, Rachel; Taylor, Gordon; Bennett, Paul; Dunbar, James; Greaves, Colin

2015-01-16

Process evaluation is important for improving theories of behavior change and behavioral intervention methods. The present study reports on the process outcomes of a pilot test of the theoretical model (the Process Model for Lifestyle Behavior Change; PMLBC) underpinning an evidence-informed, theory-driven, group-based intervention designed to promote healthy eating and physical activity for people with high cardiovascular risk. 108 people at high risk of diabetes or heart disease were randomized to a group-based weight management intervention targeting diet and physical activity plus usual care, or to usual care. The intervention comprised nine group based sessions designed to promote motivation, social support, self-regulation and understanding of the behavior change process. Weight loss, diet, physical activity and theoretically defined mediators of change were measured pre-intervention, and after four and 12 months. The intervention resulted in significant improvements in fiber intake (M between-group difference = 5.7 g/day, p < .001) but not fat consumption (-2.3 g/day, p = 0.13), that were predictive of weight loss at both four months (M between-group difference = -1.98 kg, p < .01; R(2) = 0.2, p < 0.005), and 12 months (M difference = -1.85 kg, p = 0.1; R(2) = 0.1, p < 0.01). The intervention was successful in improving the majority of specified mediators of behavior change, and the predicted mechanisms of change specified in the PMBLC were largely supported. Improvements in self-efficacy and understanding of the behavior change process were associated with engagement in coping planning and self-monitoring activities, and successful dietary change at four and 12 months. While participants reported improvements in motivational and social support variables, there was no effect of these, or of the intervention overall, on physical activity. The data broadly support the theoretical model for supporting some dietary changes, but not for physical activity. Systematic intervention design allowed us to identify where improvements to the intervention may be implemented to promote change in all proposed mediators. More work is needed to explore effective mechanisms within interventions to promote physical activity behavior.

Evaluation of a Theory of Instructional Sequences for Physics Instruction

ERIC Educational Resources Information Center

Wackermann, Rainer; Trendel, Georg; Fischer, Hans E.

2010-01-01

The background of the study is the theory of "basis models of teaching and learning", a comprehensive set of models of learning processes which includes, for example, learning through experience and problem-solving. The combined use of different models of learning processes has not been fully investigated and it is frequently not clear…

Manipulating 3D-Printed and Paper Models Enhances Student Understanding of Viral Replication

ERIC Educational Resources Information Center

Couper, Lisa; Johannes, Kristen; Powers, Jackie; Silberglitt, Matt; Davenport, Jodi

2016-01-01

Understanding key concepts in molecular biology requires reasoning about molecular processes that are not directly observable and, as such, presents a challenge to students and teachers. We ask whether novel interactive physical models and activities can help students understand key processes in viral replication. Our 3D tangible models are…

Comparison of a Conceptual Groundwater Model and Physically Based Groundwater Mode

NASA Astrophysics Data System (ADS)

Yang, J.; Zammit, C.; Griffiths, J.; Moore, C.; Woods, R. A.

2017-12-01

Groundwater is a vital resource for human activities including agricultural practice and urban water demand. Hydrologic modelling is an important way to study groundwater recharge, movement and discharge, and its response to both human activity and climate change. To understand the groundwater hydrologic processes nationally in New Zealand, we have developed a conceptually based groundwater flow model, which is fully integrated into a national surface-water model (TopNet), and able to simulate groundwater recharge, movement, and interaction with surface water. To demonstrate the capability of this groundwater model (TopNet-GW), we applied the model to an irrigated area with water shortage and pollution problems in the upper Ruamahanga catchment in Great Wellington Region, New Zealand, and compared its performance with a physically-based groundwater model (MODFLOW). The comparison includes river flow at flow gauging sites, and interaction between groundwater and river. Results showed that the TopNet-GW produced similar flow and groundwater interaction patterns as the MODFLOW model, but took less computation time. This shows the conceptually-based groundwater model has the potential to simulate national groundwater process, and could be used as a surrogate for the more physically based model.

The effectiveness of collaborative problem based physics learning (CPBPL) model to improve student’s self-confidence on physics learning

NASA Astrophysics Data System (ADS)

Prahani, B. K.; Suprapto, N.; Suliyanah; Lestari, N. A.; Jauhariyah, M. N. R.; Admoko, S.; Wahyuni, S.

2018-03-01

In the previous research, Collaborative Problem Based Physic Learning (CPBPL) model has been developed to improve student’s science process skills, collaborative problem solving, and self-confidence on physics learning. This research is aimed to analyze the effectiveness of CPBPL model towards the improvement of student’s self-confidence on physics learning. This research implemented quasi experimental design on 140 senior high school students who were divided into 4 groups. Data collection was conducted through questionnaire, observation, and interview. Self-confidence measurement was conducted through Self-Confidence Evaluation Sheet (SCES). The data was analyzed using Wilcoxon test, n-gain, and Kruskal Wallis test. Result shows that: (1) There is a significant score improvement on student’s self-confidence on physics learning (α=5%), (2) n-gain value student’s self-confidence on physics learning is high, and (3) n-gain average student’s self-confidence on physics learning was consistent throughout all groups. It can be concluded that CPBPL model is effective to improve student’s self-confidence on physics learning.

Evaluating CONUS-Scale Runoff Simulation across the National Water Model WRF-Hydro Implementation to Disentangle Regional Controls on Streamflow Generation and Model Error Contribution

NASA Astrophysics Data System (ADS)

Dugger, A. L.; Rafieeinasab, A.; Gochis, D.; Yu, W.; McCreight, J. L.; Karsten, L. R.; Pan, L.; Zhang, Y.; Sampson, K. M.; Cosgrove, B.

2016-12-01

Evaluation of physically-based hydrologic models applied across large regions can provide insight into dominant controls on runoff generation and how these controls vary based on climatic, biological, and geophysical setting. To make this leap, however, we need to combine knowledge of regional forcing skill, model parameter and physics assumptions, and hydrologic theory. If we can successfully do this, we also gain information on how well our current approximations of these dominant physical processes are represented in continental-scale models. In this study, we apply this diagnostic approach to a 5-year retrospective implementation of the WRF-Hydro community model configured for the U.S. National Weather Service's National Water Model (NWM). The NWM is a water prediction model in operations over the contiguous U.S. as of summer 2016, providing real-time estimates and forecasts out to 30 days of streamflow across 2.7 million stream reaches as well as distributed snowpack, soil moisture, and evapotranspiration at 1-km resolution. The WRF-Hydro system permits not only the standard simulation of vertical energy and water fluxes common in continental-scale models, but augments these processes with lateral redistribution of surface and subsurface water, simple groundwater dynamics, and channel routing. We evaluate 5 years of NLDAS-2 precipitation forcing and WRF-Hydro streamflow and evapotranspiration simulation across the contiguous U.S. at a range of spatial (gage, basin, ecoregion) and temporal (hourly, daily, monthly) scales and look for consistencies and inconsistencies in performance in terms of bias, timing, and extremes. Leveraging results from other CONUS-scale hydrologic evaluation studies, we translate our performance metrics into a matrix of likely dominant process controls and error sources (forcings, parameter estimates, and model physics). We test our hypotheses in a series of controlled model experiments on a subset of representative basins from distinct "problem" environments (Southeast U.S. Coastal Plain, Central and Coastal Texas, Northern Plains, and Arid Southwest). The results from these longer-term model diagnostics will inform future improvements in forcing bias correction, parameter calibration, and physics developments in the National Water Model.

Unified Models of Turbulence and Nonlinear Wave Evolution in the Extended Solar Corona and Solar Wind

NASA Technical Reports Server (NTRS)

Cranmer, Steven R.; Wagner, William (Technical Monitor)

2004-01-01

The PI (Cranmer) and Co-I (A. van Ballegooijen) made substantial progress toward the goal of producing a unified model of the basic physical processes responsible for solar wind acceleration. The approach outlined in the original proposal comprised two complementary pieces: (1) to further investigate individual physical processes under realistic coronal and solar wind conditions, and (2) to extract the dominant physical effects from simulations and apply them to a 1D model of plasma heating and acceleration. The accomplishments in Year 2 are divided into these two categories: 1a. Focused Study of Kinetic Magnetohydrodynamic (MHD) Turbulence. lb. Focused Study of Non - WKB Alfven Wave Rejection. and 2. The Unified Model Code. We have continued the development of the computational model of a time-study open flux tube in the extended corona. The proton-electron Monte Carlo model is being tested, and collisionless wave-particle interactions are being included. In order to better understand how to easily incorporate various kinds of wave-particle processes into the code, the PI performed a detailed study of the so-called "Ito Calculus", i.e., the mathematical theory of how to update the positions of particles in a probabilistic manner when their motions are governed by diffusion in velocity space.

Evaluating climate model performance in the tropics with retrievals of water isotopic composition from Aura TES

NASA Astrophysics Data System (ADS)

Field, Robert; Kim, Daehyun; Kelley, Max; LeGrande, Allegra; Worden, John; Schmidt, Gavin

2014-05-01

Observational and theoretical arguments suggest that satellite retrievals of the stable isotope composition of water vapor could be useful for climate model evaluation. The isotopic composition of water vapor is controlled by the same processes that control water vapor amount, but the observed distribution of isotopic composition is distinct from amount itself . This is due to the fractionation that occurs between the abundant H216O isotopes (isotopologues) and the rare and heavy H218O and HDO isotopes during evaporation and condensation. The fractionation physics are much simpler than the underlying moist physics; discrepancies between observed and modeled isotopic fields are more likely due to problems in the latter. Isotopic measurements therefore have the potential for identifying problems that might not be apparent from more conventional measurements. Isotopic tracers have existed in climate models since the 1980s but it is only since the mid 2000s that there have been enough data for meaningful model evaluation in this sense, in the troposphere at least. We have evaluated the NASA GISS ModelE2 general circulation model over the tropics against water isotope (HDO/H2O) retrievals from the Aura Tropospheric Emission Spectrometer (TES), alongside more conventional measurements. A small ensemble of experiments was performed with physics perturbations to the cumulus and planetary boundary layer schemes, done in the context of the normal model development process. We examined the degree to which model-data agreement could be used to constrain a select group of internal processes in the model, namely condensate evaporation, entrainment strength, and moist convective air mass flux. All are difficult to parameterize, but exert strong influence over model performance. We found that the water isotope composition was significantly more sensitive to physics changes than precipitation, temperature or relative humidity through the depth of the tropical troposphere. Among the processes considered, this was most closely, and fairly exclusively, related to mid-tropospheric entrainment strength. This demonstrates that water isotope retrievals have considerable potential alongside more conventional measurements for climate model evaluation and development.

Adaptive optimal input design and parametric estimation of nonlinear dynamical systems: application to neuronal modeling.

PubMed

Madi, Mahmoud K; Karameh, Fadi N

2018-05-11

Many physical models of biological processes including neural systems are characterized by parametric nonlinear dynamical relations between driving inputs, internal states, and measured outputs of the process. Fitting such models using experimental data (data assimilation) is a challenging task since the physical process often operates in a noisy, possibly non-stationary environment; moreover, conducting multiple experiments under controlled and repeatable conditions can be impractical, time consuming or costly. The accuracy of model identification, therefore, is dictated principally by the quality and dynamic richness of collected data over single or few experimental sessions. Accordingly, it is highly desirable to design efficient experiments that, by exciting the physical process with smart inputs, yields fast convergence and increased accuracy of the model. We herein introduce an adaptive framework in which optimal input design is integrated with Square root Cubature Kalman Filters (OID-SCKF) to develop an online estimation procedure that first, converges significantly quicker, thereby permitting model fitting over shorter time windows, and second, enhances model accuracy when only few process outputs are accessible. The methodology is demonstrated on common nonlinear models and on a four-area neural mass model with noisy and limited measurements. Estimation quality (speed and accuracy) is benchmarked against high-performance SCKF-based methods that commonly employ dynamically rich informed inputs for accurate model identification. For all the tested models, simulated single-trial and ensemble averages showed that OID-SCKF exhibited (i) faster convergence of parameter estimates and (ii) lower dependence on inter-trial noise variability with gains up to around 1000 msec in speed and 81% increase in variability for the neural mass models. In terms of accuracy, OID-SCKF estimation was superior, and exhibited considerably less variability across experiments, in identifying model parameters of (a) systems with challenging model inversion dynamics and (b) systems with fewer measurable outputs that directly relate to the underlying processes. Fast and accurate identification therefore carries particular promise for modeling of transient (short-lived) neuronal network dynamics using a spatially under-sampled set of noisy measurements, as is commonly encountered in neural engineering applications. © 2018 IOP Publishing Ltd.

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.

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.

Connections between physical, optical and biogeochemical processes in the Pacific Ocean

NASA Astrophysics Data System (ADS)

Xiu, Peng; Chai, Fei

2014-03-01

A new biogeochemical model has been developed and coupled to a three-dimensional physical model in the Pacific Ocean. With the explicitly represented dissolved organic pools, this new model is able to link key biogeochemical processes with optical processes. Model validation against satellite and in situ data indicates the model is robust in reproducing general biogeochemical and optical features. Colored dissolved organic matter (CDOM) has been suggested to play an important role in regulating underwater light field. With the coupled model, physical and biological regulations of CDOM in the euphotic zone are analyzed. Model results indicate seasonal variability of CDOM is mostly determined by biological processes, while the importance of physical regulation manifests in the annual mean terms. Without CDOM attenuating light, modeled depth-integrated primary production is about 10% higher than the control run when averaged over the entire basin, while this discrepancy is highly variable in space with magnitudes reaching higher than 100% in some locations. With CDOM dynamics integrated in physical-biological interactions, a new mechanism by which physical processes affect biological processes is suggested, namely, physical transport of CDOM changes water optical properties, which can further modify underwater light field and subsequently affect the distribution of phytoplankton chlorophyll. This mechanism tends to occur in the entire Pacific basin but with strong spatial variability, implying the importance of including optical processes in the coupled physical-biogeochemical model. If ammonium uptake is sufficient to permit utilization of DOM, that is, UB∗⩾-U{U}/{U}-{(1-r_b)}/{RB}, then bacteria uptake of DOM has the form of FB=(1-r_b){U}/{RB}, bacteria respiration, SB=r_b×U, remineralization by bacteria, EB=UC{UN}/{UC}-{(1-r_b)}/{RB}. If EB > 0, then UB = 0; otherwise, UB = -EB. If there is insufficient ammonium, that is, UB∗<-U{U}/{U}-{(1-r_b)}/{RB}, then bacteria uptake of ammonia is obtained by, UB=UB∗, bacteria uptake of DOM, FB=U+UB, bacteria respiration, SB=RBFB{r_b}/{1-r_b}, remineralization by bacteria, EB=-UB. CDOM photolysis (Bissett et al., 1999a): UVLDOC=a(410)×RtUVLDOC×{PAR(0)}/{410}×exp∫z0Kd(300)dz, UVSDOC=a(410)×RtUVSDOC×{PAR(0)}/{410}×exp∫z0Kd(300)dz, UVLDIC=a(410)×RtUVLDIC×{PAR(0)}/{410}×exp∫z0Kd(300)dz, UVSDIC=a(410)×RtUVSDIC×{PAR(0)}/{410}×exp∫z0Kd(300)dz, a(410)=acdoc∗×CLDOC, a(410)=acdoc∗×CSDOC, Kd(300)=[a(410)+a(410)]×exp[0.0145×(410-300)]+0.154. The dissolution rate for biogenic silica (Jiang et al., 2003): D=(0.19T/25+0.01)×exp(0.069(T-25)). The air-sea flux of CO2 is calculated using the transfer velocity-wind speed relationships from Wanninkhof (1992): air-sea CO flux=0.31U2(660S{()sea-()air}, where U is the wind speed at sea surface and Sc is the Schmidt number for CO2 that can be calculated as: Sc=2073.1-125.62T+3.6276T2-0.043219T3, S is the solubility of CO2 and (pCO2)air is the partial pressure of CO2 in the air. In the model, we set a spatially uniform distribution of (pCO2)air observed at the Mauna Loa Observatory (Keeling et al., 1976).Dissolved oxygen (DO) is modeled using constant oxygen-to-nitrate and oxygen-to-ammonium ratios. At the surface, air-sea exchange of O2 is calculated as: O flux=0.31U2(660(DOsat-DO), where DOsat is the saturation concentration of DO calculated from temperature and salinity. So2 is the Schmidt number for O2 that can be calculated as follows: So2=1638.0-81.83T+1.483T2-0.008004T3.

Neonatal physical therapy. Part I: clinical competencies and neonatal intensive care unit clinical training models.

PubMed

Sweeney, Jane K; Heriza, Carolyn B; Blanchard, Yvette

2009-01-01

To describe clinical training models, delineate clinical competencies, and outline a clinical decision-making algorithm for neonatal physical therapy. In these updated practice guidelines, advanced clinical training models, including precepted practicum and residency or fellowship training, are presented to guide practitioners in organizing mentored, competency-based preparation for neonatal care. Clinical competencies in neonatal physical therapy are outlined with advanced clinical proficiencies and knowledge areas specific to each role. An algorithm for decision making on examination, evaluation, intervention, and re-examination processes provides a framework for clinical reasoning. Because of advanced-level competency requirements and the continuous examination, evaluation, and modification of procedures during each patient contact, the intensive care unit is a restricted practice area for physical therapist assistants, physical therapist generalists, and physical therapy students. Accountable, ethical physical therapy for neonates requires advanced, competency-based training with a preceptor in the pediatric subspecialty of neonatology.

Earthquake cycles and physical modeling of the process leading up to a large earthquake

NASA Astrophysics Data System (ADS)

Ohnaka, Mitiyasu

2004-08-01

A thorough discussion is made on what the rational constitutive law for earthquake ruptures ought to be from the standpoint of the physics of rock friction and fracture on the basis of solid facts observed in the laboratory. From this standpoint, it is concluded that the constitutive law should be a slip-dependent law with parameters that may depend on slip rate or time. With the long-term goal of establishing a rational methodology of forecasting large earthquakes, the entire process of one cycle for a typical, large earthquake is modeled, and a comprehensive scenario that unifies individual models for intermediate-and short-term (immediate) forecasts is presented within the framework based on the slip-dependent constitutive law and the earthquake cycle model. The earthquake cycle includes the phase of accumulation of elastic strain energy with tectonic loading (phase II), and the phase of rupture nucleation at the critical stage where an adequate amount of the elastic strain energy has been stored (phase III). Phase II plays a critical role in physical modeling of intermediate-term forecasting, and phase III in physical modeling of short-term (immediate) forecasting. The seismogenic layer and individual faults therein are inhomogeneous, and some of the physical quantities inherent in earthquake ruptures exhibit scale-dependence. It is therefore critically important to incorporate the properties of inhomogeneity and physical scaling, in order to construct realistic, unified scenarios with predictive capability. The scenario presented may be significant and useful as a necessary first step for establishing the methodology for forecasting large earthquakes.

A generic biogeochemical module for earth system models

NASA Astrophysics Data System (ADS)

Fang, Y.; Huang, M.; Liu, C.; Li, H.-Y.; Leung, L. R.

2013-06-01

Physical and biogeochemical processes regulate soil carbon dynamics and CO2 flux to and from the atmosphere, influencing global climate changes. Integration of these processes into earth system models (e.g. community land models - CLM), however, currently faces three major challenges: (1) extensive efforts are required to modify modeling structures and to rewrite computer programs to incorporate new or updated processes as new knowledge is being generated, (2) computational cost is prohibitively expensive to simulate biogeochemical processes in land models due to large variations in the rates of biogeochemical processes, and (3) various mathematical representations of biogeochemical processes exist to incorporate different aspects of fundamental mechanisms, but systematic evaluation of the different mathematical representations is difficult, if not impossible. To address these challenges, we propose a new computational framework to easily incorporate physical and biogeochemical processes into land models. The new framework consists of a new biogeochemical module with a generic algorithm and reaction database so that new and updated processes can be incorporated into land models without the need to manually set up the ordinary differential equations to be solved numerically. The reaction database consists of processes of nutrient flow through the terrestrial ecosystems in plants, litter and soil. This framework facilitates effective comparison studies of biogeochemical cycles in an ecosystem using different conceptual models under the same land modeling framework. The approach was first implemented in CLM and benchmarked against simulations from the original CLM-CN code. A case study was then provided to demonstrate the advantages of using the new approach to incorporate a phosphorus cycle into the CLM model. To our knowledge, the phosphorus-incorporated CLM is a new model that can be used to simulate phosphorus limitation on the productivity of terrestrial ecosystems.

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.

Statistical physics studies of multilayer adsorption isotherm in food materials and pore size distribution

NASA Astrophysics Data System (ADS)

Aouaini, F.; Knani, S.; Ben Yahia, M.; Ben Lamine, A.

2015-08-01

Water sorption isotherms of foodstuffs are very important in different areas of food science engineering such as for design, modeling and optimization of many processes. The equilibrium moisture content is an important parameter in models used to predict changes in the moisture content of a product during storage. A formulation of multilayer model with two energy levels was based on statistical physics and theoretical considerations. Thanks to the grand canonical ensemble in statistical physics. Some physicochemical parameters related to the adsorption process were introduced in the analytical model expression. The data tabulated in literature of water adsorption at different temperatures on: chickpea seeds, lentil seeds, potato and on green peppers were described applying the most popular models applied in food science. We also extend the study to the newest proposed model. It is concluded that among studied models the proposed model seems to be the best for description of data in the whole range of relative humidity. By using our model, we were able to determine the thermodynamic functions. The measurement of desorption isotherms, in particular a gas over a solid porous, allows access to the distribution of pore size PSD.

Tangent linear super-parameterization: attributable, decomposable moist processes for tropical variability studies

NASA Astrophysics Data System (ADS)

Mapes, B. E.; Kelly, P.; Song, S.; Hu, I. K.; Kuang, Z.

2015-12-01

An economical 10-layer global primitive equation solver is driven by time-independent forcing terms, derived from a training process, to produce a realisting eddying basic state with a tracer q trained to act like water vapor mixing ratio. Within this basic state, linearized anomaly moist physics in the column are applied in the form of a 20x20 matrix. The control matrix was derived from the results of Kuang (2010, 2012) who fitted a linear response function from a cloud resolving model in a state of deep convecting equilibrium. By editing this matrix in physical space and eigenspace, scaling and clipping its action, and optionally adding terms for processes that do not conserve moist statice energy (radiation, surface fluxes), we can decompose and explain the model's diverse moist process coupled variability. Recitified effects of this variability on the general circulation and climate, even in strictly zero-mean centered anomaly physic cases, also are sometimes surprising.

Sex that moves mountains: The influence of spawning fish on river profiles over geologic timescales

NASA Astrophysics Data System (ADS)

Fremier, Alexander K.; Yanites, Brian J.; Yager, Elowyn M.

2018-03-01

A key component of resilience is to understand feedbacks among components of biophysical systems, such as physical drivers, ecological responses and the subsequent feedbacks onto physical process. While physically based explanations of biological speciation are common (e.g., mountains separating a species can lead to speciation), less common is the inverse process examined: can a speciation event have significant influence on physical processes and patterns in a landscape? When such processes are considered, such as with 'ecosystem engineers', many studies have focused on the short-term physical and biological effects rather than the long-term impacts. Here, we formalized the physical influence of salmon spawning on stream beds into a model of channel profile evolution by altering the critical shear stress required to move stream bed particles. We then asked if spawning and an adaptive radiation event (similar to the one that occurred in Pacific salmon species) could have an effect on channel erosion processes and stream profiles over geological timescales. We found that spawning can profoundly influence the longitudinal profiles of stream beds and thereby the evolution of entire watersheds. The radiation of five Pacific salmon from a common ancestor, additionally, could also cause significant geomorphic change by altering a wider section of the profile for a given distribution of grain sizes. This modeling study suggests that biological evolution can impact landscape evolution by increasing the sediment transport and erosion efficiency of mountain streams. Moreover, the physical effects of a species on its environment might be a complementary explanation for rapid radiation events in species through the creation of new habitat types. This example provides an illustrative case for thinking about the long- and short-term coupling of biotic and abiotic systems.

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.

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.

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...

Pathways to Children's Academic Performance and Prosocial Behaviour: Roles of Physical Health Status, Environmental, Family, and Child Factors

ERIC Educational Resources Information Center

King, Gillian; McDougall, Janette; DeWit, David; Hong, Sungjin; Miller, Linda; Offord, David; Meyer, Katherine; LaPorta, John

2005-01-01

The objective of this article is to examine the pathways by which children's physical health status, environmental, family, and child factors affect children's academic performance and prosocial behaviour, using a theoretically-based and empirically-based model of competence development. The model proposes that 3 types of relational processes,…

The influence of a wind tunnel on helicopter rotational noise: Formulation of analysis

NASA Technical Reports Server (NTRS)

Mosher, M.

1984-01-01

An analytical model is discussed that can be used to examine the effects of wind tunnel walls on helicopter rotational noise. A complete physical model of an acoustic source in a wind tunnel is described and a simplified version is then developed. This simplified model retains the important physical processes involved, yet it is more amenable to analysis. The simplified physical model is then modeled as a mathematical problem. An inhomogeneous partial differential equation with mixed boundary conditions is set up and then transformed into an integral equation. Details of generating a suitable Green's function and integral equation are included and the equation is discussed and also given for a two-dimensional case.

Modeling Physical Stability of Amorphous Solids Based on Temperature and Moisture Stresses.

PubMed

Zhu, Donghua Alan; Zografi, George; Gao, Ping; Gong, Yuchuan; Zhang, Geoff G Z

2016-09-01

Isothermal microcalorimetry was utilized to monitor the crystallization process of amorphous ritonavir (RTV) and its hydroxypropylmethylcellulose acetate succinate-based amorphous solid dispersion under various stressed conditions. An empirical model was developed: ln(τ)=ln(A)+EaRT-b⋅wc, where τ is the crystallization induction period, A is a pre-exponential factor, Ea is the apparent activation energy, b is the moisture sensitivity parameter, and wc is water content. To minimize the propagation of errors associated with the estimates, a nonlinear approach was used to calculate mean estimates and confidence intervals. The physical stability of neat amorphous RTV and RTV in hydroxypropylmethylcellulose acetate succinate solid dispersions was found to be mainly governed by the nucleation kinetic process. The impact of polymers and moisture on the crystallization process can be quantitatively described by Ea and b in this Arrhenius-type model. The good agreement between the measured values under some less stressful test conditions and those predicted, reflected by the slope and R(2) of the correlation plot of these 2 sets of data on a natural logarithm scale, indicates its predictability of long-term physical stability of amorphous RTV in solid dispersions. To further improve the model, more understanding of the impact of temperature and moisture on the amorphous physical stability and fundamentals regarding nucleation and crystallization is needed. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Fermi-level effects in semiconductor processing: A modeling scheme for atomistic kinetic Monte Carlo simulators

NASA Astrophysics Data System (ADS)

Martin-Bragado, I.; Castrillo, P.; Jaraiz, M.; Pinacho, R.; Rubio, J. E.; Barbolla, J.; Moroz, V.

2005-09-01

Atomistic process simulation is expected to play an important role for the development of next generations of integrated circuits. This work describes an approach for modeling electric charge effects in a three-dimensional atomistic kinetic Monte Carlo process simulator. The proposed model has been applied to the diffusion of electrically active boron and arsenic atoms in silicon. Several key aspects of the underlying physical mechanisms are discussed: (i) the use of the local Debye length to smooth out the atomistic point-charge distribution, (ii) algorithms to correctly update the charge state in a physically accurate and computationally efficient way, and (iii) an efficient implementation of the drift of charged particles in an electric field. High-concentration effects such as band-gap narrowing and degenerate statistics are also taken into account. The efficiency, accuracy, and relevance of the model are discussed.

Theoretical model to explain the problem-solving process in physics

NASA Astrophysics Data System (ADS)

Lopez, Carlos

2011-03-01

This work reports a theoretical model developed with the aim to explain the mental mechanisms of knowledge building during the problem-solving process in physics using a hybrid approach of assimilation- formation of concepts. The model has been termed conceptual chains and represents graphic diagrams of conceptual dependency, which have yielded information about the background knowledge required during the learning process, as well as about the formation of diverse structures that correspond to distinct forms of networking concepts Additionally, the conceptual constructs of the model have been classified according to five types of knowledge. Evidence was found about the influence of these structures, as well as of the distinct types of knowledge about the degree of difficulty of the problems. I want to be grateful to Laureate International Universities, Baltimore M.D., USA, for the financing granted for the accomplishment of this work.

Adsorption of diclofenac and nimesulide on activated carbon: Statistical physics modeling and effect of adsorbate size

NASA Astrophysics Data System (ADS)

Sellaoui, Lotfi; Mechi, Nesrine; Lima, Éder Cláudio; Dotto, Guilherme Luiz; Ben Lamine, Abdelmottaleb

2017-10-01

Based on statistical physics elements, the equilibrium adsorption of diclofenac (DFC) and nimesulide (NM) on activated carbon was analyzed by a multilayer model with saturation. The paper aimed to describe experimentally and theoretically the adsorption process and study the effect of adsorbate size using the model parameters. From numerical simulation, the number of molecules per site showed that the adsorbate molecules (DFC and NM) were mostly anchored in both sides of the pore walls. The receptor sites density increase suggested that additional sites appeared during the process, to participate in DFC and NM adsorption. The description of the adsorption energy behavior indicated that the process was physisorption. Finally, by a model parameters correlation, the size effect of the adsorbate was deduced indicating that the molecule dimension has a negligible effect on the DFC and NM adsorption.

The process of cognitive behaviour therapy for chronic fatigue syndrome: which changes in perpetuating cognitions and behaviour are related to a reduction in fatigue?

PubMed

Heins, Marianne J; Knoop, Hans; Burk, William J; Bleijenberg, Gijs

2013-09-01

Cognitive behaviour therapy (CBT) can significantly reduce fatigue in chronic fatigue syndrome (CFS), but little is known about the process of change taking place during CBT. Based on a recent treatment model (Wiborg et al. J Psych Res 2012), we examined how (changes in) cognitions and behaviour are related to the decrease in fatigue. We included 183 patients meeting the US Centers for Disease Control criteria for CFS, aged 18 to 65 years, starting CBT. We measured fatigue and possible process variables before treatment; after 6, 12 and 18 weeks; and after treatment. Possible process variables were sense of control over fatigue, focusing on symptoms, self-reported physical functioning, perceived physical activity and objective (actigraphic) physical activity. We built multiple regression models, explaining levels of fatigue during therapy by (changes in) proposed process variables. We observed large individual variation in the patterns of change in fatigue and process variables during CBT for CFS. Increases in the sense of control over fatigue, perceived activity and self-reported physical functioning, and decreases in focusing on symptoms explained 20 to 46% of the variance in fatigue. An increase in objective activity was not a process variable. A change in cognitive factors seems to be related to the decrease in fatigue during CBT for CFS. The pattern of change varies considerably between patients, but changes in process variables and fatigue occur mostly in the same period. © 2013.

Modeling of Turbulence Effects on Liquid Jet Atomization and Breakup

NASA Technical Reports Server (NTRS)

Trinh, Huu; Chen, C. P.

2004-01-01

Recent experimental investigations and physical modeling studies have indicated that turbulence behaviors within a liquid jet have considerable effects on the atomization process. For certain flow regimes, it has been observed that the liquid jet surface is highly turbulent. This turbulence characteristic plays a key role on the breakup of the liquid jet near to the injector exit. Other experiments also showed that the breakup length of the liquid core is sharply shortened as the liquid jet is changed from the laminar to the turbulent flow conditions. In the numerical and physical modeling arena, most of commonly used atomization models do not include the turbulence effect. Limited attempts have been made in modeling the turbulence phenomena on the liquid jet disintegration. The subject correlation and models treat the turbulence either as an only source or a primary driver in the breakup process. This study aims to model the turbulence effect in the atomization process of a cylindrical liquid jet. In the course of this study, two widely used models, Reitz's primary atomization (blob) and Taylor-Analogy-Break (TAB) secondary droplet breakup by O Rourke et al. are examined. Additional terms are derived and implemented appropriately into these two models to account for the turbulence effect on the atomization process. Since this enhancement effort is based on a framework of the two existing atomization models, it is appropriate to denote the two present models as T-blob and T-TAB for the primary and secondary atomization predictions, respectively. In the primary breakup model, the level of the turbulence effect on the liquid breakup depends on the characteristic time scales and the initial flow conditions. This treatment offers a balance of contributions of individual physical phenomena on the liquid breakup process. For the secondary breakup, an addition turbulence force acted on parent drops is modeled and integrated into the TAB governing equation. The drop size formed from this breakup regime is estimated based on the energy balance before and after the breakup occurrence. The turbulence energy is also considered in this process.

Assessing uncertainty and sensitivity of model parameterizations and parameters in WRF affecting simulated surface fluxes and land-atmosphere coupling over the Amazon region

NASA Astrophysics Data System (ADS)

Qian, Y.; Wang, C.; Huang, M.; Berg, L. K.; Duan, Q.; Feng, Z.; Shrivastava, M. B.; Shin, H. H.; Hong, S. Y.

2016-12-01

This study aims to quantify the relative importance and uncertainties of different physical processes and parameters in affecting simulated surface fluxes and land-atmosphere coupling strength over the Amazon region. We used two-legged coupling metrics, which include both terrestrial (soil moisture to surface fluxes) and atmospheric (surface fluxes to atmospheric state or precipitation) legs, to diagnose the land-atmosphere interaction and coupling strength. Observations made using the Department of Energy's Atmospheric Radiation Measurement (ARM) Mobile Facility during the GoAmazon field campaign together with satellite and reanalysis data are used to evaluate model performance. To quantify the uncertainty in physical parameterizations, we performed a 120 member ensemble of simulations with the WRF model using a stratified experimental design including 6 cloud microphysics, 3 convection, 6 PBL and surface layer, and 3 land surface schemes. A multiple-way analysis of variance approach is used to quantitatively analyze the inter- and intra-group (scheme) means and variances. To quantify parameter sensitivity, we conducted an additional 256 WRF simulations in which an efficient sampling algorithm is used to explore the multiple-dimensional parameter space. Three uncertainty quantification approaches are applied for sensitivity analysis (SA) of multiple variables of interest to 20 selected parameters in YSU PBL and MM5 surface layer schemes. Results show consistent parameter sensitivity across different SA methods. We found that 5 out of 20 parameters contribute more than 90% total variance, and first-order effects dominate comparing to the interaction effects. Results of this uncertainty quantification study serve as guidance for better understanding the roles of different physical processes in land-atmosphere interactions, quantifying model uncertainties from various sources such as physical processes, parameters and structural errors, and providing insights for improving the model physics parameterizations.

Space-time-modulated stochastic processes

NASA Astrophysics Data System (ADS)

Giona, Massimiliano

2017-10-01

Starting from the physical problem associated with the Lorentzian transformation of a Poisson-Kac process in inertial frames, the concept of space-time-modulated stochastic processes is introduced for processes possessing finite propagation velocity. This class of stochastic processes provides a two-way coupling between the stochastic perturbation acting on a physical observable and the evolution of the physical observable itself, which in turn influences the statistical properties of the stochastic perturbation during its evolution. The definition of space-time-modulated processes requires the introduction of two functions: a nonlinear amplitude modulation, controlling the intensity of the stochastic perturbation, and a time-horizon function, which modulates its statistical properties, providing irreducible feedback between the stochastic perturbation and the physical observable influenced by it. The latter property is the peculiar fingerprint of this class of models that makes them suitable for extension to generic curved-space times. Considering Poisson-Kac processes as prototypical examples of stochastic processes possessing finite propagation velocity, the balance equations for the probability density functions associated with their space-time modulations are derived. Several examples highlighting the peculiarities of space-time-modulated processes are thoroughly analyzed.

NON-HOMOGENEOUS POISSON PROCESS MODEL FOR GENETIC CROSSOVER INTERFERENCE.

PubMed

Leu, Szu-Yun; Sen, Pranab K

2014-01-01

The genetic crossover interference is usually modeled with a stationary renewal process to construct the genetic map. We propose two non-homogeneous, also dependent, Poisson process models applied to the known physical map. The crossover process is assumed to start from an origin and to occur sequentially along the chromosome. The increment rate depends on the position of the markers and the number of crossover events occurring between the origin and the markers. We show how to obtain parameter estimates for the process and use simulation studies and real Drosophila data to examine the performance of the proposed models.

Needed: A Standard Information Processing Model of Learning and Learning Processes.

ERIC Educational Resources Information Center

Carifio, James

One strategy to prevent confusion as new paradigms emerge is to have professionals in the area develop and use a standard model of the phenomenon in question. The development and use of standard models in physics, genetics, archaeology, and cosmology have been very productive. The cognitive revolution in psychology and education has produced a…

Lebedev acceleration and comparison of different photometric models in the inversion of lightcurves for asteroids

NASA Astrophysics Data System (ADS)

Lu, Xiao-Ping; Huang, Xiang-Jie; Ip, Wing-Huen; Hsia, Chi-Hao

2018-04-01

In the lightcurve inversion process where asteroid's physical parameters such as rotational period, pole orientation and overall shape are searched, the numerical calculations of the synthetic photometric brightness based on different shape models are frequently implemented. Lebedev quadrature is an efficient method to numerically calculate the surface integral on the unit sphere. By transforming the surface integral on the Cellinoid shape model to that on the unit sphere, the lightcurve inversion process based on the Cellinoid shape model can be remarkably accelerated. Furthermore, Matlab codes of the lightcurve inversion process based on the Cellinoid shape model are available on Github for free downloading. The photometric models, i.e., the scattering laws, also play an important role in the lightcurve inversion process, although the shape variations of asteroids dominate the morphologies of the lightcurves. Derived from the radiative transfer theory, the Hapke model can describe the light reflectance behaviors from the viewpoint of physics, while there are also many empirical models in numerical applications. Numerical simulations are implemented for the comparison of the Hapke model with the other three numerical models, including the Lommel-Seeliger, Minnaert, and Kaasalainen models. The results show that the numerical models with simple function expressions can fit well with the synthetic lightcurves generated based on the Hapke model; this good fit implies that they can be adopted in the lightcurve inversion process for asteroids to improve the numerical efficiency and derive similar results to those of the Hapke model.

A model teaching session for the hypothesis-driven physical examination.

PubMed

Nishigori, Hiroshi; Masuda, Kozo; Kikukawa, Makoto; Kawashima, Atsushi; Yudkowsky, Rachel; Bordage, Georges; Otaki, Junji

2011-01-01

The physical examination is an essential clinical competence for all physicians. Most medical schools have students who learn the physical examination maneuvers using a head-to-toe approach. However, this promotes a rote approach to the physical exam, and it is not uncommon for students later on to fail to appreciate the meaning of abnormal findings and their contribution to the diagnostic reasoning process. The purpose of the project was to develop a model teaching session for the hypothesis-driven physical examination (HDPE) approach in which students could practice the physical examination in the context of diagnostic reasoning. We used an action research methodology to create this HDPE model by developing a teaching session, implementing it over 100 times with approximately 700 students, conducting internal reflection and external evaluations, and making adjustments as needed. A model nine-step HDPE teaching session was developed, including: (1) orientation, (2) anticipation, (3) preparation, (4) role play, (5) discussion-1, (6) answers, (7) discussion-2, (8) demonstration and (9) reflection. A structured model HDPE teaching session and tutor guide were developed into a workable instructional intervention. Faculty members are invited to teach the physical examination using this model.

Complete Systematic Error Model of SSR for Sensor Registration in ATC Surveillance Networks

PubMed Central

Besada, Juan A.

2017-01-01

In this paper, a complete and rigorous mathematical model for secondary surveillance radar systematic errors (biases) is developed. The model takes into account the physical effects systematically affecting the measurement processes. The azimuth biases are calculated from the physical error of the antenna calibration and the errors of the angle determination dispositive. Distance bias is calculated from the delay of the signal produced by the refractivity index of the atmosphere, and from clock errors, while the altitude bias is calculated taking into account the atmosphere conditions (pressure and temperature). It will be shown, using simulated and real data, that adapting a classical bias estimation process to use the complete parametrized model results in improved accuracy in the bias estimation. PMID:28934157

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.

Inaccuracies in additive manufactured medical skull models caused by the DICOM to STL conversion process.

PubMed

Huotilainen, Eero; Jaanimets, Risto; Valášek, Jiří; Marcián, Petr; Salmi, Mika; Tuomi, Jukka; Mäkitie, Antti; Wolff, Jan

2014-07-01

The process of fabricating physical medical skull models requires many steps, each of which is a potential source of geometric error. The aim of this study was to demonstrate inaccuracies and differences caused by DICOM to STL conversion in additively manufactured medical skull models. Three different institutes were requested to perform an automatic reconstruction from an identical DICOM data set of a patients undergoing tumour surgery into an STL file format using their software of preference. The acquired digitized STL data sets were assessed and compared and subsequently used to fabricate physical medical skull models. The three fabricated skull models were then scanned, and differences in the model geometries were assessed using established CAD inspection software methods. A large variation was noted in size and anatomical geometries of the three physical skull models fabricated from an identical (or "a single") DICOM data set. A medical skull model of the same individual can vary markedly depending on the DICOM to STL conversion software and the technical parameters used. Clinicians should be aware of this inaccuracy in certain applications. Copyright © 2013 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Modeling Patient-Specific Deformable Mitral Valves.

PubMed

Ginty, Olivia; Moore, John; Peters, Terry; Bainbridge, Daniel

2018-06-01

Medical imaging has advanced enormously over the last few decades, revolutionizing patient diagnostics and care. At the same time, additive manufacturing has emerged as a means of reproducing physical shapes and models previously not possible. In combination, they have given rise to 3-dimensional (3D) modeling, an entirely new technology for physicians. In an era in which 3D imaging has become a standard for aiding in the diagnosis and treatment of cardiac disease, this visualization now can be taken further by bringing the patient's anatomy into physical reality as a model. The authors describe the generalized process of creating a model of cardiac anatomy from patient images and their experience creating patient-specific dynamic mitral valve models. This involves a combination of image processing software and 3D printing technology. In this article, the complexity of 3D modeling is described and the decision-making process for cardiac anesthesiologists is summarized. The management of cardiac disease has been altered with the emergence of 3D echocardiography, and 3D modeling represents the next paradigm shift. Copyright © 2017 Elsevier Inc. All rights reserved.

Male-initiated partner abuse during marital separation prior to divorce.

PubMed

Toews, Michelle L; McKenry, Patrick C; Catlett, Beth S

2003-08-01

The purpose of this study was to assess predictors of male-initiated psychological and physical partner abuse during the separation process prior to divorce among a sample of 80 divorced fathers who reported no physical violence during their marriages. The predictor variables examined were male gender-role identity, female-initiated divorces, dependence on one's former wife, depression, anxiety, and coparental conflict. Through ordinary least square (OLS) regression techniques, it was found that male gender-role identity was positively related to male-initiated psychological abuse during separation. Logistic regression analyses revealed that male-initiated psychological abuse, anxiety level, coparental conflict, and dependence on one's former spouse increased the odds of a man engaging in physical abuse. However, depression decreased the odds of separation physical abuse. The models predicting both male-initiated psychological abuse (F = 2.20, p < .05, R2 = .15) and physical violence during the separation process were significant (Model chi2 = 35.00, df= 7, p < .001).

Toward a Stress Process Model of Children’s Exposure to Physical Family and Community Violence

PubMed Central

Brooks-Gunn, Jeanne

2011-01-01

Theoretically informed models are required to further the comprehensive understanding of children’s ETV. We draw on the stress process paradigm to forward an overall conceptual model of ETV (ETV) in childhood and adolescence. Around this conceptual model, we synthesize research in four dominant areas of the literature which are detailed but often disconnected including: (1) exposure to three forms of physical violence (e.g., child physical maltreatment, interparental violence, and community ETV); (2) the multilevel correlates and causes of ETV (e.g., neighborhood characteristics including concentrated disadvantage; family characteristics including socio-economic status and family stressors); (3) a range of consequences of ETV (e.g., internalizing and externalizing mental health problems, role transitions, and academic outcomes); and (4) multilevel and cross domain mediators and moderators of ETV influences (e.g., school and community factors, family social support, and individual coping resources). We highlight the range of interconnected processes through which violence exposures may influence children and suggest opportunities for prevention and intervention. We further identify needed future research on children’s ETV including coping resources as well as research on cumulative contributions of violence exposure, violence exposure modifications, curvilinearity, and timing of exposure. PMID:19434492

Plasma Processes for Semiconductor Fabrication

NASA Astrophysics Data System (ADS)

Hitchon, W. N. G.

1999-01-01

Plasma processing is a central technique in the fabrication of semiconductor devices. This self-contained book provides an up-to-date description of plasma etching and deposition in semiconductor fabrication. It presents the basic physics and chemistry of these processes, and shows how they can be accurately modeled. The author begins with an overview of plasma reactors and discusses the various models for understanding plasma processes. He then covers plasma chemistry, addressing the effects of different chemicals on the features being etched. Having presented the relevant background material, he then describes in detail the modeling of complex plasma systems, with reference to experimental results. The book closes with a useful glossary of technical terms. No prior knowledge of plasma physics is assumed in the book. It contains many homework exercises and serves as an ideal introduction to plasma processing and technology for graduate students of electrical engineering and materials science. It will also be a useful reference for practicing engineers in the semiconductor industry.

Numerical analysis of the heating phase and densification mechanism in polymers selective laser melting process

NASA Astrophysics Data System (ADS)

Mokrane, Aoulaiche; Boutaous, M'hamed; Xin, Shihe

2018-05-01

The aim of this work is to address a modeling of the SLS process at the scale of the part in PA12 polymer powder bed. The powder bed is considered as a continuous medium with homogenized properties, meanwhile understanding multiple physical phenomena occurring during the process and studying the influence of process parameters on the quality of final product. A thermal model, based on enthalpy approach, will be presented with details on the multiphysical couplings that allow the thermal history: laser absorption, melting, coalescence, densification, volume shrinkage and on numerical implementation using FV method. The simulations were carried out in 3D with an in-house developed FORTRAN code. After validation of the model with comparison to results from literature, a parametric analysis will be proposed. Some original results as densification process and the thermal history with the evolution of the material, from the granular solid state to homogeneous melted state will be discussed with regards to the involved physical phenomena.

A student-centered approach for developing active learning: the construction of physical models as a teaching tool in medical physiology.

PubMed

Rezende-Filho, Flávio Moura; da Fonseca, Lucas José Sá; Nunes-Souza, Valéria; Guedes, Glaucevane da Silva; Rabelo, Luiza Antas

2014-09-15

Teaching physiology, a complex and constantly evolving subject, is not a simple task. A considerable body of knowledge about cognitive processes and teaching and learning methods has accumulated over the years, helping teachers to determine the most efficient way to teach, and highlighting student's active participation as a means to improve learning outcomes. In this context, this paper describes and qualitatively analyzes an experience of a student-centered teaching-learning methodology based on the construction of physiological-physical models, focusing on their possible application in the practice of teaching physiology. After having Physiology classes and revising the literature, students, divided in small groups, built physiological-physical models predominantly using low-cost materials, for studying different topics in Physiology. Groups were followed by monitors and guided by teachers during the whole process, finally presenting the results in a Symposium on Integrative Physiology. Along the proposed activities, students were capable of efficiently creating physiological-physical models (118 in total) highly representative of different physiological processes. The implementation of the proposal indicated that students successfully achieved active learning and meaningful learning in Physiology while addressing multiple learning styles. The proposed method has proved to be an attractive, accessible and relatively simple approach to facilitate the physiology teaching-learning process, while facing difficulties imposed by recent requirements, especially those relating to the use of experimental animals and professional training guidelines. Finally, students' active participation in the production of knowledge may result in a holistic education, and possibly, better professional practices.

Advantages and challenges of using physics curricula as a model for reforming an undergraduate biology course.

PubMed

Donovan, D A; Atkins, L J; Salter, I Y; Gallagher, D J; Kratz, R F; Rousseau, J V; Nelson, G D

2013-06-01

We report on the development of a life sciences curriculum, targeted to undergraduate students, which was modeled after a commercially available physics curriculum and based on aspects of how people learn. Our paper describes the collaborative development process and necessary modifications required to apply a physics pedagogical model in a life sciences context. While some approaches were easily adapted, others provided significant challenges. Among these challenges were: representations of energy, introducing definitions, the placement of Scientists' Ideas, and the replicability of data. In modifying the curriculum to address these challenges, we have come to see them as speaking to deeper differences between the disciplines, namely that introductory physics--for example, Newton's laws, magnetism, light--is a science of pairwise interaction, while introductory biology--for example, photosynthesis, evolution, cycling of matter in ecosystems--is a science of linked processes, and we suggest that this is how the two disciplines are presented in introductory classes. We illustrate this tension through an analysis of our adaptations of the physics curriculum for instruction on the cycling of matter and energy; we show that modifications of the physics curriculum to address the biological framework promotes strong gains in student understanding of these topics, as evidenced by analysis of student work.

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.

Fecal indicator organism modeling and microbial source tracking in environmental waters: Chapter 3.4.6

USGS Publications Warehouse

Nevers, Meredith; Byappanahalli, Muruleedhara; Phanikumar, Mantha S.; Whitman, Richard L.

2016-01-01

Mathematical models have been widely applied to surface waters to estimate rates of settling, resuspension, flow, dispersion, and advection in order to calculate movement of particles that influence water quality. Of particular interest are the movement, survival, and persistence of microbial pathogens or their surrogates, which may contaminate recreational water, drinking water, or shellfish. Most models devoted to microbial water quality have been focused on fecal indicator organisms (FIO), which act as a surrogate for pathogens and viruses. Process-based modeling and statistical modeling have been used to track contamination events to source and to predict future events. The use of these two types of models require different levels of expertise and input; process-based models rely on theoretical physical constructs to explain present conditions and biological distribution while data-based, statistical models use extant paired data to do the same. The selection of the appropriate model and interpretation of results is critical to proper use of these tools in microbial source tracking. Integration of the modeling approaches could provide insight for tracking and predicting contamination events in real time. A review of modeling efforts reveals that process-based modeling has great promise for microbial source tracking efforts; further, combining the understanding of physical processes influencing FIO contamination developed with process-based models and molecular characterization of the population by gene-based (i.e., biological) or chemical markers may be an effective approach for locating sources and remediating contamination in order to protect human health better.

Modeling DNP3 Traffic Characteristics of Field Devices in SCADA Systems of the Smart Grid

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

Yang, Huan; Cheng, Liang; Chuah, Mooi Choo

In the generation, transmission, and distribution sectors of the smart grid, intelligence of field devices is realized by programmable logic controllers (PLCs). Many smart-grid subsystems are essentially cyber-physical energy systems (CPES): For instance, the power system process (i.e., the physical part) within a substation is monitored and controlled by a SCADA network with hosts running miscellaneous applications (i.e., the cyber part). To study the interactions between the cyber and physical components of a CPES, several co-simulation platforms have been proposed. However, the network simulators/emulators of these platforms do not include a detailed traffic model that takes into account the impactsmore » of the execution model of PLCs on traffic characteristics. As a result, network traces generated by co-simulation only reveal the impacts of the physical process on the contents of the traffic generated by SCADA hosts, whereas the distinction between PLCs and computing nodes (e.g., a hardened computer running a process visualization application) has been overlooked. To generate realistic network traces using co-simulation for the design and evaluation of applications relying on accurate traffic profiles, it is necessary to establish a traffic model for PLCs. In this work, we propose a parameterized model for PLCs that can be incorporated into existing co-simulation platforms. We focus on the DNP3 subsystem of slave PLCs, which automates the processing of packets from the DNP3 master. To validate our approach, we extract model parameters from both the configuration and network traces of real PLCs. Simulated network traces are generated and compared against those from PLCs. Our evaluation shows that our proposed model captures the essential traffic characteristics of DNP3 slave PLCs, which can be used to extend existing co-simulation platforms and gain further insights into the behaviors of CPES.« less

Object schemas for grounding language in a responsive robot

NASA Astrophysics Data System (ADS)

Hsiao, Kai-Yuh; Tellex, Stefanie; Vosoughi, Soroush; Kubat, Rony; Roy, Deb

2008-12-01

An approach is introduced for physically grounded natural language interpretation by robots that reacts appropriately to unanticipated physical changes in the environment and dynamically assimilates new information pertinent to ongoing tasks. At the core of the approach is a model of object schemas that enables a robot to encode beliefs about physical objects in its environment using collections of coupled processes responsible for sensorimotor interaction. These interaction processes run concurrently in order to ensure responsiveness to the environment, while co-ordinating sensorimotor expectations, action planning and language use. The model has been implemented on a robot that manipulates objects on a tabletop in response to verbal input. The implementation responds to verbal requests such as 'Group the green block and the red apple', while adapting in real time to unexpected physical collisions and taking opportunistic advantage of any new information it may receive through perceptual and linguistic channels.

Being qua becoming: Aristotle's "Metaphysics", quantum physics, and Process Philosophy

NASA Astrophysics Data System (ADS)

Johnson, David Kelley

In Aristotle's First Philosophy, science and philosophy were partners, but with the rise of empiricism, went their separate ways. Metaphysics combined the rational and irrational (i.e. final cause/unmoved mover) elements of existence to equate being with substance, postulating prime matter as pure potential that was actuated by form to create everything. Modern science reveres pure reason and postulates its theory of being by a rigorous scientific methodology. The Standard Model defines matter as energy formed into fundamental particles via forces contained in fields. Science has proved Aristotle's universe wrong in many ways, but as physics delves deeper into the quantum world, empiricism is reaching its limits concerning fundamental questions of existence. To achieve its avowed mission of explaining existence completely, physics must reunite with philosophy in a metascience modeled on the First Philosophy of Aristotle. One theory of being that integrates quantum physics and metaphysics is Process Philosophy.

Physics-based interactive volume manipulation for sharing surgical process.

PubMed

Nakao, Megumi; Minato, Kotaro

2010-05-01

This paper presents a new set of techniques by which surgeons can interactively manipulate patient-specific volumetric models for sharing surgical process. To handle physical interaction between the surgical tools and organs, we propose a simple surface-constraint-based manipulation algorithm to consistently simulate common surgical manipulations such as grasping, holding and retraction. Our computation model is capable of simulating soft-tissue deformation and incision in real time. We also present visualization techniques in order to rapidly visualize time-varying, volumetric information on the deformed image. This paper demonstrates the success of the proposed methods in enabling the simulation of surgical processes, and the ways in which this simulation facilitates preoperative planning and rehearsal.

Physical principles for DNA tile self-assembly.

PubMed

Evans, Constantine G; Winfree, Erik

2017-06-19

DNA tiles provide a promising technique for assembling structures with nanoscale resolution through self-assembly by basic interactions rather than top-down assembly of individual structures. Tile systems can be programmed to grow based on logical rules, allowing for a small number of tile types to assemble large, complex assemblies that can retain nanoscale resolution. Such algorithmic systems can even assemble different structures using the same tiles, based on inputs that seed the growth. While programming and theoretical analysis of tile self-assembly often makes use of abstract logical models of growth, experimentally implemented systems are governed by nanoscale physical processes that can lead to very different behavior, more accurately modeled by taking into account the thermodynamics and kinetics of tile attachment and detachment in solution. This review discusses the relationships between more abstract and more physically realistic tile assembly models. A central concern is how consideration of model differences enables the design of tile systems that robustly exhibit the desired abstract behavior in realistic physical models and in experimental implementations. Conversely, we identify situations where self-assembly in abstract models can not be well-approximated by physically realistic models, putting constraints on physical relevance of the abstract models. To facilitate the discussion, we introduce a unified model of tile self-assembly that clarifies the relationships between several well-studied models in the literature. Throughout, we highlight open questions regarding the physical principles for DNA tile self-assembly.

Possibilities: A Framework for Modeling Students' Deductive Reasoning in Physics

ERIC Educational Resources Information Center

Gaffney, Jonathan David Housley

2010-01-01

Students often make errors when trying to solve qualitative or conceptual physics problems, and while many successful instructional interventions have been generated to prevent such errors, the process of deduction that students use when solving physics problems has not been thoroughly studied. In an effort to better understand that reasoning…

Gaussian Process modelling of blood glucose response to free-living physical activity data in people with type 1 diabetes.

PubMed

Valletta, John Joseph; Chipperfield, Andrew J; Byrne, Christopher D

2009-01-01

Good blood glucose control is important to people with type 1 diabetes to prevent diabetes-related complications. Too much blood glucose (hyperglycaemia) causes long-term micro-vascular complications, while a severe drop in blood glucose (hypoglycaemia) can cause life-threatening coma. Finding the right balance between quantity and type of food intake, physical activity levels and insulin dosage, is a daily challenge. Increased physical activity levels often cause changes in blood glucose due to increased glucose uptake into tissues such as muscle. To date we have limited knowledge about the minute by minute effects of exercise on blood glucose levels, in part due to the difficulty in measuring glucose and physical activity levels continuously, in a free-living environment. By using a light and user-friendly armband we can record physical activity energy expenditure on a minute-by-minute basis. Simultaneously, by using a continuous glucose monitoring system we can record glucose concentrations. In this paper, Gaussian Processes are used to model the glucose excursions in response to physical activity data, to study its effect on glycaemic control.

Modelling transport phenomena in a multi-physics context

NASA Astrophysics Data System (ADS)

Marra, Francesco

2015-01-01

Innovative heating research on cooking, pasteurization/sterilization, defrosting, thawing and drying, often focuses on areas which include the assessment of processing time, evaluation of heating uniformity, studying the impact on quality attributes of the final product as well as considering the energy efficiency of these heating processes. During the last twenty years, so-called electro-heating-processes (radio-frequency - RF, microwaves - MW and ohmic - OH) gained a wide interest in industrial food processing and many applications using the above mentioned technologies have been developed with the aim of reducing processing time, improving process efficiency and, in many cases, the heating uniformity. In the area of innovative heating, electro-heating accounts for a considerable portion of both the scientific literature and commercial applications, which can be subdivided into either direct electro-heating (as in the case of OH heating) where electrical current is applied directly to the food or indirect electro-heating (e.g. MW and RF heating) where the electrical energy is firstly converted to electromagnetic radiation which subsequently generates heat within a product. New software packages, which make easier solution of PDEs based mathematical models, and new computers, capable of larger RAM and more efficient CPU performances, allowed an increasing interest about modelling transport phenomena in systems and processes - as the ones encountered in food processing - that can be complex in terms of geometry, composition, boundary conditions but also - as in the case of electro-heating assisted applications - in terms of interaction with other physical phenomena such as displacement of electric or magnetic field. This paper deals with the description of approaches used in modelling transport phenomena in a multi-physics context such as RF, MW and OH assisted heating.

Modelling transport phenomena in a multi-physics context

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

Marra, Francesco

2015-01-22

Innovative heating research on cooking, pasteurization/sterilization, defrosting, thawing and drying, often focuses on areas which include the assessment of processing time, evaluation of heating uniformity, studying the impact on quality attributes of the final product as well as considering the energy efficiency of these heating processes. During the last twenty years, so-called electro-heating-processes (radio-frequency - RF, microwaves - MW and ohmic - OH) gained a wide interest in industrial food processing and many applications using the above mentioned technologies have been developed with the aim of reducing processing time, improving process efficiency and, in many cases, the heating uniformity. Inmore » the area of innovative heating, electro-heating accounts for a considerable portion of both the scientific literature and commercial applications, which can be subdivided into either direct electro-heating (as in the case of OH heating) where electrical current is applied directly to the food or indirect electro-heating (e.g. MW and RF heating) where the electrical energy is firstly converted to electromagnetic radiation which subsequently generates heat within a product. New software packages, which make easier solution of PDEs based mathematical models, and new computers, capable of larger RAM and more efficient CPU performances, allowed an increasing interest about modelling transport phenomena in systems and processes - as the ones encountered in food processing - that can be complex in terms of geometry, composition, boundary conditions but also - as in the case of electro-heating assisted applications - in terms of interaction with other physical phenomena such as displacement of electric or magnetic field. This paper deals with the description of approaches used in modelling transport phenomena in a multi-physics context such as RF, MW and OH assisted heating.« less

Temporal self-regulation theory: a neurobiologically informed model for physical activity behavior

PubMed Central

Hall, Peter A.; Fong, Geoffrey T.

2015-01-01

Dominant explanatory models for physical activity behavior are limited by the exclusion of several important components, including temporal dynamics, ecological forces, and neurobiological factors. The latter may be a critical omission, given the relevance of several aspects of cognitive function for the self-regulatory processes that are likely required for consistent implementation of physical activity behavior in everyday life. This narrative review introduces temporal self-regulation theory (TST; Hall and Fong, 2007, 2013) as a new explanatory model for physical activity behavior. Important features of the model include consideration of the default status of the physical activity behavior, as well as the disproportionate influence of temporally proximal behavioral contingencies. Most importantly, the TST model proposes positive feedback loops linking executive function (EF) and the performance of physical activity behavior. Specifically, those with relatively stronger executive control (and optimized brain structures supporting it, such as the dorsolateral prefrontal cortex (PFC)) are able to implement physical activity with more consistency than others, which in turn serves to strengthen the executive control network itself. The TST model has the potential to explain everyday variants of incidental physical activity, sport-related excellence via capacity for deliberate practice, and variability in the propensity to schedule and implement exercise routines. PMID:25859196

Shoreline Change and Storm-Induced Beach Erosion Modeling: A Collection of Seven Papers

DTIC Science & Technology

1990-03-01

reducing, and analyzing the data in a systematic manner. Most physical data needed for evaluating and interpreting shoreline and beach evolution processes...proposed development concepts using both physical and numerical models. b. Analyzed and interpreted model results. c. Provided technical documentation of... interpret study results in the context required for "Confirmation" hearings. 26 The Corps of Engineers, Los Angeles District (SPL), has also begun studies

Identifying Hydrogeological Controls of Catchment Low-Flow Dynamics Using Physically Based Modelling

NASA Astrophysics Data System (ADS)

Cochand, F.; Carlier, C.; Staudinger, M.; Seibert, J.; Hunkeler, D.; Brunner, P.

2017-12-01

Identifying key catchment characteristics and processes which control the hydrological response under low-flow conditions is important to assess the catchments' vulnerability to dry periods. In the context of a Swiss Federal Office for the Environment (FOEN) project, the low-flow behaviours of two mountainous catchments were investigated. These neighboring catchments are characterized by the same meteorological conditions, but feature completely different river flow dynamics. The Roethenbach is characterized by high peak flows and low mean flows. Conversely, the Langete is characterized by relatively low peak flows and high mean flow rates. To understand the fundamentally different behaviour of the two catchments, a physically-based surface-subsurface flow HydroGeoSphere (HGS) model for each catchment was developed. The main advantage of a physically-based model is its ability to realistically reproduce processes which play a key role during low-flow periods such as surface-subsurface interactions or evapotranspiration. Both models were calibrated to reproduce measured groundwater heads and the surface flow dynamics. Subsequently, the calibrated models were used to explore the fundamental physics that control hydrological processes during low-flow periods. To achieve this, a comparative sensitivity analysis of model parameters of both catchments was carried out. Results show that the hydraulic conductivity of the bedrock (and weathered bedrock) controls the catchment water dynamics in both models. Conversely, the properties of other geological formations such as alluvial aquifer or soil layer hydraulic conductivity or porosity play a less important role. These results change significantly our perception of the streamflow catchment dynamics and more specifically the way to assess catchment vulnerability to dry period. This study suggests that by analysing catchment scale bedrock properties, the catchment dynamics and the vulnerability to dry period may be assessed.

Kelp, cobbles, and currents: Biologic reduction of coarse grain entrainment stress

USGS Publications Warehouse

Masteller, Claire C; Finnegan, Noah J; Warrick, Jonathan; Miller, Ian M.

2015-01-01

Models quantifying the onset of sediment motion do not typically account for the effect of biotic processes because they are difficult to isolate and quantify in relation to physical processes. Here we investigate an example of the interaction of kelp (Order Laminariales) and coarse sediment transport in the coastal zone, where it is possible to directly quantify and test its effect. Kelp is ubiquitous along rocky coastlines and the impact on ecosystems has been well studied. We develop a physical model to explore the reduction in critical shear stress of large cobbles colonized by Nereocystis luetkeana, or bull kelp. Observations of coarse sediment motion at a site in the Strait of Juan de Fuca (northwest United States–Canada boundary channel) confirm the model prediction and show that kelp reduces the critical stress required for transport of a given grain size by as much as 92%, enabling annual coarse sediment transport rates comparable to those of fluvial systems. We demonstrate that biology is fundamental to the physical processes that shape the coastal zone in this setting.

Detailed Modeling of Physical Processes in Electron Sources for Accelerator Applications

NASA Astrophysics Data System (ADS)

Chubenko, Oksana; Afanasev, Andrei

2017-01-01

At present, electron sources are essential in a wide range of applications - from common technical use to exploring the nature of matter. Depending on the application requirements, different methods and materials are used to generate electrons. State-of-the-art accelerator applications set a number of often-conflicting requirements for electron sources (e.g., quantum efficiency vs. polarization, current density vs. lifetime, etc). Development of advanced electron sources includes modeling and design of cathodes, material growth, fabrication of cathodes, and cathode testing. The detailed simulation and modeling of physical processes is required in order to shed light on the exact mechanisms of electron emission and to develop new-generation electron sources with optimized efficiency. The purpose of the present work is to study physical processes in advanced electron sources and develop scientific tools, which could be used to predict electron emission from novel nano-structured materials. In particular, the area of interest includes bulk/superlattice gallium arsenide (bulk/SL GaAs) photo-emitters and nitrogen-incorporated ultrananocrystalline diamond ((N)UNCD) photo/field-emitters. Work supported by The George Washington University and Euclid TechLabs LLC.

Energetic investigation of the adsorption process of CH4, C2H6 and N2 on activated carbon: Numerical and statistical physics treatment

NASA Astrophysics Data System (ADS)

Ben Torkia, Yosra; Ben Yahia, Manel; Khalfaoui, Mohamed; Al-Muhtaseb, Shaheen A.; Ben Lamine, Abdelmottaleb

2014-01-01

The adsorption energy distribution (AED) function of a commercial activated carbon (BDH-activated carbon) was investigated. For this purpose, the integral equation is derived by using a purely analytical statistical physics treatment. The description of the heterogeneity of the adsorbent is significantly clarified by defining the parameter N(E). This parameter represents the energetic density of the spatial density of the effectively occupied sites. To solve the integral equation, a numerical method was used based on an adequate algorithm. The Langmuir model was adopted as a local adsorption isotherm. This model is developed by using the grand canonical ensemble, which allows defining the physico-chemical parameters involved in the adsorption process. The AED function is estimated by a normal Gaussian function. This method is applied to the adsorption isotherms of nitrogen, methane and ethane at different temperatures. The development of the AED using a statistical physics treatment provides an explanation of the gas molecules behaviour during the adsorption process and gives new physical interpretations at microscopic levels.

Heterogeneous scalable framework for multiphase flows

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

Morris, Karla Vanessa

2013-09-01

Two categories of challenges confront the developer of computational spray models: those related to the computation and those related to the physics. Regarding the computation, the trend towards heterogeneous, multi- and many-core platforms will require considerable re-engineering of codes written for the current supercomputing platforms. Regarding the physics, accurate methods for transferring mass, momentum and energy from the dispersed phase onto the carrier fluid grid have so far eluded modelers. Significant challenges also lie at the intersection between these two categories. To be competitive, any physics model must be expressible in a parallel algorithm that performs well on evolving computermore » platforms. This work created an application based on a software architecture where the physics and software concerns are separated in a way that adds flexibility to both. The develop spray-tracking package includes an application programming interface (API) that abstracts away the platform-dependent parallelization concerns, enabling the scientific programmer to write serial code that the API resolves into parallel processes and threads of execution. The project also developed the infrastructure required to provide similar APIs to other application. The API allow object-oriented Fortran applications direct interaction with Trilinos to support memory management of distributed objects in central processing units (CPU) and graphic processing units (GPU) nodes for applications using C++.« less

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.

Physician-based activity counseling: intervention effects on mediators of motivational readiness for physical activity.

PubMed

Pinto, B M; Lynn, H; Marcus, B H; DePue, J; Goldstein, M G

2001-01-01

In theory-based interventions for behavior change, there is a need to examine the effects of interventions on the underlying theoretical constructs and the mediating role of such constructs. These two questions are addressed in the Physically Active for Life study, a randomized trial of physician-based exercise counseling for older adults. Three hundred fifty-five patients participated (intervention n = 181, control n = 174; mean age = 65.6 years). The underlying theories used were the Transtheoretical Model, Social Cognitive Theory and the constructs of decisional balance (benefits and barriers), self-efficacy, and behavioral and cognitive processes of change. Motivational readiness for physical activity and related constructs were assessed at baseline, 6 weeks, and 8 months. Linear or logistic mixed effects models were used to examine intervention effects on the constructs, and logistic mixed effects models were used for mediator analyses. At 6 weeks, the intervention had significant effects on decisional balance, self-efficacy, and behavioral processes, but these effects were not maintained at 8 months. At 6 weeks, only decisional balance and behavioral processes were identified as mediators of motivational readiness outcomes. Results suggest that interventions of greater intensity and duration may be needed for sustained changes in mediators and motivational readiness for physical activity among older adults.

Applying the Transtheoretical Model to Physical Activity Behavior in Individuals With Non-Cystic Fibrosis Bronchiectasis.

PubMed

Wilson, Jason J; Kirk, Alison; Hayes, Kate; Bradbury, Ian; McDonough, Suzanne; Tully, Mark A; O'Neill, Brenda; Bradley, Judy M

2016-01-01

The transtheoretical model has been successful in promoting health behavior change in general and clinical populations. However, there is little knowledge about the application of the transtheoretical model to explain physical activity behavior in individuals with non-cystic fibrosis bronchiectasis. The aim was to examine patterns of (1) physical activity and (2) mediators of behavior change (self-efficacy, decisional balance, and processes of change) across stages of change in individuals with non-cystic fibrosis bronchiectasis. Fifty-five subjects with non-cystic fibrosis bronchiectasis (mean age ± SD = 63 ± 10 y) had physical activity assessed over 7 d using an accelerometer. Each component of the transtheoretical model was assessed using validated questionnaires. Subjects were divided into groups depending on stage of change: Group 1 (pre-contemplation and contemplation; n = 10), Group 2 (preparation; n = 20), and Group 3 (action and maintenance; n = 25). Statistical analyses included one-way analysis of variance and Tukey-Kramer post hoc tests. Physical activity variables were significantly (P < .05) higher in Group 3 (action and maintenance) compared with Group 2 (preparation) and Group 1 (pre-contemplation and contemplation). For self-efficacy, there were no significant differences between groups for mean scores (P = .14). Decisional balance cons (barriers to being physically active) were significantly lower in Group 3 versus Group 2 (P = .032). For processes of change, substituting alternatives (substituting inactive options for active options) was significantly higher in Group 3 versus Group 1 (P = .01), and enlisting social support (seeking out social support to increase and maintain physical activity) was significantly lower in Group 3 versus Group 2 (P = .038). The pattern of physical activity across stages of change is consistent with the theoretical predictions of the transtheoretical model. Constructs of the transtheoretical model that appear to be important at different stages of change include decisional balance cons, substituting alternatives, and enlisting social support. This study provides support to explore transtheoretical model-based physical activity interventions in individuals with non-cystic fibrosis bronchiectasis. (ClinicalTrials.gov registration NCT01569009.). Copyright © 2016 by Daedalus Enterprises.

How Is the Learning Environment in Physics Lesson with Using 7E Model Teaching Activities

ERIC Educational Resources Information Center

Turgut, Umit; Colak, Alp; Salar, Riza

2017-01-01

The aim of this research is to reveal the results in the planning, implementation and evaluation of the process for learning environments to be designed in compliance with 7E learning cycle model in physics lesson. "Action research", which is a qualitative research pattern, is employed in this research in accordance with the aim of the…

Prediction of Meiyu rainfall in Taiwan by multi-lead physical-empirical models

NASA Astrophysics Data System (ADS)

Yim, So-Young; Wang, Bin; Xing, Wen; Lu, Mong-Ming

2015-06-01

Taiwan is located at the dividing point of the tropical and subtropical monsoons over East Asia. Taiwan has double rainy seasons, the Meiyu in May-June and the Typhoon rains in August-September. To predict the amount of Meiyu rainfall is of profound importance to disaster preparedness and water resource management. The seasonal forecast of May-June Meiyu rainfall has been a challenge to current dynamical models and the factors controlling Taiwan Meiyu variability has eluded climate scientists for decades. Here we investigate the physical processes that are possibly important for leading to significant fluctuation of the Taiwan Meiyu rainfall. Based on this understanding, we develop a physical-empirical model to predict Taiwan Meiyu rainfall at a lead time of 0- (end of April), 1-, and 2-month, respectively. Three physically consequential and complementary predictors are used: (1) a contrasting sea surface temperature (SST) tendency in the Indo-Pacific warm pool, (2) the tripolar SST tendency in North Atlantic that is associated with North Atlantic Oscillation, and (3) a surface warming tendency in northeast Asia. These precursors foreshadow an enhanced Philippine Sea anticyclonic anomalies and the anomalous cyclone near the southeastern China in the ensuing summer, which together favor increasing Taiwan Meiyu rainfall. Note that the identified precursors at various lead-times represent essentially the same physical processes, suggesting the robustness of the predictors. The physical empirical model made by these predictors is capable of capturing the Taiwan rainfall variability with a significant cross-validated temporal correlation coefficient skill of 0.75, 0.64, and 0.61 for 1979-2012 at the 0-, 1-, and 2-month lead time, respectively. The physical-empirical model concept used here can be extended to summer monsoon rainfall prediction over the Southeast Asia and other regions.

Estimation of the viscosities of liquid binary alloys

NASA Astrophysics Data System (ADS)

Wu, Min; Su, Xiang-Yu

2018-01-01

As one of the most important physical and chemical properties, viscosity plays a critical role in physics and materials as a key parameter to quantitatively understanding the fluid transport process and reaction kinetics in metallurgical process design. Experimental and theoretical studies on liquid metals are problematic. Today, there are many empirical and semi-empirical models available with which to evaluate the viscosity of liquid metals and alloys. However, the parameter of mixed energy in these models is not easily determined, and most predictive models have been poorly applied. In the present study, a new thermodynamic parameter Δ G is proposed to predict liquid alloy viscosity. The prediction equation depends on basic physical and thermodynamic parameters, namely density, melting temperature, absolute atomic mass, electro-negativity, electron density, molar volume, Pauling radius, and mixing enthalpy. Our results show that the liquid alloy viscosity predicted using the proposed model is closely in line with the experimental values. In addition, if the component radius difference is greater than 0.03 nm at a certain temperature, the atomic size factor has a significant effect on the interaction of the binary liquid metal atoms. The proposed thermodynamic parameter Δ G also facilitates the study of other physical properties of liquid metals.

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

Development of a physically-based planar inductors VHDL-AMS model for integrated power converter design

NASA Astrophysics Data System (ADS)

Ammouri, Aymen; Ben Salah, Walid; Khachroumi, Sofiane; Ben Salah, Tarek; Kourda, Ferid; Morel, Hervé

2014-05-01

Design of integrated power converters needs prototype-less approaches. Specific simulations are required for investigation and validation process. Simulation relies on active and passive device models. Models of planar devices, for instance, are still not available in power simulator tools. There is, thus, a specific limitation during the simulation process of integrated power systems. The paper focuses on the development of a physically-based planar inductor model and its validation inside a power converter during transient switching. The planar inductor model remains a complex device to model, particularly when the skin, the proximity and the parasitic capacitances effects are taken into account. Heterogeneous simulation scheme, including circuit and device models, is successfully implemented in VHDL-AMS language and simulated in Simplorer platform. The mixed simulation results has been favorably tested and compared with practical measurements. It is found that the multi-domain simulation results and measurements data are in close agreement.

Modeling of feed-forward control using the partial least squares regression method in the tablet compression process.

PubMed

Hattori, Yusuke; Otsuka, Makoto

2017-05-30

In the pharmaceutical industry, the implementation of continuous manufacturing has been widely promoted in lieu of the traditional batch manufacturing approach. More specially, in recent years, the innovative concept of feed-forward control has been introduced in relation to process analytical technology. In the present study, we successfully developed a feed-forward control model for the tablet compression process by integrating data obtained from near-infrared (NIR) spectra and the physical properties of granules. In the pharmaceutical industry, batch manufacturing routinely allows for the preparation of granules with the desired properties through the manual control of process parameters. On the other hand, continuous manufacturing demands the automatic determination of these process parameters. Here, we proposed the development of a control model using the partial least squares regression (PLSR) method. The most significant feature of this method is the use of dataset integrating both the NIR spectra and the physical properties of the granules. Using our model, we determined that the properties of products, such as tablet weight and thickness, need to be included as independent variables in the PLSR analysis in order to predict unknown process parameters. Copyright © 2017 Elsevier B.V. All rights reserved.

The Bilinear Product Model of Hysteresis Phenomena

NASA Astrophysics Data System (ADS)

Kádár, György

1989-01-01

In ferromagnetic materials non-reversible magnetization processes are represented by rather complex hysteresis curves. The phenomenological description of such curves needs the use of multi-valued, yet unambiguous, deterministic functions. The history dependent calculation of consecutive Everett-integrals of the two-variable Preisach-function can account for the main features of hysteresis curves in uniaxial magnetic materials. The traditional Preisach model has recently been modified on the basis of population dynamics considerations, removing the non-real congruency property of the model. The Preisach-function was proposed to be a product of two factors of distinct physical significance: a magnetization dependent function taking into account the overall magnetization state of the body and a bilinear form of a single variable, magnetic field dependent, switching probability function. The most important statement of the bilinear product model is, that the switching process of individual particles is to be separated from the book-keeping procedure of their states. This empirical model of hysteresis can easily be extended to other irreversible physical processes, such as first order phase transitions.

Statistics-related and reliability-physics-related failure processes in electronics devices and products

NASA Astrophysics Data System (ADS)

Suhir, E.

2014-05-01

The well known and widely used experimental reliability "passport" of a mass manufactured electronic or a photonic product — the bathtub curve — reflects the combined contribution of the statistics-related and reliability-physics (physics-of-failure)-related processes. When time progresses, the first process results in a decreasing failure rate, while the second process associated with the material aging and degradation leads to an increased failure rate. An attempt has been made in this analysis to assess the level of the reliability physics-related aging process from the available bathtub curve (diagram). It is assumed that the products of interest underwent the burn-in testing and therefore the obtained bathtub curve does not contain the infant mortality portion. It has been also assumed that the two random processes in question are statistically independent, and that the failure rate of the physical process can be obtained by deducting the theoretically assessed statistical failure rate from the bathtub curve ordinates. In the carried out numerical example, the Raleigh distribution for the statistical failure rate was used, for the sake of a relatively simple illustration. The developed methodology can be used in reliability physics evaluations, when there is a need to better understand the roles of the statistics-related and reliability-physics-related irreversible random processes in reliability evaluations. The future work should include investigations on how powerful and flexible methods and approaches of the statistical mechanics can be effectively employed, in addition to reliability physics techniques, to model the operational reliability of electronic and photonic products.

ON NONSTATIONARY STOCHASTIC MODELS FOR EARTHQUAKES.

USGS Publications Warehouse

Safak, Erdal; Boore, David M.

1986-01-01

A seismological stochastic model for earthquake ground-motion description is presented. Seismological models are based on the physical properties of the source and the medium and have significant advantages over the widely used empirical models. The model discussed here provides a convenient form for estimating structural response by using random vibration theory. A commonly used random process for ground acceleration, filtered white-noise multiplied by an envelope function, introduces some errors in response calculations for structures whose periods are longer than the faulting duration. An alternate random process, filtered shot-noise process, eliminates these errors.

The Trans-Contextual Model of Autonomous Motivation in Education

PubMed Central

Hagger, Martin S.; Chatzisarantis, Nikos L. D.

2015-01-01

The trans-contextual model outlines the processes by which autonomous motivation toward activities in a physical education context predicts autonomous motivation toward physical activity outside of school, and beliefs about, intentions toward, and actual engagement in, out-of-school physical activity. In the present article, we clarify the fundamental propositions of the model and resolve some outstanding conceptual issues, including its generalizability across multiple educational domains, criteria for its rejection or failed replication, the role of belief-based antecedents of intentions, and the causal ordering of its constructs. We also evaluate the consistency of model relationships in previous tests of the model using path-analytic meta-analysis. The analysis supported model hypotheses but identified substantial heterogeneity in the hypothesized relationships across studies unattributed to sampling and measurement error. Based on our meta-analysis, future research needs to provide further replications of the model in diverse educational settings beyond physical education and test model hypotheses using experimental methods. PMID:27274585

The Trans-Contextual Model of Autonomous Motivation in Education: Conceptual and Empirical Issues and Meta-Analysis.

PubMed

Hagger, Martin S; Chatzisarantis, Nikos L D

2016-06-01

The trans-contextual model outlines the processes by which autonomous motivation toward activities in a physical education context predicts autonomous motivation toward physical activity outside of school, and beliefs about, intentions toward, and actual engagement in, out-of-school physical activity. In the present article, we clarify the fundamental propositions of the model and resolve some outstanding conceptual issues, including its generalizability across multiple educational domains, criteria for its rejection or failed replication, the role of belief-based antecedents of intentions, and the causal ordering of its constructs. We also evaluate the consistency of model relationships in previous tests of the model using path-analytic meta-analysis. The analysis supported model hypotheses but identified substantial heterogeneity in the hypothesized relationships across studies unattributed to sampling and measurement error. Based on our meta-analysis, future research needs to provide further replications of the model in diverse educational settings beyond physical education and test model hypotheses using experimental methods.

A MEDL Collection Showcase: A Collection of Hands-on Physical Analog Models and Demonstrations From the Department of Geosciences MEDL at Virginia Tech

NASA Astrophysics Data System (ADS)

Glesener, G. B.

2017-12-01

The Geosciences Modeling and Educational Demonstrations Laboratory (MEDL) will present a suite of hands-on physical analog models from our curriculum materials collection used to teach about a wide range of geoscience processes. Many of the models will be equipped with Vernier data collection sensors, which visitors will be encouraged to explore on-site. Our goal is to spark interest and discussion around the affordances of these kinds of curriculum materials. Important topics to discuss will include: (1) How can having a collection of hands-on physical analog models be used to effectively produce successful broader impacts activities for research proposals? (2) What kinds of learning outcomes have instructors observed when teaching about temporally and spatially challenging concepts using physical analog models? (3) What does it take for an institution to develop their own MEDL collection? and (4) How can we develop a community of individuals who provide on-the-ground support for instructors who use physical analog models in their classroom.

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...

A Method for Combining Experimentation and Molecular Dynamics Simulation to Improve Cohesive Zone Models for Metallic Microstructures

NASA Technical Reports Server (NTRS)

Hochhalter, J. D.; Glaessgen, E. H.; Ingraffea, A. R.; Aquino, W. A.

2009-01-01

Fracture processes within a material begin at the nanometer length scale at which the formation, propagation, and interaction of fundamental damage mechanisms occur. Physics-based modeling of these atomic processes quickly becomes computationally intractable as the system size increases. Thus, a multiscale modeling method, based on the aggregation of fundamental damage processes occurring at the nanoscale within a cohesive zone model, is under development and will enable computationally feasible and physically meaningful microscale fracture simulation in polycrystalline metals. This method employs atomistic simulation to provide an optimization loop with an initial prediction of a cohesive zone model (CZM). This initial CZM is then applied at the crack front region within a finite element model. The optimization procedure iterates upon the CZM until the finite element model acceptably reproduces the near-crack-front displacement fields obtained from experimental observation. With this approach, a comparison can be made between the original CZM predicted by atomistic simulation and the converged CZM that is based on experimental observation. Comparison of the two CZMs gives insight into how atomistic simulation scales.

How physiological and physical processes contribute to the phenology of cyanobacterial blooms in large shallow lakes: A new Euler-Lagrangian coupled model.

PubMed

Feng, Tao; Wang, Chao; Wang, Peifang; Qian, Jin; Wang, Xun

2018-09-01

Cyanobacterial blooms have emerged as one of the most severe ecological problems affecting large and shallow freshwater lakes. To improve our understanding of the factors that influence, and could be used to predict, surface blooms, this study developed a novel Euler-Lagrangian coupled approach combining the Eulerian model with agent-based modelling (ABM). The approach was subsequently verified based on monitoring datasets and MODIS data in a large shallow lake (Lake Taihu, China). The Eulerian model solves the Eulerian variables and physiological parameters, whereas ABM generates the complete life cycle and transport processes of cyanobacterial colonies. This model ensemble performed well in fitting historical data and predicting the dynamics of cyanobacterial biomass, bloom distribution, and area. Based on the calculated physical and physiological characteristics of surface blooms, principal component analysis (PCA) captured the major processes influencing surface bloom formation at different stages (two bloom clusters). Early bloom outbreaks were influenced by physical processes (horizontal transport and vertical turbulence-induced mixing), whereas buoyancy-controlling strategies were essential for mature bloom outbreaks. Canonical correlation analysis (CCA) revealed the combined actions of multiple environment variables on different bloom clusters. The effects of buoyancy-controlling strategies (ISP), vertical turbulence-induced mixing velocity of colony (VMT) and horizontal drift velocity of colony (HDT) were quantitatively compared using scenario simulations in the coupled model. VMT accounted for 52.9% of bloom formations and maintained blooms over long periods, thus demonstrating the importance of wind-induced turbulence in shallow lakes. In comparison, HDT and buoyancy controlling strategies influenced blooms at different stages. In conclusion, the approach developed here presents a promising tool for understanding the processes of onshore/offshore algal blooms formation and subsequent predicting. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Physical modeling of the influence of bedrock topography and ablation on ice flow and meteorite concentration in Antarctica

NASA Astrophysics Data System (ADS)

Corti, Giacomo; Zeoli, Antonio; Belmaggio, Pietro; Folco, Luigi

2008-03-01

Three-dimensional laboratory physical experiments have been used to investigate the influence of bedrock topography and ablation on ice flow. Different models were tested in a Plexiglas box, where a transparent silicone simulating ice in nature was allowed to flow. Experimental results show how the flow field (in terms of both flow lines and velocity) and variations in the topography of the free surface and internal layers of the ice are strongly influenced by the presence and height of bedrock obstacles. In particular, the buttressing effect forces the ice to slow down, rise up, and avoid the obstacle; the higher the bedrock barrier, the more pronounced the process. Only limited uplift of internal layers is observed in these experiments. In order to exhume deep material embedded in the ice, ablation (simulated by physically removing portions of silicone from the model surface to maintain a constant topographic depression) must be included in the physical models. In this case, the analogue ice replenishes the area of material removal, thereby allowing deep layers to move vertically to the surface and severely altering the local ice flow pattern. This process is analogous to the ice flow model proposed in the literature for the origin of meteorite concentrations in blue ice areas of the Antarctic plateau.

Mechanistic equivalent circuit modelling of a commercial polymer electrolyte membrane fuel cell

NASA Astrophysics Data System (ADS)

Giner-Sanz, J. J.; Ortega, E. M.; Pérez-Herranz, V.

2018-03-01

Electrochemical impedance spectroscopy (EIS) has been widely used in the fuel cell field since it allows deconvolving the different physic-chemical processes that affect the fuel cell performance. Typically, EIS spectra are modelled using electric equivalent circuits. In this work, EIS spectra of an individual cell of a commercial PEM fuel cell stack were obtained experimentally. The goal was to obtain a mechanistic electric equivalent circuit in order to model the experimental EIS spectra. A mechanistic electric equivalent circuit is a semiempirical modelling technique which is based on obtaining an equivalent circuit that does not only correctly fit the experimental spectra, but which elements have a mechanistic physical meaning. In order to obtain the aforementioned electric equivalent circuit, 12 different models with defined physical meanings were proposed. These equivalent circuits were fitted to the obtained EIS spectra. A 2 step selection process was performed. In the first step, a group of 4 circuits were preselected out of the initial list of 12, based on general fitting indicators as the determination coefficient and the fitted parameter uncertainty. In the second step, one of the 4 preselected circuits was selected on account of the consistency of the fitted parameter values with the physical meaning of each parameter.

Using a Virtual Experiment to Analyze Infiltration Process from Point to Grid-cell Size Scale

NASA Astrophysics Data System (ADS)

Barrios, M. I.

2013-12-01

The hydrological science requires the emergence of a consistent theoretical corpus driving the relationships between dominant physical processes at different spatial and temporal scales. However, the strong spatial heterogeneities and non-linearities of these processes make difficult the development of multiscale conceptualizations. Therefore, scaling understanding is a key issue to advance this science. This work is focused on the use of virtual experiments to address the scaling of vertical infiltration from a physically based model at point scale to a simplified physically meaningful modeling approach at grid-cell scale. Numerical simulations have the advantage of deal with a wide range of boundary and initial conditions against field experimentation. The aim of the work was to show the utility of numerical simulations to discover relationships between the hydrological parameters at both scales, and to use this synthetic experience as a media to teach the complex nature of this hydrological process. The Green-Ampt model was used to represent vertical infiltration at point scale; and a conceptual storage model was employed to simulate the infiltration process at the grid-cell scale. Lognormal and beta probability distribution functions were assumed to represent the heterogeneity of soil hydraulic parameters at point scale. The linkages between point scale parameters and the grid-cell scale parameters were established by inverse simulations based on the mass balance equation and the averaging of the flow at the point scale. Results have shown numerical stability issues for particular conditions and have revealed the complex nature of the non-linear relationships between models' parameters at both scales and indicate that the parameterization of point scale processes at the coarser scale is governed by the amplification of non-linear effects. The findings of these simulations have been used by the students to identify potential research questions on scale issues. Moreover, the implementation of this virtual lab improved the ability to understand the rationale of these process and how to transfer the mathematical models to computational representations.

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.

Magnetic Local Time dependency in modeling of the Earth radiation belts

NASA Astrophysics Data System (ADS)

Herrera, Damien; Maget, Vincent; Bourdarie, Sébastien; Rolland, Guy

2017-04-01

For many years, ONERA has been at the forefront of the modeling of the Earth radiation belts thanks to the Salammbô model, which accurately reproduces their dynamics over a time scale of the particles' drift period. This implies that we implicitly assume an homogeneous repartition of the trapped particles along a given drift shell. However, radiation belts are inhomogeneous in Magnetic Local Time (MLT). So, we need to take this new coordinate into account to model rigorously the dynamical structures, particularly induced during a geomagnetic storm. For this purpose, we are working on both the numerical resolution of the Fokker-Planck diffusion equation included in the model and on the MLT dependency of physic-based processes acting in the Earth radiation belts. The aim of this talk is first to present the 4D-equation used and the different steps we used to build Salammbô 4D model before focusing on physical processes taken into account in the Salammbô code, specially transport due to convection electric field. Firstly, we will briefly introduce the Salammbô 4D code developped by talking about its numerical scheme and physic-based processes modeled. Then, we will focus our attention on the impact of the outer boundary condition (localisation and spectrum) at lower L∗ shell by comparing modeling performed with geosynchronous data from LANL-GEO satellites. Finally, we will discuss the prime importance of the convection electric field to the radial and drift transport of low energy particles around the Earth.

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)

REVIEWS OF TOPICAL PROBLEMS: Physical aspects of cryobiology

NASA Astrophysics Data System (ADS)

Zhmakin, A. I.

2008-03-01

Physical phenomena during biological freezing and thawing processes at the molecular, cellular, tissue, and organ levels are examined. The basics of cryosurgery and cryopreservation of cells and tissues are presented. Existing cryobiological models, including numerical ones, are reviewed.

Experimental Validation of Various Temperature Modells for Semi-Physical Tyre Model Approaches

NASA Astrophysics Data System (ADS)

Hackl, Andreas; Scherndl, Christoph; Hirschberg, Wolfgang; Lex, Cornelia

2017-10-01

With increasing level of complexity and automation in the area of automotive engineering, the simulation of safety relevant Advanced Driver Assistance Systems (ADAS) leads to increasing accuracy demands in the description of tyre contact forces. In recent years, with improvement in tyre simulation, the needs for coping with tyre temperatures and the resulting changes in tyre characteristics are rising significantly. Therefore, experimental validation of three different temperature model approaches is carried out, discussed and compared in the scope of this article. To investigate or rather evaluate the range of application of the presented approaches in combination with respect of further implementation in semi-physical tyre models, the main focus lies on the a physical parameterisation. Aside from good modelling accuracy, focus is held on computational time and complexity of the parameterisation process. To evaluate this process and discuss the results, measurements from a Hoosier racing tyre 6.0 / 18.0 10 LCO C2000 from an industrial flat test bench are used. Finally the simulation results are compared with the measurement data.

Towards a physically-based multi-scale ecohydrological simulator for semi-arid regions

NASA Astrophysics Data System (ADS)

Caviedes-Voullième, Daniel; Josefik, Zoltan; Hinz, Christoph

2017-04-01

The use of numerical models as tools for describing and understanding complex ecohydrological systems has enabled to test hypothesis and propose fundamental, process-based explanations of the system system behaviour as a whole as well as its internal dynamics. Reaction-diffusion equations have been used to describe and generate organized pattern such as bands, spots, and labyrinths using simple feedback mechanisms and boundary conditions. Alternatively, pattern-matching cellular automaton models have been used to generate vegetation self-organization in arid and semi-arid regions also using simple description of surface hydrological processes. A key question is: How much physical realism is needed in order to adequately capture the pattern formation processes in semi-arid regions while reliably representing the water balance dynamics at the relevant time scales? In fact, redistribution of water by surface runoff at the hillslope scale occurs at temporal resolution of minutes while the vegetation development requires much lower temporal resolution and longer times spans. This generates a fundamental spatio-temporal multi-scale problem to be solved, for which high resolution rainfall and surface topography are required. Accordingly, the objective of this contribution is to provide proof-of-concept that governing processes can be described numerically at those multiple scales. The requirements for a simulating ecohydrological processes and pattern formation with increased physical realism are, amongst others: i. high resolution rainfall that adequately captures the triggers of growth as vegetation dynamics of arid regions respond as pulsed systems. ii. complex, natural topography in order to accurately model drainage patterns, as surface water redistribution is highly sensitive to topographic features. iii. microtopography and hydraulic roughness, as small scale variations do impact on large scale hillslope behaviour iv. moisture dependent infiltration as temporal dynamics of infiltration affects water storage under vegetation and in bare soil Despite the volume of research in this field, fundamental limitations still exist in the models regarding the aforementioned issues. Topography and hydrodynamics have been strongly simplified. Infiltration has been modelled as dependent on depth but independent of soil moisture. Temporal rainfall variability has only been addressed for seasonal rain. Spatial heterogenity of the topography as well as roughness and infiltration properties, has not been fully and explicitly represented. We hypothesize that physical processes must be robustly modelled and the drivers of complexity must be present with as much resolution as possible in order to provide the necessary realism to improve transient simulations, perhaps leading the way to virtual laboratories and, arguably, predictive tools. This work provides a first approach into a model with explicit hydrological processes represented by physically-based hydrodynamic models, coupled with well-accepted vegetation models. The model aims to enable new possibilities relating to spatiotemporal variability, arbitrary topography and representation of spatial heterogeneity, including sub-daily (in fact, arbitrary) temporal variability of rain as the main forcing of the model, explicit representation of infiltration processes, and various feedback mechanisms between the hydrodynamics and the vegetation. Preliminary testing strongly suggests that the model is viable, has the potential of producing new information of internal dynamics of the system, and allows to successfully aggregate many of the sources of complexity. Initial benchmarking of the model also reveals strengths to be exploited, thus providing an interesting research outlook, as well as weaknesses to be addressed in the immediate future.

Parental perceptions of neighborhood processes, stress, personal control, and risk for physical child abuse and neglect.

PubMed

Guterman, Neil B; Lee, Shawna J; Taylor, Catherine A; Rathouz, Paul J

2009-12-01

This study set out to examine whether mothers' individual perceptions of their neighborhood social processes predict their risk for physical child abuse and neglect directly and/or indirectly via pathways involving parents' reported stress and sense of personal control in the parenting role. In-home and phone interview data were examined cross-sectionally from a national birth cohort sample of 3,356 mothers across 20 US cities when the index child was 3 years of age. Mothers' perceptions of neighborhood social processes, parenting stress, and personal control were examined as predictors, and three subscales of the Parent-To-Child Conflict Tactics Scale (CTS-PC) were employed as proxies of physical child abuse and neglect risk. Structural equation modeling (SEM) was employed to test direct and indirect pathways (via parenting stress and control) from perceived neighborhood processes to proxy measures of physical child abuse and neglect. Multiple group SEM was conducted to test for differences across major ethnic groups: African American, Hispanic, and White. Although perceived negative neighborhood processes had only a mild direct role in predicting risk for physical child abuse, and no direct role on child neglect, these perceptions had a discernable indirect role in predicting risk via parenting stress and personal control pathways. Parenting stress exerted the clearest direct role on both physical abuse and neglect risk. This predictor model did not significantly differ across ethnic groups. Although neighborhood conditions may not play a clear directly observable role on physical child abuse and neglect risk, the indirect role they play underscores the importance of parents' perceptions of their neighborhoods, and especially the role they play via parents' reported stress and personal control. Such findings suggest that targeting parents' sense of control and stress in relation to their immediate social environment holds particular potential to reduce physical child abuse and neglect risk. Addressing parents' perceptions of their neighborhood challenges may serve to reduce parenting risk via improving parents' felt control and stress.

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.

Videogame Construction by Engineering Students for Understanding Modelling Processes: The Case of Simulating Water Behaviour

ERIC Educational Resources Information Center

Pretelín-Ricárdez, Angel; Sacristán, Ana Isabel

2015-01-01

We present some results of an ongoing research project where university engineering students were asked to construct videogames involving the use of physical systems models. The objective is to help them identify and understand the elements and concepts involved in the modelling process. That is, we use game design as a constructionist approach…

Mathematical modeling of high-pH chemical flooding

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

Bhuyan, D.; Lake, L.W.; Pope, G.A.

1990-05-01

This paper describes a generalized compositional reservoir simulator for high-pH chemical flooding processes. This simulator combines the reaction chemistry associated with these processes with the extensive physical- and flow-property modeling schemes of an existing micellar/polymer flood simulator, UTCHEM. Application of the model is illustrated for cases from a simple alkaline preflush to surfactant-enhanced alkaline-polymer flooding.

Predictive Models for Semiconductor Device Design and Processing

NASA Technical Reports Server (NTRS)

Meyyappan, Meyya; Arnold, James O. (Technical Monitor)

1998-01-01

The device feature size continues to be on a downward trend with a simultaneous upward trend in wafer size to 300 mm. Predictive models are needed more than ever before for this reason. At NASA Ames, a Device and Process Modeling effort has been initiated recently with a view to address these issues. Our activities cover sub-micron device physics, process and equipment modeling, computational chemistry and material science. This talk would outline these efforts and emphasize the interaction among various components. The device physics component is largely based on integrating quantum effects into device simulators. We have two parallel efforts, one based on a quantum mechanics approach and the second, a semiclassical hydrodynamics approach with quantum correction terms. Under the first approach, three different quantum simulators are being developed and compared: a nonequlibrium Green's function (NEGF) approach, Wigner function approach, and a density matrix approach. In this talk, results using various codes will be presented. Our process modeling work focuses primarily on epitaxy and etching using first-principles models coupling reactor level and wafer level features. For the latter, we are using a novel approach based on Level Set theory. Sample results from this effort will also be presented.

Coupled ocean-shelf ecosystem modelling of northern North Atlantic

NASA Astrophysics Data System (ADS)

Harle, J.; Holt, J. T.; Butenschön, M.; Allen, J. I.

2016-02-01

The biogeochemistry and ecosystems of the open-ocean and shelf seas are intimately connected. For example Northwest European continental shelf receives a substantial fraction of its nutrients from the wider North Atlantic and exports carbon at depth, sequestering it from atmospheric exchange. In the EC FP7 EuroBasin project (Holt et al 2014) we have developed a 1/12 degree basin-scale NEMO-ERSEM model with specific features relevant to shelf seas (e.g. tides and advanced vertical mixing schemes). This model is eddy resolving in the open-ocean, and resolves barotropic scales on-shelf. We use this model to explore the interaction between finely resolved physical processes and the ecosystem. Here we focus on shelf-sea processes and the connection between the shelf seas and open-ocean, and compare results with a 1/4 degree (eddy permitting) model that does not include shelf sea processes. We find tidal mixing fronts and river plume are well represented in the 1/12 degree model. Using approaches developed for the NW Shelf (Holt et al 2012), we provide estimates of across-shelf break nutrient fluxes to the seas surrounding this basin, and relate these fluxes and their interannual variability to the physical processes driving ocean-shelf exchange. Holt, J., et al, 2012. Oceanic controls on the primary production of the northwest European continental shelf: model experiments under recent past conditions and a potential future scenario. Biogeosciences 9, 97-117. Holt, J., et al, 2014. Challenges in integrative approaches to modelling the marine ecosystems of the North Atlantic: Physics to Fish and Coasts to Ocean. Progress in Oceanography doi:10.1016/j.pocean.2014.04.024.

The influence of wind-tunnel walls on discrete frequency noise

NASA Technical Reports Server (NTRS)

Mosher, M.

1984-01-01

This paper describes an analytical model that can be used to examine the effects of wind-tunnel walls on discrete frequency noise. First, a complete physical model of an acoustic source in a wind tunnel is described, and a simplified version is then developed. This simplified model retains the important physical processes involved, yet it is more amenable to analysis. Second, the simplified physical model is formulated as a mathematical problem. An inhomogeneous partial differential equation with mixed boundary conditions is set up and then transformed into an integral equation. The integral equation has been solved with a panel program on a computer. Preliminary results from a simple model problem will be shown and compared with the approximate analytic solution.

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.

Statistical analysis of experimental data for mathematical modeling of physical processes in the atmosphere

NASA Astrophysics Data System (ADS)

Karpushin, P. A.; Popov, Yu B.; Popova, A. I.; Popova, K. Yu; Krasnenko, N. P.; Lavrinenko, A. V.

2017-11-01

In this paper, the probabilities of faultless operation of aerologic stations are analyzed, the hypothesis of normality of the empirical data required for using the Kalman filter algorithms is tested, and the spatial correlation functions of distributions of meteorological parameters are determined. The results of a statistical analysis of two-term (0, 12 GMT) radiosonde observations of the temperature and wind velocity components at some preset altitude ranges in the troposphere in 2001-2016 are presented. These data can be used in mathematical modeling of physical processes in the atmosphere.

Laser powder bed fusion additive manufacturing of metals; physics, computational, and materials challenges

NASA Astrophysics Data System (ADS)

King, W. E.; Anderson, A. T.; Ferencz, R. M.; Hodge, N. E.; Kamath, C.; Khairallah, S. A.; Rubenchik, A. M.

2015-12-01

The production of metal parts via laser powder bed fusion additive manufacturing is growing exponentially. However, the transition of this technology from production of prototypes to production of critical parts is hindered by a lack of confidence in the quality of the part. Confidence can be established via a fundamental understanding of the physics of the process. It is generally accepted that this understanding will be increasingly achieved through modeling and simulation. However, there are significant physics, computational, and materials challenges stemming from the broad range of length and time scales and temperature ranges associated with the process. In this paper, we review the current state of the art and describe the challenges that need to be met to achieve the desired fundamental understanding of the physics of the process.

High-resolution modeling of a marine ecosystem using the FRESCO hydroecological model

NASA Astrophysics Data System (ADS)

Zalesny, V. B.; Tamsalu, R.

2009-02-01

The FRESCO (Finnish Russian Estonian Cooperation) mathematical model describing a marine hydroecosystem is presented. The methodology of the numerical solution is based on the method of multicomponent splitting into physical and biological processes, spatial coordinates, etc. The model is used for the reproduction of physical and biological processes proceeding in the Baltic Sea. Numerical experiments are performed with different spatial resolutions for four marine basins that are enclosed into one another: the Baltic Sea, the Gulf of Finland, the Tallinn-Helsinki water area, and Tallinn Bay. Physical processes are described by the equations of nonhydrostatic dynamics, including the k-ω parametrization of turbulence. Biological processes are described by the three-dimensional equations of an aquatic ecosystem with the use of a size-dependent parametrization of biochemical reactions. The main goal of this study is to illustrate the efficiency of the developed numerical technique and to demonstrate the importance of a high spatial resolution for water basins that have complex bottom topography, such as the Baltic Sea. Detailed information about the atmospheric forcing, bottom topography, and coastline is very important for the description of coastal dynamics and specific features of a marine ecosystem. Experiments show that the spatial inhomogeneity of hydroecosystem fields is caused by the combined effect of upwelling, turbulent mixing, surface-wave breaking, and temperature variations, which affect biochemical reactions.

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.

Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model

NASA Technical Reports Server (NTRS)

Tao, W. K.; Wang, Y.; Qian, J.; Shie, C. -L.; Lau, W. K. -M.; Kakar, R.; Starr, David O' C. (Technical Monitor)

2002-01-01

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China (Lau et al. 2000). Multiple observation platforms (e.g., soundings, Doppler radar, ships, wind seafarers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes, associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets (Johnson and Ciesielski 2002) and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional climate model and a cloud-resolving model are used to perform multi-day integrations to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil - precipitation interaction and feedback associated with a flood event that occurred in and around China's Atlantic River during SCSMEX. Sensitivity tests on various land surface models, cumulus parameterization schemes (CASE), sea surface temperature (SST) variations and midlatitude influences are also performed to understand the processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. Cloud-resolving models (CRMs) use more sophisticated and physically realistic parameterizations of cloud microphysical processes with very fine spatial and temporal resolution. One of the major characteristics of CRMs is an explicit interaction between clouds, radiation and the land/ocean surface. It is for this reason that GEWEX (Global Energy and Water Cycle Experiment) has formed the GCSS (GEWEX Cloud System Study) expressly for the purpose of improving the representation of the moist processes in large-scale models using CRMs. The Goddard Cumulus Ensemble (GCE) model is a CRM and is used to simulate convective systems associated with the onset of the South China Sea monsoon in 1998. The BRUCE model includes the same land surface model, cloud physics, and radiation scheme used in the regional climate model. A comparison between the results from the GCE model and regional climate model is performed.

Basic Modeling of the Solar Atmosphere and Spectrum

NASA Technical Reports Server (NTRS)

Avrett, Eugene H.; Wagner, William J. (Technical Monitor)

2000-01-01

During the last three years we have continued the development of extensive computer programs for constructing realistic models of the solar atmosphere and for calculating detailed spectra to use in the interpretation of solar observations. This research involves two major interrelated efforts: work by Avrett and Loeser on the Pandora computer program for optically thick non-LTE modeling of the solar atmosphere including a wide range of physical processes, and work by Kurucz on the detailed high-resolution synthesis of the solar spectrum using data for over 58 million atomic and molecular lines. Our objective is to construct atmospheric models from which the calculated spectra agree as well as possible with high-and low-resolution observations over a wide wavelength range. Such modeling leads to an improved understanding of the physical processes responsible for the structure and behavior of the atmosphere.

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.

A conceptual snow model with an analytic resolution of the heat and phase change equations

NASA Astrophysics Data System (ADS)

Riboust, Philippe; Le Moine, Nicolas; Thirel, Guillaume; Ribstein, Pierre

2017-04-01

Compared to degree-day snow models, physically-based snow models resolve more processes in an attempt to achieve a better representation of reality. Often these physically-based models resolve the heat transport equations in snow using a vertical discretization of the snowpack. The snowpack is decomposed into several layers in which the mechanical and thermal states of the snow are calculated. A higher number of layers in the snowpack allow for better accuracy but it also tends to increase the computational costs. In order to develop a snow model that estimates the temperature profile of snow with a lower computational cost, we used an analytical decomposition of the vertical profile using eigenfunctions (i.e. trigonometric functions adapted to the specific boundary conditions). The mass transfer of snow melt has also been estimated using an analytical conceptualization of runoff fingering and matrix flow. As external meteorological forcing, the model uses solar and atmospheric radiation, air temperature, atmospheric humidity and precipitations. It has been tested and calibrated at point scale at two different stations in the Alps: Col de Porte (France, 1325 m) and Weissfluhjoch (Switzerland, 2540 m). A sensitivity analysis of model parameters and model inputs will be presented together with a comparison with measured snow surface temperature, SWE, snow depth, temperature profile and snow melt data. The snow model is created in order to be ultimately coupled with hydrological models for rainfall-runoff modeling in mountainous areas. We hope to create a model faster than physically-based models but capable to estimate more physical processes than degree-day snow models. This should help to build a more reliable snow model capable of being easily calibrated by remote sensing and in situ observation or to assimilate these data for forecasting purposes.

Soil Erosion as a stochastic process

NASA Astrophysics Data System (ADS)

Casper, Markus C.

2015-04-01

The main tools to provide estimations concerning risk and amount of erosion are different types of soil erosion models: on the one hand, there are empirically based model concepts on the other hand there are more physically based or process based models. However, both types of models have substantial weak points. All empirical model concepts are only capable of providing rough estimates over larger temporal and spatial scales, they do not account for many driving factors that are in the scope of scenario related analysis. In addition, the physically based models contain important empirical parts and hence, the demand for universality and transferability is not given. As a common feature, we find, that all models rely on parameters and input variables, which are to certain, extend spatially and temporally averaged. A central question is whether the apparent heterogeneity of soil properties or the random nature of driving forces needs to be better considered in our modelling concepts. Traditionally, researchers have attempted to remove spatial and temporal variability through homogenization. However, homogenization has been achieved through physical manipulation of the system, or by statistical averaging procedures. The price for obtaining this homogenized (average) model concepts of soils and soil related processes has often been a failure to recognize the profound importance of heterogeneity in many of the properties and processes that we study. Especially soil infiltrability and the resistance (also called "critical shear stress" or "critical stream power") are the most important empirical factors of physically based erosion models. The erosion resistance is theoretically a substrate specific parameter, but in reality, the threshold where soil erosion begins is determined experimentally. The soil infiltrability is often calculated with empirical relationships (e.g. based on grain size distribution). Consequently, to better fit reality, this value needs to be corrected experimentally. To overcome this disadvantage of our actual models, soil erosion models are needed that are able to use stochastic directly variables and parameter distributions. There are only some minor approaches in this direction. The most advanced is the model "STOSEM" proposed by Sidorchuk in 2005. In this model, only a small part of the soil erosion processes is described, the aggregate detachment and the aggregate transport by flowing water. The concept is highly simplified, for example, many parameters are temporally invariant. Nevertheless, the main problem is that our existing measurements and experiments are not geared to provide stochastic parameters (e.g. as probability density functions); in the best case they deliver a statistical validation of the mean values. Again, we get effective parameters, spatially and temporally averaged. There is an urgent need for laboratory and field experiments on overland flow structure, raindrop effects and erosion rate, which deliver information on spatial and temporal structure of soil and surface properties and processes.

Nucleosynthesis in Core-Collapse Supernovae

NASA Astrophysics Data System (ADS)

Stevenson, Taylor Shannon; Viktoria Ohstrom, Eva; Harris, James Austin; Hix, William R.

2018-01-01

The nucleosynthesis which occurs in core-collapse supernovae (CCSN) is one of the most important sources of elements in the universe. Elements from Oxygen through Iron come predominantly from supernovae, and contributions of heavier elements are also possible through processes like the weak r-process, the gamma process and the light element primary process. The composition of the ejecta depends on the mechanism of the explosion, thus simulations of high physical fidelity are needed to explore what elements and isotopes CCSN can contribute to Galactic Chemical Evolution. We will analyze the nucleosynthesis results from self-consistent CCSN simulations performed with CHIMERA, a multi-dimensional neutrino radiation-hydrodynamics code. Much of our understanding of CCSN nucleosynthesis comes from parameterized models, but unlike CHIMERA these fail to address essential physics, including turbulent flow/instability and neutrino-matter interaction. We will present nucleosynthesis predictions for the explosion of a 9.6 solar mass first generation star, relying both on results of the 160 species nuclear reaction network used in CHIMERA within this model and on post-processing with a more extensive network. The lowest mass iron core-collapse supernovae, like this model, are distinct from their more massive brethren, with their explosion mechanism and nucleosynthesis being more like electron capture supernovae resulting from Oxygen-Neon white dwarves. We will highlight the differences between the nucleosynthesis in this model and more massive supernovae. The inline 160 species network is a feature unique to CHIMERA, making this the most sophisticated model to date for a star of this type. We will discuss the need and mechanism to extrapolate the post-processing to times post-simulation and analyze the uncertainties this introduces for supernova nucleosynthesis. We will also compare the results from the inline 160 species network to the post-processing results to study further uncertainties introduced by post-processing. This work is supported by the U.S. Department of Energy, Office of Nuclear Physics, and the National Science Foundation Nuclear Theory Program (PHY-1516197).

Lumped parametric model of the human ear for sound transmission.

PubMed

Feng, Bin; Gan, Rong Z

2004-09-01

A lumped parametric model of the human auditoria peripherals consisting of six masses suspended with six springs and ten dashpots was proposed. This model will provide the quantitative basis for the construction of a physical model of the human middle ear. The lumped model parameters were first identified using published anatomical data, and then determined through a parameter optimization process. The transfer function of the middle ear obtained from human temporal bone experiments with laser Doppler interferometers was used for creating the target function during the optimization process. It was found that, among 14 spring and dashpot parameters, there were five parameters which had pronounced effects on the dynamic behaviors of the model. The detailed discussion on the sensitivity of those parameters was provided with appropriate applications for sound transmission in the ear. We expect that the methods for characterizing the lumped model of the human ear and the model parameters will be useful for theoretical modeling of the ear function and construction of the ear physical model.

Using lab notebooks to examine students' engagement in modeling in an upper-division electronics lab course

NASA Astrophysics Data System (ADS)

Stanley, Jacob T.; Su, Weifeng; Lewandowski, H. J.

2017-12-01

We demonstrate how students' use of modeling can be examined and assessed using student notebooks collected from an upper-division electronics lab course. The use of models is a ubiquitous practice in undergraduate physics education, but the process of constructing, testing, and refining these models is much less common. We focus our attention on a lab course that has been transformed to engage students in this modeling process during lab activities. The design of the lab activities was guided by a framework that captures the different components of model-based reasoning, called the Modeling Framework for Experimental Physics. We demonstrate how this framework can be used to assess students' written work and to identify how students' model-based reasoning differed from activity to activity. Broadly speaking, we were able to identify the different steps of students' model-based reasoning and assess the completeness of their reasoning. Varying degrees of scaffolding present across the activities had an impact on how thoroughly students would engage in the full modeling process, with more scaffolded activities resulting in more thorough engagement with the process. Finally, we identified that the step in the process with which students had the most difficulty was the comparison between their interpreted data and their model prediction. Students did not use sufficiently sophisticated criteria in evaluating such comparisons, which had the effect of halting the modeling process. This may indicate that in order to engage students further in using model-based reasoning during lab activities, the instructor needs to provide further scaffolding for how students make these types of experimental comparisons. This is an important design consideration for other such courses attempting to incorporate modeling as a learning goal.

Building Physics Test Cases | Buildings | NREL

Science.gov Websites

building physics test cases in BESTEST-EX. In these cases, the model inputs that describe the house are programs. This diagram provides an overview of the BESTEST-EX physics case process. On the left side of the diagram is a box labeled "BESTEST-EX Document" with a list that contains two bulleted items. The

Beyond Performance Metrics: Examining a Decrease in Students' Physics Self-Efficacy through a Social Networks Lens

ERIC Educational Resources Information Center

Dou, Remy; Brewe, Eric; Zwolak, Justyna P.; Potvin, Geoff; Williams, Eric A.; Kramer, Laird H.

2016-01-01

The Modeling Instruction (MI) approach to introductory physics manifests significant increases in student conceptual understanding and attitudes toward physics. In light of these findings, we investigated changes in student self-efficacy while considering the construct's contribution to the career-decision making process. Students in the Fall 2014…

Motivational factors associated with physical activity and quality of life in people with severe mental illness.

PubMed

Farholm, Anders; Sørensen, Marit; Halvari, Hallgeir

2017-12-01

There has been increasing interest for investigating the role of motivation in physical activity among people with severe mental illness (SMI). Autonomous motivation has been suggested to have a potentially important role in adoption and maintenance of physical activity. However, the knowledge about factors that facilitate autonomous motivation among people with SMI is scarce. The aim of this study was to examine factors associated with motivation for physical activity as well as the relationships between motivation, physical activity and health-related quality of life in individuals with SMI that were currently physically active. A cross-sectional design was used, and 88 participants were recruited from a public health network promoting physical activity for people with SMI. They answered a questionnaire package consisting of scales measuring psychological need support - psychological need satisfaction - and motivation for physical activity, physical activity and health-related quality of life. The majority of participants reported to be in regular physical activity. Associations between variables were tested according to the self-determination theory process model. Structural equation modelling yielded good fit of the process model to the data. Specifically, a need-supportive environment was positively associated with psychological need satisfaction, while psychological need satisfaction was positively associated with autonomous motivation and mental health-related quality of life, and negatively associated with controlled motivation and amotivation. Physical activity was positively associated with autonomous motivation and physical health-related quality of life, and negatively associated with amotivation. This study indicates that individuals with SMI can be regularly physically active when provided with suitable opportunities. Furthermore, the present results suggest that it is vital for health-care practitioners to emphasise creating a need-supportive environment when organising physical activity because such an environment is associated with both increased autonomous motivation for physical activity and mental health-related quality of life. © 2016 Nordic College of Caring Science.

A Comparison of Curing Process-Induced Residual Stresses and Cure Shrinkage in Micro-Scale Composite Structures with Different Constitutive Laws

NASA Astrophysics Data System (ADS)

Li, Dongna; Li, Xudong; Dai, Jianfeng; Xi, Shangbin

2018-02-01

In this paper, three kinds of constitutive laws, elastic, "cure hardening instantaneously linear elastic (CHILE)" and viscoelastic law, are used to predict curing process-induced residual stress for the thermoset polymer composites. A multi-physics coupling finite element analysis (FEA) model implementing the proposed three approaches is established in COMSOL Multiphysics-Version 4.3b. The evolution of thermo-physical properties with temperature and degree of cure (DOC), which improved the accuracy of numerical simulations, and cure shrinkage are taken into account for the three models. Subsequently, these three proposed constitutive models are implemented respectively in a 3D micro-scale composite laminate structure. Compared the differences between these three numerical results, it indicates that big error in residual stress and cure shrinkage generates by elastic model, but the results calculated by the modified CHILE model are in excellent agreement with those estimated by the viscoelastic model.

Unfolding an electronic integrate-and-fire circuit.

PubMed

Carrillo, Humberto; Hoppensteadt, Frank

2010-01-01

Many physical and biological phenomena involve accumulation and discharge processes that can occur on significantly different time scales. Models of these processes have contributed to understand excitability self-sustained oscillations and synchronization in arrays of oscillators. Integrate-and-fire (I+F) models are popular minimal fill-and-flush mathematical models. They are used in neuroscience to study spiking and phase locking in single neuron membranes, large scale neural networks, and in a variety of applications in physics and electrical engineering. We show here how the classical first-order I+F model fits into the theory of nonlinear oscillators of van der Pol type by demonstrating that a particular second-order oscillator having small parameters converges in a singular perturbation limit to the I+F model. In this sense, our study provides a novel unfolding of such models and it identifies a constructible electronic circuit that is closely related to I+F.

Mathematical modeling of fluid flow in aluminum ladles for degasification with impeller - injector

NASA Astrophysics Data System (ADS)

Ramos-Gómez, E.; González-Rivera, C.; Ramírez-Argáez, M. A.

2012-09-01

In this work a fundamental Eulerian mathematical model was developed to simulate fluid flow in a water physical model of an aluminum ladle equipped with impeller for degassing treatment. The effect of critical process parameters such as rotor speed, gas flow rate on the fluid flow and vortex formation was analyzed with this model. Commercial CFD code PHOENICS 3.4 was used to solve all conservation equations governing the process for this twophase fluid flow system. The mathematical model was successfully validated against experimentally measured liquid velocity and turbulent profiles in a physical model. From the results it was concluded that the angular speed of the impeller is the most important parameter promoting better stirred baths. Pumping effect of the impeller is increased as impeller rotation speed increases. Gas flow rate is detrimental on bath stirring and diminishes pumping effect of impeller.

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.

Parameter dimensionality reduction of a conceptual model for streamflow prediction in Canadian, snowmelt dominated ungauged basins

NASA Astrophysics Data System (ADS)

Arsenault, Richard; Poissant, Dominique; Brissette, François

2015-11-01

This paper evaluated the effects of parametric reduction of a hydrological model on five regionalization methods and 267 catchments in the province of Quebec, Canada. The Sobol' variance-based sensitivity analysis was used to rank the model parameters by their influence on the model results and sequential parameter fixing was performed. The reduction in parameter correlations improved parameter identifiability, however this improvement was found to be minimal and was not transposed in the regionalization mode. It was shown that 11 of the HSAMI models' 23 parameters could be fixed with little or no loss in regionalization skill. The main conclusions were that (1) the conceptual lumped models used in this study did not represent physical processes sufficiently well to warrant parameter reduction for physics-based regionalization methods for the Canadian basins examined and (2) catchment descriptors did not adequately represent the relevant hydrological processes, namely snow accumulation and melt.

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.

Theory, modeling, and simulation of structural and functional materials: Micromechanics, microstructures, and properties

NASA Astrophysics Data System (ADS)

Jin, Yongmei

In recent years, theoretical modeling and computational simulation of microstructure evolution and materials property has been attracting much attention. While significant advances have been made, two major challenges remain. One is the integration of multiple physical phenomena for simulation of complex materials behavior, the other is the bridging over multiple length and time scales in materials modeling and simulation. The research presented in this Thesis is focused mainly on tackling the first major challenge. In this Thesis, a unified Phase Field Microelasticity (PFM) approach is developed. This approach is an advanced version of the phase field method that takes into account the exact elasticity of arbitrarily anisotropic, elastically and structurally inhomogeneous systems. The proposed theory and models are applicable to infinite solids, elastic half-space, and finite bodies with arbitrary-shaped free surfaces, which may undergo various concomitant physical processes. The Phase Field Microelasticity approach is employed to formulate the theories and models of martensitic transformation, dislocation dynamics, and crack evolution in single crystal and polycrystalline solids. It is also used to study strain relaxation in heteroepitaxial thin films through misfit dislocation and surface roughening. Magnetic domain evolution in nanocrystalline thin films is also investigated. Numerous simulation studies are performed. Comparison with analytical predictions and experimental observations are presented. Agreement verities the theory and models as realistic simulation tools for computational materials science and engineering. The same Phase Field Microelasticity formalism of individual models of different physical phenomena makes it easy to integrate multiple physical processes into one unified simulation model, where multiple phenomena are treated as various relaxation modes that together act as one common cooperative phenomenon. The model does not impose a priori constraints on possible microstructure evolution paths. This gives the model predicting power, where material system itself "chooses" the optimal path for multiple processes. The advances made in this Thesis present a significant step forward to overcome the first challenge, mesoscale multi-physics modeling and simulation of materials. At the end of this Thesis, the way to tackle the second challenge, bridging over multiple length and time scales in materials modeling and simulation, is discussed based on connection between the mesoscale Phase Field Microelasticity modeling and microscopic atomistic calculation as well as macroscopic continuum theory.

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.

Perspectives on integrated modeling of transport processes in semiconductor crystal growth

NASA Technical Reports Server (NTRS)

Brown, Robert A.

1992-01-01

The wide range of length and time scales involved in industrial scale solidification processes is demonstrated here by considering the Czochralski process for the growth of large diameter silicon crystals that become the substrate material for modern microelectronic devices. The scales range in time from microseconds to thousands of seconds and in space from microns to meters. The physics and chemistry needed to model processes on these different length scales are reviewed.

Design and Implementation of Hydrologic Process Knowledge-base Ontology: A case study for the Infiltration Process

NASA Astrophysics Data System (ADS)

Elag, M.; Goodall, J. L.

2013-12-01

Hydrologic modeling often requires the re-use and integration of models from different disciplines to simulate complex environmental systems. Component-based modeling introduces a flexible approach for integrating physical-based processes across disciplinary boundaries. Several hydrologic-related modeling communities have adopted the component-based approach for simulating complex physical systems by integrating model components across disciplinary boundaries in a workflow. However, it is not always straightforward to create these interdisciplinary models due to the lack of sufficient knowledge about a hydrologic process. This shortcoming is a result of using informal methods for organizing and sharing information about a hydrologic process. A knowledge-based ontology provides such standards and is considered the ideal approach for overcoming this challenge. The aims of this research are to present the methodology used in analyzing the basic hydrologic domain in order to identify hydrologic processes, the ontology itself, and how the proposed ontology is integrated with the Water Resources Component (WRC) ontology. The proposed ontology standardizes the definitions of a hydrologic process, the relationships between hydrologic processes, and their associated scientific equations. The objective of the proposed Hydrologic Process (HP) Ontology is to advance the idea of creating a unified knowledge framework for components' metadata by introducing a domain-level ontology for hydrologic processes. The HP ontology is a step toward an explicit and robust domain knowledge framework that can be evolved through the contribution of domain users. Analysis of the hydrologic domain is accomplished using the Formal Concept Approach (FCA), in which the infiltration process, an important hydrologic process, is examined. Two infiltration methods, the Green-Ampt and Philip's methods, were used to demonstrate the implementation of information in the HP ontology. Furthermore, a SPARQL service is provided for semantic-based querying of the ontology.

Invited review article: physics and Monte Carlo techniques as relevant to cryogenic, phonon, and ionization readout of Cryogenic Dark Matter Search radiation detectors.

PubMed

Leman, Steven W

2012-09-01

This review discusses detector physics and Monte Carlo techniques for cryogenic, radiation detectors that utilize combined phonon and ionization readout. A general review of cryogenic phonon and charge transport is provided along with specific details of the Cryogenic Dark Matter Search detector instrumentation. In particular, this review covers quasidiffusive phonon transport, which includes phonon focusing, anharmonic decay, and isotope scattering. The interaction of phonons in the detector surface is discussed along with the downconversion of phonons in superconducting films. The charge transport physics include a mass tensor which results from the crystal band structure and is modeled with a Herring-Vogt transformation. Charge scattering processes involve the creation of Neganov-Luke phonons. Transition-edge-sensor (TES) simulations include a full electric circuit description and all thermal processes including Joule heating, cooling to the substrate, and thermal diffusion within the TES, the latter of which is necessary to model normal-superconducting phase separation. Relevant numerical constants are provided for these physical processes in germanium, silicon, aluminum, and tungsten. Random number sampling methods including inverse cumulative distribution function (CDF) and rejection techniques are reviewed. To improve the efficiency of charge transport modeling, an additional second order inverse CDF method is developed here along with an efficient barycentric coordinate sampling method of electric fields. Results are provided in a manner that is convenient for use in Monte Carlo and references are provided for validation of these models.

A Study of the Ozone Formation by Ensemble Back Trajectory-process Analysis Using the Eta-CMAQ Forecast Model over the Northeastern U.S. During the 2004 ICARTT Period

EPA Science Inventory

The integrated process rates (IPR) estimated by the Eta-CMAQ model at grid cells along the trajectory of the air mass transport path were analyzed to quantitatively investigate the relative importance of physical and chemical processes for O₃ formation and evolution ov...

The effectiveness of flipped classroom learning model in secondary physics classroom setting

NASA Astrophysics Data System (ADS)

Prasetyo, B. D.; Suprapto, N.; Pudyastomo, R. N.

2018-03-01

The research aimed to describe the effectiveness of flipped classroom learning model on secondary physics classroom setting during Fall semester of 2017. The research object was Secondary 3 Physics group of Singapore School Kelapa Gading. This research was initiated by giving a pre-test, followed by treatment setting of the flipped classroom learning model. By the end of the learning process, the pupils were given a post-test and questionnaire to figure out pupils' response to the flipped classroom learning model. Based on the data analysis, 89% of pupils had passed the minimum criteria of standardization. The increment level in the students' mark was analysed by normalized n-gain formula, obtaining a normalized n-gain score of 0.4 which fulfil medium category range. Obtains from the questionnaire distributed to the students that 93% of students become more motivated to study physics and 89% of students were very happy to carry on hands-on activity based on the flipped classroom learning model. Those three aspects were used to generate a conclusion that applying flipped classroom learning model in Secondary Physics Classroom setting is effectively applicable.

Development and Optimization of Gas-Assisted Gravity Drainage (GAGD) Process for Improved Light Oil Recovery

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

Dandina N. Rao; Subhash C. Ayirala; Madhav M. Kulkarni

This is the final report describing the evolution of the project ''Development and Optimization of Gas-Assisted Gravity Drainage (GAGD) Process for Improved Light Oil Recovery'' from its conceptual stage in 2002 to the field implementation of the developed technology in 2006. This comprehensive report includes all the experimental research, models developments, analyses of results, salient conclusions and the technology transfer efforts. As planned in the original proposal, the project has been conducted in three separate and concurrent tasks: Task 1 involved a physical model study of the new GAGD process, Task 2 was aimed at further developing the vanishing interfacialmore » tension (VIT) technique for gas-oil miscibility determination, and Task 3 was directed at determining multiphase gas-oil drainage and displacement characteristics in reservoir rocks at realistic pressures and temperatures. The project started with the task of recruiting well-qualified graduate research assistants. After collecting and reviewing the literature on different aspects of the project such gas injection EOR, gravity drainage, miscibility characterization, and gas-oil displacement characteristics in porous media, research plans were developed for the experimental work to be conducted under each of the three tasks. Based on the literature review and dimensional analysis, preliminary criteria were developed for the design of the partially-scaled physical model. Additionally, the need for a separate transparent model for visual observation and verification of the displacement and drainage behavior under gas-assisted gravity drainage was identified. Various materials and methods (ceramic porous material, Stucco, Portland cement, sintered glass beads) were attempted in order to fabricate a satisfactory visual model. In addition to proving the effectiveness of the GAGD process (through measured oil recoveries in the range of 65 to 87% IOIP), the visual models demonstrated three possible multiphase mechanisms at work, namely, Darcy-type displacement until gas breakthrough, gravity drainage after breakthrough and film-drainage in gas-invaded zones throughout the duration of the process. The partially-scaled physical model was used in a series of experiments to study the effects of wettability, gas-oil miscibility, secondary versus tertiary mode gas injection, and the presence of fractures on GAGD oil recovery. In addition to yielding recoveries of up to 80% IOIP, even in the immiscible gas injection mode, the partially-scaled physical model confirmed the positive influence of fractures and oil-wet characteristics in enhancing oil recoveries over those measured in the homogeneous (unfractured) water-wet models. An interesting observation was that a single logarithmic relationship between the oil recovery and the gravity number was obeyed by the physical model, the high-pressure corefloods and the field data.« less

Outside-school physical activity participation and motivation in physical education.

PubMed

Shen, Bo

2014-03-01

Experience in non-school contexts can shape and reshape students' motivation and mediate their learning in school. Outside-school physical activity may provide students with an extensive cognitive and affective foundation and influence their motivation in physical education. Although a trans-contextual effect of physical education has been explored, very little empirical research has examined the impact from outside-school context to physical education. Using self-determination theory and a hierarchical model of motivation, this study was designed to examine the association between participation in organized outside-school physical activity programmes and self-determination process in physical education. Participants included 545 9th graders (305 males and 240 females, age range = 14-16 years, mean age = 14.66 years) enrolled in required physical education classes in three suburban high schools in a large Midwest metropolitan area in the United States. Self-determination variables were measured using relevant instruments, and information on organized outside-school physical activity experiences was gathered in a survey. Structural equation modelling analyses were conducted. Students who participated in organized outside-school physical activity programmes displayed overall higher motivation; however, the strength of associations among the self-determination variables (i.e., pathways from perceived autonomy support to relatedness, from autonomy to competence, and from self-determined motivation to in-class physical activity engagement) was stronger for their non-participant counterparts. There are dynamic relationships between participation in organized outside-school physical activity programmes and self-determination process in physical education. Physical educators need to identify, appreciate, and instructionally address individual students' differences during teaching and learning. © 2012 The British Psychological Society.

The need for sustained and integrated high-resolution mapping of dynamic coastal environments

USGS Publications Warehouse

Stockdon, Hilary F.; Lillycrop, Jeff W.; Howd, Peter A.; Wozencraft, Jennifer M.

2007-01-01

The evolution of the United States' coastal zone response to both human activities and natural processes is dynamic. Coastal resource and population protection requires understanding, in detail, the processes needed for change as well as the physical setting. Sustained coastal area mapping allows change to be documented and baseline conditions to be established, as well as future behavior to be predicted in conjunction with physical process models. Hyperspectral imagers and airborne lidars, as well as other recent mapping technology advances, allow rapid national scale land use information and high-resolution elevation data collection. Coastal hazard risk evaluation has critical dependence on these rich data sets. A fundamental storm surge model parameter in predicting flooding location, for example, is coastal elevation data, and a foundation in identifying the most vulnerable populations and resources is land use maps. A wealth of information for physical change process study, coastal resource and community management and protection, and coastal area hazard vulnerability determination, is available in a comprehensive national coastal mapping plan designed to take advantage of recent mapping technology progress and data distribution, management, and collection.

Theoretical study of hydrogen absorption-desorption on LaNi3.8Al1.2-xMnx using statistical physics treatment

NASA Astrophysics Data System (ADS)

Bouaziz, Nadia; Ben Manaa, Marwa; Ben Lamine, Abdelmottaleb

2017-11-01

The hydrogen absorption-desorption isotherms on LaNi3.8Al1.2-xMnx alloy at temperature T = 433 K is studied through various theoretical models. The analytical expressions of these models were deduced exploiting the grand canonical ensemble in statistical physics by taking some simplifying hypotheses. Among these models an adequate model which presents a good correlation with the experimental curves has been selected. The physicochemical parameters intervening in the absorption-desorption processes and involved in the model expressions could be directly deduced from the experimental isotherms by numerical simulation. Six parameters of the model are adjusted, namely the numbers of hydrogen atoms per site n1 and n2, the receptor site densities N1m and N2m, and the energetic parameters P1 and P2. The behaviors of these parameters are discussed in relation with absorption and desorption processes to better understand and compare these phenomena. Thanks to the energetic parameters, we calculated the sorption energies which are typically ranged between 266 and 269.4 KJ/mol for absorption process and between 267 and 269.5 KJ/mol for desorption process comparable to usual chemical bond energies. Using the adopted model expression, the thermodynamic potential functions which govern the absorption/desorption process such as internal energy Eint, free enthalpy of Gibbs G and entropy Sa are derived.

Advances in distributed watershed modeling: a review and application of the AgroEcoSystem-Watershed (AgES-W) model

USDA-ARS?s Scientific Manuscript database

Progress in the understanding of physical, chemical, and biological processes influencing water quality, coupled with advancements in the collection and analysis of hydrologic data, provide opportunities for significant innovations in the manner and level with which watershed-scale processes may be ...

WEPP Model applications for evaluations of best management practices

Treesearch

D. C. Flanagan; W. J. Elliott; J. R. Frankenberger; C. Huang

2010-01-01

The Water Erosion Prediction Project (WEPP) model is a process-based erosion prediction technology for application to small watersheds and hillslope profiles, under agricultural, forested, rangeland, and other land management conditions. Developed by the United States Department of Agriculture (USDA) over the past 25 years, WEPP simulates many of the physical processes...

Challenges and progress in distributed watershed modeling: applications of the AgroEcoSystem-Watershed (AgES-W) model

USDA-ARS?s Scientific Manuscript database

Progress in the understanding of physical, chemical, and biological processes influencing water quality, coupled with advances in the collection and analysis of hydrologic data, provide opportunities for significant innovations in the manner and level with which watershed-scale processes may be quan...

Integrated Modeling and Analysis of Physical Oceanographic and Acoustic Processes

DTIC Science & Technology

2015-09-30

goal is to improve ocean physical state and acoustic state predictive capabilities. The goal fitting the scope of this project is the creation of... Project -scale objectives are to complete targeted studies of oceanographic processes in a few regimes, accompanied by studies of acoustic propagation...by the basic research efforts of this project . An additional objective is to develop improved computational tools for acoustics and for the

Wolf Creek Research Basin Cold REgion Process Studies - 1992-2003

NASA Astrophysics Data System (ADS)

Janowicz, R.; Hedstrom, N.; Pomeroy, J.; Granger, R.; Carey, S.

2004-12-01

The development of hydrological models in northern regions are complicated by cold region processes. Sparse vegetation influences snowpack accumulation, redistribution and melt, frozen ground effects infiltration and runoff and cold soils in the summer effect evapotranspiration rates. Situated in the upper Yukon River watershed, the 195 km2 Wolf Creek Research Basin was instrumented in 1992 to calibrate hydrologic flow models, and has since evolved into a comprehensive study of cold region processes and linkages, contributing significantly to hydrological and climate change modelling. Studies include those of precipitation distribution, snowpack accumulation and redistribution, energy balance, snowmelt infiltration, and water balance. Studies of the spatial variability of hydrometeorological data demonstrate the importance of physical parameters on their distribution and control on runoff processes. Many studies have also identified the complex interaction of several of the physical parameters, including topography, vegetation and frozen ground (seasonal or permafrost) as important. They also show that there is a fundamental, underlying spatial structure to the watershed that must be adequately represented in parameterization schemes for scaling and watershed modelling. The specific results of numerous studies are presented.

Organizational Dimensions of Innovative Practice: A Qualitative Investigation of the Processes Supporting Innovation Adoption in Outpatient Physical Therapy Practice.

PubMed

Sabus, Carla; Spake, Ellen

2018-01-01

The ability to innovate and adapt practice is a requirement of the progressive healthcare provider. Innovative practice by rehabilitation providers has largely been approached as personal professional development; this study extends that perspective by examining innovation uptake from the organizational level. The varied professions can be expected to have distinct qualities of innovation adoption that reflect professional norms, values, and expectations. The purpose of this qualitative study was to describe the organizational processes of innovation uptake in outpatient physical therapy practice. Through nomination, two outpatient, privately owned physical therapy clinics were identified as innovation practices. Eighteen physical therapists, three owners, and a manager participated in the study. The two clinics served as case studies within a grounded theory approach. Data were collected through observation, unstructured questioning, work flow analysis, focus group sessions, and artifact analysis. Data were analyzed and coded among the investigators. A theoretical model of the innovation adoption process in outpatient physical therapy practice was developed. Elements of the model included (1) change grounded in relationship-centered care, (2) clinic readiness to accept change, and (3) clinic adaptability and resilience. A social paradigm of innovation adoption informed through this research complements the concentration on personal professional development.

Randomized Trial of a Lifestyle Physical Activity Intervention for Breast Cancer Survivors: Effects on Transtheoretical Model Variables.

PubMed

Scruggs, Stacie; Mama, Scherezade K; Carmack, Cindy L; Douglas, Tommy; Diamond, Pamela; Basen-Engquist, Karen

2018-01-01

This study examined whether a physical activity intervention affects transtheoretical model (TTM) variables that facilitate exercise adoption in breast cancer survivors. Sixty sedentary breast cancer survivors were randomized to a 6-month lifestyle physical activity intervention or standard care. TTM variables that have been shown to facilitate exercise adoption and progress through the stages of change, including self-efficacy, decisional balance, and processes of change, were measured at baseline, 3 months, and 6 months. Differences in TTM variables between groups were tested using repeated measures analysis of variance. The intervention group had significantly higher self-efficacy ( F = 9.55, p = .003) and perceived significantly fewer cons of exercise ( F = 5.416, p = .025) at 3 and 6 months compared with the standard care group. Self-liberation, counterconditioning, and reinforcement management processes of change increased significantly from baseline to 6 months in the intervention group, and self-efficacy and reinforcement management were significantly associated with improvement in stage of change. The stage-based physical activity intervention increased use of select processes of change, improved self-efficacy, decreased perceptions of the cons of exercise, and helped participants advance in stage of change. These results point to the importance of using a theory-based approach in interventions to increase physical activity in cancer survivors.

Linking Local Scale Ecosystem Science to Regional Scale Management

NASA Astrophysics Data System (ADS)

Shope, C. L.; Tenhunen, J.; Peiffer, S.

2012-04-01

Ecosystem management with respect to sufficient water yield, a quality water supply, habitat and biodiversity conservation, and climate change effects requires substantial observational data at a range of scales. Complex interactions of local physical processes oftentimes vary over space and time, particularly in locations with extreme meteorological conditions. Modifications to local conditions (ie: agricultural land use changes, nutrient additions, landscape management, water usage) can further affect regional ecosystem services. The international, inter-disciplinary TERRECO research group is intensively investigating a variety of local processes, parameters, and conditions to link complex physical, economic, and social interactions at the regional scale. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. The data are used to parameterize suite of models describing local to landscape level water, sediment, nutrient, and monetary relationships. We focus on using the agricultural and hydrological SWAT model to synthesize the experimental field data and local-scale models throughout the catchment. The approach of our study was to describe local scientific processes, link potential interrelationships between different processes, and predict environmentally efficient management efforts. The Haean catchment case study shows how research can be structured to provide cross-disciplinary scientific linkages describing complex ecosystems and landscapes that can be used for regional management evaluations and predictions.

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.

Microfluidic Experiments Studying Pore Scale Interactions of Microbes and Geochemistry

NASA Astrophysics Data System (ADS)

Chen, M.; Kocar, B. D.

2016-12-01

Understanding how physical phenomena, chemical reactions, and microbial behavior interact at the pore-scale is crucial to understanding larger scale trends in groundwater chemistry. Recent studies illustrate the utility of microfluidic devices for illuminating pore-scale physical-biogeochemical processes and their control(s) on the cycling of iron, uranium, and other important elements 1-3. These experimental systems are ideal for examining geochemical reactions mediated by microbes, which include processes governed by complex biological phenomenon (e.g. biofilm formation, etc.)4. We present results of microfluidic experiments using a model metal reducing bacteria and varying pore geometries, exploring the limitations of the microorganisms' ability to access tight pore spaces, and examining coupled biogeochemical-physical controls on the cycling of redox sensitive metals. Experimental results will provide an enhanced understanding of coupled physical-biogeochemical processes transpiring at the pore-scale, and will constrain and compliment continuum models used to predict and describe the subsurface cycling of redox-sensitive elements5. 1. Vrionis, H. A. et al. Microbiological and geochemical heterogeneity in an in situ uranium bioremediation field site. Appl. Environ. Microbiol. 71, 6308-6318 (2005). 2. Pearce, C. I. et al. Pore-scale characterization of biogeochemical controls on iron and uranium speciation under flow conditions. Environ. Sci. Technol. 46, 7992-8000 (2012). 3. Zhang, C., Liu, C. & Shi, Z. Micromodel investigation of transport effect on the kinetics of reductive dissolution of hematite. Environ. Sci. Technol. 47, 4131-4139 (2013). 4. Ginn, T. R. et al. Processes in microbial transport in the natural subsurface. Adv. Water Resour. 25, 1017-1042 (2002). 5. Scheibe, T. D. et al. Coupling a genome-scale metabolic model with a reactive transport model to describe in situ uranium bioremediation. Microb. Biotechnol. 2, 274-286 (2009).

Cascade process modeling with mechanism-based hierarchical neural networks.

PubMed

Cong, Qiumei; Yu, Wen; Chai, Tianyou

2010-02-01

Cascade process, such as wastewater treatment plant, includes many nonlinear sub-systems and many variables. When the number of sub-systems is big, the input-output relation in the first block and the last block cannot represent the whole process. In this paper we use two techniques to overcome the above problem. Firstly we propose a new neural model: hierarchical neural networks to identify the cascade process; then we use serial structural mechanism model based on the physical equations to connect with neural model. A stable learning algorithm and theoretical analysis are given. Finally, this method is used to model a wastewater treatment plant. Real operational data of wastewater treatment plant is applied to illustrate the modeling approach.

Application of the Transtheoretical Model of behavior change to the physical activity behavior of WIC mothers.

PubMed

Fahrenwald, Nancy L; Walker, Susan Noble

2003-01-01

This descriptive-correlational study examined the Transtheoretical Model (TTM) of behavior change in relationship to the physical activity behavior of mothers receiving assistance from the Women, Infants, and Children program. A purposive sample (N = 30) of six women at each of the five stages of readiness for behavior change was used. Relationships between stage of behavior change (measured using the Stage of Exercise Adoption tool) and other TTM constructs were examined. The constructs and corresponding instruments included physical activity behavior (Seven-Day Physical Activity Recall), pros, cons, decisional balance (Exercise Benefits/Barriers Scale and two open-ended questions), self-efficacy (Self-efficacy for Exercise scale), and processes of behavior change (Processes of Exercise Adoption tool and the Social Support for Exercise scale). Significant relationships were found between stage of behavior change and two physical activity energy expenditure indices (rs = 0.71-0.73, p < 0.01), daily minutes of moderate to very hard physical activity (rs = 0.81, p < 0.01), pros (rs = 0.56, p < 0.01), cons (rs = -0.52, p < 0.05), decisional balance (rs = 0.56, p < 0.01), and self-efficacy (rs = 0.56, p < 0.01). Use of the 10 processes of change differed by stage of change. Pros to physical activity included a sense of accomplishment, increased strength, stress relief, and getting in shape after pregnancy. Cons included fatigue, childcare, and cold weather. Results support the TTM as relevant to WIC mothers and suggest strategies to increase physical activity in this population.

Experimental constraints from flavour changing processes and physics beyond the Standard Model.

PubMed

Gersabeck, M; Gligorov, V V; Serra, N

Flavour physics has a long tradition of paving the way for direct discoveries of new particles and interactions. Results over the last decade have placed stringent bounds on the parameter space of physics beyond the Standard Model. Early results from the LHC, and its dedicated flavour factory LHCb, have further tightened these constraints and reiterate the ongoing relevance of flavour studies. The experimental status of flavour observables in the charm and beauty sectors is reviewed in measurements of CP violation, neutral meson mixing, and measurements of rare decays.

Temporal and Location Based RFID Event Data Management and Processing

NASA Astrophysics Data System (ADS)

Wang, Fusheng; Liu, Peiya

Advance of sensor and RFID technology provides significant new power for humans to sense, understand and manage the world. RFID provides fast data collection with precise identification of objects with unique IDs without line of sight, thus it can be used for identifying, locating, tracking and monitoring physical objects. Despite these benefits, RFID poses many challenges for data processing and management. RFID data are temporal and history oriented, multi-dimensional, and carrying implicit semantics. Moreover, RFID applications are heterogeneous. RFID data management or data warehouse systems need to support generic and expressive data modeling for tracking and monitoring physical objects, and provide automated data interpretation and processing. We develop a powerful temporal and location oriented data model for modeling and queryingRFID data, and a declarative event and rule based framework for automated complex RFID event processing. The approach is general and can be easily adapted for different RFID-enabled applications, thus significantly reduces the cost of RFID data integration.

Incorporating seismic observations into 2D conduit flow modeling

NASA Astrophysics Data System (ADS)

Collier, L.; Neuberg, J.

2006-04-01

Conduit flow modeling aims to understand the conditions of magma at depth, and to provide insight into the physical processes that occur inside the volcano. Low-frequency events, characteristic to many volcanoes, are thought to contain information on the state of magma at depth. Therefore, by incorporating information from low-frequency seismic analysis into conduit flow modeling a greater understanding of magma ascent and its interdependence on magma conditions and physical processes is possible. The 2D conduit flow model developed in this study demonstrates the importance of lateral pressure and parameter variations on overall magma flow dynamics, and the substantial effect bubbles have on magma shear viscosity and on magma ascent. The 2D nature of the conduit flow model developed here allows in depth investigation into processes which occur at, or close to the wall, such as magma cooling and brittle failure of melt. These processes are shown to have a significant effect on magma properties and therefore, on flow dynamics. By incorporating low-frequency seismic information, an advanced conduit flow model is developed including the consequences of brittle failure of melt, namely friction-controlled slip and gas loss. This model focuses on the properties and behaviour of magma at depth within the volcano, and their interaction with the formation of seismic events by brittle failure of melt.

The Global Modeling Test Bed - Building a New National Capability for Advancing Operational Global Modeling in the United States.

NASA Astrophysics Data System (ADS)

Toepfer, F.; Cortinas, J. V., Jr.; Kuo, W.; Tallapragada, V.; Stajner, I.; Nance, L. B.; Kelleher, K. E.; Firl, G.; Bernardet, L.

2017-12-01

NOAA develops, operates, and maintains an operational global modeling capability for weather, sub seasonal and seasonal prediction for the protection of life and property and fostering the US economy. In order to substantially improve the overall performance and accelerate advancements of the operational modeling suite, NOAA is partnering with NCAR to design and build the Global Modeling Test Bed (GMTB). The GMTB has been established to provide a platform and a capability for researchers to contribute to the advancement primarily through the development of physical parameterizations needed to improve operational NWP. The strategy to achieve this goal relies on effectively leveraging global expertise through a modern collaborative software development framework. This framework consists of a repository of vetted and supported physical parameterizations known as the Common Community Physics Package (CCPP), a common well-documented interface known as the Interoperable Physics Driver (IPD) for combining schemes into suites and for their configuration and connection to dynamic cores, and an open evidence-based governance process for managing the development and evolution of CCPP. In addition, a physics test harness designed to work within this framework has been established in order to facilitate easier like-to-like comparison of physics advancements. This paper will present an overview of the design of the CCPP and test platform. Additionally, an overview of potential new opportunities of how physics developers can engage in the process, from implementing code for CCPP/IPD compliance to testing their development within an operational-like software environment, will be presented. In addition, insight will be given as to how development gets elevated to CPPP-supported status, the pre-cursor to broad availability and use within operational NWP. An overview of how the GMTB can be expanded to support other global or regional modeling capabilities will also be presented.

Parameterization guidelines and considerations for hydrologic models

Treesearch

 R. W. Malone; G. Yagow; C. Baffaut; M.W  Gitau; Z. Qi; Devendra Amatya; P.B.   Parajuli; J.V. Bonta; T.R.  Green

2015-01-01

 Imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application (i.e., parameterization) are important and difficult tasks. An exponential...

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.

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.

Efficient calibration for imperfect computer models

DOE PAGES

Tuo, Rui; Wu, C. F. Jeff

2015-12-01

Many computer models contain unknown parameters which need to be estimated using physical observations. Furthermore, the calibration method based on Gaussian process models may lead to unreasonable estimate for imperfect computer models. In this work, we extend their study to calibration problems with stochastic physical data. We propose a novel method, called the L 2 calibration, and show its semiparametric efficiency. The conventional method of the ordinary least squares is also studied. Theoretical analysis shows that it is consistent but not efficient. Here, numerical examples show that the proposed method outperforms the existing ones.

Reflection processing of the large-N seismic data from the Source Physics Experiment (SPE)

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

Paschall, Olivia C.

2016-07-18

The purpose of the SPE is to develop a more physics-based model for nuclear explosion identification to understand the development of S-waves from explosion sources in order to enhance nuclear test ban treaty monitoring.

Exploring Flavor Physics with Lattice QCD

NASA Astrophysics Data System (ADS)

Du, Daping; Fermilab/MILC Collaborations Collaboration

2016-03-01

The Standard Model has been a very good description of the subatomic particle physics. In the search for physics beyond the Standard Model in the context of flavor physics, it is important to sharpen our probes using some gold-plated processes (such as B rare decays), which requires the knowledge of the input parameters, such as the Cabibbo-Kobayashi-Maskawa (CKM) matrix elements and other nonperturbative quantities, with sufficient precision. Lattice QCD is so far the only first-principle method which could compute these quantities with competitive and systematically improvable precision using the state of the art simulation techniques. I will discuss the recent progress of lattice QCD calculations on some of these nonpurturbative quantities and their applications in flavor physics. I will also discuss the implications and future perspectives of these calculations in flavor physics.

Process-oriented Observational Metrics for CMIP6 Climate Model Assessments

NASA Astrophysics Data System (ADS)

Jiang, J. H.; Su, H.

2016-12-01

Observational metrics based on satellite observations have been developed and effectively applied during post-CMIP5 model evaluation and improvement projects. As new physics and parameterizations continue to be included in models for the upcoming CMIP6, it is important to continue objective comparisons between observations and model results. This talk will summarize the process-oriented observational metrics and methodologies for constraining climate models with A-Train satellite observations and support CMIP6 model assessments. We target parameters and processes related to atmospheric clouds and water vapor, which are critically important for Earth's radiative budget, climate feedbacks, and water and energy cycles, and thus reduce uncertainties in climate models.

Testing Theory of Planned Behavior and Neo-Socioanalytic Theory models of trait activity, industriousness, exercise social cognitions, exercise intentions, and physical activity in a representative U.S. sample.

PubMed

Vo, Phuong T; Bogg, Tim

2015-01-01

Prior research identified assorted relations between trait and social cognition models of personality and engagement in physical activity. Using a representative U.S. sample (N = 957), the goal of the present study was to test two alternative structural models of the relationships among the extraversion-related facet of activity, the conscientiousness-related facet of industriousness, social cognitions from the Theory of Planned Behavior (perceived behavioral control, affective attitudes, subjective norms, intentions), Social Cognitive Theory (self-efficacy, outcome expectancies), and the Transtheoretical Model (behavioral processes of change), and engagement in physical activity. Path analyses with bootstrapping procedures were used to model direct and indirect effects of trait and social cognition constructs on physical activity through two distinct frameworks - the Theory of Planned Behavior and Neo-Socioanalytic Theory. While both models showed good internal fit, comparative model information criteria showed the Theory-of-Planned-Behavior-informed model provided a better fit. In the model, social cognitions fully mediated the relationships from the activity facet and industriousness to intentions for and engagement in physical activity, such that the relationships were primarily maintained by positive affective evaluations, positive expected outcomes, and confidence in overcoming barriers related to physical activity engagement. The resultant model - termed the Disposition-Belief-Motivation model- is proposed as a useful framework for organizing and integrating personality trait facets and social cognitions from various theoretical perspectives to investigate the expression of health-related behaviors, such as physical activity. Moreover, the results are discussed in terms of extending the application of the Disposition-Belief-Motivation model to longitudinal and intervention designs for physical activity engagement.

A generic biogeochemical module for Earth system models: Next Generation BioGeoChemical Module (NGBGC), version 1.0

NASA Astrophysics Data System (ADS)

Fang, Y.; Huang, M.; Liu, C.; Li, H.; Leung, L. R.

2013-11-01

Physical and biogeochemical processes regulate soil carbon dynamics and CO2 flux to and from the atmosphere, influencing global climate changes. Integration of these processes into Earth system models (e.g., community land models (CLMs)), however, currently faces three major challenges: (1) extensive efforts are required to modify modeling structures and to rewrite computer programs to incorporate new or updated processes as new knowledge is being generated, (2) computational cost is prohibitively expensive to simulate biogeochemical processes in land models due to large variations in the rates of biogeochemical processes, and (3) various mathematical representations of biogeochemical processes exist to incorporate different aspects of fundamental mechanisms, but systematic evaluation of the different mathematical representations is difficult, if not impossible. To address these challenges, we propose a new computational framework to easily incorporate physical and biogeochemical processes into land models. The new framework consists of a new biogeochemical module, Next Generation BioGeoChemical Module (NGBGC), version 1.0, with a generic algorithm and reaction database so that new and updated processes can be incorporated into land models without the need to manually set up the ordinary differential equations to be solved numerically. The reaction database consists of processes of nutrient flow through the terrestrial ecosystems in plants, litter, and soil. This framework facilitates effective comparison studies of biogeochemical cycles in an ecosystem using different conceptual models under the same land modeling framework. The approach was first implemented in CLM and benchmarked against simulations from the original CLM-CN code. A case study was then provided to demonstrate the advantages of using the new approach to incorporate a phosphorus cycle into CLM. To our knowledge, the phosphorus-incorporated CLM is a new model that can be used to simulate phosphorus limitation on the productivity of terrestrial ecosystems. The method presented here could in theory be applied to simulate biogeochemical cycles in other Earth system models.

Psychological Pathways Linking Social Support to Health Outcomes: A Visit with the “Ghosts” of Research Past, Present, and Future

PubMed Central

Uchino, Bert N.; Bowen, Kimberly; Carlisle, McKenzie; Birmingham, Wendy

2012-01-01

Contemporary models postulate the importance of psychological mechanisms linking perceived and received social support to physical health outcomes. In this review, we examine studies that directly tested the potential psychological mechanisms responsible for links between social support and health-relevant physiological processes (1980s to 2010). Inconsistent with existing theoretical models, no evidence was found that psychological mechanisms such as depression, perceived stress, and other affective processes are directly responsible for links between support and health. We discuss the importance of considering statistical/design issues, emerging conceptual perspectives, and limitations of our existing models for future research aimed at elucidating the psychological mechanisms responsible for links between social support and physical health outcomes. PMID:22326104

MT+, integrating magnetotellurics to determine earth structure, physical state, and processes

USGS Publications Warehouse

Bedrosian, P.A.

2007-01-01

As one of the few deep-earth imaging techniques, magnetotellurics provides information on both the structure and physical state of the crust and upper mantle. Magnetotellurics is sensitive to electrical conductivity, which varies within the earth by many orders of magnitude and is modified by a range of earth processes. As with all geophysical techniques, magnetotellurics has a non-unique inverse problem and has limitations in resolution and sensitivity. As such, an integrated approach, either via the joint interpretation of independent geophysical models, or through the simultaneous inversion of independent data sets is valuable, and at times essential to an accurate interpretation. Magnetotelluric data and models are increasingly integrated with geological, geophysical and geochemical information. This review considers recent studies that illustrate the ways in which such information is combined, from qualitative comparisons to statistical correlation studies to multi-property inversions. Also emphasized are the range of problems addressed by these integrated approaches, and their value in elucidating earth structure, physical state, and processes. ?? Springer Science+Business Media B.V. 2007.

Improving atomic displacement and replacement calculations with physically realistic damage models

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

Nordlund, Kai; Zinkle, Steven J.; Sand, Andrea E.

Atomic collision processes are fundamental to numerous advanced materials technologies such as electron microscopy, semiconductor processing and nuclear power generation. Extensive experimental and computer simulation studies over the past several decades provide the physical basis for understanding the atomic-scale processes occurring during primary displacement events. The current international standard for quantifying this energetic particle damage, the Norgett-Robinson-Torrens displacements per atom (NRT-dpa) model, has nowadays several well-known limitations. In particular, the number of radiation defects produced in energetic cascades in metals is only ~1/3 the NRT-dpa prediction, while the number of atoms involved in atomic mixing is about a factor ofmore » 30 larger than the dpa value. Here we propose two new complementary displacement production estimators (athermal recombination corrected dpa, arc-dpa) and atomic mixing (replacements per atom, rpa) functions that extend the NRT-dpa by providing more physically realistic descriptions of primary defect creation in materials and may become additional standard measures for radiation damage quantification.« less

Improving atomic displacement and replacement calculations with physically realistic damage models

DOE PAGES

Nordlund, Kai; Zinkle, Steven J.; Sand, Andrea E.; ...

2018-03-14

Atomic collision processes are fundamental to numerous advanced materials technologies such as electron microscopy, semiconductor processing and nuclear power generation. Extensive experimental and computer simulation studies over the past several decades provide the physical basis for understanding the atomic-scale processes occurring during primary displacement events. The current international standard for quantifying this energetic particle damage, the Norgett-Robinson-Torrens displacements per atom (NRT-dpa) model, has nowadays several well-known limitations. In particular, the number of radiation defects produced in energetic cascades in metals is only ~1/3 the NRT-dpa prediction, while the number of atoms involved in atomic mixing is about a factor ofmore » 30 larger than the dpa value. Here we propose two new complementary displacement production estimators (athermal recombination corrected dpa, arc-dpa) and atomic mixing (replacements per atom, rpa) functions that extend the NRT-dpa by providing more physically realistic descriptions of primary defect creation in materials and may become additional standard measures for radiation damage quantification.« less

Improving atomic displacement and replacement calculations with physically realistic damage models.

PubMed

Nordlund, Kai; Zinkle, Steven J; Sand, Andrea E; Granberg, Fredric; Averback, Robert S; Stoller, Roger; Suzudo, Tomoaki; Malerba, Lorenzo; Banhart, Florian; Weber, William J; Willaime, Francois; Dudarev, Sergei L; Simeone, David

2018-03-14

Atomic collision processes are fundamental to numerous advanced materials technologies such as electron microscopy, semiconductor processing and nuclear power generation. Extensive experimental and computer simulation studies over the past several decades provide the physical basis for understanding the atomic-scale processes occurring during primary displacement events. The current international standard for quantifying this energetic particle damage, the Norgett-Robinson-Torrens displacements per atom (NRT-dpa) model, has nowadays several well-known limitations. In particular, the number of radiation defects produced in energetic cascades in metals is only ~1/3 the NRT-dpa prediction, while the number of atoms involved in atomic mixing is about a factor of 30 larger than the dpa value. Here we propose two new complementary displacement production estimators (athermal recombination corrected dpa, arc-dpa) and atomic mixing (replacements per atom, rpa) functions that extend the NRT-dpa by providing more physically realistic descriptions of primary defect creation in materials and may become additional standard measures for radiation damage quantification.

From Random Walks to Brownian Motion, from Diffusion to Entropy: Statistical Principles in Introductory Physics

NASA Astrophysics Data System (ADS)

Reeves, Mark

2014-03-01

Entropy changes underlie the physics that dominates biological interactions. Indeed, introductory biology courses often begin with an exploration of the qualities of water that are important to living systems. However, one idea that is not explicitly addressed in most introductory physics or biology textbooks is dominant contribution of the entropy in driving important biological processes towards equilibrium. From diffusion to cell-membrane formation, to electrostatic binding in protein folding, to the functioning of nerve cells, entropic effects often act to counterbalance deterministic forces such as electrostatic attraction and in so doing, allow for effective molecular signaling. A small group of biology, biophysics and computer science faculty have worked together for the past five years to develop curricular modules (based on SCALEUP pedagogy) that enable students to create models of stochastic and deterministic processes. Our students are first-year engineering and science students in the calculus-based physics course and they are not expected to know biology beyond the high-school level. In our class, they learn to reduce seemingly complex biological processes and structures to be described by tractable models that include deterministic processes and simple probabilistic inference. The students test these models in simulations and in laboratory experiments that are biologically relevant. The students are challenged to bridge the gap between statistical parameterization of their data (mean and standard deviation) and simple model-building by inference. This allows the students to quantitatively describe realistic cellular processes such as diffusion, ionic transport, and ligand-receptor binding. Moreover, the students confront ``random'' forces and traditional forces in problems, simulations, and in laboratory exploration throughout the year-long course as they move from traditional kinematics through thermodynamics to electrostatic interactions. This talk will present a number of these exercises, with particular focus on the hands-on experiments done by the students, and will give examples of the tangible material that our students work with throughout the two-semester sequence of their course on introductory physics with a bio focus. Supported by NSF DUE.

Functional correlation approach to operational risk in banking organizations

NASA Astrophysics Data System (ADS)

Kühn, Reimer; Neu, Peter

2003-05-01

A Value-at-Risk-based model is proposed to compute the adequate equity capital necessary to cover potential losses due to operational risks, such as human and system process failures, in banking organizations. Exploring the analogy to a lattice gas model from physics, correlations between sequential failures are modeled by as functionally defined, heterogeneous couplings between mutually supportive processes. In contrast to traditional risk models for market and credit risk, where correlations are described as equal-time-correlations by a covariance matrix, the dynamics of the model shows collective phenomena such as bursts and avalanches of process failures.

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

Tuo, Rui; Wu, C. F. Jeff

Many computer models contain unknown parameters which need to be estimated using physical observations. Furthermore, the calibration method based on Gaussian process models may lead to unreasonable estimate for imperfect computer models. In this work, we extend their study to calibration problems with stochastic physical data. We propose a novel method, called the L 2 calibration, and show its semiparametric efficiency. The conventional method of the ordinary least squares is also studied. Theoretical analysis shows that it is consistent but not efficient. Here, numerical examples show that the proposed method outperforms the existing ones.

How conduit models can be used to interpret volcano monitoring data

NASA Astrophysics Data System (ADS)

Thomas, M. E.; Neuberg, J. W.; Karl, S.; Collinson, A.; Pascal, K.

2012-04-01

During the last decade there have been major advances in the field of volcano monitoring, but to be able to take full advantage of these advances it is vital to link the monitoring data with the physical processes that give rise to the recorded signals. To obtain a better understanding of these physical processes it is necessary to understand the conditions of the system at depth. This can be achieved through numerical modelling. We present the results of conduit models representative of a silicic volcanic system and demonstrate how processes identified and interpreted from these models may manifest in the recorded monitoring data. Links are drawn to seismicity, deformation, and gas emissions. A key point is how these data compliment each other, and through utilising conduit models we are able to interpret how these different data may be recorded in response to a particular process. This is an invaluable tool as it is far easier to draw firm conclusions on what is happening at a volcano if there are several different data sets that suggest the same processes are occurring. Some of these interpretations appear useful in forecasting potentially catastrophic changes in eruptive behaviour, such as a dome collapse leading to violent explosive behaviour, and the role of monitoring data in this capacity will also be addressed.

A Self-Critique of Self-Organized Criticality in Astrophysics

NASA Astrophysics Data System (ADS)

Aschwanden, Markus J.

2015-08-01

The concept of ``self-organized criticality'' (SOC) was originally proposed as an explanation of 1/f-noise by Bak, Tang, and Wiesenfeld (1987), but turned out to have a far broader significance for scale-free nonlinear energy dissipation processes occurring in the entire universe. Over the last 30 years, an inspiring cross-fertilization from complexity theory to solar and astrophysics took place, where the SOC concept was initially applied to solar flares, stellar flares, and magnetospheric substorms, and later extended to the radiation belt, the heliosphere, lunar craters, the asteroid belt, the Saturn ring, pulsar glitches, soft X-ray repeaters, blazars, black-hole objects, cosmic rays, and boson clouds. The application of SOC concepts has been performed by numerical cellular automaton simulations, by analytical calculations of statistical (powerlaw-like) distributions based on physical scaling laws, and by observational tests of theoretically predicted size distributions and waiting time distributions. Attempts have been undertaken to import physical models into numerical SOC toy models. The novel applications stimulated also vigorous debates about the discrimination between SOC-related and non-SOC processes, such as phase transitions, turbulence, random-walk diffusion, percolation, branching processes, network theory, chaos theory, fractality, multi-scale, and other complexity phenomena. We review SOC models applied to astrophysical observations, attempt to describe what physics can be captured by SOC models, and offer a critique of weaknesses and strengths in existing SOC models.

A Self-Critique of Self-Organized Criticality in Astrophysics

NASA Astrophysics Data System (ADS)

Aschwanden, Markus J.

The concept of ``self-organized criticality'' (SOC) was originally proposed as an explanation of 1/f-noise by Bak, Tang, and Wiesenfeld (1987), but turned out to have a far broader significance for scale-free nonlinear energy dissipation processes occurring in the entire universe. Over the last 30 years, an inspiring cross-fertilization from complexity theory to solar and astrophysics took place, where the SOC concept was initially applied to solar flares, stellar flares, and magnetospheric substorms, and later extended to the radiation belt, the heliosphere, lunar craters, the asteroid belt, the Saturn ring, pulsar glitches, soft X-ray repeaters, blazars, black-hole objects, cosmic rays, and boson clouds. The application of SOC concepts has been performed by numerical cellular automaton simulations, by analytical calculations of statistical (powerlaw-like) distributions based on physical scaling laws, and by observational tests of theoretically predicted size distributions and waiting time distributions. Attempts have been undertaken to import physical models into numerical SOC toy models. The novel applications stimulated also vigorous debates about the discrimination between SOC-related and non-SOC processes, such as phase transitions, turbulence, random-walk diffusion, percolation, branching processes, network theory, chaos theory, fractality, multi-scale, and other complexity phenomena. We review SOC models applied to astrophysical observations, attempt to describe what physics can be captured by SOC models, and offer a critique of weaknesses and strengths in existing SOC models.

Testing principle working mechanisms of the health action process approach for subjective physical age groups.

PubMed

Wienert, Julian; Kuhlmann, Tim; Fink, Sebastian; Hambrecht, Rainer; Lippke, Sonia

2016-01-01

This study investigated differences in social-cognitive predictors and self-regulatory planning, as proposed by the health action process approach (HAPA), across three different subjective physical age groups for physical activity. With a cross-sectional design, 521 participants across the chronological age span from 25 to 86 years (M = 48.79; SD = 12.66) were separated into three groups: those who feel physically younger than they are in terms of chronological age, the same perceived and chronological age, and feeling physically older compared to their chronological age. Participants were assessed regarding their perceived vulnerability, outcome expectancies, general intentions, planning, self-efficacy, and stages of physical activity (non-intenders, intenders, and actors). Data were analysed via mean comparison and multigroup structural equation modelling. Mean differences for all but one construct were eminent in all groups, generally showing that those feeling physically younger also report better social-cognitive predictors of physical activity (e.g. lower perceived vulnerability) in comparison to those who feel the same age or older. The model showed that basic working mechanisms of the HAPA can be applied to all groups. With that, the results provide for the first time evidence that principle working mechanism of the HAPA can be applied to all subjective physical age groups. These may be used to tailor health promoting interventions according to participants' needs as a more suitable proxy than chronological age.

Predicting Physical Activity-Related Outcomes in Overweight and Obese Adults: A Health Action Process Approach.

PubMed

Hattar, Anne; Pal, Sebely; Hagger, Martin S

2016-03-01

We tested the adequacy of a model based on the Health Action Process Approach (HAPA) in predicting changes in psychological, body composition, and cardiovascular risk outcomes with respect to physical activity participation in overweight and obese adults. Measures of HAPA constructs (action and maintenance self-efficacy, outcome expectancies, action planning, risk perceptions, intentions, behaviour), psychological outcomes (quality of life, depression, anxiety, stress symptoms), body composition variables (body weight, body fat mass), cardiovascular risk measures (total cholesterol, low density lipoprotein), and self-reported physical activity behaviour were administered to participants (N = 74) at baseline, and 6 and 12 weeks later. Data were analysed using variance-based structural equation modelling with residualised change scores for HAPA variables. The model revealed effects of action self-efficacy and outcome expectancies on physical activity intentions, action self-efficacy on maintenance self-efficacy, and maintenance self-efficacy and intentions on action planning. Intention predicted psychological and body composition outcomes indirectly through physical activity behaviour. Action planning was a direct predictor of psychological, cardiovascular, and body composition outcomes. Data supported HAPA hypotheses in relation to intentions and behaviour, but not the role of action planning as a mediator of the intention-behaviour relationship. Action planning predicted outcomes independent of intentions and behaviour. © 2016 The International Association of Applied Psychology.

Advantages and Challenges of Using Physics Curricula as a Model for Reforming an Undergraduate Biology Course

PubMed Central

Donovan, D. A.; Atkins, L. J.; Salter, I. Y.; Gallagher, D. J.; Kratz, R. F.; Rousseau, J. V.; Nelson, G. D.

2013-01-01

We report on the development of a life sciences curriculum, targeted to undergraduate students, which was modeled after a commercially available physics curriculum and based on aspects of how people learn. Our paper describes the collaborative development process and necessary modifications required to apply a physics pedagogical model in a life sciences context. While some approaches were easily adapted, others provided significant challenges. Among these challenges were: representations of energy, introducing definitions, the placement of Scientists’ Ideas, and the replicability of data. In modifying the curriculum to address these challenges, we have come to see them as speaking to deeper differences between the disciplines, namely that introductory physics—for example, Newton's laws, magnetism, light—is a science of pairwise interaction, while introductory biology—for example, photosynthesis, evolution, cycling of matter in ecosystems—is a science of linked processes, and we suggest that this is how the two disciplines are presented in introductory classes. We illustrate this tension through an analysis of our adaptations of the physics curriculum for instruction on the cycling of matter and energy; we show that modifications of the physics curriculum to address the biological framework promotes strong gains in student understanding of these topics, as evidenced by analysis of student work. PMID:23737629

Modelling episodic acidification of surface waters: the state of science.

PubMed

Eshleman, K N; Wigington, P J; Davies, T D; Tranter, M

1992-01-01

Field studies of chemical changes in surface waters associated with rainfall and snowmelt events have provided evidence of episodic acidification of lakes and streams in Europe and North America. Modelling these chemical changes is particularly challenging because of the variability associated with hydrological transport and chemical transformation processes in catchments. This paper provides a review of mathematical models that have been applied to the problem of episodic acidification. Several empirical approaches, including regression models, mixing models and time series models, support a strong hydrological interpretation of episodic acidification. Regional application of several models has suggested that acidic episodes (in which the acid neutralizing capacity becomes negative) are relatively common in surface waters in several regions of the US that receive acid deposition. Results from physically based models have suggested a lack of understanding of hydrological flowpaths, hydraulic residence times and biogeochemical reactions, particularly those involving aluminum. The ability to better predict episodic chemical responses of surface waters is thus dependent upon elucidation of these and other physical and chemical processes.

Preface

NASA Astrophysics Data System (ADS)

Jakovics, A.

2007-06-01

The International Scientific Colloquium "Modelling for Material Processing" took place last year on June 8-9. It was the fourth time the colloquium was organized. The first colloquium took place in 1999. All colloquia were organized by the University of Latvia together with Leibniz University of Hannover (Germany) that signifies a long-term tradition (since 1988) of scientific cooperation between researchers of these two universities in the field of electrothermal process modelling. During the last colloquium scientific reports in the field of mathematical modelling in industrial electromagnetic applications for different materials (liquid metals, semiconductor technology, porous materials, melting of oxides and inductive heating) were presented. 70 researchers from 10 countries attended the colloquium. The contributions included about 30 oral presentations and 12 posters. The most illustrative presentations (oral and poster) in the field of MHD were selected for publication in a special issue of the international journal "Magnetohydrodynamics". Traditionally, many reports of the colloquium discuss the problems of MHD methods and devices applied to the metallurgical technologies and processes of semiconductor crystal growth. The new results illustrate the influence of combined electromagnetic fields on the hydrodynamics and heat/mass transfer in melts. The presented reports demonstrate that the models for simulation of turbulent liquid metal flows in melting furnaces, crystallization of alloys and single crystal growth in electromagnetic fields have become much more complex. The adequate description of occurring physical phenomena and the use of high performance computer and clusters allow to reduce the number of experiments in industrial facilities. The use of software and computers for modelling technological and environmental processes has a very long history at the University of Latvia. The first modelling activities in the field of industrial MHD applications had led to the establishment of the chair of Electrodynamics and Continuum Mechanics in 1970, the first head of which was professor Juris Mikelsons. In the early 90's, when all research institutions in our country underwent dramatic changes, not all research directions and institutions managed to adapt successfully to the new conditions. Fortunately, the people who were involved in computer modelling of physical processes were among the most successful. First, the existing and newly established contacts in Western Europe were used actively to reorient the applied researches in the directions actively studied at the universities and companies, which were the partners of the University of Latvia. As a result, research groups involved in these activities successfully joined the international effort related to the application of computer models to industrial processes, and the scientific laboratory for Mathematical Modelling of Environmental and Technological Processes was founded in 1994. The second direction of modelling development was related to the application of computer-based models for the environmental and technological processes (e.g., sediment transport in harbours, heat transfer in building constructions) that were important for the companies and state institutions in Latvia. Currently, the field of engineering physics, the core of which is the computer modelling of technological and environmental processes, is one of the largest and most successfully developing parts of researches and educational programs at the Department of Physics of the University of Latvia with very good perspectives in the future for the development of new technologies and knowledge transfer.

Laser powder bed fusion additive manufacturing of metals; physics, computational, and materials challenges

DOE PAGES

King, W. E.; Anderson, A. T.; Ferencz, R. M.; ...

2015-12-29

The production of metal parts via laser powder bed fusion additive manufacturing is growing exponentially. However, the transition of this technology from production of prototypes to production of critical parts is hindered by a lack of confidence in the quality of the part. Confidence can be established via a fundamental understanding of the physics of the process. It is generally accepted that this understanding will be increasingly achieved through modeling and simulation. However, there are significant physics, computational, and materials challenges stemming from the broad range of length and time scales and temperature ranges associated with the process. In thismore » study, we review the current state of the art and describe the challenges that need to be met to achieve the desired fundamental understanding of the physics of the process.« less

Trends in Nuclear Explosion Monitoring Research & Development - A Physics Perspective

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

Maceira, Monica; Blom, Philip Stephen; MacCarthy, Jonathan K.

This document entitled “Trends in Nuclear Explosion Monitoring Research and Development – A Physics Perspective” reviews the accessible literature, as it relates to nuclear explosion monitoring and the Comprehensive Nuclear-Test-Ban Treaty (CTBT, 1996), for four research areas: source physics (understanding signal generation), signal propagation (accounting for changes through physical media), sensors (recording the signals), and signal analysis (processing the signal). Over 40 trends are addressed, such as moving from 1D to 3D earth models, from pick-based seismic event processing to full waveform processing, and from separate treatment of mechanical waves in different media to combined analyses. Highlighted in the documentmore » for each trend are the value and benefit to the monitoring mission, key papers that advanced the science, and promising research and development for the future.« less

Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.

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

Buchheit, Thomas E.; Wilcox, Ian Zachary; Sandoval, Andrew J

This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction andmore » portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.« less

Bayesian Analysis of Non-Gaussian Long-Range Dependent Processes

NASA Astrophysics Data System (ADS)

Graves, Timothy; Watkins, Nicholas; Franzke, Christian; Gramacy, Robert

2013-04-01

Recent studies [e.g. the Antarctic study of Franzke, J. Climate, 2010] have strongly suggested that surface temperatures exhibit long-range dependence (LRD). The presence of LRD would hamper the identification of deterministic trends and the quantification of their significance. It is well established that LRD processes exhibit stochastic trends over rather long periods of time. Thus, accurate methods for discriminating between physical processes that possess long memory and those that do not are an important adjunct to climate modeling. As we briefly review, the LRD idea originated at the same time as H-selfsimilarity, so it is often not realised that a model does not have to be H-self similar to show LRD [e.g. Watkins, GRL Frontiers, 2013]. We have used Markov Chain Monte Carlo algorithms to perform a Bayesian analysis of Auto-Regressive Fractionally-Integrated Moving-Average ARFIMA(p,d,q) processes, which are capable of modeling LRD. Our principal aim is to obtain inference about the long memory parameter, d, with secondary interest in the scale and location parameters. We have developed a reversible-jump method enabling us to integrate over different model forms for the short memory component. We initially assume Gaussianity, and have tested the method on both synthetic and physical time series. Many physical processes, for example the Faraday Antarctic time series, are significantly non-Gaussian. We have therefore extended this work by weakening the Gaussianity assumption, assuming an alpha-stable distribution for the innovations, and performing joint inference on d and alpha. Such a modified FARIMA(p,d,q) process is a flexible, initial model for non-Gaussian processes with long memory. We will present a study of the dependence of the posterior variance of the memory parameter d on the length of the time series considered. This will be compared with equivalent error diagnostics for other measures of d.

Advancing reservoir operation description in physically based hydrological models

NASA Astrophysics Data System (ADS)

Anghileri, Daniela; Giudici, Federico; Castelletti, Andrea; Burlando, Paolo

2016-04-01

Last decades have seen significant advances in our capacity of characterizing and reproducing hydrological processes within physically based models. Yet, when the human component is considered (e.g. reservoirs, water distribution systems), the associated decisions are generally modeled with very simplistic rules, which might underperform in reproducing the actual operators' behaviour on a daily or sub-daily basis. For example, reservoir operations are usually described by a target-level rule curve, which represents the level that the reservoir should track during normal operating conditions. The associated release decision is determined by the current state of the reservoir relative to the rule curve. This modeling approach can reasonably reproduce the seasonal water volume shift due to reservoir operation. Still, it cannot capture more complex decision making processes in response, e.g., to the fluctuations of energy prices and demands, the temporal unavailability of power plants or varying amount of snow accumulated in the basin. In this work, we link a physically explicit hydrological model with detailed hydropower behavioural models describing the decision making process by the dam operator. In particular, we consider two categories of behavioural models: explicit or rule-based behavioural models, where reservoir operating rules are empirically inferred from observational data, and implicit or optimization based behavioural models, where, following a normative economic approach, the decision maker is represented as a rational agent maximising a utility function. We compare these two alternate modelling approaches on the real-world water system of Lake Como catchment in the Italian Alps. The water system is characterized by the presence of 18 artificial hydropower reservoirs generating almost 13% of the Italian hydropower production. Results show to which extent the hydrological regime in the catchment is affected by different behavioural models and reservoir operating strategies.

Infrastructure Upgrades to Support Model Longevity and New Applications: The Variable Infiltration Capacity Model Version 5.0 (VIC 5.0)

NASA Astrophysics Data System (ADS)

Nijssen, B.; Hamman, J.; Bohn, T. J.

2015-12-01

The Variable Infiltration Capacity (VIC) model is a macro-scale semi-distributed hydrologic model. VIC development began in the early 1990s and it has been used extensively, applied from basin to global scales. VIC has been applied in a many use cases, including the construction of hydrologic data sets, trend analysis, data evaluation and assimilation, forecasting, coupled climate modeling, and climate change impact analysis. Ongoing applications of the VIC model include the University of Washington's drought monitor and forecast systems, and NASA's land data assimilation systems. The development of VIC version 5.0 focused on reconfiguring the legacy VIC source code to support a wider range of modern modeling applications. The VIC source code has been moved to a public Github repository to encourage participation by the model development community-at-large. The reconfiguration has separated the physical core of the model from the driver, which is responsible for memory allocation, pre- and post-processing and I/O. VIC 5.0 includes four drivers that use the same physical model core: classic, image, CESM, and Python. The classic driver supports legacy VIC configurations and runs in the traditional time-before-space configuration. The image driver includes a space-before-time configuration, netCDF I/O, and uses MPI for parallel processing. This configuration facilitates the direct coupling of streamflow routing, reservoir, and irrigation processes within VIC. The image driver is the foundation of the CESM driver; which couples VIC to CESM's CPL7 and a prognostic atmosphere. Finally, we have added a Python driver that provides access to the functions and datatypes of VIC's physical core from a Python interface. This presentation demonstrates how reconfiguring legacy source code extends the life and applicability of a research model.

Modeling of Electrochemical Process for the Treatment of Wastewater Containing Organic Pollutants

NASA Astrophysics Data System (ADS)

Rodrigo, Manuel A.; Cañizares, Pablo; Lobato, Justo; Sáez, Cristina

Electrocoagulation and electrooxidation are promising electrochemical technologies that can be used to remove organic pollutants contained in wastewaters. To make these technologies competitive with the conventional technologies that are in use today, a better understanding of the processes involved must be achieved. In this context, the development of mathematical models that are consistent with the processes occurring in a physical system is a relevant advance, because such models can help to understand what is happening in the treatment process. In turn, a more detailed knowledge of the physical system can be obtained, and tools for a proper design of the processes, or for the analysis of operating problems, are attained. The modeling of these technologies can be carried out using single-variable or multivariable models. Likewise, the position dependence of the model species can be described with different approaches. In this work, a review of the basics of the modeling of these processes and a description of several representative models for electrochemical oxidation and coagulation are carried out. Regarding electrooxidation, two models are described: one which summarizes the pollution of a wastewater in only one model species and that considers a macroscopic approach to formulate the mass balances and other that considers more detailed profile of concentration to describe the time course of pollutants and intermediates through a mixed maximum gradient/macroscopic approach. On the topic of electrochemical coagulation, two different approaches are also described in this work: one that considers the hydrodynamic conditions as the main factor responsible for the electrochemical coagulation processes and the other that considers the chemical interaction of the reagents and the pollutants as the more significant processes in the description of the electrochemical coagulation of organic compounds. In addition, in this work it is also described a multivariable model for the electrodissolution of anodes (first stage in electrocoagulation processes). This later model use a mixed macroscopic/maximum gradient approach to describe the chemical and electrochemical processes and it also assumes that the rates of all processes are very high, and that they can be successfully modeled using pseudoequilibrium approaches.

Physical and numerical modeling of hydrophysical proceses on the site of underwater pipelines

NASA Astrophysics Data System (ADS)

Garmakova, M. E.; Degtyarev, V. V.; Fedorova, N. N.; Shlychkov, V. A.

2018-03-01

The paper outlines issues related to ensuring the exploitation safety of underwater pipelines that are at risk of accidents. The performed research is based on physical and mathematical modeling of local bottom erosion in the area of pipeline location. The experimental studies were performed on the basis of the Hydraulics Laboratory of the Department of Hydraulic Engineering Construction, Safety and Ecology of NSUACE (Sibstrin). In the course of physical experiments it was revealed that the intensity of the bottom soil reforming depends on the deepening of the pipeline. The ANSYS software has been used for numerical modeling. The process of erosion of the sandy bottom was modeled under the pipeline. Comparison of computational results at various mass flow rates was made.

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).

Computational Cosmology

NASA Astrophysics Data System (ADS)

Abel, Tom

2013-01-01

Gravitational instability of small density fluctuations, possibly created during an early inflationary period, is the key process leading to the formation of all structure in the Universe. New numerical algorithms have recently enabled much progress in understanding the relevant physical processes dominating the first billion years of structure formation. Computational cosmologists are attempting to simulate on their supercomputers how galaxies come about. In recent years first attempts trying to follow the formation and eventual death of every single star in these model galaxies has become to be within reach. The models now include gravity for both dark matter and baryonic matter, hydrodynamics, follow the radiation from massive stars and its impact in shaping the surrounding material, gas chemistry and all the key radiative atomic and molecular physics determining the thermal state of the model gas. In a small number of cases even the rold of magnetic fields on galactic scales is being studied. At the same time we are learning more about the limitations of certain numerical techniques and developing new schemes to more accurately follow the interplay of these many different physical processes. This talk is in two parts. First we consider a birds eye view of the relevant physical processes relevant for structure formation and potential approaches in solving the relevant equations efficiently and accurately on modern supercomputers. Secondly, we focus in on one of those processes. Namely the intricate and fascinating dynamics of the likely collsionless fluid dynamics of dark matter. A novel way of following the intricate evolution of such collisionless fluids in phase space is allowing us to construct new numerical methods to help understand the nature of dark matter halos as well as problems in astrophysical and terrestial plasmas.

Comparing the cognitive differences resulting from modeling instruction: Using computer microworld and physical object instruction to model real world problems

NASA Astrophysics Data System (ADS)

Oursland, Mark David

This study compared the modeling achievement of students receiving mathematical modeling instruction using the computer microworld, Interactive Physics, and students receiving instruction using physical objects. Modeling instruction included activities where students applied the (a) linear model to a variety of situations, (b) linear model to two-rate situations with a constant rate, (c) quadratic model to familiar geometric figures. Both quantitative and qualitative methods were used to analyze achievement differences between students (a) receiving different methods of modeling instruction, (b) with different levels of beginning modeling ability, or (c) with different levels of computer literacy. Student achievement was analyzed quantitatively through a three-factor analysis of variance where modeling instruction, beginning modeling ability, and computer literacy were used as the three independent factors. The SOLO (Structure of the Observed Learning Outcome) assessment framework was used to design written modeling assessment instruments to measure the students' modeling achievement. The same three independent factors were used to collect and analyze the interviews and observations of student behaviors. Both methods of modeling instruction used the data analysis approach to mathematical modeling. The instructional lessons presented problem situations where students were asked to collect data, analyze the data, write a symbolic mathematical equation, and use equation to solve the problem. The researcher recommends the following practice for modeling instruction based on the conclusions of this study. A variety of activities with a common structure are needed to make explicit the modeling process of applying a standard mathematical model. The modeling process is influenced strongly by prior knowledge of the problem context and previous modeling experiences. The conclusions of this study imply that knowledge of the properties about squares improved the students' ability to model a geometric problem more than instruction in data analysis modeling. The uses of computer microworlds such as Interactive Physics in conjunction with cooperative groups are a viable method of modeling instruction.

Modeling erosion and sedimentation coupled with hydrological and overland flow processes at the watershed scale

NASA Astrophysics Data System (ADS)

Kim, Jongho; Ivanov, Valeriy Y.; Katopodes, Nikolaos D.

2013-09-01

A novel two-dimensional, physically based model of soil erosion and sediment transport coupled to models of hydrological and overland flow processes has been developed. The Hairsine-Rose formulation of erosion and deposition processes is used to account for size-selective sediment transport and differentiate bed material into original and deposited soil layers. The formulation is integrated within the framework of the hydrologic and hydrodynamic model tRIBS-OFM, Triangulated irregular network-based, Real-time Integrated Basin Simulator-Overland Flow Model. The integrated model explicitly couples the hydrodynamic formulation with the advection-dominated transport equations for sediment of multiple particle sizes. To solve the system of equations including both the Saint-Venant and the Hairsine-Rose equations, the finite volume method is employed based on Roe's approximate Riemann solver on an unstructured grid. The formulation yields space-time dynamics of flow, erosion, and sediment transport at fine scale. The integrated model has been successfully verified with analytical solutions and empirical data for two benchmark cases. Sensitivity tests to grid resolution and the number of used particle sizes have been carried out. The model has been validated at the catchment scale for the Lucky Hills watershed located in southeastern Arizona, USA, using 10 events for which catchment-scale streamflow and sediment yield data were available. Since the model is based on physical laws and explicitly uses multiple types of watershed information, satisfactory results were obtained. The spatial output has been analyzed and the driving role of topography in erosion processes has been discussed. It is expected that the integrated formulation of the model has the promise to reduce uncertainties associated with typical parameterizations of flow and erosion processes. A potential for more credible modeling of earth-surface processes is thus anticipated.

The impact of (n, γ) reaction rate uncertainties of unstable isotopes near N = 50 on the i-process nucleosynthesis in He-shell flash white dwarfs

NASA Astrophysics Data System (ADS)

Denissenkov, Pavel; Perdikakis, Georgios; Herwig, Falk; Schatz, Hendrik; Ritter, Christian; Pignatari, Marco; Jones, Samuel; Nikas, Stylianos; Spyrou, Artemis

2018-05-01

The first-peak s-process elements Rb, Sr, Y and Zr in the post-AGB star Sakurai's object (V4334 Sagittarii) have been proposed to be the result of i-process nucleosynthesis in a post-AGB very-late thermal pulse event. We estimate the nuclear physics uncertainties in the i-process model predictions to determine whether the remaining discrepancies with observations are significant and point to potential issues with the underlying astrophysical model. We find that the dominant source in the nuclear physics uncertainties are predictions of neutron capture rates on unstable neutron rich nuclei, which can have uncertainties of more than a factor 20 in the band of the i-process. We use a Monte Carlo variation of 52 neutron capture rates and a 1D multi-zone post-processing model for the i-process in Sakurai's object to determine the cumulative effect of these uncertainties on the final elemental abundance predictions. We find that the nuclear physics uncertainties are large and comparable to observational errors. Within these uncertainties the model predictions are consistent with observations. A correlation analysis of the results of our MC simulations reveals that the strongest impact on the predicted abundances of Rb, Sr, Y and Zr is made by the uncertainties in the (n, γ) reaction rates of 85Br, 86Br, 87Kr, 88Kr, 89Kr, 89Rb, 89Sr, and 92Sr. This conclusion is supported by a series of multi-zone simulations in which we increased and decreased to their maximum and minimum limits one or two reaction rates per run. We also show that simple and fast one-zone simulations should not be used instead of more realistic multi-zone stellar simulations for nuclear sensitivity and uncertainty studies of convective–reactive processes. Our findings apply more generally to any i-process site with similar neutron exposure, such as rapidly accreting white dwarfs with near-solar metallicities.

Physics-Based Modeling of Electric Operation, Heat Transfer, and Scrap Melting in an AC Electric Arc Furnace

NASA Astrophysics Data System (ADS)

Opitz, Florian; Treffinger, Peter

2016-04-01

Electric arc furnaces (EAF) are complex industrial plants whose actual behavior depends upon numerous factors. Due to its energy intensive operation, the EAF process has always been subject to optimization efforts. For these reasons, several models have been proposed in literature to analyze and predict different modes of operation. Most of these models focused on the processes inside the vessel itself. The present paper introduces a dynamic, physics-based model of a complete EAF plant which consists of the four subsystems vessel, electric system, electrode regulation, and off-gas system. Furthermore the solid phase is not treated to be homogenous but a simple spatial discretization is employed. Hence it is possible to simulate the energy input by electric arcs and fossil fuel burners depending on the state of the melting progress. The model is implemented in object-oriented, equation-based language Modelica. The simulation results are compared to literature data.

Ozone Lidar Observations for Air Quality Studies

NASA Technical Reports Server (NTRS)

Wang, Lihua; Newchurch, Mike; Kuang, Shi; Burris, John F.; Huang, Guanyu; Pour-Biazar, Arastoo; Koshak, William; Follette-Cook, Melanie B.; Pickering, Kenneth E.; McGee, Thomas J.;

Testing Theory of Planned Behavior and Neo-Socioanalytic Theory models of trait activity, industriousness, exercise social cognitions, exercise intentions, and physical activity in a representative U.S. sample

PubMed Central

Vo, Phuong T.; Bogg, Tim

2015-01-01

Prior research identified assorted relations between trait and social cognition models of personality and engagement in physical activity. Using a representative U.S. sample (N = 957), the goal of the present study was to test two alternative structural models of the relationships among the extraversion-related facet of activity, the conscientiousness-related facet of industriousness, social cognitions from the Theory of Planned Behavior (perceived behavioral control, affective attitudes, subjective norms, intentions), Social Cognitive Theory (self-efficacy, outcome expectancies), and the Transtheoretical Model (behavioral processes of change), and engagement in physical activity. Path analyses with bootstrapping procedures were used to model direct and indirect effects of trait and social cognition constructs on physical activity through two distinct frameworks – the Theory of Planned Behavior and Neo-Socioanalytic Theory. While both models showed good internal fit, comparative model information criteria showed the Theory-of-Planned-Behavior-informed model provided a better fit. In the model, social cognitions fully mediated the relationships from the activity facet and industriousness to intentions for and engagement in physical activity, such that the relationships were primarily maintained by positive affective evaluations, positive expected outcomes, and confidence in overcoming barriers related to physical activity engagement. The resultant model – termed the Disposition-Belief-Motivation model– is proposed as a useful framework for organizing and integrating personality trait facets and social cognitions from various theoretical perspectives to investigate the expression of health-related behaviors, such as physical activity. Moreover, the results are discussed in terms of extending the application of the Disposition-Belief-Motivation model to longitudinal and intervention designs for physical activity engagement. PMID:26300811

Computational modeling of soot nucleation

NASA Astrophysics Data System (ADS)

Chung, Seung-Hyun

Recent studies indicate that soot is the second most significant driver of climate change---behind CO2, but ahead of methane---and increased levels of soot particles in the air are linked to health hazards such as heart disease and lung cancer. Within the soot formation process, soot nucleation is the least understood step, and current experimental findings are still limited. This thesis presents computational modeling studies of the major pathways of the soot nucleation process. In this study, two regimes of soot nucleation---chemical growth and physical agglomeration---were evaluated and the results demonstrated that combustion conditions determine the relative importance of these two routes. Also, the dimerization process of polycyclic aromatic hydrocarbons, which has been regarded as one of the most important physical agglomeration processes in soot formation, was carefully examined with a new method for obtaining the nucleation rate using molecular dynamics simulation. The results indicate that the role of pyrene dimerization, which is the commonly accepted model, is expected to be highly dependent on various flame temperature conditions and may not be a key step in the soot nucleation process. An additional pathway, coronene dimerization in this case, needed to be included to improve the match with experimental data. The results of this thesis provide insight on the soot nucleation process and can be utilized to improve current soot formation models.

Prediction of Physical Activity Level Using Processes of Change From the Transtheoretical Model: Experiential, Behavioral, or an Interaction Effect?

PubMed

Romain, Ahmed Jérôme; Horwath, Caroline; Bernard, Paquito

2018-01-01

The purpose of the present study was to compare prediction of physical activity (PA) by experiential or behavioral processes of change (POCs) or an interaction between both types of processes. A cross-sectional study. This study was conducted using an online questionnaire. A total of 394 participants (244 women, 150 men), with a mean age of 35.12 ± 12.04 years and a mean body mass index of 22.97 ± 4.25 kg/m 2 were included. Participants completed the Processes of Change, Stages of Change questionnaires, and the International Physical Activity Questionnaire to evaluate self-reported PA level (total, vigorous, and moderate PA). Hierarchical multiple regression models were used to test the prediction of PA level. For both total PA (β = .261; P < .001) and vigorous PA (β = .297; P < .001), only behavioral POCs were a significant predictor. Regarding moderate PA, only the interaction between experiential and behavioral POCs was a significant predictor (β = .123; P = .017). Our results provide confirmation that behavioral processes are most prominent in PA behavior. Nevertheless, it is of interest to note that the interaction between experiential and behavioral POCs was the only element predicting moderate PA level. Experiential processes were not associated with PA level.

Integration of the Total Lightning Jump Algorithm into Current Operational Warning Environment Conceptual Models

NASA Technical Reports Server (NTRS)

Schultz, Chris; Carey, Larry; Schultz, Elise V.; Stano, Geoffrey; Gatlin, Patrick N.; Kozlowski, Danielle M.; Blakeslee, Rich J.; Goodman, Steve

2013-01-01

Key points this analysis will address: 1) What physically is going on in the cloud when there is a jump in lightning? -- Updraft variations, Ice fluxes 2) How do these processes fit in with severe storm conceptual models? 3) What would this information provide an end user? --Relate LJA to radar observations, like changes in reflectivity, MESH, VIL, etc. based multi -Doppler derived physical relationships

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.

The value of oxygen-isotope data and multiple discharge records in calibrating a fully-distributed, physically-based rainfall-runoff model (CRUM3) to improve predictive capability

NASA Astrophysics Data System (ADS)

Neill, Aaron; Reaney, Sim

2015-04-01

Fully-distributed, physically-based rainfall-runoff models attempt to capture some of the complexity of the runoff processes that operate within a catchment, and have been used to address a variety of issues including water quality and the effect of climate change on flood frequency. Two key issues are prevalent, however, which call into question the predictive capability of such models. The first is the issue of parameter equifinality which can be responsible for large amounts of uncertainty. The second is whether such models make the right predictions for the right reasons - are the processes operating within a catchment correctly represented, or do the predictive abilities of these models result only from the calibration process? The use of additional data sources, such as environmental tracers, has been shown to help address both of these issues, by allowing for multi-criteria model calibration to be undertaken, and by permitting a greater understanding of the processes operating in a catchment and hence a more thorough evaluation of how well catchment processes are represented in a model. Using discharge and oxygen-18 data sets, the ability of the fully-distributed, physically-based CRUM3 model to represent the runoff processes in three sub-catchments in Cumbria, NW England has been evaluated. These catchments (Morland, Dacre and Pow) are part of the of the River Eden demonstration test catchment project. The oxygen-18 data set was firstly used to derive transit-time distributions and mean residence times of water for each of the catchments to gain an integrated overview of the types of processes that were operating. A generalised likelihood uncertainty estimation procedure was then used to calibrate the CRUM3 model for each catchment based on a single discharge data set from each catchment. Transit-time distributions and mean residence times of water obtained from the model using the top 100 behavioural parameter sets for each catchment were then compared to those derived from the oxygen-18 data to see how well the model captured catchment dynamics. The value of incorporating the oxygen-18 data set, as well as discharge data sets from multiple as opposed to single gauging stations in each catchment, in the calibration process to improve the predictive capability of the model was then investigated. This was achieved by assessing by how much the identifiability of the model parameters and the ability of the model to represent the runoff processes operating in each catchment improved with the inclusion of the additional data sets with respect to the likely costs that would be incurred in obtaining the data sets themselves.

Why Don't They Understand Us?

NASA Astrophysics Data System (ADS)

Kvasz, Ladislav

The aim of the article is to provide teachers some ideas about the development of physical knowledge and to make them more receptive to the differences between their and the students thinking. I want to show, that these differences lie not only in the richness of experience, but also in the structure of this experience. I try to point to some of these differences lying in the content, form and meaningfulness. The article is based on an adapted version of Piaget's model of the growth of physical knowledge. The model represents the changes of semantic understanding, formal language and logical structure of a theory during its historical development. I illustrate the model on the development of classical mechanics, but similar changes can be found also in the history of electrodynamics or quantum mechanics. The central idea of the paper is to use this model of the historical development of physical knowledge in analysis of the cognitive processes in physics education.

Ensemble-type numerical uncertainty information from single model integrations

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

Rauser, Florian, E-mail: florian.rauser@mpimet.mpg.de; Marotzke, Jochem; Korn, Peter

2015-07-01

We suggest an algorithm that quantifies the discretization error of time-dependent physical quantities of interest (goals) for numerical models of geophysical fluid dynamics. The goal discretization error is estimated using a sum of weighted local discretization errors. The key feature of our algorithm is that these local discretization errors are interpreted as realizations of a random process. The random process is determined by the model and the flow state. From a class of local error random processes we select a suitable specific random process by integrating the model over a short time interval at different resolutions. The weights of themore » influences of the local discretization errors on the goal are modeled as goal sensitivities, which are calculated via automatic differentiation. The integration of the weighted realizations of local error random processes yields a posterior ensemble of goal approximations from a single run of the numerical model. From the posterior ensemble we derive the uncertainty information of the goal discretization error. This algorithm bypasses the requirement of detailed knowledge about the models discretization to generate numerical error estimates. The algorithm is evaluated for the spherical shallow-water equations. For two standard test cases we successfully estimate the error of regional potential energy, track its evolution, and compare it to standard ensemble techniques. The posterior ensemble shares linear-error-growth properties with ensembles of multiple model integrations when comparably perturbed. The posterior ensemble numerical error estimates are of comparable size as those of a stochastic physics ensemble.« less

An experimental method to verify soil conservation by check dams on the Loess Plateau, China.

PubMed

Xu, X Z; Zhang, H W; Wang, G Q; Chen, S C; Dang, W Q

2009-12-01

A successful experiment with a physical model requires necessary conditions of similarity. This study presents an experimental method with a semi-scale physical model. The model is used to monitor and verify soil conservation by check dams in a small watershed on the Loess Plateau of China. During experiments, the model-prototype ratio of geomorphic variables was kept constant under each rainfall event. Consequently, experimental data are available for verification of soil erosion processes in the field and for predicting soil loss in a model watershed with check dams. Thus, it can predict the amount of soil loss in a catchment. This study also mentions four criteria: similarities of watershed geometry, grain size and bare land, Froude number (Fr) for rainfall event, and soil erosion in downscaled models. The efficacy of the proposed method was confirmed using these criteria in two different downscaled model experiments. The B-Model, a large scale model, simulates watershed prototype. The two small scale models, D(a) and D(b), have different erosion rates, but are the same size. These two models simulate hydraulic processes in the B-Model. Experiment results show that while soil loss in the small scale models was converted by multiplying the soil loss scale number, it was very close to that of the B-Model. Obviously, with a semi-scale physical model, experiments are available to verify and predict soil loss in a small watershed area with check dam system on the Loess Plateau, China.

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.

Modelling Mathematical Reasoning in Physics Education

NASA Astrophysics Data System (ADS)

Uhden, Olaf; Karam, Ricardo; Pietrocola, Maurício; Pospiech, Gesche

2012-04-01

Many findings from research as well as reports from teachers describe students' problem solving strategies as manipulation of formulas by rote. The resulting dissatisfaction with quantitative physical textbook problems seems to influence the attitude towards the role of mathematics in physics education in general. Mathematics is often seen as a tool for calculation which hinders a conceptual understanding of physical principles. However, the role of mathematics cannot be reduced to this technical aspect. Hence, instead of putting mathematics away we delve into the nature of physical science to reveal the strong conceptual relationship between mathematics and physics. Moreover, we suggest that, for both prospective teaching and further research, a focus on deeply exploring such interdependency can significantly improve the understanding of physics. To provide a suitable basis, we develop a new model which can be used for analysing different levels of mathematical reasoning within physics. It is also a guideline for shifting the attention from technical to structural mathematical skills while teaching physics. We demonstrate its applicability for analysing physical-mathematical reasoning processes with an example.

The control of branching morphogenesis

PubMed Central

Iber, Dagmar; Menshykau, Denis

2013-01-01

Many organs of higher organisms are heavily branched structures and arise by an apparently similar process of branching morphogenesis. Yet the regulatory components and local interactions that have been identified differ greatly in these organs. It is an open question whether the regulatory processes work according to a common principle and how far physical and geometrical constraints determine the branching process. Here, we review the known regulatory factors and physical constraints in lung, kidney, pancreas, prostate, mammary gland and salivary gland branching morphogenesis, and describe the models that have been formulated to analyse their impacts. PMID:24004663

On the use of Empirical Data to Downscale Non-scientific Scepticism About Results From Complex Physical Based Models

NASA Astrophysics Data System (ADS)

Germer, S.; Bens, O.; Hüttl, R. F.

2008-12-01

The scepticism of non-scientific local stakeholders about results from complex physical based models is a major problem concerning the development and implementation of local climate change adaptation measures. This scepticism originates from the high complexity of such models. Local stakeholders perceive complex models as black-box models, as it is impossible to gasp all underlying assumptions and mathematically formulated processes at a glance. The use of physical based models is, however, indispensible to study complex underlying processes and to predict future environmental changes. The increase of climate change adaptation efforts following the release of the latest IPCC report indicates that the communication of facts about what has already changed is an appropriate tool to trigger climate change adaptation. Therefore we suggest increasing the practice of empirical data analysis in addition to modelling efforts. The analysis of time series can generate results that are easier to comprehend for non-scientific stakeholders. Temporal trends and seasonal patterns of selected hydrological parameters (precipitation, evapotranspiration, groundwater levels and river discharge) can be identified and the dependence of trends and seasonal patters to land use, topography and soil type can be highlighted. A discussion about lag times between the hydrological parameters can increase the awareness of local stakeholders for delayed environment responses.

Investigation for improving Global Positioning System (GPS) orbits using a discrete sequential estimator and stochastic models of selected physical processes

NASA Technical Reports Server (NTRS)

Goad, Clyde C.; Chadwell, C. David

1993-01-01

GEODYNII is a conventional batch least-squares differential corrector computer program with deterministic models of the physical environment. Conventional algorithms were used to process differenced phase and pseudorange data to determine eight-day Global Positioning system (GPS) orbits with several meter accuracy. However, random physical processes drive the errors whose magnitudes prevent improving the GPS orbit accuracy. To improve the orbit accuracy, these random processes should be modeled stochastically. The conventional batch least-squares algorithm cannot accommodate stochastic models, only a stochastic estimation algorithm is suitable, such as a sequential filter/smoother. Also, GEODYNII cannot currently model the correlation among data values. Differenced pseudorange, and especially differenced phase, are precise data types that can be used to improve the GPS orbit precision. To overcome these limitations and improve the accuracy of GPS orbits computed using GEODYNII, we proposed to develop a sequential stochastic filter/smoother processor by using GEODYNII as a type of trajectory preprocessor. Our proposed processor is now completed. It contains a correlated double difference range processing capability, first order Gauss Markov models for the solar radiation pressure scale coefficient and y-bias acceleration, and a random walk model for the tropospheric refraction correction. The development approach was to interface the standard GEODYNII output files (measurement partials and variationals) with software modules containing the stochastic estimator, the stochastic models, and a double differenced phase range processing routine. Thus, no modifications to the original GEODYNII software were required. A schematic of the development is shown. The observational data are edited in the preprocessor and the data are passed to GEODYNII as one of its standard data types. A reference orbit is determined using GEODYNII as a batch least-squares processor and the GEODYNII measurement partial (FTN90) and variational (FTN80, V-matrix) files are generated. These two files along with a control statement file and a satellite identification and mass file are passed to the filter/smoother to estimate time-varying parameter states at each epoch, improved satellite initial elements, and improved estimates of constant parameters.

Resilience to health challenges is related to different ways of thinking: mediators of physical and emotional quality of life in a heterogeneous rare-disease cohort.

PubMed

Schwartz, Carolyn E; Michael, Wesley; Rapkin, Bruce D

2017-11-01

We sought to understand what distinguishes people who confront health challenges but still manage to thrive. This study investigated whether resilience helps to explain the impact of health challenges on quality of life (QOL) outcomes, and how resilience relates to appraisal. A web-based survey of rare-disease panel participants included the Centers for Disease Control Healthy Days Core Module, the PROMIS-10, and comorbidities. The QOL Appraisal Profile-v2 assessed cognitive processes underlying QOL. Resilience was operationalized statistically using residual modeling, and hierarchical regressions tested the mediation hypothesis that resilience accounts for a significant amount of the relationship of appraisal to QOL. The study sample (n = 3,324; mean age 50; 86% female; 90% White) represented a range of diagnostic codes, with cancer and diseases of the nervous system being the most prevalent health conditions. After adjusting for comorbidities (catalysts), resilience was associated with better physical and emotional functioning, and different appraisal processes were associated with better or worse physical or emotional functioning. After controlling for catalysts, 62% of the association of Physical Functioning and 23% of the association between Emotional Functioning and appraisal were mediated by resilience. Physical and emotional resilience comprised some of the same appraisal processes, but physically resilient people were characterized by more appraisal processes than their emotionally resilient counterparts. Resilient people employ different appraisal processes than non-resilient people, and these processes differ for physical and emotional outcomes. Resilience was a stronger mediator of the relationship between physical rather than emotional functioning and appraisal.

Linking Physical and Numerical Modelling in Hydrogeology Using Sand Tank Experiments and Comsol Multiphysics

ERIC Educational Resources Information Center

Singha, Kamini; Loheide, Steven P., II

2011-01-01

Visualising subsurface processes in hydrogeology and building intuition for how these processes are controlled by changes in forcing is hard for many undergraduate students. While numerical modelling is one way to help undergraduate students explore outcomes of multiple scenarios, many codes are not user-friendly with respect to defining domains,…

Heat capacities and volumetric changes in the glass transition range: a constitutive approach based on the standard linear solid

NASA Astrophysics Data System (ADS)

Lion, Alexander; Mittermeier, Christoph; Johlitz, Michael

2017-09-01

A novel approach to represent the glass transition is proposed. It is based on a physically motivated extension of the linear viscoelastic Poynting-Thomson model. In addition to a temperature-dependent damping element and two linear springs, two thermal strain elements are introduced. In order to take the process dependence of the specific heat into account and to model its characteristic behaviour below and above the glass transition, the Helmholtz free energy contains an additional contribution which depends on the temperature history and on the current temperature. The model describes the process-dependent volumetric and caloric behaviour of glass-forming materials, and defines a functional relationship between pressure, volumetric strain, and temperature. If a model for the isochoric part of the material behaviour is already available, for example a model of finite viscoelasticity, the caloric and volumetric behaviour can be represented with the current approach. The proposed model allows computing the isobaric and isochoric heat capacities in closed form. The difference c_p -c_v is process-dependent and tends towards the classical expression in the glassy and equilibrium ranges. Simulations and theoretical studies demonstrate the physical significance of the model.

A modeling study of marine boundary layer clouds

NASA Technical Reports Server (NTRS)

Wang, Shouping; Fitzjarrald, Daniel E.

1993-01-01

Marine boundary layer (MBL) clouds are important components of the earth's climate system. These clouds drastically reduce the amount of solar radiation absorbed by the earth, but have little effect on the emitted infrared radiation on top of the atmosphere. In addition, these clouds are intimately involved in regulating boundary layer turbulent fluxes. For these reasons, it is important that general circulation models used for climate studies must realistically simulate the global distribution of the MBL. While the importance of these cloud systems is well recognized, many physical processes involved in these clouds are poorly understood and their representation in large-scale models remains an unresolved problem. The present research aims at the development and improvement of the parameterization of these cloud systems and an understanding of physical processes involved. This goal is addressed in two ways. One is to use regional modeling approach to validate and evaluate two-layer marine boundary layer models using satellite and ground-truth observations; the other is to combine this simple model with a high-order turbulence closure model to study the transition processes from stratocumulus to shallow cumulus clouds. Progress made in this effort is presented.

SIG-VISA: Signal-based Vertically Integrated Seismic Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.; Mayeda, K. M.; Myers, S. C.; Russell, S.

2013-12-01

Traditional seismic monitoring systems rely on discrete detections produced by station processing software; however, while such detections may constitute a useful summary of station activity, they discard large amounts of information present in the original recorded signal. We present SIG-VISA (Signal-based Vertically Integrated Seismic Analysis), a system for seismic monitoring through Bayesian inference on seismic signals. By directly modeling the recorded signal, our approach incorporates additional information unavailable to detection-based methods, enabling higher sensitivity and more accurate localization using techniques such as waveform matching. SIG-VISA's Bayesian forward model of seismic signal envelopes includes physically-derived models of travel times and source characteristics as well as Gaussian process (kriging) statistical models of signal properties that combine interpolation of historical data with extrapolation of learned physical trends. Applying Bayesian inference, we evaluate the model on earthquakes as well as the 2009 DPRK test event, demonstrating a waveform matching effect as part of the probabilistic inference, along with results on event localization and sensitivity. In particular, we demonstrate increased sensitivity from signal-based modeling, in which the SIGVISA signal model finds statistical evidence for arrivals even at stations for which the IMS station processing failed to register any detection.

Declining physical activity and the socio-cultural context of the geography of industrial restructuring: a novel conceptual framework.

PubMed

Rind, Esther; Jones, Andy

2014-05-01

At the population level, the prevalence of physical activity has declined considerably in many developed countries in recent decades. There is some evidence that areas exhibiting the lowest activity levels are those which have undergone a particularly strong transition away from employment in physically demanding occupations. We propose that processes of deindustrialization may be causally linked to unexplained geographical disparities in levels of physical activity. While the sociocultural correlates of physical activity have been well studied, and prior conceptual frameworks have been developed to explain more general patterns of activity, none have explicitly attempted to identify the components of industrial change that may impact physical activity. In this work we review the current literature on sociocultural correlates of health behaviors before using a case study centered on the United Kingdom to present a novel framework that links industrial change to declining levels of physical activity. We developed a comprehensive model linking sociocultural correlates of physical activity to processes associated with industrial restructuring and discuss implication for policy and practice. A better understanding of sociocultural processes may help to ameliorate adverse health consequences of employment decline in communities that have experienced substantial losses of manual employment.

A Novel Model for Predicting Rehospitalization Risk Incorporating Physical Function, Cognitive Status, and Psychosocial Support Using Natural Language Processing.

PubMed

Greenwald, Jeffrey L; Cronin, Patrick R; Carballo, Victoria; Danaei, Goodarz; Choy, Garry

2017-03-01

With the increasing focus on reducing hospital readmissions in the United States, numerous readmissions risk prediction models have been proposed, mostly developed through analyses of structured data fields in electronic medical records and administrative databases. Three areas that may have an impact on readmission but are poorly captured using structured data sources are patients' physical function, cognitive status, and psychosocial environment and support. The objective of the study was to build a discriminative model using information germane to these 3 areas to identify hospitalized patients' risk for 30-day all cause readmissions. We conducted clinician focus groups to identify language used in the clinical record regarding these 3 areas. We then created a dataset including 30,000 inpatients, 10,000 from each of 3 hospitals, and searched those records for the focus group-derived language using natural language processing. A 30-day readmission prediction model was developed on 75% of the dataset and validated on the other 25% and also on hospital specific subsets. Focus group language was aggregated into 35 variables. The final model had 16 variables, a validated C-statistic of 0.74, and was well calibrated. Subset validation of the model by hospital yielded C-statistics of 0.70-0.75. Deriving a 30-day readmission risk prediction model through identification of physical, cognitive, and psychosocial issues using natural language processing yielded a model that performs similarly to the better performing models previously published with the added advantage of being based on clinically relevant factors and also automated and scalable. Because of the clinical relevance of the variables in the model, future research may be able to test if targeting interventions to identified risks results in reductions in readmissions.

The Physics of Decision Making:. Stochastic Differential Equations as Models for Neural Dynamics and Evidence Accumulation in Cortical Circuits

NASA Astrophysics Data System (ADS)

Holmes, Philip; Eckhoff, Philip; Wong-Lin, K. F.; Bogacz, Rafal; Zacksenhouse, Miriam; Cohen, Jonathan D.

2010-03-01

We describe how drift-diffusion (DD) processes - systems familiar in physics - can be used to model evidence accumulation and decision-making in two-alternative, forced choice tasks. We sketch the derivation of these stochastic differential equations from biophysically-detailed models of spiking neurons. DD processes are also continuum limits of the sequential probability ratio test and are therefore optimal in the sense that they deliver decisions of specified accuracy in the shortest possible time. This leaves open the critical balance of accuracy and speed. Using the DD model, we derive a speed-accuracy tradeoff that optimizes reward rate for a simple perceptual decision task, compare human performance with this benchmark, and discuss possible reasons for prevalent sub-optimality, focussing on the question of uncertain estimates of key parameters. We present an alternative theory of robust decisions that allows for uncertainty, and show that its predictions provide better fits to experimental data than a more prevalent account that emphasises a commitment to accuracy. The article illustrates how mathematical models can illuminate the neural basis of cognitive processes.

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.

Linking growth and yield and process models to estimate impact of environmental changes on growth of loblolly pine

Treesearch

V. Clark Baldwin; Harold E. Burkhart; James A. Westfall; Kelly D. Peterson

2001-01-01

PTAEDA2 is a distance-dependent, individual tree model that simulates the growth and yield of a plantation of loblolly pine (Pinus taeda L.)on an annual basis. The MAESTRO model utilizes an array of trees in a stand to calculate and integrate the effects of biological and physical variables on the photosynthesis and respiration processes of a target...

Why Is Improvement of Earth System Models so Elusive? Challenges and Strategies from Dust Aerosol Modeling

NASA Technical Reports Server (NTRS)

Miller, Ronald L.; Garcia-Pando, Carlos Perez; Perlwitz, Jan; Ginoux, Paul

2015-01-01

Past decades have seen an accelerating increase in computing efficiency, while climate models are representing a rapidly widening set of physical processes. Yet simulations of some fundamental aspects of climate like precipitation or aerosol forcing remain highly uncertain and resistant to progress. Dust aerosol modeling of soil particles lofted by wind erosion has seen a similar conflict between increasing model sophistication and remaining uncertainty. Dust aerosols perturb the energy and water cycles by scattering radiation and acting as ice nuclei, while mediating atmospheric chemistry and marine photosynthesis (and thus the carbon cycle). These effects take place across scales from the dimensions of an ice crystal to the planetary-scale circulation that disperses dust far downwind of its parent soil. Representing this range leads to several modeling challenges. Should we limit complexity in our model, which consumes computer resources and inhibits interpretation? How do we decide if a process involving dust is worthy of inclusion within our model? Can we identify a minimal representation of a complex process that is efficient yet retains the physics relevant to climate? Answering these questions about the appropriate degree of representation is guided by model evaluation, which presents several more challenges. How do we proceed if the available observations do not directly constrain our process of interest? (This could result from competing processes that influence the observed variable and obscure the signature of our process of interest.) Examples will be presented from dust modeling, with lessons that might be more broadly applicable. The end result will either be clinical depression or there assuring promise of continued gainful employment as the community confronts these challenges.

The Role of Laboratory-Based Studies of the Physical and Biological Properties of Sea Ice in Supporting the Observation and Modeling of Ice Covered Seas

NASA Astrophysics Data System (ADS)

Light, B.; Krembs, C.

2003-12-01

Laboratory-based studies of the physical and biological properties of sea ice are an essential link between high latitude field observations and existing numerical models. Such studies promote improved understanding of climatic variability and its impact on sea ice and the structure of ice-dependent marine ecosystems. Controlled laboratory experiments can help identify feedback mechanisms between physical and biological processes and their response to climate fluctuations. Climatically sensitive processes occurring between sea ice and the atmosphere and sea ice and the ocean determine surface radiative energy fluxes and the transfer of nutrients and mass across these boundaries. High temporally and spatially resolved analyses of sea ice under controlled environmental conditions lend insight to the physics that drive these transfer processes. Techniques such as optical probing, thin section photography, and microscopy can be used to conduct experiments on natural sea ice core samples and laboratory-grown ice. Such experiments yield insight on small scale processes from the microscopic to the meter scale and can be powerful interdisciplinary tools for education and model parameterization development. Examples of laboratory investigations by the authors include observation of the response of sea ice microstructure to changes in temperature, assessment of the relationships between ice structure and the partitioning of solar radiation by first-year sea ice covers, observation of pore evolution and interfacial structure, and quantification of the production and impact of microbial metabolic products on the mechanical, optical, and textural characteristics of sea ice.

An analytical model of SAGD process considering the effect of threshold pressure gradient

NASA Astrophysics Data System (ADS)

Morozov, P.; Abdullin, A.; Khairullin, M.

2018-05-01

An analytical model is proposed for the development of super-viscous oil deposits by the method of steam-assisted gravity drainage, taking into account the nonlinear filtration law with the limiting gradient. The influence of non-Newtonian properties of oil on the productivity of a horizontal well and the cumulative steam-oil ratio are studied. Verification of the proposed model based on the results of physical modeling of the SAGD process was carried out.

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.

Problem solving based learning model with multiple representations to improve student's mental modelling ability on physics

NASA Astrophysics Data System (ADS)

Haili, Hasnawati; Maknun, Johar; Siahaan, Parsaoran

2017-08-01

Physics is a lessons that related to students' daily experience. Therefore, before the students studying in class formally, actually they have already have a visualization and prior knowledge about natural phenomenon and could wide it themselves. The learning process in class should be aimed to detect, process, construct, and use students' mental model. So, students' mental model agree with and builds in the right concept. The previous study held in MAN 1 Muna informs that in learning process the teacher did not pay attention students' mental model. As a consequence, the learning process has not tried to build students' mental modelling ability (MMA). The purpose of this study is to describe the improvement of students' MMA as a effect of problem solving based learning model with multiple representations approach. This study is pre experimental design with one group pre post. It is conducted in XI IPA MAN 1 Muna 2016/2017. Data collection uses problem solving test concept the kinetic theory of gasses and interview to get students' MMA. The result of this study is clarification students' MMA which is categorized in 3 category; High Mental Modelling Ability (H-MMA) for 7

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

Sjöstrand, Torbjörn; Ask, Stefan; Christiansen, Jesper R.

The Pythia program is a standard tool for the generation of events in high-energy collisions, comprising a coherent set of physics models for the evolution from a few-body hard process to a complex multiparticle final state. It contains a library of hard processes, models for initial- and final-state parton showers, matching and merging methods between hard processes and parton showers, multiparton interactions, beam remnants, string fragmentation and particle decays. It also has a set of utilities and several interfaces to external programs. Pythia 8.2 is the second main release after the complete rewrite from Fortran to C++, and now hasmore » reached such a maturity that it offers a complete replacement for most applications, notably for LHC physics studies. Lastly, the many new features should allow an improved description of data.« less

Ablation dynamics - from absorption to heat accumulation/ultra-fast laser matter interaction

NASA Astrophysics Data System (ADS)

Kramer, Thorsten; Remund, Stefan; Jäggi, Beat; Schmid, Marc; Neuenschwander, Beat

2018-05-01

Ultra-short laser radiation is used in manifold industrial applications today. Although state-of-the-art laser sources are providing an average power of 10-100 W with repetition rates of up to several megahertz, most applications do not benefit from it. On the one hand, the processing speed is limited to some hundred millimeters per second by the dynamics of mechanical axes or galvanometric scanners. On the other hand, high repetition rates require consideration of new physical effects such as heat accumulation and shielding that might reduce the process efficiency. For ablation processes, process efficiency can be expressed by the specific removal rate, ablated volume per time, and average power. The analysis of the specific removal rate for different laser parameters, like average power, repetition rate or pulse duration, and process parameters, like scanning speed or material, can be used to find the best operation point for microprocessing applications. Analytical models and molecular dynamics simulations based on the so-called two-temperature model reveal the causes for the appearance of limiting physical effects. The findings of models and simulations can be used to take advantage and optimize processing strategies.

Effects of the local structure dependence of evaporation fields on field evaporation behavior

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

Yao, Lan; Marquis, Emmanuelle A., E-mail: emarq@umich.edu; Withrow, Travis

2015-12-14

Accurate three dimensional reconstructions of atomic positions and full quantification of the information contained in atom probe microscopy data rely on understanding the physical processes taking place during field evaporation of atoms from needle-shaped specimens. However, the modeling framework for atom probe microscopy has only limited quantitative justification. Building on the continuum field models previously developed, we introduce a more physical approach with the selection of evaporation events based on density functional theory calculations. This model reproduces key features observed experimentally in terms of sequence of evaporation, evaporation maps, and depth resolution, and provides insights into the physical limit formore » spatial resolution.« less

Uncertainty analysis of signal deconvolution using a measured instrument response function

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

Hartouni, E. P.; Beeman, B.; Caggiano, J. A.

2016-10-05

A common analysis procedure minimizes the ln-likelihood that a set of experimental observables matches a parameterized model of the observation. The model includes a description of the underlying physical process as well as the instrument response function (IRF). Here, we investigate the National Ignition Facility (NIF) neutron time-of-flight (nTOF) spectrometers, the IRF is constructed from measurements and models. IRF measurements have a finite precision that can make significant contributions to the uncertainty estimate of the physical model’s parameters. Finally, we apply a Bayesian analysis to properly account for IRF uncertainties in calculating the ln-likelihood function used to find the optimummore » physical parameters.« less

A MATHEMATICAL MODEL OF ELECTROSTATIC PRECIPITATION. (REVISION 1): VOLUME I. MODELING AND PROGRAMMING

EPA Science Inventory

The report briefly describes the fundamental mechanisms and limiting factors involved in the electrostatic precipitation process. It discusses theories and procedures used in the computer model to describe the physical mechanisms, and generally describes the major operations perf...

PREDICTION OF THE VAPOR PRESSURE, BOILING POINT, HEAT OF VAPORIZATION AND DIFFUSION COEFFICIENT OF ORGANIC COMPOUNDS

EPA Science Inventory

The prototype computer program SPARC has been under development for several years to estimate physical properties and chemical reactivity parameters of organic compounds strictly from molecular structure. SPARC solute-solute physical process models have been developed and tested...

Biomedically relevant chemical and physical properties of coal combustion products.

PubMed Central

Fisher, G L

1983-01-01

The evaluation of the potential public and occupational health hazards of developing and existing combustion processes requires a detailed understanding of the physical and chemical properties of effluents available for human and environmental exposures. These processes produce complex mixtures of gases and aerosols which may interact synergistically or antagonistically with biological systems. Because of the physicochemical complexity of the effluents, the biomedically relevant properties of these materials must be carefully assessed. Subsequent to release from combustion sources, environmental interactions further complicate assessment of the toxicity of combustion products. This report provides an overview of the biomedically relevant physical and chemical properties of coal fly ash. Coal fly ash is presented as a model complex mixture for health and safety evaluation of combustion processes. PMID:6337824

Cross-disciplinary links in environmental systems science: Current state and claimed needs identified in a meta-review of process models.

PubMed

Ayllón, Daniel; Grimm, Volker; Attinger, Sabine; Hauhs, Michael; Simmer, Clemens; Vereecken, Harry; Lischeid, Gunnar

2018-05-01

Terrestrial environmental systems are characterised by numerous feedback links between their different compartments. However, scientific research is organized into disciplines that focus on processes within the respective compartments rather than on interdisciplinary links. Major feedback mechanisms between compartments might therefore have been systematically overlooked so far. Without identifying these gaps, initiatives on future comprehensive environmental monitoring schemes and experimental platforms might fail. We performed a comprehensive overview of feedbacks between compartments currently represented in environmental sciences and explores to what degree missing links have already been acknowledged in the literature. We focused on process models as they can be regarded as repositories of scientific knowledge that compile findings of numerous single studies. In total, 118 simulation models from 23 model types were analysed. Missing processes linking different environmental compartments were identified based on a meta-review of 346 published reviews, model intercomparison studies, and model descriptions. Eight disciplines of environmental sciences were considered and 396 linking processes were identified and ascribed to the physical, chemical or biological domain. There were significant differences between model types and scientific disciplines regarding implemented interdisciplinary links. The most wide-spread interdisciplinary links were between physical processes in meteorology, hydrology and soil science that drive or set the boundary conditions for other processes (e.g., ecological processes). In contrast, most chemical and biological processes were restricted to links within the same compartment. Integration of multiple environmental compartments and interdisciplinary knowledge was scarce in most model types. There was a strong bias of suggested future research foci and model extensions towards reinforcing existing interdisciplinary knowledge rather than to open up new interdisciplinary pathways. No clear pattern across disciplines exists with respect to suggested future research efforts. There is no evidence that environmental research would clearly converge towards more integrated approaches or towards an overarching environmental systems theory. Copyright © 2017 Elsevier B.V. All rights reserved.

Endodontic Treatment of an Anomalous Anterior Tooth with the Aid of a 3-dimensional Printed Physical Tooth Model.

PubMed

Byun, Chanhee; Kim, Changhwan; Cho, Seungryong; Baek, Seung Hoon; Kim, Gyutae; Kim, Sahng G; Kim, Sun-Young

2015-06-01

Endodontic treatment of tooth formation anomalies is a challenge to clinicians and as such requires a complete understanding of the aberrant root canal anatomy followed by careful root canal disinfection and obturation. Here, we report the use of a 3-dimensional (3D) printed physical tooth model including internal root canal structures for the endodontic treatment of a challenging tooth anomaly. A 12-year-old boy was referred for endodontic treatment of tooth #8. The tooth showed class II mobility with swelling and a sinus tract in the buccal mucosa and periapical radiolucency. The tooth presented a very narrow structure between the crown and root by distal concavity and a severely dilacerated root. Moreover, a perforation site with bleeding and another ditching site were identified around the cervical area in the access cavity. A translucent physical tooth model carrying the information on internal root canal structures was built through a 3-step process: data acquisition by cone-beam computed tomographic scanning, virtual modeling by image processing, and manufacturing by 3D printing. A custom-made guide jig was then fabricated to achieve a safe and precise working path to the root canal. Endodontic procedures including access cavity preparation were performed using the physical tooth model and the guide jig. At the 7-month follow-up, the endodontically treated tooth showed complete periapical healing with no clinical signs and symptoms. This case report describes a novel method of endodontic treatment of an anomalous maxillary central incisor with the aid of a physical tooth model and a custom-made guide jig via 3D printing technique. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Fault-tolerant Control of a Cyber-physical System

NASA Astrophysics Data System (ADS)

Roxana, Rusu-Both; Eva-Henrietta, Dulf

2017-10-01

Cyber-physical systems represent a new emerging field in automatic control. The fault system is a key component, because modern, large scale processes must meet high standards of performance, reliability and safety. Fault propagation in large scale chemical processes can lead to loss of production, energy, raw materials and even environmental hazard. The present paper develops a multi-agent fault-tolerant control architecture using robust fractional order controllers for a (13C) cryogenic separation column cascade. The JADE (Java Agent DEvelopment Framework) platform was used to implement the multi-agent fault tolerant control system while the operational model of the process was implemented in Matlab/SIMULINK environment. MACSimJX (Multiagent Control Using Simulink with Jade Extension) toolbox was used to link the control system and the process model. In order to verify the performance and to prove the feasibility of the proposed control architecture several fault simulation scenarios were performed.

Mechanism study and numerical simulation of Uranium nitriding induced by high energy laser

NASA Astrophysics Data System (ADS)

Zhu, Yuan; Xu, Jingjing; Qi, Yanwen; Li, Shengpeng; Zhao, Hui

2018-06-01

The gradients of interfacial tension induced by local heating led to Marangoni convection, which had a significant effect on surface formation and the process of mass transport in the laser nitriding of uranium. An experimental observation of the underlying processes was very difficult. In present study, the Marangoni convection was considered and the computational fluid dynamic (CFD) analysis technique of FLUENT program was performed to determine the physical processes such as heat transfer and mass transport. The progress of gas-liquid falling film desorption was presented by combining phase-change model with fluid volume function (VOF) model. The time-dependent distribution of the temperature had been derived. Moreover, the concentration and distribution of nitrogen across the laser spot are calculated. The simulation results matched with the experimental data. The numerical resolution method provided a better approach to know the physical processes and dependencies of the coating formation.

A multi-scale ''soil water structure'' model based on the pedostructure concept

NASA Astrophysics Data System (ADS)

Braudeau, E.; Mohtar, R. H.; El Ghezal, N.; Crayol, M.; Salahat, M.; Martin, P.

2009-02-01

Current soil water models do not take into account the internal organization of the soil medium and, a fortiori, the physical interaction between the water film surrounding the solid particles of the soil structure, and the surface charges of this structure. In that sense they empirically deal with the physical soil properties that are all generated from this soil water-structure interaction. As a result, the thermodynamic state of the soil water medium, which constitutes the local physical conditions, namely the pedo-climate, for biological and geo-chemical processes in soil, is not defined in these models. The omission of soil structure from soil characterization and modeling does not allow for coupling disciplinary models for these processes with soil water models. This article presents a soil water structure model, Kamel®, which was developed based on a new paradigm in soil physics where the hierarchical soil structure is taken into account allowing for defining its thermodynamic properties. After a review of soil physics principles which forms the basis of the paradigm, we describe the basic relationships and functionality of the model. Kamel® runs with a set of 15 soil input parameters, the pedohydral parameters, which are parameters of the physically-based equations of four soil characteristic curves that can be measured in the laboratory. For cases where some of these parameters are not available, we show how to estimate these parameters from commonly available soil information using published pedotransfer functions. A published field experimental study on the dynamics of the soil moisture profile following a pounded infiltration rainfall event was used as an example to demonstrate soil characterization and Kamel® simulations. The simulated soil moisture profile for a period of 60 days showed very good agreement with experimental field data. Simulations using input data calculated from soil texture and pedotransfer functions were also generated and compared to simulations of the more ideal characterization. The later comparison illustrates how Kamel® can be used and adapt to any case of soil data availability. As physically based model on soil structure, it may be used as a standard reference to evaluate other soil-water models and also pedotransfer functions at a given location or agronomical situation.

Stochastic Processes in Physics: Deterministic Origins and Control

NASA Astrophysics Data System (ADS)

Demers, Jeffery

Stochastic processes are ubiquitous in the physical sciences and engineering. While often used to model imperfections and experimental uncertainties in the macroscopic world, stochastic processes can attain deeper physical significance when used to model the seemingly random and chaotic nature of the underlying microscopic world. Nowhere more prevalent is this notion than in the field of stochastic thermodynamics - a modern systematic framework used describe mesoscale systems in strongly fluctuating thermal environments which has revolutionized our understanding of, for example, molecular motors, DNA replication, far-from equilibrium systems, and the laws of macroscopic thermodynamics as they apply to the mesoscopic world. With progress, however, come further challenges and deeper questions, most notably in the thermodynamics of information processing and feedback control. Here it is becoming increasingly apparent that, due to divergences and subtleties of interpretation, the deterministic foundations of the stochastic processes themselves must be explored and understood. This thesis presents a survey of stochastic processes in physical systems, the deterministic origins of their emergence, and the subtleties associated with controlling them. First, we study time-dependent billiards in the quivering limit - a limit where a billiard system is indistinguishable from a stochastic system, and where the simplified stochastic system allows us to view issues associated with deterministic time-dependent billiards in a new light and address some long-standing problems. Then, we embark on an exploration of the deterministic microscopic Hamiltonian foundations of non-equilibrium thermodynamics, and we find that important results from mesoscopic stochastic thermodynamics have simple microscopic origins which would not be apparent without the benefit of both the micro and meso perspectives. Finally, we study the problem of stabilizing a stochastic Brownian particle with feedback control, and we find that in order to avoid paradoxes involving the first law of thermodynamics, we need a model for the fine details of the thermal driving noise. The underlying theme of this thesis is the argument that the deterministic microscopic perspective and stochastic mesoscopic perspective are both important and useful, and when used together, we can more deeply and satisfyingly understand the physics occurring over either scale.

Electric Motorboat Drag Racing: A Hands-On Physics Project that Motivates Students from Start to Finish

ERIC Educational Resources Information Center

Barry, Reno

2008-01-01

Electric Motorboat Drag Racing is a culminating high school physics project designed to apply and bring to life many content standards for physics. Students need to be given several weeks at home to design and build their model-sized electric motorboats for the 5-meter drag racing competition down rain gutters. In the process, they are discussing…

Space Particle Hazard Measurement and Modeling

DTIC Science & Technology

2016-09-01

understand the interactions of the physical processes driving, then specify and ultimately predict the state of the energetic particle populations...Hudson, and B. T. Kress (2013), Direct observation of the CRAND proton radiation belt source, J. Geophys. Res. Space Physics , 118, doi:10.1002...anticritical temperature for spacecraft charging, J. Geophys Res.: Space Physics , 113, 2156-2202, doi: 10.1029/2008JA013161 2010 – Tested basic

The distribution of density in supersonic turbulence

NASA Astrophysics Data System (ADS)

Squire, Jonathan; Hopkins, Philip F.

2017-11-01

We propose a model for the statistics of the mass density in supersonic turbulence, which plays a crucial role in star formation and the physics of the interstellar medium (ISM). The model is derived by considering the density to be arranged as a collection of strong shocks of width ˜ M^{-2}, where M is the turbulent Mach number. With two physically motivated parameters, the model predicts all density statistics for M>1 turbulence: the density probability distribution and its intermittency (deviation from lognormality), the density variance-Mach number relation, power spectra and structure functions. For the proposed model parameters, reasonable agreement is seen between model predictions and numerical simulations, albeit within the large uncertainties associated with current simulation results. More generally, the model could provide a useful framework for more detailed analysis of future simulations and observational data. Due to the simple physical motivations for the model in terms of shocks, it is straightforward to generalize to more complex physical processes, which will be helpful in future more detailed applications to the ISM. We see good qualitative agreement between such extensions and recent simulations of non-isothermal turbulence.

Patterns of Clinical Reasoning in Physical Therapist Students.

PubMed

Gilliland, Sarah; Wainwright, Susan Flannery

2017-05-01

Clinical reasoning is a complex, nonlinear problem-solving process that is influenced by models of practice. The development of physical therapists' clinical reasoning abilities is a crucial yet underresearched aspect of entry-level (professional) physical therapist education. The purpose of this qualitative study was to examine the types of clinical reasoning strategies physical therapist students engage in during a patient encounter. A qualitative descriptive case study design involving within and across case analysis was used. Eight second-year, professional physical therapist students from 2 different programs completed an evaluation and initial intervention for a standardized patient followed by a retrospective think-aloud interview to explicate their reasoning processes. Participants' clinical reasoning strategies were examined using a 2-stage qualitative method of thematic analysis. Participants demonstrated consistent signs of development of physical therapy-specific reasoning processes, yet varied in their approach to the case and use of reflection. Participants who gave greater attention to patient education and empowerment also demonstrated greater use of reflection-in-action during the patient encounter. One negative case illustrates the variability in the rate at which students may develop these abilities. Participants demonstrated development toward physical therapist--specific clinical reasoning, yet demonstrated qualitatively different approaches to the patient encounter. Multiple factors, including the use of reflection-in-action, may enable students to develop greater flexibility in their reasoning processes. © 2017 American Physical Therapy Association

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.

Interannual variability of primary production and air-sea CO2 flux in the Atlantic and Indian sectors of the Southern Ocean.

NASA Astrophysics Data System (ADS)

Dufour, Carolina; Merlivat, Liliane; Le Sommer, Julien; Boutin, Jacqueline; Antoine, David

2013-04-01

As one of the major oceanic sinks of anthropogenic CO2, the Southern Ocean plays a critical role in the climate system. However, due to the scarcity of observations, little is known about physical and biological processes that control air-sea CO2 fluxes and how these processes might respond to climate change. It is well established that primary production is one of the major drivers of air-sea CO2 fluxes, consuming surface Dissolved Inorganic Carbon (DIC) during Summer. Southern Ocean primary production is though constrained by several limiting factors such as iron and light availability, which are both sensitive to mixed layer depth. Mixed layer depth is known to be affected by current changes in wind stress or freshwater fluxes over the Southern Ocean. But we still don't know how primary production may respond to anomalous mixed layer depth neither how physical processes may balance this response to set the seasonal cycle of air-sea CO2 fluxes. In this study, we investigate the impact of anomalous mixed layer depth on surface DIC in the Atlantic and Indian sectors of the Subantarctic zone of the Southern Ocean (60W-60E, 38S-55S) with a combination of in situ data, satellite data and model experiment. We use both a regional eddy permitting ocean biogeochemical model simulation based on NEMO-PISCES and data-based reconstruction of biogeochemical fields based on CARIOCA buoys and SeaWiFS data. A decomposition of the physical and biological processes driving the seasonal variability of surface DIC is performed with both the model data and observations. A good agreement is found between the model and the data for the amplitude of biological and air-sea flux contributions. The model data are further used to investigate the impact of winter and summer anomalies in mixed layer depth on surface DIC over the period 1990-2004. The relative changes of each physical and biological process contribution are quantified and discussed.

Interplay between the b →s l l anomalies and dark matter physics

NASA Astrophysics Data System (ADS)

Kawamura, Junichiro; Okawa, Shohei; Omura, Yuji

2017-10-01

Recently, the LHCb Collaboration has reported the excesses in the b →s l l processes. One of the promising candidates for new physics to explain the anomalies is the extended Standard Model (SM) with vectorlike quarks and leptons. In that model, Yukawa couplings between the extra fermions and SM fermions are introduced, adding extra scalars. Then, the box diagrams involving the extra fields achieve the b →s l l anomalies. It has been known that the excesses require the large Yukawa couplings of leptons, so that this kind of model can be tested by studying correlations with other observables. In this paper, we consider the extra scalar to be a dark matter (DM) candidate, and investigate DM physics as well as the flavor physics and the LHC physics. The DM relic density and the direct-detection cross section are also dominantly given by the Yukawa couplings, so that we find some explicit correlations between DM physics and the flavor physics. In particular, we find the predictions of the b →s l l anomalies against the direct detection of DM.

A Complex Approach to UXO Discrimination: Combining Advanced EMI Forward Models and Statistical Signal Processing

DTIC Science & Technology

2012-01-01

discrimination at live-UXO sites. Namely, under this project first we developed and implemented advanced, physically complete forward EMI models such as, the...detection and discrimination at live-UXO sites. Namely, under this project first we developed and implemented advanced, physically complete forward EMI...Shubitidze of Sky Research and Dartmouth College, conceived, implemented , and tested most of the approaches presented in this report. He developed

Multi-scale heat and mass transfer modelling of cell and tissue cryopreservation

PubMed Central

Xu, Feng; Moon, Sangjun; Zhang, Xiaohui; Shao, Lei; Song, Young Seok; Demirci, Utkan

2010-01-01

Cells and tissues undergo complex physical processes during cryopreservation. Understanding the underlying physical phenomena is critical to improve current cryopreservation methods and to develop new techniques. Here, we describe multi-scale approaches for modelling cell and tissue cryopreservation including heat transfer at macroscale level, crystallization, cell volume change and mass transport across cell membranes at microscale level. These multi-scale approaches allow us to study cell and tissue cryopreservation. PMID:20047939

Autonomy Support and Its Links to Physical Activity and Competitive Performance: Mediations through Motivation, Competence, Action Orientation and Harmonious Passion, and the Moderator Role of Autonomy Support by Perceived Competence

ERIC Educational Resources Information Center

Halvari, Hallgeir; Ulstad, Svein Olav; Bagoien, Tor Egil; Skjesol, Knut

2009-01-01

The purpose of the present study was to test a Self-Determination Theory (SDT) process model in relation to involvement in physical activity and competitive performance among students (N = 190). In this model, perceived autonomy support from teachers and coaches was expected to be positively related to autonomous motivation, perceived competence,…

Statistically Modeling I-V Characteristics of CNT-FET with LASSO

NASA Astrophysics Data System (ADS)

Ma, Dongsheng; Ye, Zuochang; Wang, Yan

2017-08-01

With the advent of internet of things (IOT), the need for studying new material and devices for various applications is increasing. Traditionally we build compact models for transistors on the basis of physics. But physical models are expensive and need a very long time to adjust for non-ideal effects. As the vision for the application of many novel devices is not certain or the manufacture process is not mature, deriving generalized accurate physical models for such devices is very strenuous, whereas statistical modeling is becoming a potential method because of its data oriented property and fast implementation. In this paper, one classical statistical regression method, LASSO, is used to model the I-V characteristics of CNT-FET and a pseudo-PMOS inverter simulation based on the trained model is implemented in Cadence. The normalized relative mean square prediction error of the trained model versus experiment sample data and the simulation results show that the model is acceptable for digital circuit static simulation. And such modeling methodology can extend to general devices.

A Novel Numerical Method for Fuzzy Boundary Value Problems

NASA Astrophysics Data System (ADS)

Can, E.; Bayrak, M. A.; Hicdurmaz

2016-05-01

In the present paper, a new numerical method is proposed for solving fuzzy differential equations which are utilized for the modeling problems in science and engineering. Fuzzy approach is selected due to its important applications on processing uncertainty or subjective information for mathematical models of physical problems. A second-order fuzzy linear boundary value problem is considered in particular due to its important applications in physics. Moreover, numerical experiments are presented to show the effectiveness of the proposed numerical method on specific physical problems such as heat conduction in an infinite plate and a fin.

Modelling of Molecular Structures and Properties. Proceedings of the International Meeting of Physical Chemistry on Modeling of Molecular Structures and Properties in Physical Chemistry and Biophysics Organized by the Division de Chimie Physique of the Societe Francaise de Chimie Held in Nancy, France on 11-15 September 1989

DTIC Science & Technology

1990-01-01

expert systems, "intelligent" computer-aided instruction , symbolic learning . These aspects will be discussed, focusing on the specific problems the...VLSI chips) according to preliminary specifications. Finally ES are also used in computer-aided instruction (CAI) due to their ability of... instructions to process controllers), academic teaching (for mathematics , physics, foreign language, etc.). Domains of application The different

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.

PHOTONICS AND NANOTECHNOLOGY Laser-induced modification of transparent crystals and glasses

NASA Astrophysics Data System (ADS)

Bulgakova, N. M.; Stoian, Razvan; Rosenfeld, A.

2010-12-01

We analyse the processes taking place in transparent crystals and glasses irradiated by ultrashort laser pulses in the regimes typical of various applications in optoelectronics and photonics. We consider some phenomena, which have been previously described by the authors within the different model representations: charging of the dielectric surface due to electron photoemission resulting in a Coulomb explosion; crater shaping by using an adaptive control of the laser pulse shape; optimisation of the waveguide writing in materials strongly resistant to laser-induced compaction under ordinary irradiation conditions. The developed models and analysis of the processes relying on these models include the elements of the solid-state physics, plasma physics, thermodynamics, theory of elasticity and plasticity. Some important experimental observations which require explanations and adequate description are summarised.

An efficient surrogate-based simulation-optimization method for calibrating a regional MODFLOW model

NASA Astrophysics Data System (ADS)

Chen, Mingjie; Izady, Azizallah; Abdalla, Osman A.

2017-01-01

Simulation-optimization method entails a large number of model simulations, which is computationally intensive or even prohibitive if the model simulation is extremely time-consuming. Statistical models have been examined as a surrogate of the high-fidelity physical model during simulation-optimization process to tackle this problem. Among them, Multivariate Adaptive Regression Splines (MARS), a non-parametric adaptive regression method, is superior in overcoming problems of high-dimensions and discontinuities of the data. Furthermore, the stability and accuracy of MARS model can be improved by bootstrap aggregating methods, namely, bagging. In this paper, Bagging MARS (BMARS) method is integrated to a surrogate-based simulation-optimization framework to calibrate a three-dimensional MODFLOW model, which is developed to simulate the groundwater flow in an arid hardrock-alluvium region in northwestern Oman. The physical MODFLOW model is surrogated by the statistical model developed using BMARS algorithm. The surrogate model, which is fitted and validated using training dataset generated by the physical model, can approximate solutions rapidly. An efficient Sobol' method is employed to calculate global sensitivities of head outputs to input parameters, which are used to analyze their importance for the model outputs spatiotemporally. Only sensitive parameters are included in the calibration process to further improve the computational efficiency. Normalized root mean square error (NRMSE) between measured and simulated heads at observation wells is used as the objective function to be minimized during optimization. The reasonable history match between the simulated and observed heads demonstrated feasibility of this high-efficient calibration framework.

Modelling surface water-groundwater interaction with a conceptual approach: model development and application in New Zealand

NASA Astrophysics Data System (ADS)

Yang, J.; Zammit, C.; McMillan, H. K.

2016-12-01

As in most countries worldwide, water management in lowland areas is a big concern for New Zealand due to its economic importance for water related human activities. As a result, the estimation of available water resources in these areas (e.g., for irrigation and water supply purpose) is crucial and often requires an understanding of complex hydrological processes, which are often characterized by strong interactions between surface water and groundwater (usually expressed as losing and gaining rivers). These processes are often represented and simulated using integrated physically based hydrological models. However models with physically based groundwater modules typically require large amount of non-readily available geologic and aquifer information and are computationally intensive. Instead, this paper presents a conceptual groundwater model that is fully integrated into New Zealand's national hydrological model TopNet based on TopModel concepts (Beven, 1992). Within this conceptual framework, the integrated model can simulate not only surface processes, but also groundwater processes and surface water-groundwater interaction processes (including groundwater flow, river-groundwater interaction, and groundwater interaction with external watersheds). The developed model was applied to two New Zealand catchments with different hydro-geological and climate characteristics (Pareora catchment in the Canterbury Plains and Grey catchment on the West Coast). Previous studies have documented strong interactions between the river and groundwater, based on the analysis of a large number of concurrent flow measurements and associated information along the river main stem. Application of the integrated hydrological model indicates flow simulation (compared to the original hydrological model conceptualisation) during low flow conditions are significantly improved and further insights on local river dynamics are gained. Due to its conceptual characteristics and low level of data requirement, the integrated model could be used at local and national scales to improve the simulation of hydrological processes in non-topographically driven areas (where groundwater processes are important), and to assess impact of climate change on the integrated hydrological cycle in these areas.

Computational physics of the mind

NASA Astrophysics Data System (ADS)

Duch, Włodzisław

1996-08-01

In the XIX century and earlier physicists such as Newton, Mayer, Hooke, Helmholtz and Mach were actively engaged in the research on psychophysics, trying to relate psychological sensations to intensities of physical stimuli. Computational physics allows to simulate complex neural processes giving a chance to answer not only the original psychophysical questions but also to create models of the mind. In this paper several approaches relevant to modeling of the mind are outlined. Since direct modeling of the brain functions is rather limited due to the complexity of such models a number of approximations is introduced. The path from the brain, or computational neurosciences, to the mind, or cognitive sciences, is sketched, with emphasis on higher cognitive functions such as memory and consciousness. No fundamental problems in understanding of the mind seem to arise. From a computational point of view realistic models require massively parallel architectures.

A meta-model based approach for rapid formability estimation of continuous fibre reinforced components

NASA Astrophysics Data System (ADS)

Zimmerling, Clemens; Dörr, Dominik; Henning, Frank; Kärger, Luise

2018-05-01

Due to their high mechanical performance, continuous fibre reinforced plastics (CoFRP) become increasingly important for load bearing structures. In many cases, manufacturing CoFRPs comprises a forming process of textiles. To predict and optimise the forming behaviour of a component, numerical simulations are applied. However, for maximum part quality, both the geometry and the process parameters must match in mutual regard, which in turn requires numerous numerically expensive optimisation iterations. In both textile and metal forming, a lot of research has focused on determining optimum process parameters, whilst regarding the geometry as invariable. In this work, a meta-model based approach on component level is proposed, that provides a rapid estimation of the formability for variable geometries based on pre-sampled, physics-based draping data. Initially, a geometry recognition algorithm scans the geometry and extracts a set of doubly-curved regions with relevant geometry parameters. If the relevant parameter space is not part of an underlying data base, additional samples via Finite-Element draping simulations are drawn according to a suitable design-table for computer experiments. Time saving parallel runs of the physical simulations accelerate the data acquisition. Ultimately, a Gaussian Regression meta-model is built from the data base. The method is demonstrated on a box-shaped generic structure. The predicted results are in good agreement with physics-based draping simulations. Since evaluations of the established meta-model are numerically inexpensive, any further design exploration (e.g. robustness analysis or design optimisation) can be performed in short time. It is expected that the proposed method also offers great potential for future applications along virtual process chains: For each process step along the chain, a meta-model can be set-up to predict the impact of design variations on manufacturability and part performance. Thus, the method is considered to facilitate a lean and economic part and process design under consideration of manufacturing effects.

Using large hydrological datasets to create a robust, physically based, spatially distributed model for Great Britain

NASA Astrophysics Data System (ADS)

Lewis, Elizabeth; Kilsby, Chris; Fowler, Hayley

2014-05-01

The impact of climate change on hydrological systems requires further quantification in order to inform water management. This study intends to conduct such analysis using hydrological models. Such models are of varying forms, of which conceptual, lumped parameter models and physically-based models are two important types. The majority of hydrological studies use conceptual models calibrated against measured river flow time series in order to represent catchment behaviour. This method often shows impressive results for specific problems in gauged catchments. However, the results may not be robust under non-stationary conditions such as climate change, as physical processes and relationships amenable to change are not accounted for explicitly. Moreover, conceptual models are less readily applicable to ungauged catchments, in which hydrological predictions are also required. As such, the physically based, spatially distributed model SHETRAN is used in this study to develop a robust and reliable framework for modelling historic and future behaviour of gauged and ungauged catchments across the whole of Great Britain. In order to achieve this, a large array of data completely covering Great Britain for the period 1960-2006 has been collated and efficiently stored ready for model input. The data processed include a DEM, rainfall, PE and maps of geology, soil and land cover. A desire to make the modelling system easy for others to work with led to the development of a user-friendly graphical interface. This allows non-experts to set up and run a catchment model in a few seconds, a process that can normally take weeks or months. The quality and reliability of the extensive dataset for modelling hydrological processes has also been evaluated. One aspect of this has been an assessment of error and uncertainty in rainfall input data, as well as the effects of temporal resolution in precipitation inputs on model calibration. SHETRAN has been updated to accept gridded rainfall inputs, and UKCP09 gridded daily rainfall data has been disaggregated using hourly records to analyse the implications of using realistic sub-daily variability. Furthermore, the development of a comprehensive dataset and computationally efficient means of setting up and running catchment models has allowed for examination of how a robust parameter scheme may be derived. This analysis has been based on collective parameterisation of multiple catchments in contrasting hydrological settings and subject to varied processes. 350 gauged catchments all over the UK have been simulated, and a robust set of parameters is being sought by examining the full range of hydrological processes and calibrating to a highly diverse flow data series. The modelling system will be used to generate flow time series based on historical input data and also downscaled Regional Climate Model (RCM) forecasts using the UKCP09 Weather Generator. This will allow for analysis of flow frequency and associated future changes, which cannot be determined from the instrumental record or from lumped parameter model outputs calibrated only to historical catchment behaviour. This work will be based on the existing and functional modelling system described following some further improvements to calibration, particularly regarding simulation of groundwater-dominated catchments.

Report from the Integrated Modeling Panel at the Workshop on the Science of Ignition on NIF

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

Marinak, M; Lamb, D

2012-07-03

This section deals with multiphysics radiation hydrodynamics codes used to design and simulate targets in the ignition campaign. These topics encompass all the physical processes they model, and include consideration of any approximations necessary due to finite computer resources. The section focuses on what developments would have the highest impact on reducing uncertainties in modeling most relevant to experimental observations. It considers how the ICF codes should be employed in the ignition campaign. This includes a consideration of how the experiments can be best structured to test the physical models the codes employ.

Search for physics beyond the standard model in events with τ leptons, jets, and large transverse momentum imbalance in pp collisions at [Formula: see text].

PubMed

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Hall-Wilton, R; Herndon, M; Hervé, A; Klabbers, P; Klukas, J; Lanaro, A; Lazaridis, C; Leonard, J; Loveless, R; Mohapatra, A; Ojalvo, I; Palmonari, F; Pierro, G A; Ross, I; Savin, A; Smith, W H; Swanson, J

A search for physics beyond the standard model is performed with events having one or more hadronically decaying τ leptons, highly energetic jets, and large transverse momentum imbalance. The data sample corresponds to an integrated luminosity of 4.98 fb -1 of proton-proton collisions at [Formula: see text] collected with the CMS detector at the LHC in 2011. The number of observed events is consistent with predictions for standard model processes. Lower limits on the mass of the gluino in supersymmetric models are determined.

Rail vehicle dynamic response to a nonlinear physical 'in-service' model of its secondary suspension hydraulic dampers

NASA Astrophysics Data System (ADS)

Wang, W. L.; Zhou, Z. R.; Yu, D. S.; Qin, Q. H.; Iwnicki, S.

2017-10-01

A full nonlinear physical 'in-service' model was built for a rail vehicle secondary suspension hydraulic damper with shim-pack-type valves. In the modelling process, a shim pack deflection theory with an equivalent-pressure correction factor was proposed, and a Finite Element Analysis (FEA) approach was applied. Bench test results validated the damper model over its full velocity range and thus also proved that the proposed shim pack deflection theory and the FEA-based parameter identification approach are effective. The validated full damper model was subsequently incorporated into a detailed vehicle dynamics simulation to study how its key in-service parameter variations influence the secondary-suspension-related vehicle system dynamics. The obtained nonlinear physical in-service damper model and the vehicle dynamic response characteristics in this study could be used in the product design optimization and nonlinear optimal specifications of high-speed rail hydraulic dampers.

IR characteristic simulation of city scenes based on radiosity model

NASA Astrophysics Data System (ADS)

Xiong, Xixian; Zhou, Fugen; Bai, Xiangzhi; Yu, Xiyu

2013-09-01

Reliable modeling for thermal infrared (IR) signatures of real-world city scenes is required for signature management of civil and military platforms. Traditional modeling methods generally assume that scene objects are individual entities during the physical processes occurring in infrared range. However, in reality, the physical scene involves convective and conductive interactions between objects as well as the radiations interactions between objects. A method based on radiosity model describes these complex effects. It has been developed to enable an accurate simulation for the radiance distribution of the city scenes. Firstly, the physical processes affecting the IR characteristic of city scenes were described. Secondly, heat balance equations were formed on the basis of combining the atmospheric conditions, shadow maps and the geometry of scene. Finally, finite difference method was used to calculate the kinetic temperature of object surface. A radiosity model was introduced to describe the scattering effect of radiation between surface elements in the scene. By the synthesis of objects radiance distribution in infrared range, we could obtain the IR characteristic of scene. Real infrared images and model predictions were shown and compared. The results demonstrate that this method can realistically simulate the IR characteristic of city scenes. It effectively displays the infrared shadow effects and the radiation interactions between objects in city scenes.

A physics based method for combining multiple anatomy models with application to medical simulation.

PubMed

Zhu, Yanong; Magee, Derek; Ratnalingam, Rishya; Kessel, David

2009-01-01

We present a physics based approach to the construction of anatomy models by combining components from different sources; different image modalities, protocols, and patients. Given an initial anatomy, a mass-spring model is generated which mimics the physical properties of the solid anatomy components. This helps maintain valid spatial relationships between the components, as well as the validity of their shapes. Combination can be either replacing/modifying an existing component, or inserting a new component. The external forces that deform the model components to fit the new shape are estimated from Gradient Vector Flow and Distance Transform maps. We demonstrate the applicability and validity of the described approach in the area of medical simulation, by showing the processes of non-rigid surface alignment, component replacement, and component insertion.

Phenomenological Modeling of Infrared Sources: Recent Advances

NASA Technical Reports Server (NTRS)

Leung, Chun Ming; Kwok, Sun (Editor)

1993-01-01

Infrared observations from planned space facilities (e.g., ISO (Infrared Space Observatory), SIRTF (Space Infrared Telescope Facility)) will yield a large and uniform sample of high-quality data from both photometric and spectroscopic measurements. To maximize the scientific returns of these space missions, complementary theoretical studies must be undertaken to interpret these observations. A crucial step in such studies is the construction of phenomenological models in which we parameterize the observed radiation characteristics in terms of the physical source properties. In the last decade, models with increasing degree of physical realism (in terms of grain properties, physical processes, and source geometry) have been constructed for infrared sources. Here we review current capabilities available in the phenomenological modeling of infrared sources and discuss briefly directions for future research in this area.

Model-independent determination of the triple Higgs coupling at e + e – colliders

DOE PAGES

Barklow, Tim; Fujii, Keisuke; Jung, Sunghoon; ...

2018-03-20

Here, the observation of Higgs pair production at high-energy colliders can give evidence for the presence of a triple Higgs coupling. However, the actual determination of the value of this coupling is more difficult. In the context of general models for new physics, double Higgs production processes can receive contributions from many possible beyond-Standard-Model effects. This dependence must be understood if one is to make a definite statement about the deviation of the Higgs field potential from the Standard Model. In this paper, we study the extraction of the triple Higgs coupling from the process e +e –→Zhh. We showmore » that, by combining the measurement of this process with other measurements available at a 500 GeV e +e – collider, it is possible to quote model-independent limits on the effective field theory parameter c 6 that parametrizes modifications of the Higgs potential. We present precise error estimates based on the anticipated International Linear Collider physics program, studied with full simulation. Our analysis also gives new insight into the model-independent extraction of the Higgs boson coupling constants and total width from e +e – data.« less

Model-independent determination of the triple Higgs coupling at e + e – colliders

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

Barklow, Tim; Fujii, Keisuke; Jung, Sunghoon

Here, the observation of Higgs pair production at high-energy colliders can give evidence for the presence of a triple Higgs coupling. However, the actual determination of the value of this coupling is more difficult. In the context of general models for new physics, double Higgs production processes can receive contributions from many possible beyond-Standard-Model effects. This dependence must be understood if one is to make a definite statement about the deviation of the Higgs field potential from the Standard Model. In this paper, we study the extraction of the triple Higgs coupling from the process e +e –→Zhh. We showmore » that, by combining the measurement of this process with other measurements available at a 500 GeV e +e – collider, it is possible to quote model-independent limits on the effective field theory parameter c 6 that parametrizes modifications of the Higgs potential. We present precise error estimates based on the anticipated International Linear Collider physics program, studied with full simulation. Our analysis also gives new insight into the model-independent extraction of the Higgs boson coupling constants and total width from e +e – data.« less

Model-independent determination of the triple Higgs coupling at e+e- colliders

NASA Astrophysics Data System (ADS)

Barklow, Tim; Fujii, Keisuke; Jung, Sunghoon; Peskin, Michael E.; Tian, Junping

2018-03-01

The observation of Higgs pair production at high-energy colliders can give evidence for the presence of a triple Higgs coupling. However, the actual determination of the value of this coupling is more difficult. In the context of general models for new physics, double Higgs production processes can receive contributions from many possible beyond-Standard-Model effects. This dependence must be understood if one is to make a definite statement about the deviation of the Higgs field potential from the Standard Model. In this paper, we study the extraction of the triple Higgs coupling from the process e+e-→Z h h . We show that, by combining the measurement of this process with other measurements available at a 500 GeV e+e- collider, it is possible to quote model-independent limits on the effective field theory parameter c6 that parametrizes modifications of the Higgs potential. We present precise error estimates based on the anticipated International Linear Collider physics program, studied with full simulation. Our analysis also gives new insight into the model-independent extraction of the Higgs boson coupling constants and total width from e+e- data.

Development of Spectral and Atomic Models for Diagnosing Energetic Particle Characteristics in Fast Ignition Experiments

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

MacFarlane, Joseph J.; Golovkin, I. E.; Woodruff, P. R.

2009-08-07

This Final Report summarizes work performed under DOE STTR Phase II Grant No. DE-FG02-05ER86258 during the project period from August 2006 to August 2009. The project, “Development of Spectral and Atomic Models for Diagnosing Energetic Particle Characteristics in Fast Ignition Experiments,” was led by Prism Computational Sciences (Madison, WI), and involved collaboration with subcontractors University of Nevada-Reno and Voss Scientific (Albuquerque, NM). In this project, we have: Developed and implemented a multi-dimensional, multi-frequency radiation transport model in the LSP hybrid fluid-PIC (particle-in-cell) code [1,2]. Updated the LSP code to support the use of accurate equation-of-state (EOS) tables generated by Prism’smore » PROPACEOS [3] code to compute more accurate temperatures in high energy density physics (HEDP) plasmas. Updated LSP to support the use of Prism’s multi-frequency opacity tables. Generated equation of state and opacity data for LSP simulations for several materials being used in plasma jet experimental studies. Developed and implemented parallel processing techniques for the radiation physics algorithms in LSP. Benchmarked the new radiation transport and radiation physics algorithms in LSP and compared simulation results with analytic solutions and results from numerical radiation-hydrodynamics calculations. Performed simulations using Prism radiation physics codes to address issues related to radiative cooling and ionization dynamics in plasma jet experiments. Performed simulations to study the effects of radiation transport and radiation losses due to electrode contaminants in plasma jet experiments. Updated the LSP code to generate output using NetCDF to provide a better, more flexible interface to SPECT3D [4] in order to post-process LSP output. Updated the SPECT3D code to better support the post-processing of large-scale 2-D and 3-D datasets generated by simulation codes such as LSP. Updated atomic physics modeling to provide for more comprehensive and accurate atomic databases that feed into the radiation physics modeling (spectral simulations and opacity tables). Developed polarization spectroscopy modeling techniques suitable for diagnosing energetic particle characteristics in HEDP experiments. A description of these items is provided in this report. The above efforts lay the groundwork for utilizing the LSP and SPECT3D codes in providing simulation support for DOE-sponsored HEDP experiments, such as plasma jet and fast ignition physics experiments. We believe that taken together, the LSP and SPECT3D codes have unique capabilities for advancing our understanding of the physics of these HEDP plasmas. Based on conversations early in this project with our DOE program manager, Dr. Francis Thio, our efforts emphasized developing radiation physics and atomic modeling capabilities that can be utilized in the LSP PIC code, and performing radiation physics studies for plasma jets. A relatively minor component focused on the development of methods to diagnose energetic particle characteristics in short-pulse laser experiments related to fast ignition physics. The period of performance for the grant was extended by one year to August 2009 with a one-year no-cost extension, at the request of subcontractor University of Nevada-Reno.« less

Inner Magnetospheric Physics

NASA Technical Reports Server (NTRS)

Gallagher, Dennis

2018-01-01

Outline - Inner Magnetosphere Effects: Historical Background; Main regions and transport processes: Ionosphere, Plasmasphere, Plasma sheet, Ring current, Radiation belt; Geomagnetic Activity: Storms, Substorm; Models.

Definitions: Health, Fitness, and Physical Activity.

ERIC Educational Resources Information Center

Corbin, Charles B.; Pangrazi, Robert P.; Franks, B. Don

2000-01-01

This paper defines a variety of fitness components, using a simple multidimensional hierarchical model that is consistent with recent definitions in the literature. It groups the definitions into two broad categories: product and process. Products refer to states of being such as physical fitness, health, and wellness. They are commonly referred…

Processes Underlying Children's Adjustment in Families Characterized by Physical Aggression.

ERIC Educational Resources Information Center

Onyskiw, Judee; Hayduk, Leslie A.

2001-01-01

The hypothesis that physical aggression in the family affects children's adjustment through both observational learning/modeling and through its impact on parenting was tested, via LISREL, using data from a sample of Canadian children (N=11,221). Results showed observational learning and disrupted parenting provide reasonable explanations of…